Supplementary Online Material
A randomised study of augmentation therapy in alpha-1 antitrypsin deficiency:
exploring the role of CT densitometry
A. Dirksen, E. Piitulainen, D.G. Parr, C. Deng, M. Wencker, S.B. Shaker and R.A.
Stockley
METHODS
Inclusion/exclusion criteria
Eligible patients were at least 18 yrs of age, had a history of at least one exacerbation in
the past 2 yrs, and had a post-bronchodilator forced expiratory volume in 1 s (FEV1)
≥25% and ≤80% predicted and a ratio of post-bronchodilator FEV1 to slow vital capacity
(VC) ≤0.70. Patients with normal spirometry could be included if a carbon monoxide
transfer coefficient (KCO) was ≤80% of the predicted value. Patients were excluded from
the study if they had a post-bronchodilator FEV1 <25% predicted or body weight <42 kg
or >92 kg, had had any lung surgery or augmentation therapy within the past 2 yrs, had
a history of lung transplantation or were on the waiting list for any thoracic surgery, and
had smoked during the past 6 months or were plasma-positive for cotinine.
Randomisation and blinding
When all appropriate study entrance criteria had been met, subjects were randomised in
a 1:1 ratio to receive Prolastin® or placebo. A computer-generated random code was
1
used to produce randomisation envelopes that were issued to the unblinded pharmacist
or designee at each study centre and which were to be kept confidential. The
randomisation envelopes were sent to the pharmacist with the study medication. The
randomisation numbers were assigned to subjects in ascending order at the baseline
visit, when the subject’s eligibility had been confirmed.
Several measures were taken to ensure blinding, both with regard to the study drug and
to the assessment of efficacy results. Blinding of different study groups was guaranteed
by ensuring that all subjects received the same total volume per kg body weight of study
medication with no visible difference in the external aspect between Prolastin® and
placebo (variation in colour by lot was masked by using opaque sleeves).
Throughout the course of the study, individual treatment assignments were unknown to
the treating investigators and nurses, the subjects, the clinical management and
monitoring team, the central computed tomography (CT) scan facility, and the sponsor’s
data management, clinical and biostatistical teams. Every effort was made to maintain
the integrity of the blinding through locking of the database. The randomisation block
size was not disclosed to the study sites. During the course of the study, the
randomisation code was maintained in a secure fashion and was made available only to
designated unblinded team members, which included the clinical site pharmacy
personnel who prepared the study medication and the BeroSearch monitor responsible
for monitoring the pharmacy.
2
CT densitometry
CT image acquisition
In all three centres a low-dose volumetric scanning protocol was used. Multidetector
array CT scans of the chest were performed in the supine position and during
approximately 10 s breath hold. Patients were told to inspire as close to total lung
capacity as possible in order to improve reproducibility and reduce low-density artefacts
arising from air-trapping. Scanning was performed 30 min (and within a maximum of 4 h)
after inhaled bronchodilator therapy. Three deep inspiratory manoeuvres were
performed immediately prior to scanning to ensure standardised expansion and
ventilation of basal areas that are susceptible to atelectatic changes. All scanning was
performed in a caudo-cranial direction in order to reduce artefacts arising from
diaphragm movement, and with the arms raised above the head to reduce densitometric
artefact arising from X-ray spectral changes and beam scatter due to juxtaposition of
dense tissue adjacent to the lungs. No contrast medium was injected.
All raw data were reconstructed using an edge-smoothing image reconstruction
algorithm and were saved in DICOM format at the time of imaging. Data were
transferred to CD for shipment to the central facility for densitometric analysis.
Scan acquisition parameters were standardised, taking account of the differences in
scanner manufacturers and models that existed between the three centres. The minor
differences in scanner settings are shown in table 1. The scanner model used at each
site was consistent throughout the study. Preferred scanning parameters were 140 kVp,
40 mA and pitch 1.5, with reconstructed slice thickness of 5 mm and with an increment
of 2.5 mm. Radiation per CT scan was low at around 1 mSv. For the three different
scanners, detailed protocol instructions were provided by MEDIS Medical Imaging
Systems BV, Leiden, The Netherlands, who also verified adherence to the CT
3
acquisition guidelines. Quality assurance and the independent, blinded quantitative
analysis of CT images were undertaken by a central facility (Heart Core Global Medical
Imaging).
Scanner calibration
Mandatory scanner air calibration was performed according to the scanner
manufacturers’ instructions within 3 h of the first patient scan and every 3 h during
scanning lists. Mandatory water calibration was performed by the manufacturers (using
the manufacturers’ water phantom) at least every 3 months using the clinical scan
protocol. These two processes are intended to ensure that scanner Hounsfield numbers
for air and water are measured at -1000 Hounsfield units (HU) and 0 HU for different
scan protocols, including the study protocol. Lung density values lie between these two
points and, if linearity is assumed, adjustment of air and water numbers should ensure
validity of lung values.
Phantom analysis
A dedicated Perspex and foam phantom was used for additional quality assurance data.
Phantom scans were performed prior to site initiation and prior to the first patient scan at
each site, and every 6 months throughout the study. Additional phantom scans were
performed following any scanner technical changes, e.g. X-ray tube replacement.
Densitometric assessment of foam from phantom images generated numbers that were
averaged to provide a single figure for evaluation of scanner calibration.
4
Site assessment
Site assessment, including descriptive data relating to the scanner model, was recorded
on the Core Laboratory Questionnaire and phantom scan (see above). An additional visit
to the Copenhagen centre for more detailed scanner assessment was necessary prior to
initiation. Scanner software at this site had an unusually high cut-off for low voxel
densities at -1000 HU, which prevented the use of “main air density” for densitometric
adjustment as an integral component of patient scan analysis, and a satisfactory method
of acquiring appropriate internal air calibration data at this site could not be identified.
This software limitation was a recognised feature of the scanner model at Copenhagen,
and it was agreed before study commencement that no air internal calibration and only
the blood internal calibration method [1] would be used for imaging acquired at the
Copenhagen centre.
Scan analysis
Lung imaging was analysed centrally (Heart Core Global Medical Imaging) using semiautomated software (Pulmo-CMS, MEDIS Medical Imaging Systems BV, Leiden, The
Netherlands) as described previously [2]. This program delineates lung parenchyma by
automatic lung segmentation (defined by an upper threshold of -380 HU) using a method
known as the “seeded-region growing technique”. The trachea is located manually, and
the program automatically identifies low-density voxels below the chosen threshold value
that are contiguous with the tracheal origin. Exclusion of the trachea between the point
of seeding and the carina then occurs automatically after lung segmentation. Internal
calibration allows adjustment of densitometric values by re-scaling lung segmentation
according to measurements obtained from the image series. Measurement of blood
density in the subdiaphragmatic descending thoracic aorta [1] and air density in the pre-
5
ventral area [3] were used for internal calibration on image sequences acquired at the
Birmingham and Malmö centres. Measurement of blood density in the subdiaphragmatic
descending thoracic aorta was used for internal calibration at the Copenhagen centre
(see above).
Blood calibration is performed semi-automatically commencing with the manual location
of markers within the aortic lumen to define the upper and lower limits of sampling. A
circular region of interest of approximately 5000 voxels is then automatically located
within the aortic lumen on each image between the defined upper and lower boundaries,
and the mean blood density (in HU) is calculated [4]. The same process is applied to the
pre-ventral air for internal air calibration [3]. Automatic detection of the septum
delineates right and left lungs, allowing calculation of parameters for both lungs
individually and as a whole. Errors in contour detection, such as inclusion of oesophagus
or bowel, or errors in left/right labelling require manual correction using a computer
“mouse” as scribe. There is an inherent potential for error secondary to variability in
operator performance [1], although this error is small and analysis at a central facility
(Heart Core) would be expected to minimise variability.
Blinded review of scan data
All CT scan data were assessed prior to study analysis by a blinded review panel of
experts (D. Parr, M. Brantly, A. Dirksen, T. Grobben). The panel carried out visual
inspection of images to identify any densitometric values that were not reliable because
of technical issues such as scan acquisition and image quality, and confounding factors
such as recent exacerbations, pneumonia, heart failure and presence of bullous lung.
Decisions were made by mutual consent and were fully documented. Any CT scan that
was considered invalid was excluded from the primary efficacy analysis. Reasons for
6
exclusion of scans were: (a) patient discontinued from the study prior to month 12 such
that no post-baseline scan was available; (b) a problem with the scanning procedure, the
scanner or the calibration of the scanner was detected; and (c) identification of a
pulmonary process unrelated to emphysema progression that affected lung density.
Parameter for CT end-points
Based on previous studies [5–7] and recommendations of an expert review [8], the 15th
percentile point was chosen as the parameter for the CT end-points and expressed as
the 15th percentile density (PD15). The 15th percentile point is defined as the value (HU)
at which 15% of the voxels in the frequency distribution histogram have a lower density
[6, 9], and it may be expressed as PD15 (g/L) by the simple addition of 1000 to the
Hounsfield value of the 15th percentile point.
Calculation of TLC-adjusted lung density
TLC-adjusted 15th percentile of lung density was calculated as follows:
Adjusted LD = Observed LD x (Observed TLV / Predicted TLC)
where “LD” represents 15th percentile of lung density measured by CT scan and “TLV”
represents lung volume achieved with full inspiratory effort during scan acquisition
(measured from whole CT imaging series).
Predicted TLC is estimated from:
7.99 x (height in m)  7.08 for males, and 6.60 x (height in m)  5.79 for females [10].
7
RESULTS
CT scan data at 3 months
Optional additional scans were performed at 3 months with the intention of identifying
any initial influence of treatment. No difference was found between the Prolastin® and
placebo groups over this short time period. Overall mean (SD) TLC-adjusted PD15
values for changes from baseline at 3 months were 1.37 g/L (4.09) in the Prolastin®
group and -0.29 g/L (2.77) in the placebo group (p=0.159). Three-month data were only
available from 36 of 71 participants in the modified intent-to-treat (mITT) population and
from two of the three centres. These data were not included in the final analysis of any
treatment effect.
Change in lung volume and lung weight
Mean values of lung volume as assessed by CT remained almost unchanged over the
course of the study (table 2). Comparison of the slopes showed that there was a greater
decrease in lung weight in the placebo group, although the treatment difference was not
statistically significant (table 3).
Change in lung function end-points
Mean annual decreases in FEV1 were -0.043 L (95% CI -0.063– -0.024) and -0.023 L (0.043– -0.004) in the Prolastin® and placebo groups, respectively (p=0.147); for diffusing
capacity of lung for carbon monoxide (DLCO), the corresponding annual decreases were
-0.460 mmol/min/kPa (95% CI -0.603– -0.317) and -0.343 mmol/min/kPa (-0.489– -0.196)
(p=0.257). There was a large variation in changes in KCO among individual patients. The
mean annual changes in KCO were nearly identical for the Prolastin® and placebo groups
8
(-0.036 mmol/min/kPa/L (95% CI -0.051– -0.020) and -0.035 mmol/min/kPa/L (-0.051– 0.020), respectively; p=0.967).
Serious adverse events (SAEs)
A listing of the numbers of subjects with at least one SAE is shown in table 4.
DISCUSSION
Additional discussion of the physiological adjustment method to correct lung
density for variation in inspiratory level
In Methods 1 and 3, adjustment of lung densities is physiologically based on the
assumption that the lung behaves like a sponge (sponge-model) [11]. The “sponge
model” makes two assumptions: weight = volume × density, and the total lung weight
stays constant during the breathing cycle, which means that, for example, halving the
volume should double the density. The latter assumption may seem incompatible with
the fact that the generation of negative intrathoracic pressure required for inspiration will
necessarily be accompanied by a variable increase in blood flow to the lung. However,
most of the blood flow into the lung is intercepted by large capacitance veins and, with a
threshold for the soft tissue–lung interface of -380 HU, large vessels were excluded from
the “lung” by the region-growing algorithm. Consequently, this physiological effect should
not influence the weight of the lung as calculated from the CT scans using the PulmoCMS software [11].
9
REFERENCES
1 Stoel BC, Vrooman HA, Stolk J, Reiber JH. Sources of error in lung densitometry with
CT. Invest Radiol 1999; 34: 303–309.
2 Stolk J, Ng WH, Bakker ME, Reiber JH, Rabe KF, Putter H, Stoel BC. Correlation
between annual change in health status and computer tomography derived lung density
in subjects with alpha1-antitrypsin deficiency. Thorax 2003; 58: 1027–1030.
3 Parr DG, Stoel BC, Stolk J, Nightingale PG, Stockley RA. Influence of calibration on
densitometric studies of emphysema progression using computed tomography. Am J
Respir Crit Care Med 2004; 170: 883–890.
4 Stoel BC, Stolk J. Optimization and standardization of lung densitometry in the
assessment of pulmonary emphysema. Invest Radiol 2004; 39(11): 681–688.
5 Dirksen A, Friis M, Olesen KP, Skovgaard LT, Sorensen K. Progress of emphysema in
severe alpha 1-antitrypsin deficiency as assessed by annual CT. Acta Radiol 1997; 38:
826–832.
6 Parr DG, Stoel BC, Stolk J, Stockley RA. Validation of computed tomographic lung
densitometry for monitoring emphysema in alpha1-antitrypsin deficiency. Thorax 2006;
61: 485–490.
7 Parr DG, Sevenoaks M, Deng C, Stoel BC, Stockley RA. Detection of emphysema
progression in alpha 1-antitrypsin deficiency using CT densitometry; methodological
advances. Respir Res 2008; 9(1): 21.
8 Newell JD, Hogg JC, Snider GL. Report of a workshop: quantitative computed
tomography scanning in longitudinal studies of emphysema. Eur Respir J 2004; 23: 769–
775.
9 Dirksen A, Dijkman JH, Madsen F, Stoel B, Hutchinson DC, Ulrik CS, Skovgaard LT,
Kok-Jensen A, Rudolphus A, Seersholm N, Vrooman HA, Reiber JH, Hansen NC,
10
Heckscher T, Viskum K, Stolk J. A randomized clinical trial of alpha 1-antitrypsin
augmentation therapy. Am J Respir Crit Care Med 1999; 160: 1468–1472.
10 Quanjer PH, Tammeling GJ, Cotes JE, Pedersen OF, Peslin R, Yernault JC. Lung
volumes and forced ventilatory flows. Report Working Party Standardization of Lung
Function Tests, European Community for Steel and Coal. Official Statement of the
European Respiratory Society. Eur Respir J Suppl 1993; 16: 5–40.
11 Shaker SB, Dirksen A, Laursen LC, Skovgaard LT, Holstein-Rathlou NH. Volume
adjustment of lung density by computed tomography scans in patients with emphysema.
Acta Radiol 2004; 45: 417–423.
11
TABLE 1 Scanner settings at the three active study centres
Parameter
Birmingham
Copenhagen
Malmö
GE
Philips
Siemens
Lightspeed
MX 8000 jdt
Somotom sensation
4
16
16
kVp
140
140
140
mA
40
60
60
mAs
20
eff.mAs=20/ mAs=30#
eff.mAs=20/ mAs=30#
0.5
0.5
0.5
6
24
24
Beam pitch mm
1.5
1.5
1.5
Collimation mm
4x5
16 x 1.5
16 x 1.5
5
5
5
Increment mm
2.5
2.5
2.5
Filter
Soft
A
B10f
CT scanner manufacturer
Type
Detector rows n
Image acquisition
Rotation time s
Detector pitch mm
Slice thickness mm
CT: computed tomography. #: scanners Copenhagen and Malmö were using the so-called effective mAs. Instead of effective mAs = 20 the actual mAs was 30.
12
TABLE 2 Changes (in litres) in CT-measured total lung volume from baseline (mITT population)
Prolastin®
Placebo
(n=36)
(n=35)
Month 12 (n=34, 33)
-0.029±0.390
-0.104±0.414
Month 24 (n=35, 32)
-0.011±0.376
0.041±0.277
Month 30 (n=18, 16)
-0.005±0.356
-0.045±0.284
0.002 (-0.049–0.053)
0.004 (-0.049–0.057)
Statistic
Change from baseline mean±SD
Random coefficient model# mean slope¶ 95% CI
Estimated treatment difference in mean slopes 95% CI
p-value for treatment difference+
-0.002 (-0.075–0.071)
0.959
CI: confidence interval. #: lung volume (L) as dependent variable, treatment, centre, treatment-by-time interaction as the fixed effects,
and intercept and time as the random effects; ¶: average annual loss of lung volume (L); +: Prolastin® minus placebo.
13
TABLE 3 Changes in CT-measured lung weight (g) from baseline (mITT population)
Prolastin®
Placebo
(n=36)
(n=35)
Month 12 (n=34, 33)
-6.028±31.283
-17.963±31.853
Month 24 (n=35, 32)
-8.631±44.524
-18.426±27.636
Month 30 (n=18, 16)
-13.210±45.342
-14.644±32.441
-4.901 (-10.196–0.394)
-9.770 (-15.275– -4.266)
Statistic
Change from baseline mean± SD
Random coefficient model# mean slope¶ 95% CI
Estimated treatment difference in mean slopes 95% CI
p-value for treatment difference+
4.869 (-2.768–12.507)
0.207
CI: confidence interval. #: lung weight (g) as dependent variable, treatment, centre, treatment-by-time interaction as the fixed effects,
and intercept and time as the random effects; ¶: average annual loss of lung weight (g); +: Prolastin® minus placebo.
14
TABLE 4 Numbers of subjects with at least one SAE
Prolastin®
Placebo
n=38
n=39
n (%)
n (%)
28
40
10 (26)
18 (46)
Severe exacerbations#
5 (13)
6 (15)
Pneumonia
3 (8)
4 (10)
Pneumothorax
2 (5)
0
Atrial fibrillation
2 (5)
0
Biliary colic
1 (3)
0
Constipation
1 (3)
0
Epistaxis
1 (3)
0
Gall bladder disorder
1 (3)
1 (3)
Gastro-oesophageal reflux
1 (3)
0
Malaria
1 (3)
0
Menorrhagia
1 (3)
0
Psoriasis
1 (3)
0
Transient ischaemic attack
1 (3)
0
Upper limb fracture
1 (3)
0
Abdominal pain
0
1 (3)
Intra-abdominal haemorrhage
0
1 (3)
Rectal haemorrhage
0
1 (3)
Nodule
0
1 (3)
Cholestatic jaundice
0
1 (3)
Appendicitis
0
1 (3)
Sepsis
0
1 (3)
Adverse event
Total number of SAEs
Number of patients with any SAE
16
Subcutaneous abscess
0
1 (3)
Urinary tract infection
0
1 (3)
Arthralgia
0
1 (3)
Osteoarthritis
0
1 (3)
Breast cancer
0
1 (3)
Chronic obstructive pulmonary
0
1 (3)
Dyspnoea
0
1 (3)
Pleural effusion
0
1 (3)
Pulmonary embolism
0
2 (5)
Pulmonary oedema
0
1 (3)
Lichen sclerosus
0
1 (3)
disease
SAE: serious adverse event. #: severe exacerbation with hospitalisation not previously
reported as SAE.
17