3D DOSIMETRY
Prof. Mauro Valente, PhD.
Medical Physics – FaMAF
http://www.famaf.unc.edu.ar/~valente/
CONICET & Universidad Nacional de Cordoba
ARGENTINA
The GOAL
Could be possible to develop a novel dosimetric
technique with tissue-equivalent properties and capable of
3D dosimetry as well as dose separation at mixed fields?
HINT: water-based dosimeters with wide flexibility (chemical
& isotopic composition, shape, density)
Glossary and Outlines
 Modern Radiotherapy: Demand of accurate 3D dosimetric systems
Standard dosimetry techniques and Fricke gel dosimetry
 Preparation and characterization of Fricke gel dosimetry
Background – Optimizations and Developed preparation Protocol
Dose-response characterization and Tissue-Equivalence study
 Ferric ion diffusion of Fricke gel layer dosimeters
Diffusion coefficient determination – Correction by means of dedicated timedeconvolution algorithms
 Suitable method for Fricke gel layer dosimeter imaging
Characterization of the optical system – Limitations of the technique
 Mixed field techniques requiring dose contribution separation
Preliminary tests – BNCT applications – Soft tissue-equivalent and lung-equivalent
compositions – Chemical & isotopic flexibility suitable for BNCT dosimtry
 Suitable method for 3D dose distribution determination
Modeling a target volume by means of Fricke gel layer dosimeters – Dose Imaging: 3D
reconstruction – “AQUILES – Real 3D”: a novel tool for 3D dose Imaging
 General conclusions
Developed preparation Protocol – Applications to dose distribution measurements –
Developed 3D dose imaging method: Highlights – Main Advantages-Disadvantages and
future improvements
Modern Radiotherapy: “Complex” irradiation techniques
During the last years, sifnificant developments in
Radiotherapy techniques, mainly due to the increasing
technology and computer capability

Conformal Radiotherapy

Dynamic Radiotherapy

Radiosurgery

Intraoperative Radiotherapy

High dose rate Brachitherapy

Micro Beam Radiotherapy (mBR)

Intensity Modulated RadioTherapy (IMRT)

BNCT
Modern RT: Demand for suitable detectors










High resolution
High accuracy and precision
Linearity of signal with dose over a wide range
(prefered)
Three dimensionality
Independence of incident beam orientation
Dose integration capability
Independence of energy
Independence of dose rate
Tissue equivalence
Important to know the limitations (suitably
characterizated)
What is Fricke gel dosimetry?
• Continuous chemical dosimeter
• Based on ferrous sulphate solution
• Chemical yield: Fe2+→ Fe3+
• Fixed to gel matrix (Spatial resolution)
• Originally imaged by MRI [Gore et al.]
Suitably shaped in form of thin layers





Negligible alteration of in-phantom transport
properties
Suitable for visible light tranmittance analysis
Not complicated correction algorithms
Versatility regarding chemical composition
Important advantages for neutron field irradiations
(dose contribution separation)
Current traditional dosimeters
Charact.
Dose Integ.
High Resol.
T-E
En. Ind.
DR Ind.
3D
Lect. Stability
Ori. Ind.
Rel. L-C C-Av.
Short T-C
Ion. Ch.
TLD
Diode
Film
Fricke Gel
•Demand and Motivation for accurate 3D dosimetry







Growth in multi-field techniques
Growth in 3-D planning
Growth in dynamic delivery
Verification of 3-D plans
Dosimetry in complex geometries
BNCT dose contributions separation
MC techniques and numerical algoritms for
Dosimetry in 3-D
FRICKE GEL DOSIMETERS ARE A PROMISING TOOL
… some disadvantages??
1. ACCESS TO MRI FACILITIES
2. FERRIC ION DIFFUSION
Fricke gel chemical composition
Costituent
Quantity
Ultra pure water
192ml
Ferrous sulphate
0.0392g
Xylenol Orange
0.0251g
Gel powder (P.S.)
6.0779g
Sulphuric acid
2.78ml
Fricke gel main Preparation Procedure
1.
2.
3.
4.
5.
6.
7.
8.
Gel powder is combined with half of the total quantity of water
Solution is heated (constant stirring and monitoring of temperature)
Solution is maintained at 45◦C for 20 minutes (gel powder dissolution)
Separate flask: Fricke (fer. sulph., sulp. acid), and XO with rest of the water
Gel solution led to cool until Fricke solution is added (T=42-40ºC)
Mixed solution should become clear, transparent orange
Final solution is transferred into pre-elaborated suitable containers
Normal T, P conditions for 10 minutes. Put batches (at least 12 hours) into
the fridge (T=6-10ºC)
Developed dedicated PROTOCOL
Fricke Gel
solution
Optical imaging method for Fricke gel layer dosimeters
Spectroscopy Analysis
Standard Fricke solution: Absorption peak around 302nm


Fixing standard Fricke solution to gel matrix (information spatially firmed)
Adding X.O. (marker) → Abs. peak displacement (585nm) and Diffusion
slow down
Visible light (yellow-orange)
… therefore, optical analysis by means of visible light transmittance becomes suitable for Fricke
gel dosimetry
Fricke gel dosimeter Imaging: Optical system
Detector
(CCD)
Monochr. filter
Dosimeter
Dark mask
Illuminator (homog. plane
paral. visible light beam)
Transmittance measurement


Interaction:
sˆ    material
rbeam
a  (μ,sμ)–IInc.
, sˆ (parallel
 sfiltered
I rpolychr.)
, sˆ  S
a
s
Radiation Transport
Equation


2
 I r , sˆ     sˆ, sˆ' I r , sˆ' d sˆ'   sˆ, sˆ' d 2 sˆ'  1
 I z 
  a   s  I z    s I z      sin  d
z
 min
 max
 sˆ, sˆ'  f sˆ  sˆ'   sˆ, sˆ'    
Bouger-Lambert-Beer Law
I z   I 0exp a   s z
A   C d A   log10 T 
Beer’s Law (Abs.):
Fe3+ chemical yield:

C Fe
3

 I inc 
 I 0 
A
1


 log10 

log10  fin 
3
3
 Fe
 I z  d   C Fe3   Fe
I 

 



ABSORBED DOSE CORRELATED TO Fe3+ CONCENTRATION,
MEASURABLE BY MEANS OF TRANSMITTANCE IMAGES
 
3
D  f C Fe
  D  CFe 
 GL Before 
 GL  f ( I )   I
D  log10 
After 
 GL

3
  cte
Fricke gel layer dosimeter dose-response
The dosimeter dose response depends on several factors, but it has been shown
that under proper conditions, dose response is linear to some extent.
Characterization of some parameters affecting dosimeter dose-response
0.7





0.6
Xylenol Orange concentration
0.5
Cooling rate
Radiation quality 0.4
and dose rate
0.3
Dosimeter layer width
0.2
Irradiation temperature
Time elapsed between
preparation and irradiation
0.1
OD

0.0
0
10
20
30
40
50
Dose [Gy]
Fricke dosimeter (3% GPS) layer dose response curve and linear fit up to 30
Gy for a 18 MV photon beam.
Ferric ion diffusion in Fricke gel layer dosimeters
Diffusion effect in Fricke gel dosimeters. Gel matrix is used to locally fix the XOinfused ferrous sulphate solution, enabling spatial resolution due to the slowing
down in the movement of the ferric ions produced.
Dose distribution is deteriorated: Limitation of Time interval for sample imaging
Accurate dose distribution measurements: Prompt Imaging or
Correction Algorithms
TASK
Diffusion is a convolution process
→
distributions at any time with the initial one.
correlation between concentration
Full description of the ferric ion diffusion effect: 1. 3D solution of the diffusion
equation
2. considering steepness of the
concentration distribution.
Diffusion model and diffusion coefficient calculation
D-E derived from: 1. Langevin equation (considerating Brownian motion)
2. Fokker-Planck equation (evolution of stochastic systems)



 Pr , t 
  2 Dr , t  Pr , t 
t
1D approach for the diffusion coefficient calculation



Suitable initial dose distribution: Step-Function (Heaviside)
Experimental Arrengement: dedicated cerrobend blocks
conforming circular (Ǿ=3cm) and rectangular (4x2cm2)
12MeV electron beam F.S.=5x5cm2
2D approach for the diffusion coefficient calculation



Suitable initial dose distribution: Almost-punctual (Dirac Delta)
Experimental Arrengement: dedicated cerrobend block with hole
circular (Ǿ=1mm)
12MeV electron beam F.S.=10x10cm2
Diffusion: 1D Approach
T0
T=300min
T=600min
2 P 
T=900min
T=1200min
T=3000min
1 P
0
D t
1D solution (actual bond. and initial cond.)
 x  x0  
P( x, t )  A erf 

 2 Dt  t 0  
Experimental data and proposed model Differences
0.2
90 minutes
0.2
30 minutes
0.15
0.15
Deviation (%)
0.05
0.10
0.10
0.05
0.00
-0.05
-0.10
-0.15
240
260
280
300
320
340
Distance
(píx)
280
300
320
260
340
2 
600 minutes
0.2
0.5
1

N i 1
0.3
0.2
Deviation (%)
Deviation (%)
(OD)
0.15
0.1
0.0
0.1 -0.1
-0.2
-0.4
240
-0.10
250
260
260
270
280
290
300
280Distance
300 (pixel)
320
Distance (pixel)
310
340
360
280
300
320
340
360
Pixel
250
260
270
280
290
300
310
320
Distance (pixel)
1200 minutes
0.2

0.15
0.10 0.15
2
i
1200 minutes
0.05
0.00
0.1
-0.05
0.05
-0.15
260
320
260
 yi  ~yi 2
-0.10
0.05 -0.3
240
-0.05
240
N
600 minutes
0.4
0.05
-0.15
360
Distance (pixel)
0.00
240
360
-0.20
240
0.1
0.05
(OD)
0.1
90 minutes
0.15
0.15
Deviation (%)
(OD)
0.20
(OD)
30 minutes
270
240
280
290
300
260Distance
280 (pix)
300
310
320
320
340
360
Distance (pixel)
Some relative deviation of optimized model and experimental data. Top on the left: 30
Sequence
of irradiation,
some optical
(ΔOD) profiles
and modelbottom
fits (red
minutes
after
topdensity
on thedifferences
right: 90 minutes
after irradiation,
left:solid
600
lines) after
at several
times
irradiation
corresponding
to the rectangular initial
minutes
irradiation
andafter
bottom
right: 1200
minutes after irradiation.
distribution. Top on the left: 30 minutes after, top on right: 90 minutes after, bottom on
the left: 600 minutes after, bottom on the right: 1200 minutes after.
0.40
0.35
0.35
0.30
0.30
0.25
0.25
2
 (cm )
0.20
0.20
2
2
2
 (cm )
0.40
0.15
0.15
0.10
0.10
0.05
0.05
0
2
4
6
8
time (h)
10
12
14
16
0
2
4
6
8
10
12
14
16
time (h)
Square of 1D Gaussian spreads in function of time and linear fit for rectangular shape (left) and circular shape (right).
1D
D
2 1
 (1.24  0.07)mm h
Diffusion: 2D Approach
     0 2 
exp

4 Dt


P(  , , t ) 
4 Dt

2 
2

2
   P( , ,t )  d d  2nDt
0 0
n is the “isotropic dimensionality”
n=1 for 1D and n=2 for 2D (isotropic media)
Transmittance (585nm) image (45 minutes after
irradiation) and region within D was calculated.
(OD)
2D
  2   0 2 
 y0 
exp

2
w
w 2


A
350
300
2
2
w (pix )
250
200
150
100
50
0.5
1.0
1.5
2.0
2.5
Time (h)
3.0
3.5
4.0
380 pix:= 130mm
Square of Gaussian spreads as a function of time and linear fit.
Sequence of some relative deviations of experimental and the optimized proposed method for 2D
approach. Top on the left: 45 minutes after, top middle: 94 minutes after, top on the right: 124 minutes
after, bottom on the left: 163 minutes after, bottom middle: 203 minutes after and bottom right: 239
minutes after.
D
2D
2 1
 (1.15  0.05)mm h
Spatial distribution corrections by means of calculated Dif. Coef.
Dedicated experiment




120x120mm2 Fricke gel dosimeter
12MeV electron beam (Varian Clinac) F.S. 20x20 cm2
suitable shielding cerrobend block (collimation): narrow beam
irradiated positioning the hole of the shielding at two different positions
and delivering 8 and 16Gy, respectively.
Optical density differences at 200 minutes after irradiation. Gaussian’s
“presumed” centres indicayed with the coloured cross.
Experimental (left) and calculated (rigth) dose distributions at 45 minutes after irradiation
Dose
distributions
at 200 (rigth) and 45 (left) minutes after irradiation and
and dose
difference (bottom).
dose difference (bottom).
Fricke gel layer dosimeters: Single Beam
Application to Photon (Gamma and high energy R-X) beams
Ion. Chamber
MC Simulation
Fricke Gel
100
90
70
60
PDD
90
Normalized Dose
80
50
40
30
20
Ion. Chamber
MC simulation
Fricke Gel
100
80
70
60
50
40
30
20
10
10
0
0
0
1
2
3
4
5
6
7
Depth (cm)
60Co
8
9
10 11
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
Beam Width (cm)
Gamma Beam (F.S.:10x10cm2, SSD:80cm)
Application to Photon (Gamma and high energy R-X) beams
100
Normalized Dose
90
80
70
60
PDD
Film dosimeter
MC Simulation
Fricke Gel
Film dosimeter
100
MC Simulation
90
Fricke Gel
50
40
30
20
10
80
70
60
50
40
30
20
10
0
0
0
1
2
3
Depth (cm)
4
5
6
0
1
2
3
4
5
6
7
8
9
10
Beam Width (cm)
6MV Beam Varian 600C (F.S.: 10x10cm2, SSD:100cm)
Application to Photon (Gamma and high energy R-X) beams
Ion. Chamber
MC Simulation
Fricke Gel
100
90
100
80
90
PDD
60
50
40
30
20
10
80
Normalized Dose
Ion. Chamber
Fricke Gel
MC Simulation
70
70
60
50
40
30
20
10
0
0
0
1
2
3
Depth (cm)
4
5
6
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
Beam Width (cm)
10MV Beam Varian 18 (F.S.: 10x10cm2, SSD:100cm)
Application to Photon (Gamma and high energy R-X) beams
Ion. Chamber
MC Simulation
Fricke Gel
100
90
Normalized Dose
80
70
PDD
60
50
40
30
20
10
Ion. Chamber
Fricke Gel
MC Simulation
100
90
80
70
60
50
40
30
20
10
0
0
0
1
2
3
4
5
6
7
Depth (cm)
8
9
10 11
-5
-4
-3
-2
-1
0
1
2
3
4
5
Beam Width (cm)
18MV Beam Varian 2100 (F.S.: 5x5cm2, SSD:100cm)
Application to high energy electron beams
Ion. Chamber
MC Simulation
Fricke Gel
100
80
PDD
60
40
20
0
0
1
2
3
4
5
6
7
8
9
10 11
Depth (cm)
16MeV Beam Varian 2100 (F.S.: 10x10cm2, SSD:100cm)
Application to high energy electron beams
Ion. Chamber
MC Simulation
Fricke Gel
100
80
PDD
60
40
20
0
0
1
2
3
4
5
Depth (cm)
6MeV Beam Varian 18 (F.S.: 20x20cm2, SSD:100cm)
AQUILES:
1.
2.
3.
4.
5.
6.
7.
8.
Dedicated software for 3D dose imaging
Read out Images (GLBef,GLAft). Convert to matrices.
Correct power supply and optical path variations.
Choose the ROI.
Calculate DDO and Dose (suitable coef.).
For 3D imaging: definition of dose tensor.
Scale according pix:=mm.
Calculate corresponding errors.
Visualization: punctual, profiles, surfaces or volumetric dose distribtions.
AQUILES: Dose Imaging software
• MatLab environment
• Dedicated algorithms for Image
recognition, process and analysis.
• User Graphic Interface
• Algorithm and Numeric Methods
Optimization (speeding up)
Calculation Algorithms - AQUILES:
 GL1P i, j    PP12 GL1P i, j   ...   PPN1 GLPN i, j 
Di, j    log10 

D1
D
DN
D
 P1 GL1 i, j   ...   P1 GLN i, j 


2




D
2
 D i, j      
   

2
2

 N   D 2   D 2   N   D 2




2
2
2

D

D
2
 
  P 
  D 
  D1 



  GL   




i
i
 i 1  GL P    GL D    i 2    Pi P 
   Di P 
   D1P   1 
i 
i 

 P1 
 P1 
 
   P1 

 

γ
0.45
0.40
0.35
κ
OD
0.30
0.25
0.20
-
OD(16MeV e )= 0.0144D
0.15
OD(
137
Cs)= 0.0139D
0.10
0.05
5
10
15
20
Dose (Gy)
25
30
35
 
 
AQUILES: Application Examples
Fricke
gel
layer
data
dosimeters
process
and(Scanner
analysis
Imaged)
Fricke
gel
layer
dosimeters
(CCD
Imaged)
MonteTPS
Carlo
dose
distributrion
analysis
Suitable method for 3D dose Imaging
TASK
…dose
but,…
hard
• Novel method for 3D
Imaging
byprocedure??
means of Fricke gel layer dosimeters
beam
• Dedicated Graphic Interface for volumeIncident
visualization
Large
time-consuming???
• 3D body reconstruction
(single
slices, e.g. computerized tomography)
Hight
• 3D sensitive volumes suitably conformed by piling up several gel layers
Phantom
• Defining Tensor from claculated single layers
• 3D Reconstruction by means of 3rd order
spline method
Piled up gel dosimeters
• Sample-to-sample sensitivity normalization (pre-irradiation,…???)
AQUILES - Real 3D
Schematic set up of piled up Fricke gel dosimeter layers for
irradiation.
AQUILES – Real 3D: Versatile AQUILES subroutine for
accurate 3D dose Imaging
AQUILES – Real 3D
AQUILES – Real 3D:
Application Great capability for
3D dose Imaging
Multiple
Volumes
Isodose
3D
Dynamic
dose Imaging
radiotherapy
byof
means
(90ºof
Arc
7Visualization
piled
tenchnique)
up Fricke gel
layer
bydosimeters
means of dedicated
for Multiple-Field
MC simulations
(Box) technique
Surface Intersection (ARBITRARY) 3D Reconstruction
Fricke gel layer dosimeters for “Complex”
Tenchnique Irradiations
Multiple-field
Dynamic
IMRTirradiation
technique
radiotherapy
techniques
25
90
Normalized Dose
50
Normalized Dose
Normalized Dose
Normalized Dose
100
75
100
Fricke Gel
MC simulation
100
100
2.5
75
75
Multileaf collimator technique
Conformal block technique
80
70
MC
TPS
o Fricke Gel
60
50
50
25
50
80
90
60
25
0
40
-2.0
30 -1.5 -1.0 -0.5
0.0
0.5
1.0
1.5
2.0
-2.0 -1.5 -1.0 -0.5
Width (cm)
20
0.0
0.5
1.0
1.5
Width (cm)
2.0
70
-2.0 -1.5 -1.0 -0.5
0.0
0.5
1.0
1.5
2.0
Width (cm)
10
0
-5
-4
-3
-2
-1
0
1
2
3
Distance to Isocenter (cm)
4
5
-2.5
-5
0
5
600
Y Axis [pixel]
500
400
10
70
80
300
60
200
40
30
20
50
100
50
100
200 distribution
250
HDRB: Scanner Image
(right) 150
and Dose
X Axis [pixel]
(left)
9.0
8.5
8.0
20
7.5
7.0
Y Axis Title
6.5
6.0
40
60
5.5
80
5.0
4.5
9080
4.0
40
3.5
20
90
60
3.0
2.5
2.0
2
X Axis Title
4
In terms of standard IMRT criteria for accuracy (GammaFricke
gelmeasurement
layer dosimeter
(up) and the
TPSbest
(bottom)
Function)
this
represents
one ever
a typical
IMRTscanning
(non-perpend.
done for
(EPID,
Film,
Sys)beam)
at Irradiation
an important
Radiotherapy Institute
BNCT: Examples of utilized phantoms
Cylindric phantoms (height 14 cm, diameter 16 cm).
• Phantom 0 (Ph0) is of homogeneous Polyethylene.
• Phantom A (PhA) is a Polyethylene shell containing gel with
10 ppm of 10B.
• Phantom B (PhB) is like
PhA, with a cylindrical
volume containing 35
ppm of 10B.
One half of phantom PhB
Example of results:
TOTAL DOSE (gamma, fast neutrons, charged
particles emitted in the 10B(n,)7Li reaction with
35 ppm of 10B) in the central plane of a cylindrical
gel phantom containing 10 ppm of 10B in all the
volume (PhA).
and SEPARATION
of the doses due
to ( + nfast) and
to the charged
particles from 10B
(35 ppm).
Control of the correctness of the separation
8,E+07
nth flux (cm s kW )
Gel Dosimeter
-2
-1
-1
1. The 6,E+07
central profile has been extracted
from the
TLD
10B dose image.
4,E+07
Activation Foils
2. From the dose profile, by means of kerma
factors, the flux profile has been evaluated.
2,E+07
3. The so obtained flux profile has been compared
with0,E+00
the results obtained by means of TLDs or
20
40
60
80
100
120
Au foils.0
Depth in phantom (mm)
Flux profile in the central axis of the phantom,
obtained from the 10B dose image and comparison
with the results of TLDs and activation foils.
Gamma and fast neutron doses are separated by
means of a couple of gel dosimeters, one made
with H2O and the other with D2O.
CONCLUSIONS
General conclusions: 1. 3D Dosimetric system (Fricke gel
layers, illuminator CCD, dedicated developed software for
image acquisition, analysis and dose distribution evaluation)
has proved to provide overall consistent and reliable results for
dose Imaging
3D dose
imaging,
 In view of its capability
2.and
Thisreliability
techniquefor
offers
significant
the
Fricke gelover
layer
dosimetry
method
represents
advantages
others,
specially
for achieving
dosea valuable
distributions
for “complex”
irradiations.
promising tool
for several
complex dosimetric purposes
moddern
radiotherapy
including mixed field techniques
3. relevant and
drawbacks:
diffusion
limits
the time elapsed between
and sample imaging
TPS irradiation
verification.

4. versatility: chemical composition
suitably changed to achieve good tissue-equivalence for
different organs

3D DOSIMETRY
... Do you remember our initial question-goal?
Could be possible to develop a novel dosimetric technique with tissue-equivalent
properties and capable of 3D dosimetry as well as dose separation at mixed fields?
Optically analized Fricke gel dosimeter layer may be our
solution for the desired “magic” dosimetric method!!!
... KEEP THIS IN MIND...
3D DOSIMETRY
Prof. Mauro Valente, PhD.
Medical Physics – FaMAF
http://www.famaf.unc.edu.ar/~valente/
Thanks for your kind attention !!!
CONICET & Universidad Nacional de Cordoba
ARGENTINA