An interventional study of Multiparametric magnetic resonance imaging (mpMRI) in Prostate Cancer, sponsored by Chang Gung Memorial Hospital. Active, not recruiting at 1 site in Taiwan. Open to male participants aged 20 Years and older. Per ClinicalTrials.gov, last updated 2026-03-20.
Sponsored by Chang Gung Memorial Hospital · Not applicable, Interventional, and Other
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.
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.
6,367 studies on the registry are indexed under Prostatic Neoplasms; 1,397 are open to participants now.
This study's planned enrollment of 125 is above the median of 58 across 4,821 interventional studies indexed under Prostatic Neoplasms.
Browse Prostatic Neoplasms studies →Chang Gung Memorial Hospital is the lead sponsor of 1,064 studies on the registry; 235 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
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.
MR characteristics assessment-T2WI
T2-weighted images (T2WI)
Time frame: 1.5 year
MR characteristics assessment- DWI
Axial diffusion weighted images (DWI)
Time frame: 1.5 year
MR characteristics assessment- ADC
Apparent diffusion coefficient maps (ADC)
Time frame: 1.5 year
Plan to share: No — Plan to make individual participant data.
No publications or documents are linked to this record.
This study is active, not recruiting, as verified in Mar 2026. You cannot join it, but the record below documents what was studied.
Get an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
Chang Gung Memorial Hospital