Radiomics of Treatment-naive Prostate Cancer Patients on Multiparametric MRI for Risk Stratification and Treatment Outcomes Predictions

Prostate cancers (PCA) are a heterogeneous group which include indolent tumors that has no clinical significance to very aggressive cancer that could result in morbidities and mortality. Thus, an accurate risk stratification at the time of PCA diagnosis is crucial. The histological examination of PCA biopsy specimens could not accurately predict the final tumor aggressiveness shown on radical prostatectomy specimens because of heterogeneous distributions of the most malignant tumor cells. Prostate multiparametric magnetic resonance imaging (mpMRI) has been generally accepted to be the best imaging modality for detecting and localizing prostate cancers themselves. Furthermore, the rapid development of radiomics provide comprehensive quantitative information of all tumor data which could be used for risk stratification and prognosis prediction. Thus, this study plans to enroll 200 eligible patients who undergo prostate mpMRI first, followed by radical prostatectomy for prostate cancers. We use radiomics extracted from prostate mpMRI for risk stratification patients of histological aggressiveness as well as to predict very early recurrence of PCA patients within 6 months after radical prostatectomy.

Study Overview

• Status: Active, not recruiting
• Conditions: Prostate Cancer
• Intervention / Treatment: Diagnostic test: Multiparametric magnetic resonance imaging (mpMRI)

Detailed Description

Prostate cancer is the 2nd most common malignancy in the world as well as the leading cancer in male population in Taiwan. The treatment selections of prostate cancer are limited by the uncertainty of its aggressiveness (i.e.: histological graded) and staging before treatment. Although prostate mpMRI has much better ability for detection and localization of prostate cancers than other imaging modalities and diagnostic tests, there is still gap for risk stratifications and treatment selection based on prostate mpMRI findings. Thus, a robust radiomics prediction models based on imaging biomarkers on prostate mpMRI with high prediction accuracy could fill the gap of misclassification of risk stratifications of prostate cancers, guides treatment selections and providing monitoring schedules for treated patients as well as early timely additional treatments (i.e.: target therapy or immunotherapy) for patients with high risk of early recurrence. Furthermore, radiomics could provide consistent information which help in decreasing interobserver and intra-observer variability of interpretating prostate cancer even in the use of PIRADS. In this way, this would save the fee of inappropriate or ineffective treatment and avoid unnecessary time and cost of monitoring low risk patients as well as improve patients' survivals and possibly life-quality as well.

• Study Type: Interventional
• Enrollment (Estimated): 125
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Taiwan
  • Taiwan
    • Taoyuan District, Taiwan, Taiwan, 333
      • Li-Jen Wang

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

1. Aged over 20 years old.
2. Suspected or confirmed prostate cancer.
3. Undergoing prostate mpMRI before clinical treatment.
4. Normal renal function(i.e.: estimated GFR ≧60).
5. No allergy history to gadolinium based contrast agent.
6. Agree to participate this study and sign informed consent.

Exclusion Criteria:

1. mpMRI photography not completed.
2. mpMRI images are damaged or poor in quality and cannot be interpreted.
3. Without pathological examination confirmed prostate cancer.
4. Patient withdraw informed consent.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Multiparametric magnetic resonance imaging; Detecting and localizing prostate cancers. The radiomics provide comprehensive quantitative information of all tumor data which could be used for risk stratification and prognosis prediction.	Diagnostic test: Multiparametric magnetic resonance imaging (mpMRI); Detecting and localizing prostate cancers and using radiomics extracted from prostate mpMRI for risk stratification patients of histological aggressiveness as well as to predict very early recurrence of PCA patients within 6 months after radical prostatectomy.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
MR characteristics assessment-T2WI	T2-weighted images (T2WI)	1.5 year
MR characteristics assessment- DWI	Axial diffusion weighted images (DWI)	1.5 year
MR characteristics assessment- ADC	Apparent diffusion coefficient maps (ADC)	1.5 year

Collaborators and Investigators

• Sponsor: Chang Gung Memorial Hospital
• Investigators: Principal Investigator: Li-Jen Wang, M.D., M.P.H., Chang Gung Memorial Hospital

Study record dates

Study Major Dates

• Study Start (Actual): February 15, 2022
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026

Study Registration Dates

• First Submitted: November 6, 2023
• First Submitted That Met QC Criteria: November 9, 2023
• First Posted (Actual): November 13, 2023

Study Record Updates

• Last Update Posted (Actual): March 20, 2026
• Last Update Submitted That Met QC Criteria: March 18, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: Prostate cancer; Recurrence; Risk stratification; Prediction; Multiparametric MRI; Radiomics
• Additional Relevant MeSH Terms: Urogenital Diseases; Genital Diseases; Pathologic Processes; Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Prostatic Diseases; Male Urogenital Diseases; Disease Attributes; Pathological Conditions, Signs and Symptoms; Prostatic Neoplasms; Recurrence; Diagnostic Techniques and Procedures; Diagnosis; Tomography; Diagnostic Imaging; Magnetic Resonance Imaging; Multiparametric Magnetic Resonance Imaging
• Other Study ID Numbers: 202002364B0

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Plan to make individual participant data.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No