MRI-PREDICT: Can MRI of the Prostate Combined With a Radiomics Evaluation Determine the Invasive Capacity of a Tumour

Sponsor

Nova Scotia Health Authority (Other)

Overall Status

Recruiting

CT.gov ID

NCT05024162

Collaborator

(none)

Enrollment

Location

Arm

19.9

Anticipated Duration (Months)

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

Prostate cancer is the most common cancer diagnosed in men in Canada. Magnetic resonance imaging (MRI) may become a valuable tool to non-invasively identify prostate cancer and assess its biological aggressiveness, which in turn will help doctors make better decisions about how to treat an individual patient's prostate cancer.

Despite the promise of MRI for detecting and characterizing prostate cancer, there are several recognized limitations and challenges. These include lack of standardized interpretation and reporting of prostate MRI exams.

The investigators propose to validate and improve a computer program computerized prediction tool that will use information from MR images to inform us how aggressive a prostate cancer is. The hypothesis is that this computer-aided approach will increase the reproducibility and accuracy of MRI in predicting the tumor biology information about the imaged prostate cancer.

Condition or Disease	Intervention/Treatment	Phase
Prostate Cancer	Diagnostic Test: MRT Accuracy Diagnostic Test: MRT Stability	N/A

Detailed Description

Prostate biopsies are the gold standard assessment of how prostate cancer is diagnosed and how low risk prostate cancers are surveilled. The investigators have produced a machine-learning based algorithm which uses MRI characteristics (radiomic features or textures) to predict the results of a prostate biopsy. The field has numerous concerns that such radiomic based predictions will not be reproducible, as there as so many subtle changes between MRI scans of different patients.

The interventions are the use of the MRT and the use of a second MRI of the prostate (MRI-P).

Two primary outcomes will be investigated. First, the existing radiomics predictive model, labeled as the MRI-P based Radiomics Tool (MRT) will predict the Grade Group (GG) and compare it to the gold standard, pathologist's evaluation of the Grade Group (GG). Second, the stability of the predicted GG between two shortly spaced MRI-Ps will be compared.

Patients with a detectable prostate nodule on MRI-P which localizes to a biopsy confirmed prostate cancer will be approached for enrollment. If enrolled, participants will attend for a subsequent MRI-P in a brief time frame relative to the acquisition of the first MRI-P. Attempts will be made to obtain participants that allow for even distribution among all GGs.

Study Design

Study Type:

Interventional

Anticipated Enrollment :

60 participants

Allocation:

N/A

Intervention Model:

Single Group Assignment

Masking:

None (Open Label)

Primary Purpose:

Diagnostic

Official Title:

Can Magnetic Resonance Imaging of the Prostate Combined With a Radiomics Evaluation Determine the Invasive Capacity of a Tumour (Can MRI-PREDICT)

Actual Study Start Date :

Jan 4, 2022

Anticipated Primary Completion Date :

Sep 1, 2023

Anticipated Study Completion Date :

Sep 1, 2023

Arms and Interventions

Arm	Intervention/Treatment
Experimental: Prospective Cohort Sixty patients with a new diagnosis of prostate cancer that meet eligibility criteria. The group will have two standard MRI-P's completed. The first MRI-P will be acquired as standard of care and the second will be an additional investigation for the purposes of this study. The efficacy of the MRT will be compared at both time points, evaluating if the MRT demonstrates clinically sufficient stability in its findings (i.e., does the MRT report an accurate and similar result at both time points).	Diagnostic Test: MRT Accuracy Predicted Grade Group (GG) by the MRI-based Radiomics Tool (MRT) at each Magnetic Resonance Imaging of the Prostate (MRI-P) Diagnostic Test: MRT Stability MRT's predicted GG at second MRI-P.

Arm

Intervention/Treatment

Experimental: Prospective Cohort

Sixty patients with a new diagnosis of prostate cancer that meet eligibility criteria. The group will have two standard MRI-P's completed. The first MRI-P will be acquired as standard of care and the second will be an additional investigation for the purposes of this study. The efficacy of the MRT will be compared at both time points, evaluating if the MRT demonstrates clinically sufficient stability in its findings (i.e., does the MRT report an accurate and similar result at both time points).

Diagnostic Test: MRT Accuracy

Predicted Grade Group (GG) by the MRI-based Radiomics Tool (MRT) at each Magnetic Resonance Imaging of the Prostate (MRI-P)

Diagnostic Test: MRT Stability

MRT's predicted GG at second MRI-P.

Outcome Measures

Primary Outcome Measures

MRT Classification Change [Baseline, 8 weeks]
Stability of participants' MRT classification (each of the five GG groups) between two shortly spaced MRIs.
MRT Classification: Baseline [Baseline]
The accuracy of the GG classification from the MRT. Will be compared to the Gold Standard - prostate biopsy results. The percentage of MRT classifications that show agreement between the two methods (i.e. Gold Standard and MRT) in terms of GG classification will be reported.
MRT Classification: Week 8 [8 weeks]
The accuracy of the GG classification from the MRT. Will be compared to the Gold Standard - prostate biopsy results. The percentage of MRT classifications that show agreement between the two methods (i.e. Gold Standard and MRT) in terms of GG classification will be reported.

Secondary Outcome Measures

Model optmization with novel radiomic features and clinical covariates [At study completion, 2 years.]
Gwet's first order agreement coefficient; McNemar's test to test agreement across the two time points, regarding GG classification agreement. Intra-class correlation coefficient (ICC) will to test the reliability of individual radiomic features at time points 1 and 2. Stability will be defined as an ICC ≥0.85. Ordinal logistic regression with a cumulative logic link will be used to model GG classification. Clinical covariates, PIRADS scores, and exclusively "reliable" radiomic features will be explored in secondary analyses.

Eligibility Criteria

Criteria

Ages Eligible for Study:

N/A and Older

Sexes Eligible for Study:

Male

Accepts Healthy Volunteers:

Inclusion Criteria:

An appropriate diagnostic MRI-P, defined as:

Being performed on 3T MRI at the Halifax Infirmary Building
Taken place within 5 weeks of study enrolment
Having a detectable nodule which anatomically localizes to prostate cancer (PCa) identified in diagnostic biopsy specimen
Acquired T1+contrast, T2, and attenuated diffusion coefficient (ADC) series axial images of the prostate

An appropriate diagnostic biopsy, defined as:

Taken place within 2 months of the participant's MRI-P 1
Taken place within 3 months of participant's study enrolment
Reports diagnosis of PCa
Reports a systematic assessment of the biopsy, assessing at least 12 cores
Reports at least on core involved with PCa and this core must anatomically localise to a nodule seen on MRI-P 1