Academic Journal
Baseline Whole-Gland MRI Radiomics for Risk Stratification After Suspicious mpMRI and Negative Biopsy:A MULTIPROS Sub-Analysis
| Τίτλος: | Baseline Whole-Gland MRI Radiomics for Risk Stratification After Suspicious mpMRI and Negative Biopsy:A MULTIPROS Sub-Analysis |
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| Συγγραφείς: | Aloufi, Wafa, Szewczyk-Bieda, Magdalena, Aloufi, Asma, Wei, Cheng, Manfredi, Luigi |
| Πηγή: | Aloufi, W, Szewczyk-Bieda, M, Aloufi, A, Wei, C & Manfredi, L 2026, 'Baseline Whole-Gland MRI Radiomics for Risk Stratification After Suspicious mpMRI and Negative Biopsy : A MULTIPROS Sub-Analysis', Cancers, vol. 18, no. 17, 2823. https://doi.org/10.3390/cancers18172823 |
| Έτος έκδοσης: | 2026 |
| Συλλογή: | Discovery - University of Dundee Online Publications |
| Θεματικοί όροι: | radiomics, prostate cancer, multiparametric MRI, clinically significant prostate cancer, negative biopsy, TRUS, follow-up, prediction model, machine learning |
| Περιγραφή: | Background/Objectives: Patients with suspicious prostate mpMRI but negative baseline biopsy remain challenging to manage, as some are later diagnosed with clinically significant prostate cancer (csPCa). This study evaluated whether baseline whole-gland radiomic features from T2-weighted imaging and apparent diffusion coefficient (ADC) maps could predict subsequent csPCa detection. Methods: This retrospective radiomics sub-analysis of the MULTIPROS trial included men with suspicious baseline mpMRI findings (PI-RADS v2.0 categories 3–5) and no csPCa detected at baseline biopsy. The primary outcome was subsequent csPCa detection during follow-up, defined as ISUP Grade Group ≥2. Whole-gland prostate segmentation was performed on baseline T2-weighted images using a semi-automated approach with manual refinement, and the resulting T2-derived masks were applied to the spatially corresponding ADC maps. Radiomic features were extracted using PyRadiomics version 3.1.0a2 after standardised preprocessing. Feature robustness was assessed in a 20-patient reproducibility subset using intra- and inter-reader intraclass correlation coefficients, followed by correlation filtering and LASSO-based feature prioritisation. Radiomics-only, clinicoradiological-only, and clinicoradiological–radiomic logistic regression models were evaluated using stratified five-fold cross-validation. Results: T2-based modelling included 151 patients, of whom 36/151 (23.8%) had subsequent csPCa detected; the median time to csPCa detection or last follow-up was 64 months. ADC analyses included 144 patients, of whom 34/144 (23.6%) had subsequent csPCa detected. The T2 clinicoradiological–radiomic model achieved a mean AUC of 0.696 ± 0.060, compared with 0.713 ± 0.072 for the T2 clinicoradiological-only model and 0.456 ± 0.091 for the T2 radiomics-only model. In the ADC-available cohort, ADC radiomics-only, ADC clinicoradiological–radiomic, and combined T2 + ADC clinicoradiological–radiomic models achieved mean AUCs of 0.684 ± 0.052, 0.635 ± 0.157, and ... |
| Τύπος εγγράφου: | article in journal/newspaper |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| ISSN: | 2072-6694 |
| Relation: | info:eu-repo/semantics/altIdentifier/pissn/2072-6694 |
| DOI: | 10.3390/cancers18172823 |
| Διαθεσιμότητα: | https://discovery.dundee.ac.uk/en/publications/a53e7d52-a0e9-4148-9ea0-6d59c31096e2 https://doi.org/10.3390/cancers18172823 https://discovery.dundee.ac.uk/ws/files/177437650/cancers-18-02823.pdf |
| Rights: | info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ |
| Αριθμός Καταχώρησης: | edsbas.DDDB11BB |
| Βάση Δεδομένων: | BASE |
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