Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT04708483 |
| Other study ID # |
BC/6466 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
January 7, 2021 |
| Est. completion date |
December 31, 2022 |
Study information
| Verified date |
February 2021 |
| Source |
Hyperfusion |
| Contact |
Maarten Van Hoorickx |
| Phone |
+32483308781 |
| Email |
maarten[@]hyperfusion.ai |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
DCE-CT of thoracic tumors as an early biomarker for treatment monitoring in comparison with
morphologic criteria.
1. Rationale of the clinical investigation
For the evaluation of response to anti-tumoral therapy in thoracic tumors, merely
morphologic information is often not sufficient for early response evaluation as
dimensions of the oncologic lesions are not changing during the first weeks of
treatment. To be able to measure functional changes, dynamic contrast-enhanced CT
(DCE-CT) seems promising as a biomarker for early therapy monitoring.
Having an early biomarker for treatment monitoring will allow to increase patients'
prognosis if a non-responder is earlier detected, will optimize the use of expensive
treatments, is expected to shorten hospitalization and shorten absence at work, and to
decrease side-effects of (adjuvant) medication.
2. Objective of the study
2.1.Primary objectives The primary objective is to investigate the potential of functional
imaging (i.e. DCE-CT), as analyzed by the Hyperfusion analytic software, as an early
biomarker for the evaluation of therapy response in primary thoracic malignancy.
2.2.Secondary objectives
There are two secondary objectives:
1. To define internal system parameters and perfusion parameter thresholds that maximize
the accuracy of the outcomes and to define the correct category (PD, SD, PR, CR); and
2. To compare the predicted categorization to the assessed RECIST1.1 categorization.
3. Endpoints 3.1.Primary Endpoint The primary endpoint is to directly compare the biomarker
of the HF analysis software at week 3 (+- 1 week) and week 8 (+- 3 weeks) with the
eventually reported Progression-Free Survival (PFS) intervals and Overall Survival (OS)
in this study. PFS intervals are determined by the clinician and are based on RECIST1.1
and additional clinical and biochemical progression markers. The focus will be on
evaluating the accuracy of the prediction as well as how early the prediction was
correct.
3.2.Secondary Endpoints There are two secondary endpoints corresponding to the two secondary
objectives.
1. The internal parameters for the HF biomarker, e.g. magnitude of the Ktrans decrease, and
the change in volume of unhealthy tissue, need to be determined to define the
classification (PD, SD, PR and CR) by the HF analysis software. These parameters are
optimized to optimally predict the classification according to PFS and OS. This will be
done by splitting the data into a train and test set to ensure generalization.
2. The classification of the HF analysis software will be compared to the purely
morphological classification by RECIST1.1 to identify correlation. Furthermore, some
cases will be investigated where the HF analysis performs noticeably better or worse
than RECIST1.1 in predicting PFS and OS. Finally, the difference in time to the first
correct prediction is compared between HF and RECIST1.1.
4.Study Design
This prospective study is part of the clinical β-phase. We aim to test pre-release versions
of the Hyperfusion.ai software under real-world working conditions in a hospital (clinical)
setting. It is important to note, though, that the results of the software analysis will not
be used by interpreting physicians to alter clinical judgement during the course of the
clinical trial.
A prospective study including 100 inoperable patients in UZ Gent suffering from primary
thoracic malignancy (≥15mm diameter) will be conducted. For this study, in total 3 CT scan
examinations of the thorax will be performed (a venous CT examination of the thorax in
combination with a DCE-CT scan of the tumoral region).
All patients will be recruited from the pulmonology department. Oncologic patients are
clinically referred with certain intervals for a clinically indicated CT scan (being part of
standard care). In the study, two clinical CT examinations that are performed standard of
care (baseline CT examination and CT examination at week 8 (+- 3 weeks) after start of
systemic therapy) will be executed by also adding a DCE-image of the lung adenocarcinoma to
this examination. This DCE-image is performed during the waiting time before the
venous/morphologic phase. Consequently, from a clinical point-of-view, the time to scan
remains exactly the same. With regard to the contrast agent, an identical amount is injected
as is the case in standard of care, but the contrast bolus is split in two parts - see also
addendum with DCE protocol.
In this study there is one additional CT-examination (DCE-scan of the thoracic malignancy in
combination with venous CT scan of the thorax) at week 3 (± 1 week).
Description:
Introduction Background information
Below, you will find an overview the publications on DCE-CT, in the context of the evaluation
of treatment effect in cancer patients:
Strauch L et al (Diagnostics 2016: 21;6(3) - doi: 10.3390/diagnostics6030028) provide an
overview of the literature available on DCE-CT as a tool to evaluate treatment response in
patients with lung cancer. In studies where patients were treated with systemic chemotherapy
with or without anti-angiogenic drugs, four out of the seven studies found a significant
decrease in permeability after treatment. Four out of five studies that measured blood flow
post anti-angiogenic treatments found that blood flow was significantly decreased. This
review concluded that DCE-CT may be a useful tool in assessing treatment response in patients
with lung cancer. It seemed that particularly permeability and blood flow are important
perfusion values for predicting treatment outcome. However, the heterogeneity in scan
protocols, scan parameters, and time between scans makes it difficult to compare the reviewed
papers.
The research group of van Elmpt W and Lambin P (Radiother Oncol 2017: 125(3):379-384)
identified tumor subregions with characteristic phenotypes based on pre-treatment
multi-parametric functional imaging and correlated these subregions to treatment outcome. The
subregions were created using imaging of metabolic activity (FDG- Positron Emission
Tomography (PET)/CT), hypoxia (HX4-PET/CT) and tumor vasculature (DCE-CT). Thirty-six
non-small cell lung cancer (NSCLC) patients underwent functional imaging prior to radical
radiotherapy. Kinetic analysis was performed on DCE-CT scans to acquire blood flow (BF) and
volume (BV) maps. HX4-PET/CT and DCE-CT scans were non-rigidly co-registered to the planning
FDG-PET/CT. Two clustering steps were performed on multi-parametric images: first to segment
each tumor into homogeneous subregions (i.e. supervoxels) and second to group the supervoxels
of all tumors into phenotypic clusters. Patients were split based on the absolute or relative
volume of supervoxels in each cluster; overall survival was compared using a log-rank test.
Unsupervised clustering of supervoxels yielded four independent clusters. One cluster (high
hypoxia, high FDG, intermediate BF/BV) related to a high-risk tumor type: patients assigned
to this cluster had significantly worse survival compared to patients not in this cluster (p
= 0.035). It was concluded that subregional analysis for multi-parametric imaging in NSCLC
has the potential as a biomarker for prognosis. This methodology allows for a comprehensive
data-driven analysis of multi-parametric functional images.
Qiao P et al (Clin Transl Oncol 2016: 18(1):47-57) have studied the feasibility and clinical
value of DCE-CT for early evaluation of targeted therapy efficacy in non-small cell lung
cancer (NSCLC). They measured tumor diameter, peak height (PH), time to peak (TP), tumor
mass-aortic peak height ratio (M/A), and blood perfusion (BP) in 20 patients with advanced
NSCLC using DCE-CT before and 7 days after treatment. Therapy efficacy was assessed with
conventional CT 4-6 weeks post-treatment. Patients were grouped into those with partial
response (PR), stable disease (SD), and progressive disease (PD) according to the therapy
efficacy assessment at 4-6 weeks post-treatment. The PR group primary tumor diameter (P =
0.0007) and BP (P = 0.0225) were reduced at 7 days post-treatment; the SD group DCE-CT value
changes were not significant. The PD group M/A (P = 0.0443) and BP (P = 0.0268) were
increased 7 days post-treatment. The BP decrease group had significantly longer
progression-free survival than the BP increase group (median, 54 vs. 6 weeks). This study
concluded that DCE-CT can evaluate targeted therapy efficacy at 7 days post-treatment.
Decreased primary tumor diameter and BP indicate tumor sensitivity to therapy; increased BP
with unchanged tumor diameter suggests the tumor is not sensitive to therapy. Reduced BP
suggests treatment effectiveness.
Hwang et al (Eur Radiol 2013: 23(6):1573-81) compared tumor enhancement patterns measured
using DCE-CT with tumor metabolism measured using PET-CT in patients with non-small cell lung
cancer (NSCLC) and stable disease after chemotherapy or chemoradiotherapy. After treatment,
75 NSCLC tumors in 65 patients who had stable disease on DCE-CT according to Response
Evaluation Criteria in Solid Tumor (RECIST) were evaluated using PET-CT. On DCE-CT, relative
enhancement ratios (RER) of tumor at 30, 60, 90, 120 s and 5 min after injection of contrast
material were measured. Metabolic responses of tumors were classified into two groups
according to the maximum standardized uptake value (SUVmax) by PET-CT: complete metabolic
response (CR) with an SUVmax of less than 2.5, and non-complete metabolic response (NR) with
an SUVmax of at least 2.5. Using the optimal RER₆₀ cutoff value of 43.7 % to predict NR of
the tumor gave 95.7 % sensitivity, 64.2 % specificity, and 82.1 % positive and 95.0 %
negative predictive values. After adjusting for tumor size, the odds ratio for NR in the
tumor with an RER60 of at least 43.7 % was 70.85 (95 % CI = 7.95-630.91; P < 0.05). Even when
disease was stable according to RECIST, DCE-CT predicted hypermetabolic status of residual
tumor in patients with NSCLC after treatment.
Rationale of the clinical investigation
For the evaluation of response to anti-tumoral therapy in thoracic tumors, merely morphologic
information is often not sufficient for early response evaluation as dimensions of the
oncologic lesions are not changing during the first weeks of treatment. To be able to measure
functional changes, dynamic contrast-enhanced CT (DCE-CT) seems promising as a biomarker for
early therapy monitoring.
Having an early biomarker for treatment monitoring will allow to increase patients' prognosis
if a non-responder is earlier detected, will optimize the use of expensive treatments, is
expected to shorten hospitalization and shorten absence at work, and to decrease side-effects
of (adjuvant) medication.
Objective of the study
Primary objectives The primary objective is to investigate the potential of functional
imaging (i.e. DCE-CT), as analyzed by the Hyperfusion analytic software, as an early
biomarker for the evaluation of therapy response in primary thoracic malignancy.
Secondary objectives
There are two secondary objectives:
To define internal system parameters and perfusion parameter thresholds that maximize the
accuracy of the outcomes and to define the correct category (PD, SD, PR, CR); and To compare
the predicted categorization to the assessed RECIST1.1 categorization.
Endpoints Primary Endpoint The primary endpoint is to directly compare the biomarker of the
HF analysis software at week 3 (+- 1 week) and week 8 (+- 3 weeks) with the eventually
reported Progression-Free Survival (PFS) intervals and Overall Survival (OS) in this study.
The prediction of the four classes (PD, SD, PR and CR) is based on "significant changes" (see
7.2) in HF biomarker. PFS intervals are determined by the clinician and are based on
RECIST1.1 and additional clinical and biochemical progression markers. The focus will be on
evaluating the accuracy of the prediction as well as how early the prediction was correct.
Secondary Endpoints There are two secondary endpoints corresponding to the two secondary
objectives.
The internal parameters for the HF biomarker, e.g. magnitude of the Ktrans decrease, and the
change in volume of unhealthy tissue, need to be determined to define the classification (PD,
SD, PR and CR) by the HF analysis software. These parameters are optimized to optimally
predict the classification according to PFS and OS. This will be done by splitting the data
into a train and test set to ensure generalization.
The classification of the HF analysis software will be compared to the purely morphological
classification by RECIST1.1 to identify correlation. Furthermore, some cases will be
investigated where the HF analysis performs noticeably better or worse than RECIST1.1 in
predicting PFS and OS. Finally, the difference in time to the first correct prediction is
compared between HF and RECIST1.1.
Study Design
This prospective, monocentric (currently, however we do foresee to collaborate with other
centres to include patients with colorectal liver metastases; also other types of solid
tumors could be included; see ) study is part of the clinical β-phase. We aim to test
pre-release versions of the Hyperfusion.ai software under real-world working conditions in a
hospital (clinical) setting. It is important to note, though, that the results of the
software analysis will not be used by interpreting physicians to alter clinical judgement
during the course of the clinical trial.
A prospective study including 100 inoperable patients in UZ Gent suffering from primary
thoracic malignancy (≥15mm diameter) will be conducted. For this study, in total 3 CT scan
examinations of the thorax will be performed (a venous CT examination of the thorax in
combination with a DCE-CT scan of the tumoral region).
All patients will be recruited from the pulmonology department. Oncologic patients are
clinically referred with certain intervals for a clinically indicated CT scan (being part of
standard care). In the study, two clinical CT examinations that are performed standard of
care (baseline CT examination and CT examination at week 8 (+- 3 weeks) after start of
systemic therapy) will be executed by also adding a DCE-image of the primary thoracic
malignancy to this examination. This DCE-image is performed during the waiting time before
the venous/morphologic phase. Consequently, from a clinical point-of-view, the time to scan
remains exactly the same. With regard to the contrast agent, an identical amount is injected
as is the case in standard of care, but the contrast bolus is split in two parts - see also
addendum with DCE protocol.
In this study there is one additional CT-examination (DCE-scan of the thoracic malignancy in
combination with venous CT scan of the thorax) at week 3 (± 1 week).
Population Number of subjects At least one hundred patients will be included in this study.
Inclusion criteria Inoperable patients suffering from primary thoracic malignancy or second
line patients having had a therapy pause of at least 6 weeks; at least one tumoral
lesion/component should be at least 15mm in diameter.
Exclusion criteria All patients less than 18-years-old. Documented allergy for iodine.
Neutropenia (absolute White Blood Cell count ≤ 1.5 × 109/l). Thrombopenia (absolute platelet
count ≤ 100 × 109/l). Renal insufficiency: serum creatinine ≥ 1.5× the upper limit of normal
(ULN); 24-hours creatinine clearance ≤ 50ml/min).
Serum bilirubine ≥ 1,5 x ULN, AST ≥ 2,5 x ULN, ALT ≥ 2,5x ULN. Brain metastases. Withdrawal
and replacement of subjects
Criteria for withdrawal
Subjects may prematurely discontinue from the clinical investigation at any time. Premature
discontinuation from the study is to be understood when the subject did not undergo end of
study examination.
Subjects can be withdrawn under the following circumstances:
at their own request; if the investigator feels it would not be in the best interest of the
subject to continue; if the subject violates conditions laid out in the informed consent form
or disregards instructions by the clinical investigation personal; in case of significant
study intervention non-compliance;
In all cases, the reason why subjects are withdrawn will be recorded in detail in the CRF and
in the subject's medical records.
A subject will be considered lost to follow-up if he or she fails to return for the scheduled
visits and is unable to be contacted by the study site staff. The following actions must be
taken if a subject fails to return to the clinic for a required study visit:
The site will attempt to contact the subject and reschedule the missed visit. Before a
subject is deemed lost to follow-up, the investigator or designee will make every effort to
regain contact with the subject (where possible, 3 telephone calls and, if necessary, a
certified letter to the subject's last known mailing address or local equivalent methods).
These contact attempts should be documented in the subject's medical record or study file.
Should the subject continue to be unreachable, he or she will be considered to have withdrawn
from the study with a primary reason of being lost to follow-up.
Should the clinical investigation be discontinued prematurely, all clinical investigation
materials will be retained and the sponsor will notify the relevant regulatory authorities
and ethical committees.
Replacement policy
Drop-outs will be replaced.
Restrictions and prohibitions for the subjects
All patients must refrain from any food and drinks at least 4 hours before the CT-examination
(standard of care).
Possible advantages and risks for the subjects
At this stage there are no advantages for the patients studied. As a result of this study, we
anticipate that DCE-CT and the concurring Hyperfusion.ai analysis will function as an early
biomarker for treatment monitoring, thereby optimizing tumor treatments. So, for future
patients it is hoped that this study will prolong the PFS (progression-free survival).
There are no other risks than those associated with an intravenous injection of iodine-based
contrast-agent (fully comparable with standard of care IV injections of iodine). In this
patient population, there is no risk associated with the increased x-ray dose applied.
Methodology
Medical device description
Intended use and instructions for use Intended use
Hyperfusion.ai's software as a medical device is intended to be used by physicians in order
to perform a post-processing analysis of DCE-imaging, with the intention of accurately
calculating perfusion parameters.
Hyperfusion.ai's software is a radiological computer-assisted therapy monitoring software
device intended to be used concurrently by interpreting physicians while analysing DCE-images
that stem from medical imaging types and modalities, such as compatible computed tomography
scanners (CT), magnetic resonance imaging scanners, and others. The system computes perfusion
parameters within one scanning session and calculates the relative difference between
different scanning sessions. These findings assist interpreting physicians in evaluating
tumor response rate that may be confirmed or dismissed by the interpreting physician.
Consequently, this software is perceived as Class IIb, according to (Rule 11) of the MDR
2017/745, in the idea that Hyperfusion's software is 'intended to provide information which
is used to take decisions with diagnosis or therapeutic purposes.'
Delivery of the medical device The medical device software will not be accessible at the site
during the course of the clinical trial. Hyperfusion's software analysis is cloud-based and
can currently only be accessible by personnel of the manufacturer.
During the course of the clinical trial, the site (Department of Radiology) will be asked to
send the DICOM-data to Hyperfusion.ai via a highly-secure DNS-server that will be provided by
Hyperfusion.ai.
The processing result will be made available to the physician for download at an agreed cloud
location.
Storage of the medical device
The output of Hyperfusion.ai software analysis, will be stored at the highly-secure cloud
storage servers Hyperfusion uses.
Packaging and labeling of the medical device
The results will be provided to the physician in a digital form including the perfusion
parameter maps and the generated PDF-report. There will be a supporting document
(Instructions for use) to aid physicians in accurately interpreting the report. The following
information will be mentioned as 'label' on the PDF report:
The Medical Device Regulation 2017/745 requires for each investigational device to be
specifically labelled. As this concerns a software analysis (without user interface) which
generates a PDF-report for the user, the first page of this (unique) report contains the
following information:
Identification of the investigational device Hyperfusion.ai Kleemburg 1, 9050 Gentbrugge
Belgium info@hyperfusion.ai
The information in this report can only be used in the context of clinical investigation. If
interpreting physicians intend to use this report to alter their clinical judgement,
Hyperfusion.ai will not be held accountable.
UDI: 'HF-61fcda38 Report identificator: 'HF-8901
Known reactions/side effects of the medical device
Since the medical device functions in the form of a pipeline of software-algorithms, no side
effects can occur.
Study Specific Procedures
Screening visit This step is standard of care. At time of the first referral consultation
within the framework of the patient's oncologic rehabilitation, the pneumonologist will
determine whether the patient is eligible for systemic treatment, and fits the inclusion and
exclusion criteria.
Informed consent will be explained to the patient at first by the study coordinator. If the
patient is willing to participate more detailed information is communicated by the physician.
Final informed consent is obtained by the physician and 3 CT examinations (baseline, week 3
and week 8) will be planned.
Baseline CT examination A baseline CT-examination is standard of care. Maximally 28 days
before the start of systemic treatment the baseline CT examination is performed. This
includes a standard of care CT in combination with a study specific DCE-CT scan. Detailed
information on how to perform the study specific DCE-CT scan can be found in addendum with
DCE-CT protocol. The patient receives an identical dose of intravenous iodine based contrast
agent as in standard of care (venous phase) CT examination (contrast agent bolus is split in
2 parts - see explanation earlier/above).
Follow-up visit 1 The follow-up visit 1 is standard of care. 3 weeks (+/- 1 week) after the
start of the systemic treatment, a study specific DCE-CT scan will be scheduled at this visit
in combination with a venous phase CT. Detailed information on how to perform the study
specific DCE scan can be found in addendum with DCE-CT protocol. The patient receives an
identical amount of contrast agent during this CT examination when compared to standard of
care (venous) CT.
Follow-up visit 2 The follow-up visit 2 is standard of care. 8 weeks (+/- 3 weeks) after the
start of the systemic treatment follow-up visit 2 is planned. This visit is identical as
follow-up visit 1.
Follow-up until PFS. After follow-up visit 2, no study specific assessments will be performed
anymore. Data on the morphologically (standard of care) CT examinations based RECIST 1.1 will
be collected until PFS (and potentially Overall Survival). All patients will be in follow-up
at least until PFS (even after closing the clinical trial when the last patient has been
included). A maximum term for follow-up is however set at 1 year after the initiation of
therapy in all patients.
All patients are followed-up in standard care until PFS. For this clinical trial we aim at
following-up the patient until PFS but a maximum term for follow-up is set at 1 year after
the initiation of therapy for the patient. Data on adverse events will not be collected
anymore during follow-up until PFS. Only 'Death' will be reported to the sponsor.
During the clinical trial, data on tumor-type, applied systemic treatment, medical history,
gender and age will be collected.
Flowchart
Screening Baseline (T0 -28d) start systemic treatment (T0) FU visit 1 (T0 + 3 weeks (+/- 1
week)) FU visit 2 (T0 +8 weeks (+/- 3 weeks)) FU until PFS (max 1 year) Informed consent x
Inclusion/exclusion criteria check x
medical history x
demographic data x
morphologic scan, including RECIST
x x x x x documentation of applied treatment
x
DCE- CT scan
x
x x
Adverse event check
x x x x
reporting of death
x x x x x FU = Follow-up End of study
The end of study intervention is reached when the last subject (inclusion of patient 100),
has completed follow-up visit 2.
Overall, the end of the study is reached when PFS is reached in all included patients or 1
year after the last patient has started treatment. Between the end of study intervention and
PFS, data of standard of care CT examinations based on RECIST 1.1 will be collected.
Blinding
Blinding of patients or study personnel is not applicable in this trial.
Study analysis
Sample size calculation
One hundred patients will be used as a sample size. A preliminary power analysis for
determining the sample size was performed. Preliminary results have shown that a Ktrans
reduction of 40% would be indicative for differentiating between treatment responders and
non-responders. A preliminary power analysis under these assumptions shows that for a
statistically significant difference in mean value of 0.6 results in a power of 0.8439 for
100 patients.
Statistical analysis
The statistical analysis would be performed in-house by Ir. Verhack, PhD
(ruben@hyperfusion.ai) and Ir. Van den Abeele, PhD (floris@hyperfusion.ai).
In the following, two analyses will be proposed that support the primary endpoint and the
second secondary endpoint. Both analyses will be performed twice, once using the HF
prediction at week 3 (+- 1 week) and once using the prediction of week 8 (+- 3 weeks).
Two interim analyses will be performed over the course of the clinical study. The first will
be after 10 patients have been followed up for 6 months, and the second will be when 50
patients have been followed up for a year. The final analysis will be performed at the end of
the year 2 follow-up.
1. Analysis of correlation between HF biomarker and PFS and OS
First, the goal is to investigate if the HF biomarker based on Ktrans is indeed a viable
early biomarker to indicate treatment response or not. Therefore, a to-be-defined
descriptive statistic of the evolution of Ktrans (i.e. HF biomarker) will be compared to
the binary dependent variable responder/non-responder. The dependent variable is
determined from PFS and, in parallel, from OS. If there has been no event (progression
or death) before the last follow-up, then the patient is considered to be a "responder".
Two hypotheses will be tested. The first hypothesis states that the HF biomarker does
not significantly decrease for the responders group. The second hypothesis states that
for the non-responder group, there is no significant decrease in the HF biomarker. In
order to assess statistical significance for testing the null hypotheses, a paired
t-test is used with a p-value of 0.05 is considered. Note that the above sample size
calculation is based on this analysis.
Second, an analysis will be performed in which the survival curves of each prediction
class (CR, PR, SD, PD) is compared. As such, the duration until progression is taken
into account as well. Alternatively, these categories can be grouped into responders
(CR, PR) and non-responders (SD, PD). The survival curves are estimated using
Kaplan-Meier estimates [Friedman2010], keeping in mind the common pitfalls in working
with censored data using PFS [Korn2013].
2. Analysis of the correlation between the HF classification and RECIST1.1
Both prediction strategies result in the same classification which involves ordinal data with
four choices (CR, PR, SD, PD). The statistical analysis will investigate the correlation
between the two ordinal variables. The null hypothesis is that there is no linear relation
between the two variables. A p-value of 0.05 will be used to determine statistical
significance. The two ordinal variables will be compared using cross tabulation, Pearson and
Spearman's correlation coefficient. Alternatively, if there are issues with this statistical
analysis, e.g. it might be difficult for the HF software to distinguish between SD and PD,
then these two categories will be merged accompanied by an explanation.
[Korn2013] Korn, R. L., & Crowley, J. J. (2013). Overview: Progression-Free Survival as an
Endpoint in Clinical Trials with Solid Tumors. Clinical Cancer Research, 19(10), 2607-2612.
https://doi.org/10.1158/1078-0432.CCR-12-2934
[Friedman2010] Friedman, L. M., Furberg, C. D., & DeMets, D. L. (2010). Fundamentals of
Clinical Trials. https://doi.org/10.1007/978-1-4419-1586-3
Indemnity insurance
During their participation in the clinical investigation the patients will be insured as
defined by legal requirements. An insurance with no fault responsibility has been foreseen by
the sponsor in accordance with the Belgian law concerning experiments on humans, 7 May 2004.
Final Report
Within one year after the final completion of the study, a full final report will be written
by the sponsor and submitted to the central ethical committee and competent authority. The
Sponsor will pass this report to all local Principal Investigators for submission to their
local EC if defined by their institution's procedure.
Publication policy
This study will be registered at Clinicaltrials.gov prior to inclusion of the first subject.
Results information from this study will be submitted to Clinicaltrials.gov. Furthermore, the
sponsor & cooperating departments aim to publish in the following journals:
The New England Journal of Medicine British Medical Journal The Lancet Oncology Journal of
Clinical Oncology
Data Handling Case Report Form (CRF)
The source documents are to be completed at the time of the subject's visit. The CRFs are to
be completed within reasonable time after the subject's visit. For this study a digital CRF,
Smart-Trial software will be used. The following data might be collected in the CRFs over the
course of the clinical trial:
Demographic info Age Gender Medical history Other relevant demographic parameters
Diagnostic info:
Clinical diagnosis files Medication Specific to tumoral pathology Chemotherapy:
Platinum-based doublets, carboplatin/nab-P regimen, … Targeted therapy (biologicals:
Pembrolizumab, anti-PD-(L1) inhibitors, Nivolumab plus ipilimumab,...) Immunotherapy General
medication Blood analysis Complet (red blood cells, white blood cells, platelets) Liver
enzymes (transaminases, bilirubin, gGT) Renal function (creatinine, ureum, Glomerular
Filtration Rate) Bone biochemistry (calcium, calcitonin) Tumor markers: CEA
PET/CT-examinations: DICOM-images of other examinations that will be performed over the
course of this clinical trial.
For each subject enrolled the CRF will be signed by the principal investigator or
co-investigator. This also applies to those subjects who fail to complete the study. If a
subject withdraws from the study, the reason must be noted on the CRF. CRF entries and
corrections will only be performed by study site staff, authorized by the investigator and in
accordance with ISO 14155.
Errors will be logged by the software and corrections will be initiated and dated by the
study member that made the correction.
Entries will be checked by trained personnel (Monitor) and any errors or inconsistencies will
be changed immediately.
The original completed and signed CRFs will be collected at the end of the study by the
sponsor.
The Principal investigator must verify that all data entries in the CRFs are accurate and
correct. If certain information is Not Done, Not Available or Not Applicable, "N.D." or
"N.AV." or "N.AP", should be entered in the appropriate space.
Data directly collected in the CRF (no source available)
The DCE-images (in DICOM-format) can be regarded as sources-files and will, consequently, be
collected in the CRF directly. They will be pseudonymized before being sent to the sponsor.
Pseudonymized data will be sent to the cloud where it can be downloaded by Hyperfusion.ai.
Hyperfusion.ai analysis will be performed in a pseudonymised way. A PDF-report will be shared
after each CT examination to the study coordinator.
Direct access to source data / documents
The investigator will permit trial-related monitoring, audits, IRB/IEC review, and regulatory
inspection(s), providing direct access to source data/documents.
Archiving
The investigator and sponsor specific essential documents will be retained for at least 20
years. At that moment, it will be judged whether it is necessary to retain them for a longer
period, according to applicable regulatory or other requirement(s).
Quality assurance and periodic monitoring
The investigator will maintain adequate and accurate records to enable the conduct of the
study to be fully documented and the study data to be subsequently verified. These documents
will be classified into two different categories: investigator's file, and subject clinical
source documents.
The investigator's file will contain the documents as per EUROPEAN Standard of EN ISO 14155
(incl. GCP) and local regulations.
Regular monitoring will be performed by Hiruz CTU according to ICH GCP and ISO 14155. Data
will be evaluated for compliance with the protocol and accuracy in relation to source
documents. Following written standard operating procedures, the monitors will verify that the
clinical trial is conducted and data are generated, documented and reported in compliance
with the protocol, ISO 14155 and the applicable regulatory requirements. To be ISO 14155
compliant at least 3 monitoring visits are scheduled. An initiation visit, one routine visit
and a final visit after the last patient had finished the study. The monitor will be working
according to SOPs and will provide a monitoring report after each visit for the sponsor and a
follow-up letter to the investigator. Depending on the quality of the data, additional
monitoring visits will be necessary according to the sponsor's discretion.
More detailed information regarding the monitoring can be found in the monitoring plan which
will be the responsibility of the HIRUZ.
14 Designation
I certify that I will conduct the study in compliance with the protocol, any amendments,
GCP/ISO 14155, the declaration of Helsinki, and all applicable regulatory requirements.
Principal Investigator:
Name: Professor Veerle Surmont
Title: Prof. dr.
Date: 18/07/2020
