BS ISO 20046:2019
BSI Standards Publication
Radiological protection — Performance criteria
for laboratories using Fluorescence In Situ
Hybridization (FISH) translocation assay for
assessment of exposure to ionizing radiation
BS ISO 20046:2019
BRITISH STANDARD
National foreword
This British Standard is the UK implementation of ISO 20046:2019.
The UK participation in its preparation was entrusted to Technical
Committee NCE/2, Radiation protection and measurement.
A list of organizations represented on this committee can be obtained on
request to its secretary.
This publication does not purport to include all the necessary provisions
of a contract. Users are responsible for its correct application.
© The British Standards Institution 2019
Published by BSI Standards Limited 2019
ISBN 978 0 580 91588 8
ICS 13.280
Compliance with a British Standard cannot confer immunity from
legal obligations.
This British Standard was published under the authority of the
Standards Policy and Strategy Committee on 31 March 2019.
Amendments/corrigenda issued since publication
Date
Text affected
INTERNATIONAL
STANDARD
BS ISO 20046:2019
ISO
20046
First edition
2019-03-19
Radiological protection —
Performance criteria for laboratories
using Fluorescence In Situ
Hybridization (FISH) translocation
assay for assessment of exposure to
ionizing radiation
Radioprotection — Critères de performance pour les laboratoires
utilisant l'analyse des translocations visualisées par hybridation
in situ fluorescente (FISH) pour évaluer l'exposition aux
rayonnements ionisants
Reference number
ISO 20046:2019(E)
© ISO 2019
BS ISO 20046:2019
ISO 20046:2019(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 2019, Published in Switzerland
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© ISO 2019 – All rights reserved
BS ISO 20046:2019
ISO 20046:2019
Contents
Page
Foreword...........................................................................................................................................................................................................................................v
Introduction................................................................................................................................................................................................................................. vi
1
2
3
4
5
6
7
8
9
10
11
12
Scope.................................................................................................................................................................................................................................. 1
Normative references....................................................................................................................................................................................... 1
Terms and definitions...................................................................................................................................................................................... 1
Translocation assay by FISH...................................................................................................................................................................... 5
4.1
General............................................................................................................................................................................................................ 5
4.2
Culturing and fixation........................................................................................................................................................................ 5
4.3
Types of staining.................................................................................................................................................................................... 5
4.4
Scoring............................................................................................................................................................................................................. 6
4.5
General requirement of the laboratory............................................................................................................................... 6
Responsibility of the customer............................................................................................................................................................... 6
Responsibility of the laboratory........................................................................................................................................................... 7
6.1
Setup and sustainment of the QA program...................................................................................................................... 7
6.2
Responsibility during service...................................................................................................................................................... 7
Confidentiality of personal information....................................................................................................................................... 8
7.1
Overview....................................................................................................................................................................................................... 8
7.2
Applications of the principle of confidentiality........................................................................................................... 8
7.2.1
Delegation of responsibilities within the laboratory........................................................................ 8
7.2.2
Requests for analysis..................................................................................................................................................... 9
7.2.3
Transmission of confidential information.................................................................................................. 9
7.2.4
Anonymity of samples.................................................................................................................................................. 9
7.2.5
Reporting of results........................................................................................................................................................ 9
7.2.6
Storage of data and results....................................................................................................................................... 9
Laboratory safety requirements........................................................................................................................................................... 9
8.1
Overview....................................................................................................................................................................................................... 9
8.2
Microbiological safety requirements................................................................................................................................. 10
8.3
Chemical safety requirements................................................................................................................................................. 10
8.4
Optical safety requirements...................................................................................................................................................... 11
8.5
Safety plan................................................................................................................................................................................................. 11
Sample processing............................................................................................................................................................................................11
9.1
Culturing and staining.................................................................................................................................................................... 11
9.2
Scoring.......................................................................................................................................................................................................... 12
9.2.1
Criteria for scoring....................................................................................................................................................... 12
9.2.2
Conversion of translocation frequencies to genome equivalence....................................... 12
Background levels of translocations..............................................................................................................................................13
Calibration curves.............................................................................................................................................................................................13
11.1 Calibration source(s)....................................................................................................................................................................... 13
11.2 Establishment of calibration curve(s).............................................................................................................................. 14
Criteria for converting a measured aberration frequency into an estimate of
absorbed dose.......................................................................................................................................................................................................16
12.1 Determination of estimated whole-body absorbed dose and confidence limits......................... 16
12.1.1 General................................................................................................................................................................................... 16
12.1.2 Comparison with the background level: Characterisation of the minimum
detectable dose............................................................................................................................................................... 16
12.1.3 Confidence limits on the number of translocations........................................................................ 19
12.1.4 Adjustment for background yield................................................................................................................... 20
12.1.5 Calculation of absorbed dose.............................................................................................................................. 21
12.1.6 Calculation of uncertainty on absorbed dose....................................................................................... 22
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13
14
12.1.7 Acute and non-acute exposure cases........................................................................................................... 22
12.1.8 Other exposure scenarios...................................................................................................................................... 23
Reporting of results.........................................................................................................................................................................................23
13.1 General......................................................................................................................................................................................................... 23
13.2 Content of the report (see Annex C for an example of a standard form)............................................ 23
13.3 Interpretation of the results...................................................................................................................................................... 24
Quality assurance and quality control.........................................................................................................................................24
14.1 Overview.................................................................................................................................................................................................... 24
14.2 Specific requirements..................................................................................................................................................................... 24
14.2.1 General................................................................................................................................................................................... 24
14.2.2 Performance checks by inter-laboratory comparisons................................................................ 24
14.2.3 Performance check of scorer qualification.............................................................................................. 25
14.2.4 Performance checks of sample transport integrity......................................................................... 25
14.2.5 Performance checks of sample integrity by service laboratory............................................ 26
14.2.6 Performance checks of instrumentation................................................................................................... 26
14.2.7 Performance checks of sample protocol................................................................................................... 26
14.2.8 Performance checks of sample scoring...................................................................................................... 26
14.2.9 Performance checks of result report generation............................................................................... 26
Annex A (informative) Sample instructions for customer...........................................................................................................27
Annex B (informative) Sample questionnaire..........................................................................................................................................29
Annex C (informative) Sample of report.........................................................................................................................................................31
Annex D (informative) Sample data sheets for recording painted aberrations....................................................32
Annex E (informative) Fitting of the dose response-curve by the method of maximum
likelihood and calculating the uncertainty of the absorbed dose estimate..........................................34
Annex F (informative) Process for dose estimation...........................................................................................................................35
Bibliography.............................................................................................................................................................................................................................. 40
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ISO 20046:2019
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see the following
URL: www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 85, Nuclear energy, nuclear technologies
and radiological protection, Subcommittee SC 2, Radiological protection.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.
© ISO 2019 – All rights reserved
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BS ISO 20046:2019
ISO 20046:2019
Introduction
The purpose of this document is to define the use of fluorescent in situ hybridization (FISH) for
chromosome translocation analysis on human peripheral blood lymphocytes for biological dosimetry
of exposure to ionizing radiation. Biological dosimetry, based on the study of chromosomal aberrations,
mainly the dicentric assay, has become a routine component of accidental dose assessment. Dicentric
aberrations, however, disappear with time after exposure, making this assay useful only in the short
term after exposure. Translocations, however, are more stable, allowing dose estimates to be made long
times after exposure or after protracted exposures.
This document provides a guideline for performing the translocation assay by FISH for dose assessment
using documented and validated procedures. The minimum requirements for testing translocation
yield in peripheral blood lymphocytes, by precisely defining the technical aspects of staining
chromosomes (number of chromosomes and types of painting), selecting types of aberrations and
cells, scoring aberrations, converting aberration yield to dose, statistical considerations, problems
related to heterogeneous, chronic or delayed exposures and extrapolation to full genome are described.
Dose assessment using the FISH assay has relevance in medical management, radiation-protection
management, record keeping, and medical/legal requirements.
A part of the information in this document is contained in other international guidelines and scientific
publications, primarily in the International Atomic Energy Agency’s (IAEA) technical reports series
on biological dosimetry. However, this document expands and standardizes the quality assurance and
quality control and the evaluation of performance.
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© ISO 2019 – All rights reserved
BS ISO 20046:2019
INTERNATIONAL STANDARD
ISO 20046:2019
Radiological protection — Performance criteria
for laboratories using Fluorescence In Situ
Hybridization (FISH) translocation assay for assessment of
exposure to ionizing radiation
1 Scope
The purpose of this document is to provide criteria for quality assurance (QA), quality control (QC) and
evaluation of the performance of biological dosimetry by cytogenetic service laboratories.
This document addresses:
a)
the responsibilities of both the customer and the laboratory;
c)
the laboratory safety requirements;
e)
the calibration sources and calibration dose ranges useful for establishing the reference
dose‑response curves that contribute to the dose estimation from chromosome aberration
frequency and the detection limit;
b) the confidentiality of personal information, for the customer and the laboratory;
d) sample processing; culturing, staining and scoring, including the criteria for scoring for
translocation analysis by FISH;
f)
the scoring procedure for translocations stained by FISH used for evaluation of exposure;
g) the criteria for converting a measured aberration frequency into an estimate of absorbed dose
(also appears as “dose”);
h) the reporting of results;
i)
j)
the QA and QC;
Annexes A to F containing sample instructions for the customer, sample questionnaire, sample
datasheet for recording aberrations, sample of report and fitting of the low dose-response curve by
the method of maximum likelihood and calculating the uncertainty of dose estimate.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp
— IEC Electropedia: available at https://www.electropedia.org/
© ISO 2019 – All rights reserved
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BS ISO 20046:2019
ISO 20046:2019
3.1
absorbed dose
D
quantity of ionizing radiation energy imparted per unit mass of a specified material
3.2
acentric
terminal or interstitial chromosome fragment of varying size lacking a centromere, referred
to as an excess acentric fragment when it is formed independently of a dicentric or centric ring
chromosome aberration
3.3
anticoagulant
drug which prevents blood from clotting
3.4
background frequency/level
spontaneous frequency (or number) of chromosome aberrations recorded in a general population
3.5
buffy coat
layer of an anticoagulated blood sample after centrifugation that contains most of the white blood cells
3.6
calibration curve
graphical or mathematical description of the dose effect relation derived by the in vitro irradiation of
blood samples to known absorbed doses
Note 1 to entry: The curve is used to determine, by interpolation, the absorbed radiation dose to a potentially
exposed individual.
3.7
centromere
specialized constricted region of a chromosome that appears during mitosis and joins together the
chromatid pair
3.8
chromatid
either of the two strands of a duplicated chromosome that are joined by a single centromere and
separate during cell division to become individual chromosomes
3.9
chromosome
structure comprised of discrete packages of DNA and proteins that carries genetic information, which
condense to form characteristically shaped bodies during nuclear division
3.10
chromosome aberration
change in the normal structure of a chromosome involving both chromatids of a single chromosome at
the same locus as observed in metaphase
3.11
colcemid
alkaloid compound that inhibits spindle formation during cell division
Note 1 to entry: It is used to collect a large number of metaphase cells by preventing them from progressing
to anaphase.
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3.12
complex aberration
aberration involving three or more breaks in two or more chromosomes and is characteristically
induced after exposure to densely ionizing radiation or high doses of sparsely ionizing radiation
3.13
confidence interval
range within which the true value of a statistical quantity lies with a specified probability
3.14
covariance
measure of the correlation of the variance between two (or more) dependent sets of data or parameters
3.15
decision threshold
value of the estimator of the measurand, which when exceeded by the result of the actual measurement
using a given measurement procedure of a measurand quantifying a physical effect, one decides that
the physical effect is present
Note 1 to entry: The decision threshold is defined such that in cases where the measurement result, y, exceeds
the decision threshold, y*, the probability that the true value of the measurand is zero is less or equal to a chosen
probability, α.
Note 2 to entry: If the result, y, is below the decision threshold, y*, the result cannot be attributed to the physical
effect; nevertheless it cannot be concluded that it is absent.
3.16
detection limit
smallest true value of the measurand which ensures a specified probability of being detectable by the
measurement procedure
Note 1 to entry: With the decision threshold (3.15), the detection limit is the smallest true value of the measurand
for which the probability of wrongly deciding that the true value of the measurand is zero is equal to a specified
value, β, when, in fact, the true value of the measurand is not zero
3.17
dicentric
aberrant chromosome bearing two centromeres derived from the joining of parts from two broken
chromosomes, generally accompanied by an acentric fragment
3.18
fluorescence in situ hybridization
FISH
technique that uses specific sequences of DNA as probes to particular parts of the genome, allowing
the chromosomal regions to be highlighted or “painted” in different colours by attachment of various
fluorochromes
3.19
fluorochrome
molecules that are fluorescent when appropriately excited
Note 1 to entry: They are used for FISH cytogenetics to highlight specific chromosomal regions.
3.20
genome equivalent
number of translocations that would be observed with all chromosomes painted, calculated from the
number of translocations detected with a limited number of painted chromosomes
3.21
insertion
chromosome rearrangement in which a piece of one chromosome has been inserted within
another chromosome
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3.22
interphase
period of a cell cycle between the mitotic divisions
3.23
linear energy transfer
LET
radiation energy lost per unit length of path through a biological material
3.24
metaphase
stage of mitosis when the nuclear membrane is dissolved, the chromosomes condensed to their minimum
lengths and aligned for division
3.25
protocol for aberration identification and nomenclature terminology
PAINT
terminology used in FISH analysis for describing chromosomal aberrations
3.26
precision
concept employed to describe dispersion of measurements with respect to a measure of location or
central tendency
3.27
proficiency test
evaluation of participant performance against pre-established criteria by means of interlaboratory comparisons
3.28
quality assurance
QA
planned and systematic actions necessary to provide adequate confidence that a process, measurement
or service satisfies given requirements for quality
3.29
quality control
QC
part of quality assurance intended to verify that systems and components conform with predetermined
requirements
3.30
radiation-induced translocation
among the observed translocations, the ones that can be attributed to a radiation exposure i.e. not
translocations induced by other sources (e.g. age, lifestyle factors)
3.31
ring
aberrant circular chromosome resulting from the joining of two breaks within one chromosome
Note 1 to entry: Rings can be centric or acentric.
3.32
service laboratory
laboratory performing biological dosimetry measurements
3.33
stable aberration
aberration which is not lethal to the cell and can be passed on to daughter cells (e.g. simple translocation)
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3.34
stable cell
cell without unstable aberrations, that may be entirely undamaged or contain stable type aberrations
only, and are likely to survive division
3.35
translocation
stable chromosome aberration in which parts of two or more chromosomes are exchanged
3.36
unstable aberration
aberration which is lethal to the cell (e.g. dicentrics/centric rings/acentric fragments)
4 Translocation assay by FISH
4.1 General
The frequency of chromosomal aberrations seen at metaphase in cultured human peripheral blood
lymphocytes is used for absorbed dose estimation after suspected exposure to ionizing radiation. This
document focuses on retrospective evaluation of exposures which occurred in the past or protracted
exposures where the dicentric assay (see ISO 19238) and the cytokinesis block micronucleus assay
(see ISO 17099) are not applicable due to the decrease in this type of damage over time. The aberrations
to be used are translocations and insertions in stable cells. For the application of this document, the
service laboratory shall choose which type of aberrations to score for the purpose of assessing absorbed
dose estimates and shall be consistent throughout.
It has been well established that the background translocation frequency in individuals varies with
age due to various confounding factors (i.e. nutritional status, genotoxic exposures, lifestyle factors,
malsegregation of sex chromosomes). This is an important consideration to take into account for
absorbed dose estimations using translocation analysis.
Hereafter, chromosome aberrations are referred to as translocations but may include insertions if
determined by the service laboratory.
4.2 Culturing and fixation
Similarly to ISO 19238, lymphocytes are cultured by a method that maximizes first-division
metaphases. This requires whole blood, or lymphocytes separated from the other blood components, to
be incubated in a culture medium containing a mitogen that stimulates lymphocyte cycling into mitosis.
For translocation analysis, cell cycle control is recommended. A mitotic blocking agent, colcemid, is
added to arrest and collect dividing lymphocytes in metaphase. The duration of the cell culture and the
timing of the addition of the arresting agent are optimized to ensure an adequate mitotic index.
Metaphases are recovered from the cultures, using a hypotonic salt solution and fixing in a mixture of
methanol and acetic acid. Fixed cells are dropped on microscope slides and stained. The exact protocol
for cell culture, harvesting metaphases, and staining employed by a service laboratory shall be formally
documented (See Clause 9).
4.3 Types of staining
Whole chromosome FISH staining shall be conducted and can involve one colour painting for all selected
chromosome pairs or two or three different colours, one for each pair of chromosomes selected. Painting
of three of the larger chromosomes covers about 20 % to 24 % of the total human DNA content, however
there are many choices of the number of fluorochromes and which chromosomes could be selected for
painting. It is recommended that chromosomes selected cover a large amount of DNA.
© ISO 2019 – All rights reserved
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Some examples are described below:
a)
one colour painting of three chromosome pairs [e.g. chromosome pairs 1, 4 and 8 all painted with
FITC (green)];
b) three colour painting of three chromosome pairs [e.g. chromosome pair 1 painted with Texas Red
(red), chromosome pair 2 painted with FITC (green) and chromosome pair 4 painted with FITC and
Texas Red (yellow)].
It is possible to increase the number of painted chromosome pairs to analyse a higher proportion of the
genome, but the staining of a few chromosome pairs is an efficient method in most cases.
All chromosomes should be counterstained with a fluorescent DNA dye such as DAPI
(4',6‑diamidino‑2‑phenylindole). The use of a pan-centromeric probe may also be added but is not
necessary for translocation analysis, when the centromeres can be clearly identified.
4.4 Scoring
Microscope slides containing stained cells are methodically scanned to identify suitable metaphase
cells. The frequency of translocations observed in an appropriate number of scored metaphase cells is
converted to an estimate of radiation dose by reference to calibration data.
There are many types of chromosomal aberrations visible with whole chromosome FISH including
stable and unstable, which should all be recorded during the scoring procedure. For the application
of this document, the focus is on the scoring of translocations in stable cells so that this method can
be applied to retrospective analysis of exposures that have occurred in the past. Therefore, it is
recommended that unstable aberrations detected in counterstained chromosomes should also be
recorded to determine whether the translocation occurs in a stable or unstable cell. To avoid slowing
down the scoring, the analysis of all the counterstained chromosomes can be performed only in cells
with stable aberrations visible in the painted chromosomes.
The service laboratory shall choose which chromosome pairs and type of aberrations to score for the
purpose of assessing absorbed dose estimates and shall be consistent throughout.
Metaphases selected for scoring should be well-spread and appear to be complete.
There are several aberration classification systems currently in use (e.g. PAINT)[3]. For the application
of this document, the service laboratory shall choose which type of scoring system to be used and shall
be consistent throughout. It is recommended that all visible damage be recorded but only translocations
in stable cells are to be counted for generating the calibration curve and providing absorbed dose
estimates. The information about the frequencies of all observed aberrations allows an opportunity for
further interpretation of the exposure conditions.
4.5 General requirement of the laboratory
The laboratory shall be well-equipped with the required standard laboratory equipment for lymphocyte
culture, cell processing, slide preparation, and fluorescence microscopy scoring of cells. The laboratory
should maintain QA documents, including those describing periodic calibration and maintenance of the
equipment used for cell culture as required.
5 Responsibility of the customer
This clause includes items that are not controlled by the laboratory. Prior to blood sampling,
coordination between the customer and the service laboratory should occur. Essential requirements
should be explained to the customer and this should be by a standardised instruction sheet as illustrated
in Annex A. The essential features are:
a)
6
blood sampling shall use a collection system, containing lithium or sodium heparin as the
anticoagulant, which has been sent or specified by the service laboratory;
© ISO 2019 – All rights reserved
BS ISO 20046:2019
ISO 20046:2019
b) blood shall be collected (ideally about 10 ml), labelled accurately and unambiguously, maintained
between 6 °C and 30 °C and sent to the laboratory as soon as possible (ideally within 48 h);
c)
precautions to ensure the integrity of the container and to prevent leakage during shipment shall
be observed. Blood samples should be kept between 6 °C and 30 °C during shipping. A temperature
recorder should be included to monitor the temperature during shipment. Packaging and labelling
shall conform to national and international regulations. If air transportation is involved, a physical
dosimeter shall be included to monitor whether the sample was irradiated in transit;
d) a questionnaire provided by the laboratory shall be completed accurately and returned promptly;
particularly listing previous medical or occupational radiation exposures (see Annex B).
Accurate biological dosimetry is limited for patients who have received a previous unknown
medical exposure;
e)
the laboratory shall be alerted of biologically contaminated and/or infectious samples.
6 Responsibility of the laboratory
6.1 Setup and sustainment of the QA program
The laboratory shall establish and maintain a QA program (see Clause 14), which covers all aspects of
the service. The QA program should address the following issues:
a)
the laboratory’s QA program shall include periodic internal checks of equipment operations,
reagent suitability, and various performance checks (i.e., intra-laboratory comparisons, operator
qualifications, sample protocol, scoring, absorbed dose estimations, report generation, etc.);
b) the laboratory’s QA program shall include periodic external checks of the laboratory’s operations.
The external audits shall include a review of the service laboratory’s documentation of equipment
operations, reagent suitability, and various performance checks (i.e., inter‑laboratory comparisons,
operator qualifications, sample transport integrity, etc.).
The laboratory shall establish the frequency of these QA checks.
6.2 Responsibility during service
The service laboratory shall provide necessary guidance, procedures, and reporting to provide
absorbed dose assessment by cytogenetic analysis in response to a request for service. The service
activities shall address the following issues:
a)
the laboratory shall have documentation, reviewed and endorsed by a designated, competent
person including the following:
1) an instruction sheet to be sent to the customer describing shipping procedures (see Annex A);
2) a questionnaire that shall elicit patient consent and information on whole or partial body
exposure, source and quality of the radiation, circumstances of the exposure, exposure location
(country, city, company, etc.), date and time of exposure, previous occupational or medical
exposures to radiation, intake of pharmaceuticals, infection, smoking habit, and significant
exposures to any other DNA damaging agents (such as organic solvents or heavy metals)
(see Annex B);
3) step by step procedures for processing the blood sample from receipt of the sample to reporting
of the absorbed dose;
b) if required, a blood collection system (10 ml) containing lithium or sodium heparin as the
anticoagulant shall be sent to the customer, also including the appropriately labelled and addressed
packaging material for the return of the sample to the service laboratory. The packaging shall
conform to national and/or international regulations for the transit of potentially infectious
pathological specimens (see 14.2.4);
© ISO 2019 – All rights reserved
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c)
after receipt of the blood sample, the following steps shall be performed:
1) document the receipt of the blood sample (date, time, consignee);
2) blind code the blood sample;
3) document the place of storage until the setting up of cultures;
4) set up cultures in parallel as soon as possible and document date, time and operator;
5) document, with lot numbers as appropriate, all reagents used for culturing;
6) document addition of reagents and end of culture (date, time, operator);
7) document short- and long-term storage of sample until slide making;
8) document slide codes, number of slides and location of storage;
9) document the results from scoring;
10) store slides and case documents in an appropriate place for a time period defined by the
laboratory for possible medico-legal re-evaluation of the case;
d) the service laboratory shall interpret results and prepare reports (see Annex C);
e)
the service laboratory shall sustain a dialogue with the requestor, reprioritizing cases as required,
and providing results to the requestor.
7 Confidentiality of personal information
7.1 Overview
Biological dosimetry investigations made by the laboratory shall be undertaken in accordance with
national regulations regarding confidentiality. This would normally include the maintenance of
confidentiality of the patient's identity, medical data and social status. In addition, the commercial
confidentiality of the patient's employer and any other organizations involved in a radiological
accident/incident should be observed.
This requirement extends to
a)
written, electronic or verbal communications between the laboratory and the person/organization
requesting the analysis and receiving the report, and
b) the secure protection of confidential information held within the organization where the service
laboratory is located.
7.2 Applications of the principle of confidentiality
7.2.1
Delegation of responsibilities within the laboratory
The head of the laboratory may authorise a limited number of laboratory staff to deal with documents
related to the analysis. Persons with this authority shall have signed a commitment to confidentiality
regarding their duties within the laboratory.
The laboratory shall maintain the signed confidentiality agreements and ensure the security and safety
of all confidential documents.
8
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7.2.2
Requests for analysis
Depending on national regulations, the request for an analysis should normally be made by a doctor
representing the patient, by the patient him/herself or could be requested due to legal claims. In most
cases the blood sampling for chromosome analysis shall be made with the patient’s informed consent.
The laboratory, depending on the national regulations, may be required to maintain the record of the
patient's informed consent.
7.2.3
Transmission of confidential information
Whatever the chosen means of communication, confidentiality shall be ensured during the exchange of
information and reports between the service laboratory and the requestor of the analysis.
The laboratory needs to define all processes for information transmission and assurance of
confidentiality.
7.2.4
Anonymity of samples
The laboratory needs to have established protocols for maintaining the anonymity of samples. To avoid
the identification of the patient while guaranteeing the traceability of the analysis, the blood samples
should be coded upon arrival in the service laboratory. The coding is performed in an unambiguous
way according to a standard procedure. The same code is to be used for all stages of the analysis. The
code is assigned by an authorized person as defined in 7.2.1. Decoding, interpretation of results and
compiling the report are also to be performed by an authorized person.
7.2.5
Reporting of results
The final report containing the results and their interpretation (when needed) is communicated to
the requestor of the analysis and those so specified in the signed informed consent form. Depending
on national regulations, further copies may, with appropriate approvals, be passed to other
responsible persons.
7.2.6
Storage of data and results
The laboratory shall define how data and results are stored. All laboratory documents relating to a
case and which could permit the patient and/or employer to be identified shall be stored in a place
only accessible to the authorized persons. Documents shall be retained in an appropriate place for a
time defined by the laboratory for possible medico-legal re-evaluation of the case. Final disposal of
documents shall be by secure means such as shredding.
8 Laboratory safety requirements
8.1 Overview
Staff shall conform to their national legislation and institutional regulations regarding safety in the
laboratories. There are some particular features concerning safety in service laboratories that are
worth highlighting. These include microbiological, chemical, and optical considerations.
WARNING — The use of this document can involve hazardous materials, operations and
equipment. It does not purport to address all of the safety or environmental problems associated
with its use. It is the responsibility of users of this document to take appropriate measures
to ensure the safety and health of personnel and the environment prior to application of the
document and fulfil statutory and regulatory requirements for this purpose.
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8.2 Microbiological safety requirements
Handling human blood poses some risk of blood-borne pathogens being transmitted to laboratory staff.
All specimens shall be regarded as being potentially infectious even if they are known to be derived
from apparently healthy persons. Staff should be offered available vaccinations against appropriate
blood-borne diseases.
8.3 Chemical safety requirements
Certain chemicals and pharmaceuticals are routinely used in the procedures covered in this document.
When present in cultures or used in staining procedures they are mostly used in small volumes
and in dilutions that generally present no health hazard. They are however prepared and stored in
concentrated stock solutions. The main reagents of concern and their internationally agreed upon
hazard statements (H-Statements) according to the GHS classification system are listed in Table 1 with
the key to the H-statements in Table 2. Note that commercially available products may vary depending
on the physical form/quantity/composition — always check the hazard and precautionary statements
on safety data sheets available from suppliers for your own reagents.
Table 1 — List of reagents and corresponding hazard statement
Reagent
Hazard Statement
4',6-diamidino-2-phenylindole (DAPI)
H315, H317, H335
Colcemid
H300
Acetic Acid
H226, H314
Benzylpenicillin
H317, H334
Ethanol
H225, H319
Formamide
H351, H360, H373
Hoechst stain (Bisbenzimide)
H302, H315, H319
Methanol
H225, H301, H311, H331, H370
Propidium iodide
H315, H319, H335, H341
Phytohaemagglutinin (PHA)
Streptomycin sulphate
H302, H317, H332
H302, H361
Table 2 — Key to hazard statements
Hazard Statement
H225
H226
H300
H301
H302
H311
H314
H315
H317
H319
H331
H332
H334
H335
H341
10
Key
Highly flammable liquid and vapour
Flammable liquid and vapour
Fatal if swallowed
Toxic if swallowed
Harmful if swallowed
Toxic in contact with skin
Causes severe skin burns and eye damage
Causes skin irritation
May cause an allergic skin reaction
Causes serious eye irritation
Toxic if inhaled
Harmful if inhaled
May cause allergy or asthma symptoms or breathing difficulties if inhaled
May cause respiratory irritation
Suspected of causing genetic defects
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Hazard Statement
H351
H360
H361
H370
H373
Key
Suspected of causing cancer
May damage fertility or the unborn child
Suspected of damaging fertility or the unborn child
Causes damage to organs
Causes damage to organs through prolonged or repeated exposure
8.4 Optical safety requirements
When ultraviolet lamps are used in sterilising the interior of microbiological safety cabinets or exposing
slides during the FISH with harlequin staining procedure, shielding and working procedures shall be in
place to avoid direct irradiation of the skin or eyes of laboratory staff.
8.5 Safety plan
The laboratory shall define written safety procedures for protection against microbiological, chemical,
and optical hazards.
The laboratory shall maintain a record of accidents and protocols or procedures to avoid repeating
similar accidents.
9 Sample processing
9.1 Culturing and staining
The same culturing conditions shall be used for establishing the calibration curve as for analysing
aberrations in a case of suspected overexposure.
The exact protocol for the translocation by FISH assay shall be established by each laboratory and there
are several critical aspects that shall be adhered to as listed below:
a)
for calibration curves, blood shall be incubated for a minimum of 2 h at 37 °C immediately following
irradiation and prior to culture;
c)
the culture vessels shall be sterile and used in a way to avoid microbial contamination;
e)
a mitogen (e.g. PHA) shall be added to the media to stimulate lymphocytes into mitosis;
b) cells shall be cultured at 37 °C ± 1 °C either as whole blood, as enriched lymphocyte suspension
(buffy coat) or isolated lymphocytes;
d) specific culture media that allows peripheral blood lymphocytes to proliferate shall be
used. For example RPMI-1640, Ham’s F10, MEM, or McCoy supplemented with Foetal
Bovine Serum (FBS) between 10 % and 20 % 200 mM L-glutamine, and Penicillin/Streptomycin
(100 IU·ml−1/100 μg·ml−1) is commonly used;
f)
colcemid shall be added, at a time and concentration determined by the laboratory, to the cell
culture to block cells in mitosis;
g) cells are centrifuged in order to separate the cells from the medium. Thereafter, cells shall be
treated with a hypotonic solution such as 0,075 mol/l KCl for 10 min to 15 min to swell the cells
prior to fixation;
h) after centrifugation the supernatant shall be removed and cells shall be fixed in freshly prepared
fixative solution (i.e., 1:3 acetic acid:methanol) and washed 3 or 4 times with the fixative until the
cell suspension is clear;
i)
if storage of fixed cells is required then cell suspensions shall be kept in a −20 °C freezer;
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j)
slides shall be prepared to allow an unambiguous identification of chromosomal aberrations.
Humidity and temperature conditions can be adjusted to improve the quality of the metaphases;
l)
slides shall be stored below 4 °C.
k) slides shall be stained according to protocols established in each laboratory;
9.2 Scoring
9.2.1
9.2.1.1
Criteria for scoring
Coding of samples and slides
All samples, slides, and intra- or inter-laboratory validation standards shall be coded. Complete records
of coding shall be maintained.
9.2.1.2
Scoring techniques
The laboratory shall establish and implement procedures for the scoring techniques used. When scoring
is at least partially performed with computer assisted metaphase finding and/or image analysis, the
system used should have been previously subjected to QA trials with results documented.
Methodical scanning of slides is crucial to ensure complete analysis without scoring any cell more than
once. It is recommended that more than one slide be scored for each sample.
It is standard practice in service laboratories for all chromosomal aberrations to be recorded regardless
of whether the cell is stable or unstable. It is recommended that only translocations in stable cells be
used for creating the calibration curve if it is to be used for retrospective biodosimetry. Alternatively
laboratories can use their own established procedures suitable for the case being analysed.
Translocations are used for absorbed dose estimation and can be described as simple or complex, the
latter defined as when three or more breaks in two or more chromosomes are required to produce the
observed chromosome aberration(s). However, painting a subset of chromosomes does not allow the
origin of all the rejoined portions to be identified; therefore simple aberrations can only be considered
as “apparently” simple. All types of translocations in stable cells may be used in the absorbed dose
estimate as long as the same types of translocations are consistently used. If complex aberrations
are included in the calibration curve, they shall be converted into the equivalent number of simple
translocations according to the defined laboratory rules.
There are several aberration classification systems currently in use. For example, in the PAINT system,
a two-way translocation between a painted chromosome and a counterstained one is described as t(Ab)
plus t(Ba) and scored as one translocation where A and a represent the counterstained material and
B and b represent the painted material. In this scoring system the capital letter refers to the part of
the chromosome containing the centromere and the small letter refers to the part of the chromosome
not containing a centromere. Sometimes all exchanges are not visible, and only a t(Ba) or a t(Ab) is
visible in the metaphase. These aberrations can also be stable and are named as incomplete or oneway translocations. The main reason of this type of one-way aberration is the resolution limit of the
painting techniques, where the corresponding piece is too small to visualize. A dicentric formed by a
painted and a counterstained chromosome is described as dic(AB) ace(ab).
A standardised scoring sheet shall be used with data recorded such that the number of aberrations in
each cell scored is derivable. An example is shown in Annex D.
9.2.2
Conversion of translocation frequencies to genome equivalence
In order to be able to compare data from different sets of chromosomes, it is appropriate to apply
genome equivalent corrections to the translocation frequencies. Depending on the data available at the
laboratory level this should be done to both the calibration curve data (before curve fitting) and also to
the observed yield of excess (radiation induced) translocations. In this case, the Lucas formula[4] should
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be applied, to calculate the proportional number of aberrations that would have been observed if the
full genome had been painted, according to Formula (1):
f P / f G = 2 , 05
where
fP
fG
Fi
∑ i Fi (1 − Fi ) − ∑ i < j Fi F j
(1)
is the translocation frequency measured by FISH;
is the full genome equivalent translocation frequency;
is the fraction of the genome painted each colour i, which can be taken from IAEA (2011)[5].
The calculation can be implemented in freely available software tools produced in the community[6][7].
In each case, a consistent approach between calibration and scoring of a suspected overexposure case
should always be applied.
10 Background levels of translocations
For the purpose of radiation biodosimetry using translocation frequency in lymphocytes, it is assumed
that an individual’s base-line translocation frequency value prior to the ionizing radiation exposure
event is equivalent to the mean translocation frequency value of unirradiated cells for their age. Ideally
the data set of background translocation frequencies would include results for at least three age groups
separated into 1 to 25, 26 to 50, 51 to 80 years and include at least 5 individuals in each group to include
base-line values across different age groups.
In the absence of a laboratory having their own local age-background information, a comprehensive
meta-analysis published by Sigurdson, et al. 2008[8] currently provides the best international database,
broken down by age, gender, race and smoking habits. From this study, it appears clearly that age is the
major factor that determines the background frequency of translocations. This study includes a large
number of individuals for each age group. Therefore they can be used as a control value assuming:
— the mean frequency of translocation of this publication has been confirmed at least by two samples
from two different age groups. If no deviation is detected between the published data and the sample
tested, the published data can be used as the control by the service laboratory;
— the reference to such published data is mentioned in the report.
Whatever the approach used, it is recommended to score at least 500 genome equivalent cells per donor
or 100 translocations [see Formula (1)].
As many confounding factors can create translocations which persist over time, a precise questionnaire
including any known relevant genotoxic exposures, particularly prior medical radiological exposures,
shall be established. The retrospective absorbed dose estimation is not possible when a potential
exposed person has undergone radiotherapy in the past, and due consideration of accumulated past
exposures should be undertaken for absorbed dose assessment for radiation workers.
11 Calibration curves
11.1 Calibration source(s)
The laboratory shall provide a report, reviewed and endorsed by a competent person (i.e., radiation
physicist or the laboratory) that addresses the following issues:
a)
description of radiation quality [e.g. Philips X-ray machine with a 2,1 mm Cu half value layer (HVL),
250 kVp, filament current 12,5 mA, and a source-to-surface distance (SSD) of 50 cm] for all radiation
source(s) used to generate in vitro calibration curves;
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b) characterization of the radiation source(s) used to generate each in vitro calibration curve and
traceability to a national/international radiation standard;
c)
description of the dosimetry protocol including details of the quantity that has been measured,
the procedure to certify that the dosimetry method is calibrated to a standard, the method used to
measure dose uniformity in the experimental array, and the written procedures and documentation
to verify dose and dose-rate determinations for individual experiments;
d) provision of a summary dosimetry report for each calibration-source dose-response curve.
For more details on irradiation parameters and conditions please refer to the IAEA manual[5].
11.2 Establishment of calibration curve(s)
The selection of the radiation sources for calibration curves should reflect the most likely cases that
are analysed. It is important to ensure that the interpretation of the results takes into account the
quality of radiation of the calibration curve. Typically acute dose-rates of above 0,1 Gy/min should
be chosen and the calibration source shall be traceable to national standards. The calibration curve
can be fitted for simple observed or genome equivalent translocations (see 9.2.2), whether one or two
way translocations, or total translocations present in stable cells. The laboratory decides which type
of translocation is used assuming the calibration curve is established under the same experimental
conditions and identical expertise assessment.
A minimum of 7 doses should be selected with at least 5 doses below 1 Gy including 0 Gy. The typical
doses for a calibration curve range from 0,1 Gy to 3 Gy for low-LET radiation (e.g. photons). The selection
of these two dose points is important because they define the lowest and highest dose the laboratory is
allowed to report.
For high-LET radiation (e.g. neutrons), the upper dose limit is typically 1 Gy due to the high level of
damage to cells at higher doses. It is recommended that 500 genome equivalent cells be scored.
For low-LET radiation, it is recommended that for absorbed doses under 1 Gy, 2 000 genome equivalent
cells be scored. For absorbed doses over 1 Gy, scoring 500 genome equivalent cells is recommended.
Increasing numbers of cells scored reduces the uncertainty in the absorbed dose estimates.
In order to minimise the uncertainties associated with age correction (see 12.1.4), the simplest
recommended method is to fit multiple calibration curves based on individuals from multiple age groups.
The following definitions are used for further calculations:
— y: observed translocations: The absolute number of translocations observed in n1 genome
equivalent cells
— μ: observed translocation yield: The observed number of translocations per genome equivalent cell
without background correction
— y′: excess translocations: The absolute number of translocations in n1 genome equivalent cells
corrected for background translocations
— μ′: excess translocation yield: The observed number of translocations induced by radiation per
equivalent cell; the translocation yield corrected for background translocations
The observed yield of translocations, μ, (or μ′, if preferred) should be fitted to the linear or linearquadratic models [Formula (2)].
(
)
µ = C ( ± SE C ) + α ( ± SE α ) D + β ± SE β D 2
14
(2)
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with µ =
y
.
n1
According to the IAEA manual, the lower and upper 95 % confidence limits of the curve can be calculated
by the equation:
µ = C + α D + β D2 ±
R ² var ( C ) + var (α ) D ² + var ( β ) D 4 + 2covar ( C ,α ) D + 2covar ( C , β ) D ² + 2covar (α , β ) D 3
where
D
α, β, C
SE
R2
var
covar
(3)
is the absorbed dose;
are coefficients of the fit to the linear-quadratic model;
is the standard error of the coefficients;
is the coefficient of determination, and is the 95 % confidence limit of a chi-square distribution, χ2
(degrees of freedom, 95 %), with 2 or 3 degrees of freedom. For a linear-quadratic curve (degrees of
freedom = 3) χ2 is 7,81, and for a linear curve it is 5,99;
is the variance of the coefficient in brackets;
is the covariance of the two coefficients in brackets, available from most standard software packages.
The statistical significance of the coefficients should be tested with an F-test. For a linear-quadratic
model, it is important that both the α and β coefficients are statistically significant. As the LET increases,
the β coefficient tends towards zero, once it is no longer statistically significant the linear model should
be used, in which case the data should be fitted to a linear model, excluding βD2 from Formula (2).
Two methods are proposed for curve fitting, the iteratively reweighted least squares method and
the maximum likelihood method (see Annex E maximum likelihood method)[9][10]. As a minimum
requirement, when the obtained value of chi‑squared is higher than the degrees of freedom, standard
errors should be increased by (chi-square/degree of freedom)1/2. Other consistent methods can be
applied as long they have been validated.
The laboratory should use documented and validated curve fitting software. Several such software
packages have been developed by the international biological dosimetry community and are freely
available[6][7]. Others, including commercially available software tools, can be found through open
literature and the Web. Whichever software is used, validation should include testing against
published data.
The laboratory shall provide a report, reviewed and endorsed by a designated, competent person that
addresses the following issues:
a)
describing the experimental exposure set-up (sample holder, temperature control, etc.) and
procedures to verify reproducibility of exposure set-up for individual experiments;
b) detailing the in vitro calibration data and their fit to a calibration curve. Goodness of fit, significance
of the fitted linear and quadratic coefficients, and uncertainty estimates should also be reported.
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12 Criteria for converting a measured aberration frequency into an estimate of
absorbed dose
12.1 Determination of estimated whole-body absorbed dose and confidence limits
12.1.1 General
Several factors need to be taken into account when determining the absorbed dose using translocation
frequency including age, time delay between exposure and analysis, occupational exposures to
chemicals and other confounding factors. All of these factors can increase the uncertainty of the
absorbed dose estimate and shall be considered on a case by case basis.
Where sufficient information is available, the service laboratory shall provide the estimated whole
body absorbed dose and confidence limits in result reports. Uncertainties should be expressed in terms
of the combined standard uncertainty (combined standard deviation) and expanded uncertainty: 95 %
confidence limits. Note that uncertainties should be propagated throughout the analysis according
to the ISO/IEC Guide 98‑3[11]. Other characteristic limits (the decision threshold and detection limit)
or confidence percentage values should also be reported, if appropriate to each particular case, as
discussed below.
12.1.2 Comparison with the background level: Characterisation of the minimum detectable dose
In ISO 11929 two characteristic limits are defined:
— the decision threshold ( yd) or minimum resolvable number of translocations, which is the threshold
above which the physical effect is assumed to be quantifiably present. In other words, the decision
threshold can be understood as the minimum number of translocations that is significantly
different from the expected background number of translocations for a given significance level α
(e.g. α = 0,05).
— the detection limit ( yz) is the smallest true value of the measurand (number of translocations), which
can be detected. It gives information on the practical operating range of the assay and is thus used
to assess whether the measurement procedure is appropriate in a particular set of circumstances.
The decision threshold and the detection limit should be calculated before the measurement
is performed.
Table 3 — Error rates for the inference of positive and negative conclusions
Inferred conclusion
True
state
Test person
exposed
H0 false
Test person not
exposed
H0 true
Test person
exposed
H0 rejected
True positive
Type 1 error
α
2
False positive
Test person not
exposed
H0 accepted
Type 2 error
(β)
False negative
True negative
If a test person shows a number of translocations greater than the decision threshold, the null
hypothesis (H0) that the test person was not exposed or that the observed translocation yield is equal
α
to the background translocation yield, can be rejected with a type 1 error rate , and it is concluded
2
that the physical effect is present, therefore a dose estimate should be made. If the observed number of
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translocations, y, is below the decision threshold, yd, it is decided that the result cannot be attributed to
the physical effect, i.e. it cannot be concluded that the person was exposed. Nevertheless, depending on
the unknown true state (see Table 3) the probability for a false negative result might still be relatively
high and, therefore, it cannot be concluded that the person was not exposed (see Figure 1). In cases
where the observed number of translocations is below the decision threshold, the detection limit shall
be reported. The detection limit provides valuable information about the true dose (or number of
translocations) above which fewer than 100·β % false negative results are expected. The detection limit
can be interpreted in the following way: Given that a test person was exposed (true state, see Table 3), if
the true dose/translocation number of the test person was higher than the detection limit, the
probability of observing a translocation number lower than the decision threshold and thus inferring a
false negative conclusion would be less than β.
Key
1
2
H0 accepted
H0 rejected
sampling distribution under H0
decision threshold yd
sampling distribution under H1 (mean at yd)
sampling distribution under H1 (mean at yz)
detection limit yz
Figure 1 — Illustration of the decision threshold and the detection limit (μ0 = const)
Top panel: Given the null hypothesis H0 (test person not exposed) is true (i.e. translocation yield µ of
the test person is equal to the background translocation yield μ0), the probability for wrongly rejecting
α
H0 or for observing a translocation number that exceeds the decision threshold ( yd) is less than .
2
Bottom panel: Given that the alternative hypothesis H1 (test person exposed) is true, if the true dose or
the true number of translocations, respectively, is equal to the decision threshold ( yd), the probability
for wrongly accepting H0 is approximately 0,5 (light gray area under the curve
). If the true dose
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or the true number of translocations, respectively, is greater than the detection limit, the probability
for wrongly accepting H0 is lower than a predefined type 2 error rate β (e.g. β = 0,1).
To define the decision threshold it is assumed, that the test person has not been exposed, i.e. the
translocation yield of the test person μ is equal to the background translocation yield μ0( j) for a person
of j years old. The null hypothesis is given by μ = μ0( j) [or n1μ = n1μ0( j)], respectively. Assuming that
the background translocation yield is constant, i.e. has no uncertainty, the decision threshold, yd, can be
defined by the following probability:
∞
∑ k = yd +1
P y > y d n1 µ = n1 µ 0 ( j ) =
=1−
where
n1
α
y
e
∑ k =d0
− n1 µ 0 ( j )
e
n1 µ 0 ( j )
k!
− n1 µ 0 ( j )
k
(4)
k
n1 µ 0 ( j )
α
≤
k!
2
is the number of genome equivalent cells for the test person;
is the probability for a type 1 (false positive) error, which is generally taken to be 5 %.
Assuming that the number of background translocations is Poisson distributed, i.e. the background has
µ
an uncertainty, the null hypothesis can be defined by
= 1 and the decision threshold can be
µ0 ( j )
obtained by solving the following formula for yd.
P y > y d µ = µ 0 ( j ) = 1 −
where
n0
n0 µ 0 ( j ) + y d + 1
k
∑
k
n0 µ 0 ( j ) + y d + 1 n1
n1
1−
k =0
n1 + n0
k
n1 + n0
yd
n0 µ 0 ( j )+ y d +1−k
≤
α
(5)
2
is the number of genome equivalent cells for the background data;
is the relevant binomial coefficient in this case.
Again, assuming that the translocation number of the test person follows a Poisson distribution, the
detection limit for the number of translocations, yz, is defined by the following formula:
P y < y d n1 µ = y z =
∑
e − y z y zk
=β
k =0
k!
yd
The latter [Formula (6)] can be solved analytically using
yz =
18
(6)
χ2
2( y d +1) ,1− β
(7)
2
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where
χ2
is the chi-squared quantile (the inverse of the chi distribution);
β
is the type 2 (false negative) error, which would generally be between 5 % and 20 %;
2( yd + 1) are the respective degrees of freedom.
A detailed example for the calculation of the decision threshold and detection limit can be
found in Annex F.
Indeed, for the FISH translocation assay, the decision threshold and detection limit are a function
of number of factors including the laboratory’s measured or chosen control background levels of
translocations, the age of the suspected exposed individual and the number of cells chosen for analysis.
It is thus necessary to assess the detection limit and decision threshold on a case by case basis. The
detection limit can be converted to a ‘minimum detectable dose’ by application of the calibration curve,
according to 12.1.5 below. However, in all cases, the minimum detectable dose is limited to the lowest
dose used in the appropriate calibration curve.
If the observed number of excess translocations does exceed the decision threshold, this means that
there is evidence to refute the null hypothesis of no significant difference between the expected and
observed numbers of translocations. The calculation of observed absorbed dose should then be carried
out and reported according to 12.1.5. If not, then the detection limit should be reported.
If the true number of translocations is higher than the detection limit (or the true dose is higher than
the minimum detectable dose), the probability of observing a lower number of translocations than the
decision threshold (or the probability to infer false negative conclusions) is lower than β.
12.1.3 Confidence limits on the number of translocations
There are several methods for deriving confidence limits on an observed number of translocations.
Confidence limits on Poisson observations may be obtained from standard tables, by exact or
approximate calculations. If a measured aberration is over-dispersed (see ISO 19238) with respect to
Poisson, the Poisson-derived uncertainty should be increased by the square root of the ratio of variance
to mean or a more appropriate model should be used to describe the distribution of aberrations
(see 11.2). Alternatively, for over dispersed data, more appropriate distributions can be applied, such
as the negative binomial or Neyman type A distribution, in order to take into account both the mean
yield of aberrations and the dispersion coefficient[13]. The laboratory shall provide justification for and
validation of the chosen model(s).
The exact Poisson observed number can be calculated as:
yL =
yU =
χ 22 y ,α /2
2
χ 22
( y +1),1−α /2
(9)
2
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(8)
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where
χ2
α/2
is the chi-squared quantile (the inverse of the chi distribution);
1 − α/2
is the upper tail probability (usually 0,975);
2y or
2( y + 1)
is the lower tail probability (usually 0,025 for α = 0,05);
are the respective degrees of freedom.
The following formulae for the normal approximation to the 95 % confidence limits of the translocation
yield and number of translocations for a test person can be used if the number of cells is large.
µ L = µ − 1 , 96
µ
and y L = n1 µ L
n1
µ U = µ + 1 , 96
µ
and y U = n1 µ U
n1
(10)
(11)
The confidence limits for the adjusted (excess) number of translocations of a test person at age j years
can then be calculated according to Formula (13).
12.1.4 Adjustment for background yield
As described in Clause 10, the background levels of translocations increase with age due to confounding
factors. For this reason, once the measurement has been carried out, the background level of
translocations should be adjusted for the age of the individual and this value is required to convert the
observed yield to absorbed dose (see 12.1.5).
As described above, ideally, the calibration curve data should be based on one or several individuals
of a similar age. Then, it is strongly recommended, that age adjustments are performed after the
curve fitting and after uncertainty estimation for the unadjusted number of translocations of the test
person. If uncertainties are directly estimated on the adjusted (excess) number of translocations, y′, the
uncertainties are underestimated. If the data for the calibration curve and the test person are based on
different age groups, the data shall be adjusted to ensure that the dose estimates are being made based
on a curve that is appropriate to the age of the test person. This can be accomplished by making age
adjustments for both the calibration curve and the test person or by making age adjustments only to
the curve to match the age of the test person (as in example in Annex F). The laboratory should decide
on the most appropriate analysis method: ideally, age should be included into the calibration model as
an additional covariate.
Further, ideally, the uncertainties of the age specific background should be included into the process
of uncertainty estimation. However, assuming that a large enough amount of information is available
on age-specific background rates, so that the uncertainty on the age specific background yield tends
to zero, the background yield at the age corresponding to the data used to obtain the calibration
curve (= k years) and at the age (= j years) of the test person can be approximated by constants, i.e.
μ0(k) = const and μ0( j) = const.
In the ideal situation, the adjustment for age of the test individual should be based on the laboratories’
own local age-background information, otherwise on the information from Sigurdson, et. al., 2008[8].
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Either data from Table 3 of Sigurdson, et. al., 2008[8] or the given fitted relationship between age, j, and
background yield of translocations can be used:
(
µ 0 ( j ) = e −7 ,925 + e −9 ,284 j ⋅ e j⋅0,010 62
)
(12)
where μ0( j) is the age specific background translocation yield per cell equivalents (including both oneway and two-way translocations) and age, j, is in years.
For converting the number of translocations of the test person to dose, the age adjusted (excess)
translocation number, y′, is then calculated according to:
y ′ = n1 µ − µ 0 ( j )
with the lower and upper confidence limits of the adjusted (excess) number of translocations:
y L′ = y L − n1 ⋅ µ 0 ( j ) and y ′U = y U − n1 ⋅ µ 0 ( j )
where
yL, yU
y′L, y′U
(13)
(14)
are the lower and upper confidence limits of the unadjusted number of translocations in n1 genome
equivalent cells;
are the lower and upper confidence limits of the adjusted (excess) number of translocations in n1
genome equivalent cells.
Based on the fit of the unadjusted calibration curve from Formula (2), we obtain the age adjusted
calibration curve:
µ ′ = µ − µ0 (k ) = C + α D + β D2 − µ0 (k )
where the lower and the upper confidence limits can be approximated by
µ ′ = C + α D + β D2 − µ0 (k ) ±
R 2 var ( C ) + var (α ) D 2 + var ( β ) D 4 + 2covar ( C ,α ) D + 2covar ( C ,β ) D 2 + 2covar (α ,β ) D 3
12.1.5 Calculation of absorbed dose
(15)
(16)
If the observed excess number of translocations satisfactorily exceeds the decision threshold as defined
above, then the absorbed dose should be calculated by comparison with an appropriate calibration
curve, created as described in 11.2, and defined by Formula (2). It shall be ensured that the data used for
the estimation of the calibration curve is representative for the test person and that confounding factors
(e.g. factors influencing the background translocation rate) have been accounted for appropriately as
described in 12.1.4. The absorbed dose, D, is calculated by solving the linear or quadratic equations
which is possible using the freely or commercially available software tools[6][7]. The information on
how the calculations are performed within the software should be documented and updates performed
periodically.
It is important to reiterate that the calibration curve and the number of translocations of the test person
shall be adjusted for the corresponding age (and any other appropriate factor) related background
levels as described in Formulae (13) and (15), respectively, according to the documented standard
procedures of the laboratory.
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A point estimate for the absorbed dose based on age adjusted data can be obtained by solving
the equation:
{
}
−α + α 2 + 4 β µ − µ 0 ( j ) − C − µ 0 ( k )
D=
2β
where
C, α, β
µ
µ0(j)
µ0(k)
(17)
are the coefficients of the unadjusted calibration curve;
is the observed unadjusted translocation yield of the test person;
is the background translocation yield at the age of the test person (= j years);
is the background translocation yield at the age corresponding to the data used to obtain the
calibration curve (= k years).
If C − µ0(k) < 0, zero or a small positive value shall be used instead [e.g. C − µ0(k) = 0,001].
In normal circumstances, calibration curves should be fitted according to the standard scoring practice
of the laboratory, i.e. using total numbers of aberrations amongst the painted chromosomes.
12.1.6 Calculation of uncertainty on absorbed dose
The resulting estimated absorbed dose represents the best estimate possible given the associated
dispersion, which arises from the experimental and intrinsic uncertainties. It is thus necessary to
estimate measurement uncertainty using appropriate methods.
The general procedure for assessing uncertainty relies on formal combination of all the sources of
experimental uncertainty according to standard methods of error propagation (ISO/IEC Guide 98‑3).
In brief, the relationship between the absorbed dose and the input quantities should first be clearly
defined, the sources of uncertainty relevant to the particular case should be identified and quantified,
then the combined uncertainty should be calculated (see ISO 5725‑1).
In practice, the recommended methodology to calculate uncertainty on absorbed dose in the context
of the FISH translocation assay is to combine the confidence limits on the translocation frequency with
the uncertainties on the calibration curve coefficients [see Formula (2)] which in many cases represent
the dominant sources of uncertainty. This can be achieved by using Merkle’s method[5] based on
Formulae (13) to (16) or using the current version of Dose Estimate which is based on Formula (17).
However, the uncertainty associated with an assessment varies widely depending on a large number
of factors, including the necessary age adjustment. As such, it is recommended that the uncertainty
is assessed according to the above procedure on a case by case basis. The laboratory shall define the
methods used to determine confidence limits. The service laboratory shall report the method used to
determine the standard uncertainty (the standard deviation) and the expanded uncertainty (which
gives the 95 % confidence interval). The laboratory should also retain records of the uncertainty
budget (a list of the uncertainty components and how they were evaluated) together with details of any
systematic uncertainties accounted for and all other corrections and constants employed (See Annex F
for example).
12.1.7 Acute and non-acute exposure cases
If an overexposure is known to have been received acutely i.e., below 0,5 h, the absorbed dose estimate
may be obtained by reference to an acute in vitro calibration curve where one is scoring translocations
in stable cells. For a linear-quadratic dose-response relationship, the absorbed dose is estimated by
solving the quadratic Equation utilising the calibration curve coefficients and observed yield. If an
overexposure is known to have been protracted, the absorbed dose estimate may be obtained by
reference to just the background level and linear coefficients of the acute calibration curve. As with
curve fitting, most of the freely available bespoke software packages developed by the international
biological dosimetry community include tools for dose estimation[6][7] and further information and
examples are given in IAEA 2011[5].
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The service laboratory shall state in the result reports the method used to correct for non-acute
absorbed dose estimates and, when appropriate, also justify its assumptions.
12.1.8 Other exposure scenarios
When there is a high degree of uncertainty in the conversion of the measured yield to dose, calculation
of the dose may not be prudent. In this case, it is possible to use the comparison of radiation induced
frequency of translocations to the background to give an indication of whether or not an exposure has
occurred (e.g. in the case of internal exposures).
Detailed examples of a number of different exposure scenarios in which the translocation assay has
been applied are given in IAEA 2011[5].
13 Reporting of results
13.1 General
The report should contain relevant information provided by the customer since this may influence the
interpretation of the findings in the service laboratory. All observed aberrations shall be listed and
interpreted based on the current understanding of mechanisms for radiation-induced chromosome
aberration formation.
13.2 Content of the report (see Annex C for an example of a standard form)
The report should include information on the following:
a)
title of the report, e.g. “test report”;
c)
identification of the report by a unique number, i.e. a specific document number provided by the
institutional registry;
e)
date of request;
b) name and address of the laboratory performing the analysis;
d) name and address of the customer;
f)
identification of the method of analysis, i.e. providing the number and name of the method as
described in the in-house quality system, and where relevant, any deviations from the test method;
g) unambiguous identification of the sample, i.e. name, internal code and date of birth of the subject;
h) description of the case: all relevant information provided by the requester that is relevant to
the interpretation of the result shall be stated (may also be dealt with in the interpretation of
the results);
i)
j)
date and location of blood sampling, date of sample arrival in the laboratory, date of setting up
cultures (if different) and date of completed analysis;
test results: number of cells scored, numbers and types of aberrations found;
k) interpretation of test results: see 13.3;
l)
name(s), title(s), position(s) and signature(s) of those authorizing the report and their contact
information.
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13.3 Interpretation of the results
This varies depending on the circumstances of each case but the report should include one or more of
the following:
a)
a comparison of the translocation frequency to the background level, specifying if using the
background translocation frequency from the laboratory results or the Sigurdson, et. al. 2008
meta-analysis[8], together with the appropriate characteristic limits — confidence limits and
decision threshold or detection limit, as described in 12.1.1;
b) an absorbed dose estimate based on the frequency of translocations expressed in SI units of
absorbed dose (Gy) along with a quantification of the uncertainties on the absorbed dose estimate.
This would normally be an upper, and where appropriate, a lower confidence limit, and the percent
level of confidence;
c)
a statement on the likelihood that any aberrations used in absorbed dose estimation relate to this
particular radiological incident;
e)
a statement on whether the absorbed dose estimate was made assuming acute or protracted
irradiation and, if the latter, how protraction had been accounted for;
d) the coefficients of the calibration curve used for converting the absorbed dose from the
aberration yield;
f)
if appropriate, the interpretation needs to consider partial-body irradiation and excessive delay
between the accident and blood sampling;
g) a comment, and if appropriate a dosimetric interpretation, on cells observed with multiple damage;
h) comments regarding the frequencies of other aberration types scored but not used for absorbed
dose estimation;
i)
j)
a summary of the essential key elements from the points above. This would normally include the
best estimate of absorbed dose based on the cytogenetic findings;
at the end of the report: an invitation for the requester to contact the laboratory if he/she requires
further clarification or explanation about the results and/or the assay.
14 Quality assurance and quality control
14.1 Overview
Quality assurance (QA) and quality control (QC) shall be established with elements as described
in Clause 14.
14.2 Specific requirements
14.2.1 General
Performance checks with other accredited or suitably qualified cytogenetic biodosimetry laboratories
and networks shall be established through periodic inter-laboratory comparisons.
ISO 5725 is dedicated to statistical analysis to test the reliability and the precision of a technique. The
tests proposed can be applied only if many samples are analysed.
14.2.2 Performance checks by inter-laboratory comparisons
Proficiency tests are essential tools for the QA of the laboratories as they constitute an objective
evaluation of its performance, from both human and technical point of view.
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The inclusion of individual laboratories or results in an inter-laboratory comparison that appear to be
inconsistent with all other laboratories may change the average absorbed dose estimates. To discard or
correct inconsistent data, two approaches can be used (ISO 5725‑2, ISO 5725‑5):
a)
numerical outlier tests (Cochran and Grubbs tests): To discard data that give rise to a test statistic
that exceeds the critical value of the test at the 1 % significance level;
b) robust methods for data analysis: To yield robust values of the average and standard deviation of
the data (see ISO 13528);
The robust methods procedure is as follows:
a)
the outlier test for laboratory inter-laboratory comparison performance requires a minimum of
five laboratories for statistical robustness (see ISO 5725‑1);
c)
determination of the laboratory’s performance: Calculation of the z-score parameter from the
laboratory results, the reference value and the estimated standard deviation. Determination of the
u-score parameter (this evaluation includes both participant measurements and reference value
uncertainties)[5].
b) estimation of the inter-laboratory mean value and the standard deviation once outliers are
discarded or corrected. The preferred method is the calculation of the robust parameters;
14.2.3 Performance check of scorer qualification
The laboratory is responsible for ensuring that the individuals carrying out the assays are appropriately
trained. All individuals should periodically participate in intra- and inter-laboratory comparisons.
A set of calibration samples should be used to verify that the accuracy of results is well within the
expected range.
A list of qualified observers is established at least every second year by intra-laboratory comparison.
To be qualified, each observer shall score a sample of lymphocytes exposed to an absorbed dose above
1 Gy (acute photons) and a sample of lymphocytes exposed to an absorbed dose below 1 Gy (acute
photons) according to the standard practice of the laboratory.
A scorer is regarded as qualified if both of their measured absorbed doses are within the 95 %
confidence limits of the absorbed dose from the laboratory’s calibration curve. For example, if a scorer
finds that his/her measured absorbed dose in a test sample is 0,40 Gy for a reference sample irradiated
with 0,50 Gy; this agrees with the laboratory’s calibration curve which, for an absorbed dose of 0,50 Gy,
has confidence limits of 0,34 Gy to 0,63 Gy. Alternatively, the formal statistical methodologies described
in 14.2.2 can also be applied for intra-laboratory comparisons.
Automatic scoring systems may be used if appropriate QA and QC procedures have been defined.
14.2.4 Performance checks of sample transport integrity
In many cases blood collection occurs at sites distant from the processing laboratory and transportation
is necessary. The requester is responsible for ensuring the blood samples are transported in optimal
temperature conditions (6 °C up to 30 °C). When air transportation is used, X-irradiation at the security
checkpoints should be avoided. For international transport, the appropriate permits shall be obtained
in advance and included in the shipment to avoid delays at customs. All details concerning blood
collection and storage should be recorded.
It is recommended that blood samples be shipped using an experienced express service for diagnostic
material and the samples declared as UN 3373 Biological Substance Category B. Packaging and labelling
shall conform to national and international regulations. A temperature logger and a physical dosimeter
to monitor the temperature and any absorbed dose received by the samples during transport are
advisable. A standardized sample instruction sheet, (see Annex A), can be used to inform customers of
the correct procedure.
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14.2.5 Performance checks of sample integrity by service laboratory
A system for recording the collection, transport and storage of the blood samples shall be established
so that sample integrity is guaranteed. The use of coded samples is critical to avoid potential bias in
the scoring.
14.2.6 Performance checks of instrumentation
The laboratory’s QA and QC program should include periodic internal checks of equipment operations.
Examples of critical equipment include incubators, balances, thermometers, pipettes and freezers.
For example, the stability of the temperature of the incubators shall be controlled. If used, the balance
shall be checked periodically.
These checks shall be sufficient to demonstrate that the measurement equipment is properly calibrated
and that all components are functioning properly.
14.2.7 Performance checks of sample protocol
As internal QA, negative controls from unexposed individuals and where possible internal positive
controls shall be included in the study to prove the reliability of the procedure. Blood from both samples
and internal controls shall be handled in the same manner. The samples of both populations shall be
taken as concurrently as practically possible.
For the interpretation of results it can be useful to perform a differential count for each blood sample
before starting the cultures. The culture, fixation and staining procedures shall be described in detail. It
is recommended that the same lot of media and reagents be used throughout the study. The composition
of all reagents shall be recorded as accurately as possible.
14.2.8 Performance checks of sample scoring
Uniform criteria for scoring shall be used. Scoring shall be performed by trained and experienced
observers. If different scorers are involved, a balanced scoring design shall be used. Each scorer should
analyse the same number of metaphases from the slides of all subjects rather than different scorers
analysing all cells from different subjects. Cross-checking of scoring results is required. The identity of
the scorer of the slides shall be recorded.
14.2.9 Performance checks of result report generation
The reports to customers shall be examined to ensure that they contain the necessary information
as defined in this document (see Clause 13) namely: subject and customer identifiers, exposure
information, exposure and sampling dates, the scoring results, the interpretation of the results in terms
of absorbed dose and its uncertainty and information on how this was derived.
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Annex A
(informative)
Sample instructions for customer
PROCEDURES FOR COLLECTING BLOOD FOR CHROMOSOMAL ANALYSIS
Analysis of chromosomal aberrations in human peripheral blood lymphocytes is the present day
standard for the biological assessment of radiation exposure. It is used when a person’s physical
dosimeter is absent or inoperative or when the reading of the physical dosimeter is missing or in
dispute. To optimize the recovery of lymphocytes from the blood, it is very important that the blood be
collected and shipped according to protocol outlined below.
X
Before the blood sample is taken please notify us so that we can prepare for its arrival and pick
up.
X
Package the blood sample carefully to prevent breakage of the tubes in transit. The customer is
responsible for assuring the blood samples are transported in optimal temperature conditions
(6 °C up to 30 °C). If temperature extremes are likely to be encountered a minimum-maximum
thermometer can be included in the package. Blood samples shall not be frozen. One method of maintaining blood at room temperature is to place the tubes on a gel pack that has been
allowed to stay at room temperature for several hours to ensure that the samples do not freeze
during transportation (e.g. Air-mail).
X
X
X
X
X
X
X
All blood samples are to be collected into lithium heparin tubes, at least 10 ml (2 × 5 ml
tubes). Gently rock the tubes for 2 min to ensure proper mixing. Label the tubes unambiguously and complete the questionnaire.
Mark on the external packaging and the shipping documents Biological Substances —
Category B — DO NOT FREEZE.
When air transportation is used, the X-irradiation at the security checkpoints should be avoided. A physical dosimeter may be included in the shipping package to verify this. For international transport, the appropriate permits shall be obtained in advance and included in the shipment to avoid delays at the customs. For air transport packaging and labelling should conform
to the current International Air Transport Association (IATA) regulations. These require that
blood samples should be packed to conform to UN 3373 infectious materials. The package itself
and the 'Nature and Quantity of Goods' box of the air waybill should show the following wording: “Biological Substances — Category B packed in compliance with IATA packing instruction
650”.
Mark the package and shipping documents DO NOT X-RAY.
Immediately after blood collection, ship the sample by special transportation and use overnight air express so we can receive the blood early in the morning following sample collection. Contact the laboratory to confirm the shipment and inform us of the Way Bill number.
THIS IS IMPORTANT FOR TRACKING THE SAMPLE.
For best results blood shall be received within 24 h of sampling.
All details concerning blood collection and storage should be recorded.
© ISO 2019 – All rights reserved
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(Service Laboratory Head)
(Service Laboratory address)
Phone: (XXX) XXX-XXX
Fax: (XXX) XXX-XXX
E-mail
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ISO 20046:2019
Annex B
(informative)
Sample questionnaire
EXPOSURE INFORMATION FOR CHROMOSOME ABERRATION ANALYSIS
(TO BE FILLED OUT BY THE REQUESTOR)
I, ………………….… (Name), born ……………..……… (dd/mm/yy) consent to giving a blood sample for the
purpose of estimating chromosome aberrations induced by exposure to ionizing radiation.
.......................................
Signature
...............................................................................................................................................................................................
Blood sample taken by: ..................................................... Laboratory name: ..............................................
Laboratory address: ....................................................................................................................................................
Telephone #: ........................................ Fax: ........................................ E-mail: .................................................
Date and time blood sample taken: ........................... (dd/mm/yy) Specify anticoagulant: .....................
Exposure Data: Radiation Worker or Non-Radiation Worker
Occupation: .....................................................
Date and time of overexposure: .......................……. (dd/mm/yy — time)
Place: ..................................................... Company: .....................................................….
1. Brief description of:
2. Whole-body exposure O
Dose value: ....................
Partial-body exposure O
Internal contamination O
Part of body: ................................ Nuclide: ……………………..
Dose value: ................................... Dose value: ………………...
How was this dose value obtained: …………………………………………………………………………………..
3. Type of radiation:
X-ray
O
Energy? ……............................…….
γ
O
Origin? …………………………………
Neutrons
O
Origin? …………….... Energy? …...........…
α
Electrons
© ISO 2019 – All rights reserved
O
O
Origin? .…………………………………
Origin? ……………… Energy? …............…
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Patient Data:
1. Previous exposure through medical practice:
Radiation therapy
X-ray diagnoses
Nuclear medicine
O
O
O
Date, Part of Body.......................................
Date, Part of Body.......................................
Date, Part of Body.......................................
2. Illness within the last 4 weeks before taking the blood sample: ....................................................
3. Intake of medication: O
Name of medication: .......................................... Dose: ……………….. Duration: ……………….
4. Smoker:
5. Other diseases:
HIV
O
no:
O
Hepatitis
yes:
O
number cigarettes/day: ....................
O
.......................................................................................................................................................
Results of chromosomal analyses to be sent to:
Name: .................................................................
Address: .............................................................
.............................................................
Telephone #: ....................................................
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Annex C
(informative)
Sample of report
Address of lab performing analysis
ID No of report
Requestor name, address, phone, e-mail
Date of request
BIOLOGICAL DOSE ASSESSMENT/CHROMOSOME ANALYSIS (FISH analysis)
Sample
Sampling date/location
Arrival date
Code, name and date
of birth of exposed
subject
Date of analysis
Method(s) of analysis
Additional sampling
Description of case
Results
Table. Test results
Sample
Number of cells analysed
Translocations
Others
Interpretation of results
Signatures and contact
information
This test report may only be published and copied in full, except with a prior written permission by
the (name of test laboratory). The test results only apply to the tested samples.
© ISO 2019 – All rights reserved
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Annex D
(informative)
Sample data sheets for recording painted aberrations
Three colour painting:
Slide Code:
Microscope N°
Cell Number
Coordinates
1
2
3
4
5
Scorer:
Date:
Description of all
observed aberrant chromosome
pieces
Aberrations affecting
Painted Chromosomes
(Rr,Gg,Yy): 1, 2, 4
T2
T1
Dic/R
ace
1
1
1
1
1
1
t(Ra) t(Ar) t(Ga)
dic(YA) ace(ay)
dic(AA) ace(a)
t(Ga) t(Ag) t(Ya)
t(Ra) t(Ar) t(Ga)
ace(ag) r(R) ace(r)
ace(a)
t(Yay)
t(Ag) ace(g) ace(a)
T2 = two-way simple translocation
T1 =one-way simple translocation
1
0
0
1
0
0
0
1
0
Unpainted chromosomes (Aa)a
Dic/R
ace
1
1
1
2
0
1
0
0
1
0
0
0
Stable
cell
C
No
0
No
1(3)
No
0
0
Yes
0
Yes
1
0
1(3)
Dic = dicentric
R = ring
C = complex aberration with the minimal number of breaks to produce the observed complex aberrations in parentheses
a
32
Refers to completely unpainted chromosomes.
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One colour painting:
Slide Code:
Microscope N°
Cell
Number
Coordinates
1
2
3
4
5
Scorer:
Date:
Description of all
observed aberrant chromosome
pieces
Aberrations affecting
Painted Chromosomes
(Bb): 1, 2, 4
T2
T1
Dic/R
ace
1
1
1
1
1
1
t(Ba) t(Ab) t(Ba)
dic(BA) ace(ab)
dic(AA)ace(a)
t(Ba) t(Ab) t(Ba)
t(Ba) t(Ab) t(Ba)
ace(ab) r(B) ace(b)
ace(a)
t(Bab)
t(Ab) ace(b) ace(a)
T2 = two-way simple translocation
T1 =one-way simple translocation
1
0
0
1
0
0
0
1
0
Unpainted chromosomes (Aa)a
Dic/R
ace
1
1
1
2
0
1
0
0
1
0
0
0
Stable
cell
C
No
0
No
1(3)
No
0
0
Yes
0
Yes
1
0
1(3)
Dic = dicentric
R = ring
C = complex aberration with the minimal number of breaks to produce the observed complex aberrations in parentheses
a
Refers to completely unpainted chromosomes.
© ISO 2019 – All rights reserved
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Annex E
(informative)
Fitting of the dose response-curve by the method of maximum
likelihood and calculating the uncertainty of the absorbed
dose estimate
Let us consider exposing blood lymphocytes to N doses of radiation xi (i = 1, 2,…, N). The following data
is obtained:
— μi = number of aberrations;
— ni = number of scored cells for doses xi;
— yi = μi/ni − frequency of aberrations per cell for doses xi.
In this example, it is assumed that cells are exposed to radiation of low-LET, where the distribution of
aberrations is Poissonian. Hence:
P ( µi ) =
( ni λ i ) µ i
µi !
e − ni λi
where niλi = E(μi) and λi = E( yi) (the expected frequency of aberrations per cell). The variance for yi is
V( yi) = E( yi).
Thus, for the data {x1, x2, ..., xN}, {μ1, μ2, ..., μN} and { y1, y2, ..., yN} the probability distribution is
N
( ni λi ) µ i − ni λi
characterised by the likelihood function: L ( µ 1 , µ 2 ,… µ N ) =
e
. The observed
µi !
∏
i =1
relationship between the absorbed dose and the aberration frequency can be fitted by a linear-quadratic
equation λi = C + α x i + β x i2 , where C, α, β are not known.
The aim of the fitting procedure is to find such coefficients C, α, β for which the likelihood function
reaches a maximum. This maximum can be calculated by the iterative method of maximal likelihood, by
solution of the likelihood function defined above. Many programs are available to solve the likelihood
equation, which should be done using the Poisson linear model with identity link, collecting the
estimations of coefficients of beta and the variance-covariance matrix. Full details can be found in P.
McCullagh and J. A. Nelderand[18] and in D.G. Papworth[9]. An example fitting method and more details
are presented in the IAEA manual (2011)[5].
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Annex F
(informative)
Process for dose estimation
F.1
Decision threshold and detection limit
The first stage of the analysis is to calculate the decision threshold and the detection limit. Ideally, each
laboratory would have its own background data for the particular age group. However, in this case, the
laboratory does not have their own background data, and so shall use data from the literature.
Assuming the decision threshold and detection limit shall be estimated for (40 to 44) years old male
individuals. From Sigurdson, et al., 2008[8], the background translocation yield for this age group
is 0,67 translocations in 100 cells, i.e. μ0( j) = 0,006 7 translocations per cell. For this age group, the
cell number from Sigurdson, et al. was relatively high and the age specific background translocation
frequency can therefore be approximated by a constant, neglecting the uncertainty. Assuming that the
data follow a Poisson distribution, the decision threshold yd for a type I error α = 0,05 can be estimated
by solving Formula (4) for yd.
P ( y > y d |µ = 0 , 006 7 ) = 1 −
yd
∑
k =0
− 0 ,006
e (
7⋅n1 )
(0 , 006 7 ⋅ n1 ) k
k!
≤ 0 , 025
This can be solved by using tables for the cumulative Poisson distribution or by finding yd using the
function ppois(y, 0,006 7·n1, lower.tail = FALSE) in R (see example R script in F.6) or 1‑POISSON.DIST( y,
0,006 7·n1,TRUE) in Microsoft Excel for different values of y until the resulting output is ≤0,025. For
instance, for n1 = 500 genome equivalent cells: P( y > 6 | μ = 0,006 7) = 0,054 > 0,025 and
P( y > 7 | μ = 0,006 7) = 0,021 > 0,025. Therefore the decision threshold for the scoring of 500 genome
equivalent cells for this example can be estimated by yd = 7. If the observed number of translocations is
larger than 7, the null hypothesis that the translocation yield of the test person is equal to the
α
background translocation yield can be rejected at the significance level . Similarly, for this age group,
2
the decision threshold based on n1 = 1 000 genome equivalent cells can be estimated by yd = 12.
To calculate the detection limit, it is then necessary to decide on the value of the type 2, false negative
detection rate. This decision depends on the relative importance of the type 1 and type 2 errors. Many
researchers view false positives as being approximately four times more serious than false negatives,
thus a type 2 detection rate of 10 % is commonly applied. However, the type 2 error detection rate, β,
should be decided on a case by case basis.
The detection limit (β = 0,1, i.e. type 2 detection rate 10 %) of the number of translocations yz can be
estimated by using Formula (7):
yz =
χ2
2( y d +1) ,0 ,9
2
where the quantile of the chi-squared distribution can be obtained from appropriate tables or
calculated in Microsoft Excel using the ‘=CHISQ.INV’ function: CHISQ.INV(0.9, 2*( yd + 1))/2, for decision
threshold yd and in the R software package the ‘qchisq’ function can used: qchisq(0.9, 2*( yd + 1))/2.
Hence, the detection limit for this example with n1 = 500 cells is yz = 11,77. Thus, if the true number of
translocations (or the corresponding true dose) in 500 cells is greater than yz = 11,77, the probability
for inferring a false negative conclusion is lower 10 %. For n1 = 1 000 the detection limit is yz = 17,78. A
summary of these values is shown in Table F.1.
© ISO 2019 – All rights reserved
35
BS ISO 20046:2019
ISO 20046:2019
It is assumed that the laboratory has established a relevant age adjusted (according to Formula 15)
standard translocation calibration curve for excess genome equivalent cells of y′ = 0,000 1
(±0,002 1) + 0,015 2 (±0,010 8) D + 0,080 9 (±0,006 1) D2[19]. To obtain the minimum detectable
dose, the detection limit yz is adjusted for the background translocation yield of a (40 to 44) years
old male, e.g. 3,35 translocations in 500 genome equivalent cells. The age corrected detection limit
of approximately 8,4 translocations per 500 genome equivalent cells can then be used to calculate
the minimum detectable dose based on the age corrected calibration curve (e.g using Dose Estimate
software). The resulting minimum detectable dose is approximately 370 mGy. The probability to infer a
false negative conclusion, i.e. to infer the conclusion that a test person was not exposed although (s)he
was exposed is lower than β = 0,1, if the true dose is higher than 370 mGy.
Table F.1 — Summary of decision threshold and detection limit values
Background level (genome equivalent translocation yield per cell for 40 to44 years
old)
from Sigurdson, et al., 2008, μ0( j)
0,006 7
Decision threshold for 1 000 cells (α = 5 %), yd
12
Background level in 1 000 cells y0( j)
6,7
Decision threshold for 500 cells (α = 5 %), yd
7
Background level in 500 cells y0( j)
3,35
Detection limit (β = 10 %, 1 000 cells), yz
17,78
Detection limit (β = 10 %, 500 cells), yz
F.2
11,77
Conversion to genome equivalent
In the next stage, the FISH translocation assay has been carried out for three test persons (42 years
old male), with 1 500 cells analysed and 11 translocations observed for test person 1, 6 translocations
observed for test person 2 and 18 translocations observed for test person 3. As the laboratory carries
out 1 colour painting and then applies analyses towards dose estimation according to numbers of
translocations in genome equivalent cells, the first step is to convert the observed yield in the painted
fraction to the genome equivalent yield, according to Formula (1).
The laboratory paints 3 pairs of chromosomes (2, 3, and 5) with a single colour and counterstains
the rest. According to IAEA (2011), chromosomes 2, 3 and 5 yield a painted fraction, f, of 0,209, which
according to Equation (1) gives a ratio fP/fG of 0,339. The genome equivalent observations are thus 11, 6
and 18 translocations in 1 500 * 0,339 = 509 cells for test persons 1, 2 and 3 (Table F.2). This calculation
can be carried out in freely available software tools, including Reference [6].
Table F.2 — Conversion to genome equivalent translocations yield
Test person 1
Test person 2
Test person 3
(42 years old
male)
(42 years old
male)
(42 years old
male)
11
6
18
Initial number of scored translocations, y
Number of scored cells
1 500
Fraction of genome painted, f
(chromosomes 2, 3 and 5, IAEA, 2011)
fP/f G
1 500
0,209
0,209
509
509
509
0,339
Genome equivalent number of cells, n1
1 500
0,209
0,339
0,339
Therefore, as the observed number of translocations of test person 1 (10,8 translocations in 500 genome
equivalent cells) is greater than the decision threshold yd = 7, the null hypothesis that the number of
translocations of the test person is equal to the background translocation number can be rejected at
the two-sided significance level (α = 0,05). It is concluded that the physical effect is present, i.e. the test
person was exposed, and the dose estimation shall be performed as described in F.3 to F.5.
36
© ISO 2019 – All rights reserved
BS ISO 20046:2019
ISO 20046:2019
In contrast, the observed number of translocations of test person 2 (5,9 translocations in 500
genome equivalent cells) is lower than the decision threshold. The null hypothesis that the number
of translocations of the test person is equal to the number of background translocations cannot be
rejected. In such cases the detection limit, 11,77, shall be reported as described in 12.1.1.
For test person 3, the observed number of translocations is 17,68 in 500 cells which is higher than
the detection limit yz = 11,77 translocations in 500 cells (or the true dose >370 mGy. In this case, dose
estimation shall also be performed following the method used for case 1, as demonstrated in F.3 to F.5.
F.3
Confidence limits on the yield of translocations
The Poisson confidence limits on the yield of translocations are then calculated according to
Formulae (8), (9) and (14).
As described in F.1, the lower confidence limit, yL can be calculated in Microsoft Excel using the ‘=CHISQ.
INV’ function: CHISQ.INV(0.025, 2*y)/2, for an observation of y, a lower tail probability value of
α
= 0 , 025 , and in the R software package the ‘qchisq’ function can used: qchisq(0.025, 2*y)/2.
2
For the upper confidence limit, yU, the corresponding calculations are CHISQ.INV(0.975, 2*(1 + y))/2 in
Microsoft Excel and qchisq(0.975, 2*(1 + y))/2 in R.
Values for upper and lower confidence limits for this example are shown in Table F.3.
Table F.3 — Confidence limits on the yield of translocations for test person 1
Translocations in 509 genome equivalent cells, y
11
Lower 95 % Poisson confidence limit, yL
qchisq(0,025, 2·11)/2 = 5,49
Upper 95 % Poisson confidence limit, yU
F.4
qchisq[0,975, 2·(1 + 11)]/2 = 19,68
Adjustment for background yield
The next stage in the dose estimation process is adjustment for the background yield. As already
discussed, the laboratory does not have its own background data, and shall again use data from an
appropriate publication. In this case Sigurdson, et al., 2008 is chosen to be most appropriate and only
age is adjusted for. The background can then either be calculated using Formula (12) in 12.1.3 or can be
taken from Table 3 of Sigurdson’s data: i.e. for a 42 years old male, the estimated background yield of
translocations, y0( j), is 3,41 in 509 genome equivalent cells (Table F.4).
Table F.4 — Adjustment for background yield
Total number of observed translocations in 509 genome equivalent
cells, y
11
Estimated excess radiation induced translocations, y′
7,59
Background level (genome equivalent yield for 40 to 44 years old in
509 cells) from Sigurdson, et al., 2008, y0( j)
Lower 95 % Poisson confidence limit, yL′
Upper 95 % Poisson confidence limit, yU′
3,41
5,49 – 3,41 = 2,08
19,68 – 3,41 = 16,27
Thus, for an observation of 11 genome equivalent translocations, the estimated yield of excess radiation
induced translocations, y′, is 7,59 in the 509 genome equivalent cells scored in this case.
© ISO 2019 – All rights reserved
37
BS ISO 20046:2019
ISO 20046:2019
F.5
Calculation of absorbed dose and uncertainty
The frequency of translocations shall then be converted into a radiation dose, using an appropriate
calibration curve, as described in Formula (2) in 11.2. This example calculates the dose for case 1 above.
The dose for case 3 can be calculated following the same method.
It is assumed that the laboratory has established a relevant standard translocation calibration
curve for excess genome equivalent cells of y′ = 0,000 1 (±0,002 1) + 0,015 2 (±0,010 8) D + 0,080 9
(±0,006 1) D2[19].
The laboratory uses the standard minimum acceptable method of assessing uncertainty, assuming
that uncertainty on absorbed dose can be estimated by combining the two largest contributors: the
uncertainty on the Poisson observation and the uncertainty on the calibration curve coefficients.
The laboratory uses the Dose Estimate software[6] to calculate the absorbed dose and uncertainty. As
the laboratory already has a genome equivalent curve, and the Dose Estimate software is used, the
age adjusted calibration curve y′ shall be translated such that the background translocations are age
matched to that of the test person. This means that it is then not necessary to use the background
corrected translocation yield, rather the original observed number of translocations should be used.
Again, the translocation rate of 0,006 7 translocations per cell for a 40 to 44 years old male from Table 3
in Sigurdson, et al. is used, 2008 and it is assumed that the background translocation rate is constant.
The parallel translated calibration curve y = (0,000 1 + 0,006 7) (±0,002 1) + 0,015 2 (±0,010 8)
D + 0,0809 (±0,006 1) D2 provides an estimate for the calibration curve of a (40 to 44) years old male
individual (Table F.5).
Table F.5 — Input and output parameters for dose estimate[6] calculation of absorbed dose
Translocation yield in 500 genome equivalent cells, y
11
Calibration coefficient α (linear term)
0,015 2 ± 0,010 8
Genome equivalent number of cells, n
509
Calibration coefficient C (constant)
0,006 8 ± 0,002 1
Calibration coefficient β (quadratic term)
0,080 9 ± 0,006 1
Estimated absorbed dose in Gy, D
0,344[0,15–0,54]
Note that in this example the covariance between the coefficients has been ignored.
F.6
R script for calculating the decision threshold
rm(list = ls())
# Example: n1=509 test cells
# background rate 0,0067 translocations/cell
# type I error alpha = 0,05
# type II error beta = 0,1
mu0 <– 0.0067
alpha <– 0.05
beta <– 0.1
n1 <– 1000
# Calculation of the decision threshold
# constant background rate mu0
38
© ISO 2019 – All rights reserved
BS ISO 20046:2019
ISO 20046:2019
y <– 1:100
y_d_const <– min(y[which(sapply(y, function(x) ppois(x, mu0*n1, lower.tail = FALSE)) <= alpha/2)])
cat("decision threshold:", y_d_const )
# Calculation of the decision threshold
# constant variable rate mu0
# n0=20000 background cells
fun.dec.thresh.variable <– function(y, y0, n1, n0){
y.seq <– 0:y
p <– n1/(n1 + n0)
}
return(1-sum(exp(lchoose(y0 + y + 1, y.seq) + y.seq*log(p) + (y0 + y + 1 -y.seq)*log(1-p))))
n0 <– 2e4
y_d_var <– min(y[which(sapply(y, fun.dec.thresh.variable,
n1 = n1, n0 = n0, y0=mu0*n0) <= alpha/2)])
cat("decision threshold:", y_d_var)
# P value for the comparison of two poison rates
cat("P(y_d_var vs background)=",
poisson.test(c(y_d_var, mu0*n0), c(n1, n0))$p.value)
cat("P(y_d_var + 1 vs background)=",
poisson.test(c(y_d_var + 1, mu0*n0), c(n1, n0))$p.value)
# calculation of the detection limit:
y_z_const <– qchisq(1-beta, 2*(y_d_const + 1))/2
cat("detection limit:", y_z_const )
y_z_var <– qchisq(1-beta, 2*(y_d_var + 1))/2
cat("detection limit:", y_z_var)
© ISO 2019 – All rights reserved
39
BS ISO 20046:2019
ISO 20046:2019
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41
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