Clinical trial · Observational
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
NCT07760857CI-TRIAL-00121679not yet recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Prostate Cancer (Diagnosis) | Malignant Prostate Neoplasm | CURATED_EXACT | 0.85 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (6)
- measure
- Area under Receiver-Operating-Curve of using the Centre-adaptive multi-modal fusion framework (Cad-MMFF)
- timeFrame
- Through study completion, an average of 1 year
- measure
- The number of unnecessary biopsy rate decreased of using the Centre-adaptive multi-modal fusion framework (Cad-MMFF)
- timeFrame
- Through study completion, an average of 1 year
- measure
- Proportion of MRI safely saved of using the Centre-adaptive multi-modal fusion framework (Cad-MMFF)
- timeFrame
- Through study completion, an average of 1 year
- measure
- Net-Benefit of using the Centre-adaptive multi-modal fusion framework (Cad-MMFF)
- timeFrame
- Through study completion, an average of 1 year
- description
- By Decision Curve analysis
Eligibility
Eligibility (as posted)
- Sex
- Male
- Minimum age
- 45 Years
Show eligibility criteria text
Inclusion Criteria: * Ethnically Chinese men aged ≥ 50 * Suspicion of PCa \[elevated PSA (\>4-ng/ml) or abnormal DRE/PHI\] and indicated for prostate biopsy * Obtained clinical consent (for prospectively enrolled patients only) Exclusion Criteria: * Prior biopsy/treatments for PCa * History of genitourinary cancer * Poor image quality * Incomplete imaging scans/clinical data/pathological results
References
Publications (26)
- BACKGROUNDTRANSFORM Trial: Trial of Randomised Approaches for National Screening FOR Men (TRANSFORM) [Internet]. ISRCTN registry; 2025 [cited 2026 Mar 28]. ISRCTN13801649.
- BACKGROUNDCentre for Health Protection. Prostate cancer [Internet]. Hong Kong: Department of Health; 2026 [cited 2026 Mar 28]. Available from: https://www.chp.gov.hk/en/healthtopics/content/25/5781.html
- BACKGROUNDChiu PK, Roobol MJ, Nieboer D, Teoh JY, Yuen SK, Hou SM, Yiu MK, Ng CF. Adaptation and external validation of the European randomised study of screening for prostate cancer risk calculator for the Chinese population. Prostate Cancer Prostatic Dis. 2017 Mar;20(1):99-104. doi: 10.1038/pcan.2016.57. Epub 2016 Nov 29. PMID 27897172
- BACKGROUNDHajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics. J Biomed Inform. 2014 Apr;48:193-204. doi: 10.1016/j.jbi.2014.02.013. Epub 2014 Feb 26. PMID 24582925
- BACKGROUNDWu D, Lawhern VJ, Gordon S, Lance BJ, Lin C. Driver Drowsiness Estimation From EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR). IEEE Trans Fuzzy Syst. 2017;25(6):1522-35. doi:10.1109/TFUZZ.2016.2633379
- BACKGROUNDYue G, Wei P, Zhou T, Song Y, Zhao C, Wang T, Lei B. Specificity-Aware Federated Learning With Dynamic Feature Fusion Network for Imbalanced Medical Image Classification. IEEE J Biomed Health Inform. 2024 Nov;28(11):6373-6383. doi: 10.1109/JBHI.2023.3319516. Epub 2024 Nov 6. PMID 37751333
- BACKGROUNDJahanandish H, Sang S, Li CX, Vesal S, Bhattacharya I, Lee JH, et al. Multimodal MRI-Ultrasound AI for Prostate Cancer Detection Outperforms Radiologist MRI Interpretation: A Multi-Center Study [Preprint]. arXiv:2502.00146v1. 2025. doi:10.48550/arXiv.2502.00146
- BACKGROUNDWei P, Zhou T, Liu W, et al. FedPDN: Personalized federated learning with inter-class similarity constraint for medical image classification through parameter decoupling. IEEE Trans Instrum Meas. 2025; 74:1-13, Art no. 4001213, doi: 10.1109/TIM.2025.3527597