Not yet recruitingObservationalLast updated Aug 12, 2026

Investigation of an Intelligent Centre-adaptive Multi-modal Fusion Framework (Cad- MMFF) to Overcome Unnecessary Prostate Biopsies and Optimize MRI Utilization

Investigation of an Intelligent Centre-adaptive Multi-modal Fusion Framework (Cad- MMFF) to Overcome Unnecessary Prostate Biopsies and Optimize MRI Utilization: a Hybrid Retrospective-prospective Study

Overview

ClinicalTrials.gov ID: NCT07760857
Lead Sponsor: Chinese University of Hong KongOTHER
Brief Summary: This study aims to investigate a novel Centre-Adaptive Multi-Modal Fusion Framework (Cad-MMFF) that integrates clinical, ultrasound, and MRI data to improve the detection of clinically significant prostate cancer (csPCa), reduce unnecessary biopsies, and optimize MRI utilization.
Study Type

Status

Overall Status: Not yet recruiting
Start Date: Sep 1, 2026Estimated
Primary Completion Date: Sep 1, 2026Estimated
Completion Date: Mar 31, 2030Estimated

Study Record Dates

First Submitted: Aug 2, 2026
First Submitted that Met QC Criteria: Aug 7, 2026
First Posted: Aug 12, 2026Actual
Last Update Submitted that Met QC Criteria: Aug 7, 2026
Last Update Posted: Aug 12, 2026Actual
Last Verified: Aug 2026

NCT06589154Completed

The Application of Multimodal Artificial Intelligence Systems in Prostate Cancer Diagnosis and Prognosis Analysis

NCT01964638Completed

Use of Multi-Parametric MRI With Prostate Biopsy for Cancer Diagnosis.

NCT06183905Active, not recruiting

Multi-parametric Ultrasound Versus Multi-parametric MRI for Prostate Cancer Detection

NCT07690306Enrolling by invitation

Development and Validation of a Non-Invasive AI Diagnostic Model for Prostate Cancer Using Multiparametric MRI and PSMA PET/CT

NCT07631806Active, not recruiting

Intelligent Screening and Precision Diagnosis of Prostate Cancer Based on Multimodal Data

NCT07614256Recruiting

Multimodal Imaging and Digital Pathology for Prostate Cancer Prediction