MRI and Radiomics Evaluation for Prostate Cancer

(MRI-PREDICT Trial)

Overseen By Beverly A Lieuwen, BSc

Age: Any Age

Sex: Male

Trial Phase: Academic

Sponsor: Nova Scotia Health Authority

Disqualifiers: Past prostatic interventions, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 3 Jurisdictions This treatment is already approved in other countries

Compensation: Varies

Number of Visits: 2

60 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to enhance the use of MRI scans in understanding prostate cancer. Researchers plan to develop a computer program to analyze MRI images and assess the aggressiveness of prostate cancer. This tool could assist doctors in determining the best treatment for each patient. Men newly diagnosed with prostate cancer who have had an MRI scan revealing a suspicious nodule may be suitable for this study. As an unphased trial, this study allows participants to contribute to groundbreaking research that could improve future prostate cancer diagnosis and treatment.

Do I need to stop my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that this MRI and radiomics evaluation is safe for prostate cancer patients?

Research has shown that using MRI with radiomics to study prostate cancer is safe. MRI, or magnetic resonance imaging, is a common medical tool that uses strong magnets and radio waves to create detailed images of the body's interior. Studies have found that MRI, when combined with radiomics—a technique that extracts extensive information from these images—can accurately evaluate prostate cancer without surgery.

No reports of serious side effects have emerged from using MRI for prostate cancer. This trial does not involve new drugs or surgeries; it focuses on advanced imaging techniques. Patients generally find this method easy to handle. Overall, based on current evidence and the method's non-invasive nature, participating in this study is expected to be low-risk. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the MRI and Radiomics Evaluation for Prostate Cancer because it combines advanced imaging techniques with data analysis to potentially improve diagnostic accuracy. Unlike traditional methods that rely solely on MRI scans, this approach uses radiomics, which extracts a large number of features from medical images to uncover patterns not visible to the naked eye. This could lead to more precise detection and monitoring of prostate cancer, helping doctors tailor treatments more effectively to individual patients. Ultimately, this innovative approach aims to enhance the reliability of prostate cancer evaluations, providing more consistent and accurate results.

What evidence suggests that MRI with Radiomics Evaluation is effective for prostate cancer?

Research shows that using MRI scans with radiomics holds promise for detecting and evaluating prostate cancer. Studies have found that multiparametric MRI (mp-MRI) accurately identifies prostate cancer, reducing errors like false positives or missed diagnoses. Radiomics, which analyzes data from medical images, enhances this process by providing detailed tumor information. Early research suggests that combining radiomics with MRI can help predict cancer aggressiveness, leading to better treatment choices. Overall, this method could improve how doctors understand and treat prostate cancer. In this trial, participants will undergo two MRI scans to assess the stability and accuracy of this combined approach over time. ^{6 7 8 9 10}

Who Is on the Research Team?

Dr. Michael Kucharczyk

Principal Investigator

Nova Scotia Health Authority

Are You a Good Fit for This Trial?

This trial is for men in Canada with prostate cancer who have had a specific type of MRI at the Halifax Infirmary and a diagnostic biopsy showing at least one nodule corresponding to cancer. They must not have altered testosterone levels, past interventions affecting prostate structure, or conditions causing significant MRI artifacts.

Inclusion Criteria

- Being performed on 3T MRI at the Halifax Infirmary Building

- Acquired T1+contrast, T2, and attenuated diffusion coefficient (ADC) series axial images of the prostate

- Having a detectable nodule which anatomically localizes to prostate cancer (PCa) identified in diagnostic biopsy specimen

Exclusion Criteria

Alterations to physiological testosterone levels

Inability to position one's self in a reproducible fashion for an MRI-P

Patient factors reported to produce significant artifact on MRI-P 1

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Baseline MRI-P

Participants undergo the first MRI-P as part of the standard of care

Baseline

1 visit (in-person)

Follow-up MRI-P

Participants undergo a second MRI-P to assess the stability of MRT classification

8 weeks

1 visit (in-person)

Follow-up

Participants are monitored for the accuracy and stability of MRT classification compared to biopsy results

8 weeks

What Are the Treatments Tested in This Trial?

Interventions

• MRI of the Prostate Combined with Radiomics Evaluation

Trial Overview

The study aims to validate and enhance a computer program that uses MR images to predict the aggressiveness of prostate cancer. It will assess if this tool can improve the standardization and accuracy of MRI evaluations in determining tumor biology.

How Is the Trial Designed?

Group I: Prospective Cohort Experimental Treatment 2 Interventions

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).

Who Is Running the Clinical Trial?

Nova Scotia Health Authority

Lead Sponsor

Trials

302

Recruited

95,300+

Published Research Related to This Trial

Multiparametric MRI (mp-MRI) is highly effective for detecting prostate cancer (PCa) and is essential for tumor localization, cancer staging, and monitoring recurrence, making it a key tool in patient management.

Radiomics enhances the evaluation of PCa by converting MRI images into detailed data, which can help in assessing tumor aggressiveness, reducing unnecessary biopsies, and improving predictions for treatment outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multiparametric MRI and Radiomics in Prostate Cancer: A Review of the Current Literature. Midiri, F., Vernuccio, F., Purpura, P., et al.[2021]

A multi-parametric MRI (mp-MRI)-based radiomics signature was developed using data from 280 prostate cancer patients, showing significant ability to distinguish between clinically significant prostate cancer (csPCa) and insignificant prostate cancer (ciPCa).

The radiomics signature demonstrated strong classification performance with an area under the curve (AUC) of 0.872 in the training cohort and 0.823 in the test cohort, indicating its potential as a noninvasive diagnostic tool for prostate cancer assessment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multi-parametric MRI-based radiomics signature for discriminating between clinically significant and insignificant prostate cancer: Cross-validation of a machine learning method. Min, X., Li, M., Dong, D., et al.[2019]

Multiparametric magnetic resonance imaging (mpMRI) significantly enhances the detection and risk classification of prostate cancer, especially in patients with previous negative biopsies and elevated PSA levels.

While mpMRI improves diagnostic accuracy, it may still miss smaller tumors, highlighting the need for continued advancements in imaging techniques to support safe treatment options like focal therapy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multiparametric magnetic resonance imaging: Overview of the technique, clinical applications in prostate biopsy and future directions. Demirel, HC., Davis, JW.[2020]

Multiparametric prostatic MRI (mpMRI) is currently the best imaging tool for detecting prostate cancer (PCa), aiding in diagnosis, treatment planning, and follow-up, despite some limitations in identifying significant cancers in certain patients.

Inter-reader variability in interpreting mpMRI results is a major limitation, but advancements in radiomics may help improve detection accuracy and reduce costs by identifying imaging biomarkers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multiparametric magnetic resonance imaging of the prostate: Lights and shadows. Santoro, AA., Di Gianfrancesco, L., Racioppi, M., et al.[2021]

Multiparametric MRI (mpMRI) combined with radiomics can enhance the identification of different tumor habitats in prostate cancer, allowing for better differentiation between indolent and aggressive disease, which can lead to more personalized treatment decisions.

The use of radiogenomics may improve biopsy targeting and reduce unnecessary procedures by non-invasively identifying areas likely to harbor aggressive cancers, potentially leading to more effective and less toxic treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Prostate cancer radiomics and the promise of radiogenomics. Stoyanova, R., Takhar, M., Tschudi, Y., et al.[2022]

Multiparametric prostate MRI (mpMRI) is evolving from just staging prostate cancer to also detecting and categorizing lesions, thanks to the emerging field of radiomics, which analyzes data from medical images.

Radiomics can help predict important factors like Gleason scores and the likelihood of cancer spreading, and future advancements in artificial intelligence may further enhance its effectiveness in prostate cancer diagnosis and management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Radiomics and Prostate MRI: Current Role and Future Applications. Cutaia, G., La Tona, G., Comelli, A., et al.[2021]

In a study of 78 men with non-suspicious multiparametric MRI results, 92.3% had no cancer detected in subsequent biopsies, indicating a high negative predictive value for mpMRI in ruling out significant prostate cancer.

Among the few cases where prostate cancer was found (7.7%), the majority were classified as indolent, suggesting that non-suspicious mpMRI can effectively identify patients at low risk for aggressive disease.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Relationship between non-suspicious MRI and insignificant prostate cancer: results from a monocentric study. Renard-Penna, R., Roupret, M., Compérat, E., et al.[2018]

A radiomics approach using multiparametric MRI features can effectively quantify the phenotype of clinically significant prostate cancer, with the best model achieving an area under the curve (AUC) of 0.870 based on T2-weighted and diffusion-weighted imaging.

While dynamic contrast-enhanced imaging (DCE) features were included, their removal did not significantly affect diagnostic performance, indicating that T2-weighted and diffusion-weighted imaging are the key components for effective diagnosis.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer. Bleker, J., Kwee, TC., Dierckx, RAJO., et al.[2021]

A multimodal MRI-based radiomics nomogram was developed and validated using data from 141 training cases and 182 external validation cases, showing improved accuracy in predicting clinically significant prostate cancer (CS-PCa) compared to traditional evaluations.

The nomogram, which combines a radiomics signature derived from MRI scans with the PI-RADS scoring system, significantly outperformed subjective assessments in all datasets, indicating its potential for noninvasive and precise cancer prediction.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Prediction of clinically significant prostate cancer with a multimodal MRI-based radiomics nomogram. Jing, G., Xing, P., Li, Z., et al.[2022]

A hybrid model combining MRI radiomics features and clinical data was highly effective in predicting progression-free survival (PFS) in prostate cancer patients, achieving AUCs of 0.926 in the training group and 0.917 in the validation group based on a study of 191 patients.

The developed nomogram serves as a non-invasive tool for risk stratification, indicating that patients in the high-risk group had shorter PFS compared to those in the low-risk group, highlighting its potential clinical application.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

MRI radiomics predicts progression-free survival in prostate cancer. Jia, Y., Quan, S., Ren, J., et al.[2023]

Radiomics models using high-resolution T2-weighted MRI were found to be more effective for detecting prostate cancer compared to dynamic contrast-enhanced MRI, based on a study of 32 patients with high prostate-specific antigen levels.

The best-performing model achieved 100% accuracy, specificity, and sensitivity in classifying prostate lesions, demonstrating the potential of machine learning techniques to improve the reliability of prostate cancer diagnosis in MRI images.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Radiomics-based machine-learning method to diagnose prostate cancer using mp-MRI: a comparison between conventional and fused models. Jamshidi, G., Abbasian Ardakani, A., Ghafoori, M., et al.[2023]

MRI-based radiomics models demonstrated good performance in distinguishing between benign and malignant prostate lesions, with the best model achieving an area under the curve (AUC) of 0.905 when combining T2-weighted imaging and apparent diffusion coefficient features.

The integrated models also showed promise in predicting extracapsular extension (ECE) and positive surgical margins (PSM), with the highest AUC for ECE being 0.728, indicating that these models could enhance clinical diagnosis and treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

MRI-based radiomics models to assess prostate cancer, extracapsular extension and positive surgical margins. He, D., Wang, X., Fu, C., et al.[2021]

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