Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer. Issue 2 (5th July 2021)

• Record Type: Journal Article
• Authors: Montoya Perez, Ileana; Merisaari, Harri; Jambor, Ivan; Ettala, Otto; Taimen, Pekka; Knaapila, Juha; Kekki, Henna; Khan, Ferdhos L.; Syrjälä, Elise; Steiner, Aida; Syvänen, Kari T.; Verho, Janne; Seppänen, Marjo; Rannikko, Antti; Riikonen, Jarno; Mirtti, Tuomas; Lamminen, Tarja; Saunavaara, Jani; Falagario, Ugo; Martini, Alberto; Pahikkala, Tapio; Pettersson, Kim; Boström, Peter J.; Aronen, Hannu J.
• Is Part Of: Journal of magnetic resonance imaging. Volume 55:Issue 2(2022)
• Page Start: 465
• Page End: 477
• Publication Date: 2021-07-05
• Subjects: biparametric MRI -- diffusion weighted imaging -- kallikreins -- prostate cancer -- PSA -- multi‐institutional trial -- prostate cancer screening; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.27811
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Background: Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group ≥ 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI). Purpose: To develop and validate radiomics and kallikrein models for the detection of csPCa. Study Type: Retrospective. Population: A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5‐alpha‐reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated. Field strength/Sequence: A 3 T/1.5 T, TSE T2‐weighted imaging, 3x SE DWI. Assessment: In total, 20, 363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate‐specific antigen, four kallikreins, MRI‐based qualitative (PI‐RADSv2.1/IMPROD bpMRI Likert) scores. Statistical Tests: For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P ‐value < 0.05 were considered significant. Results: The highest prediction performance was achieved by IMPROD bpMRI Likert and PI‐RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion‐derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P ‐value = 0.306; split 2: AUC = 0.83, P ‐value = 0.488). Data Conclusion: The use of radiomics and kallikreins failed to outperform PI‐RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains. Level of Evidence: 1 Technical Efficacy: Stage 2