Novel radiomic analysis on bi-parametric MRI for characterizing differences between MR non-visible and visible clinically significant prostate cancer.

around one third of clinically significant prostate cancer (CsPCa) foci are reported to be MRI non-visible (MRI─).

To quantify the differences between MR visible (MRI+) and MRI─ CsPCa using intra- and peri-lesional radiomic features on bi-parametric MRI (bpMRI).

This retrospective and multi-institutional study comprised 164 patients with pre-biopsy 3T prostate multi-parametric MRI from 2014 to 2017. The MRI─ CsPCa referred to lesions with PI-RADS v2 score < 3 but ISUP grade group > 1. Three experienced radiologists were involved in annotating lesions and PI-RADS assignment. The validation set (Dv) comprised 52 patients from a single institution, the remaining 112 patients were used for training (Dt). 200 radiomic features were extracted from intra-lesional and peri-lesional regions on bpMRI.Logistic regression with least absolute shrinkage and selection operator (LASSO) and 10-fold cross-validation was applied on Dt to identify radiomic features associated with MRI─ and MRI+ CsPCa to generate corresponding risk scores RMRI─ and RMRI+. RbpMRI was further generated by integrating RMRI─ and RMRI+. Statistical significance was determined using the Wilcoxon signed-rank test.

Both intra-lesional and peri-lesional bpMRI Haralick and CoLlAGe radiomic features were significantly associated with MRI─ CsPCa (p < 0.05). Intra-lesional ADC Haralick and CoLlAGe radiomic features were significantly different among MRI─ and MRI+ CsPCa (p < 0.05). RbpMRI yielded the highest AUC of 0.82 (95 % CI 0.72-0.91) compared to AUCs of RMRI+ 0.76 (95 % CI 0.63-0.89), and PI-RADS 0.58 (95 % CI 0.50-0.72) on Dv. RbpMRI correctly reclassified 10 out of 14 MRI─ CsPCa on Dv.

Our preliminary results demonstrated that both intra-lesional and peri-lesional bpMRI radiomic features were significantly associated with MRI─ CsPCa. These features could assist in CsPCa identification on bpMRI.

European journal of radiology open. 2023 Jun 13*** epublish ***

Lin Li, Rakesh Shiradkar, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, Pingfu Fu, Amr Mahran, Christina Buzzy, Phillip D Stricker, Ardeshir R Rastinehad, Cristina Magi-Galluzzi, Lee Ponsky, Eric Klein, Andrei S Purysko, Anant Madabhushi

Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, Cleveland, OH, USA., Department of Radiology, University Hospitals, Cleveland, OH, USA., Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA., Urology Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, USA., Department of Urology, St. Vincent's Clinic, Sydney, NSW 2010, Australia., Department of Urology, Lenox Hill Hospital, Northwell Health, New York, NY, USA., Department of Pathology, University of Alabama at Birmingham, AL, USA., Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA., Department of Biomedical Engineering, Emory University and Georgia Institute of Technology.