Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT05855941 |
| Other study ID # |
Dnr 2022-04207-01 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 23, 2023 |
| Est. completion date |
May 2032 |
Study information
| Verified date |
August 2023 |
| Source |
Region Västerbotten |
| Contact |
Erika Figaro |
| Phone |
+46907850499 |
| Email |
erika.figaro[@]regionvasterbotten.se |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
The goal of this observational study is to learn about the added diagnostic and prognostic
value of advanced medical imaging procedures in cervical cancer, endometrial cancer and
ovarian cancer. The main questions it aims to answer are:
- Does advanced medical imaging predict survival?
- Can advanced medical imaging improve radiotherapy target planning?
- Are advanced medical imaging results associated with risk markers found in tumor tissue?
Participants will
- Undergo four additional imaging procedures, as compared to clinical routine
examinations, two at baseline and two after three months.
- Be subject to clinical follow-up for five years.
Description:
This study has a retrospective and a prospective part, where the main aims are to:
1. Retrospectively validate the added value of radiological staging to clinical staging
according to the International Federation of Gynecology and Obstetrics (FIGO) tumor
classification system, in cervical cancer, endometrial cancer, and epithelial ovarian
cancer.
2. Prospectively identify prognostic biomarkers with 18F-2-fluoro-2-deoxy-D-glucose
fluorodeoxyglucose (FDG)-positron emission tomography (PET)/CT and FDG-PET/MRI in
cervical cancer, endometrial cancer, and epithelial ovarian cancer
3. Assess the possible effect of PET/MRI on radiotherapy target delineation in cervical
cancer
4. Improve non-invasive lymph node staging in endometrial cancer
5. Develop a machine learning decision support tool for characterization of ovarian lesions
Material and methods (retrospective):
All eligible patients from the multi-disciplinary gynecological tumor conference at Umea
University Hospital during 2013-2022, with newly diagnosed cervical, endometrial, or
epithelial ovarian cancer, known cFIGO, >18 years old, and no other known current or previous
malignancy within the last 10 years, will be included in a retrospective evaluation of
radiological stage (rFIGO) based on all pre-operative imaging (MRI, CT and FDG-PET/CT),
clinical stage (cFIGO) based on examination under anesthesia (EUA), and histopathological
stage (pFIGO) based on available surgical and histopathological findings. The analysis will
be carried out in two cohort groups - 2016-01-01-2018-05-31, and 2018-06-01-2022-06-01,
before and after the implementation of the 2018 revised FIGO classification, after which the
cFIGO may be influenced to larger extent by imaging results. For all epithelial ovarian
cancer patients, Ovarian-Reporting and Data System (O-RADS) score will be annotated for each
MRI examination.
Agreement between rFIGO and cFIGO will be evaluated, and if feasible, compared to pFIGO. The
investigators will thus be able to validate rFIGO in cervical cancer with cFIGO up to Ib2,
and in endometrial and epithelial ovarian cancer treated with surgery.
The added value of rFIGO in terms of metastasis assessment and change of therapy, as well as
pattern and incidence of radiotherapy side effects will be evaluated in patients who were
considered inoperable.
Hypotheses (retrospective):
1. The degree of agreement is high between rFIGO T stage and cFIGO T stage in cervical,
endometrial, and epithelial ovarian cancer.
2. There is high sensitivity, specificity, accuracy, and negative and positive predictive
values of rFIGO to predict pFIGO in ovarian cancer of epithelial subtype.
3. There is an added value of rFIGO for metastasis assessment and change of patient
management in cervical cancer stages >Ib2, and in endometrial and epithelial ovarian
cancer patients who are considered inoperable.
Material and methods (prospective)
All eligible patients with newly diagnosed cervical cancer stage >1a, endometrial cancer type
2 and/or minimum stage 1, or strongly suspected epithelial ovarian cancer, consecutively
referred to the gynecological- oncological department of Umea University Hospital, with
written informed consent, will be included in a prospective study of the diagnostic and
prognostic value of FDG-PET/CT and FDG-PET/MRI at baseline and at therapy response evaluation
after 3 months. The subgroup of patients with cervical and endometrial cancer treated with
radiotherapy, will undergo one additional stand-alone MRI with dedicated tumor protocol after
one week of treatment for early response evaluation.
Patient demographics and age of menarche, menopause and parity will be collected to
characterize the study population. Furthermore, for epithelial ovarian cancer, levels of
tumor markers cancer antigen (CA)-125 and CA-19-9 as well as risk of malignancy index will be
collected.
The FDG-PET/CT will be performed according to clinical routine with intravenous injection of
FDG 3 megabecquerel (MBq)/kg, 60 minutes post-injection (with the addition of Sharp Inversion
Recovery (IR) reconstruction to be used for comparison with the FDG-PET/MRI), but without
intravenous iodine contrast agent, since the FDG-PET/MRI will be performed 120 minutes after
the same FDG-injection and will be prioritized for administration of gadolinium-based
contrast agent.
The FDG-PET/MRI will be designed according to standard clinical MRI protocol, dedicated for
each cancer type as described in detail below, with preparatory administration of 2 ml
Buscopan 20 mg/ml and gadolinium-based contrast agent Dotarem 279.3 mg/ml, 0.2 ml/kg body
weight (maximum 20 ml). If renal function is moderately impaired (relative GFR 45-59
ml/min/1.73 m2), the dose will be reduced to 0.1 ml/kg. If relative GFR is <45 ml/min/1.73 m2
the examination will be performed without iv contrast agent. The total examination time is
estimated to approximately 40 minutes.
Cervical cancer: T2-weighted (T2W) (sagittal, axial, coronal oblique, axial oblique), T1
Dixon all (axial), diffusion-weighted imaging (DWI) (b 100, 800, axial), optional Gd+ T1
Dixon (axial).
Endometrial cancer: T2W (sagittal, axial, axial oblique), T1Dixon all (axial oblique), DWI (b
100, 800, axial oblique), Gd+T1 Dixon (axial oblique, sagittal oblique).
Ovarian cancer: T2W (sagittal, axial, coronal), T1 Dixon all (axial), DWI (b 100, 800,
axial), Gd+T1Dixon (axial, sagittal).
Clinical evaluation will take place at 3 months, 6 months, 1 year and 5 years after start of
treatment with collection of clinical data progression-free survival (PFS, defined as the
time from start of treatment to progression or specific cancer-related death), overall
survival (OS, defined as the time from start of treatment to death from any cause), and
pattern and incidence of any radiotherapy side effects.
In FDG-PET/CT, pathological uptake of the suspected primary tumor will be visually
categorized into 1 = uptake < mediastinal background, 2 = uptake > mediastinal background and
< liver background, 3 = moderate uptake > liver background, or 4 = intense uptake > liver
background. From the PET/CT and PET/MRI examinations, primary tumor PET parameters will also
be quantified in maximum standardized uptake value (SUVmax), mean standardized uptake value
(SUVmean), functional tumor volume (FTV) and total lesion glycolysis (TLG). In addition, the
categorical parameters tumor heterogeneity, suspected radiological lymph node metastases
(present or not, N1 or N0) will be reported for both, and distant metastases (M1 or M0) will
be reported for PET/CT. CT and MRI parameters volume, delineation, contrast enhancement and
diffusion restriction, as well as tumor heterogeneity will also be assessed. Interpretation
of rFIGO will be reported for both PET/MRI and PET/CT.
At the 3 months´evaluation, the same imaging parameters will be evaluated and absolute
differences in continuous parameters as well as up-grading or down-grading of categorical
parameters will be analyzed. The patients treated with radiotherapy or chemotherapy will be
categorized into responders, defined as complete or partial metabolic response, and
non-responders, defined as stable metabolic disease or progressive metabolic disease,
according to PERCIST criteria (see References). The feasibility of FDG-PET/MRI for
radiotherapy dose planning guidance will be compared to standard imaging-based guidance
regarding target delineation of gross tumor volume (GTV), and the prognostic difference
between the group of early responders (any perceptible response) at one week´s stand-alone
MRI evaluation, compared to non-responders (stable or progressive disease), will be assessed.
In the histopathological analysis, prognostic factors will be recorded and if applicable,
immunohistochemical stainings for P53, Ki-67, ER, D240 and CD31, as well as molecular
analysis of microsatellite instability (MSI), breast cancer susceptibility gene (BRCA)-, and
polymerase-epsilon (POLE)-mutations and possible additional genes of emerging interest will
be performed.
For the study participants with endometrial cancer scheduled for surgery with sentinel node
algorithm, imaging characteristics of suspected lymph nodes will be described in terms of
visually quantified pathological FDG-PET uptake according to the four previously mentioned
categories, and PET parameters SUVmax, SUVmean, FTV, TLG and tumor heterogeneity. CT and MRI
parameters size, shape, delineation, contrast enhancement, diffusion restriction and tumor
heterogeneity will also be assessed. The lymph node with the highest metabolic activity
(SUVmax) will be selected for each affected lymph node region: external iliac, internal
iliac, common iliac, obturator and infrarenal paraaortic regions. In addition, the same
parameters will be analyzed for the primary tumor to evaluate its predictive value of lymph
node metastases. Regarding histopathology in this sub-study, as a starting point
morphological patterns detected on hematoxylin-eosin stained glass will be recorded. These
patterns will then guide further immunohistochemical and molecular analyses to highlight the
changes that have occurred in the metastatic lymph nodes.
For the ovarian cancer dataset, the investigators will develop a machine learning method for
diagnostic decision support and prognostic prediction. The modeling data set will consist of
the various MRI data from different MRI scanners and protocols, annotated with O-RADS (MRI),
from ovarian cancer patients from the previous retrospective part of the PRODIGYN study. The
matching dataset of controls will be acquired from the non-ovarian (cervical and endometrial)
cancer patient cohort from the above-mentioned retrospective study. After training,
validation and testing, the investigators will apply the machine learning method for O-RADS
(MRI) risk categorization on the prospective study dataset and compare the diagnostic
performance of the machine learning method with two radiologists, by area under the receiver
operating characteristic curve (AUC-ROC) analysis, with ground truth histopathology. The
prognostic predictive performance will be assessed using O-RADS 4 and 5 lesion labeling as
markers of poor prognostic outcome, with ground truth PFS and OS.
Hypotheses (prospective):
1. FDG-PET/CT and FDG-PET/MRI biomarkers can predict PFS and OS in cervical, endometrial,
and epithelial ovarian cancer
2. FDG-PET/CT and FDG-PET/MRI metrics at follow-up of therapy response have higher
prognostic impact than baseline
3. Early tumor response on MRI after radiotherapy predicts better prognosis
4. Early response patterns in organs at risk may predict serious adverse events
5. Target delineation of GTV in cervical cancer is significantly different with FDG-PET/MRI
compared to local standard MRI
6. Degree of agreement, sensitivity, specificity and accuracy of FDG-PET/CT and FDG-PET/MRI
are high for lymph node metastases on regional and on patient basis in endometrial
cancer
7. Primary tumor FDG-PET/CT and FDG-PET/MRI imaging characteristics can predict aggressive
histological type II, MSI phenotype and presence of lymph node metastases in endometrial
cancer
8. FDG-PET/MRI can be used to distinguish BRCA-mutated from non-BRCA-mutated ovarian cancer
by differences in growth pattern and metabolic activity
9. The histopathological immune response in sentinel nodes can predict prognosis and
correlate with FDG-PET/CT and FDG-PET/MRI biomarkers in endometrial cancer
10. There is an added value of FDG-PET/CT and FDG-PET/MRI to the sentinel node algorithm,
for detection of para-aortic lymph node metastases in endometrial cancer
11. The machine learning method performs similarly to radiologists in O-RADS 1-4 but is
inferior in O-RADS 5
