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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., (© 2021 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC. on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Multiparametric MRI of the prostate has been shown to improve the risk stratification of men with an elevated prostate-specific antigen (PSA). However, long acquisition time, high cost, and inter-center/reader variability of a routine prostate multiparametric MRI limit its wider adoption., Purpose: To develop and validate nomograms based on unique rapid biparametric MRI (bpMRI) qualitative and quantitative derived variables for prediction of clinically significant cancer (SPCa)., Study Type: Retrospective analyses of single (IMPROD, NCT01864135) and multiinstitution trials (MULTI-IMPROD, NCT02241122)., Population: 161 and 338 prospectively enrolled men who completed the IMPROD and MULTI-IMPROD trials, respectively., Field Strength/sequence: IMPROD bpMRI: 3T/1.5T, T 2 -weighted imaging, three separate diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm 2 ; 2) b values 0, 1500 s/mm 2 ; 3) values 0, 2000 s/mm 2 ., Assessment: The primary endpoint of the combined trial analysis was the diagnostic accuracy of the combination of IMPROD bpMRI and clinical variables for detection of SPCa., Statistical Tests: Logistic regression models were developed using IMPROD trial data and validated using MULTI-IMPROD trial data. The model's performance was expressed as the area under the curve (AUC) values for the detection of SPCa, defined as ISUP Gleason Grade Group ≥2., Results: A model incorporating clinical variables had an AUC (95% confidence interval) of 0.83 (0.77-0.89) and 0.80 (0.75-0.85) in the development and validation cohorts, respectively. The corresponding values for a model using IMPROD bpMRI findings were 0.93 (0.89-0.97), and 0.88 (0.84-0.92), respectively. Further addition of the quantitative DWI-based score did not improve AUC values (P < 0.05)., Data Conclusion: A prediction model using qualitative IMPROD bpMRI findings demonstrated high accuracy for predicting SPCa in men with an elevated PSA. Online risk calculator: http://petiv.utu.fi/multiimprod/ Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1556-1567., (© 2019 International Society for Magnetic Resonance in Medicine.)

Background: Accurate risk stratification of men with a clinical suspicion of prostate cancer (cSPCa) remains challenging despite the increasing use of MRI., Purpose: To evaluate the diagnostic accuracy of a unique biparametric MRI protocol (IMPROD bpMRI) combined with clinical and molecular markers in men with cSPCa., Study Type: Prospective single-institutional clinical trial (NCT01864135)., Subjects: Eighty men with cSPCa., Field Strength/sequence: 3T, surface array coils. Two T 2 -weighted and three diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm 2 ; 2) b-values 0,1500 s/mm 2 ; 3) b-values 0, 2000 s/mm 2 ., Assessment: IMPROD bpMRI examinations were qualitatively (IMPROD bpMRI Likert score) and quantitatively (DWI-based Gleason grade score) prospectively reported. Men with IMPROD bpMRI Likert 3-5 had two targeted biopsies followed by 12-core systematic biopsies (SB); those with IMPROD bpMRI Likert 1-2 had only SB. Additionally, 2-core from normal-appearing prostate areas were obtained for the mRNA expression of ACSM1, AMACR, CACNA1D, DLX1, PCA3, PLA2G7, RHOU, SPINK1, SPON2, TMPRSS2-ERG, and TDRD1 measured by quantitative reverse-transcription polymerase chain reaction., Statistical Tests: Univariate and multivariate analysis using regularized least-squares, feature selection and tournament leave-pair-out cross-validation (TLPOCV), as well as 10 random splits of the data in training-testing sets, were used to evaluate the mRNA, clinical and IMPROD bpMRI parameters in detecting clinically significant prostate cancer (SPCa) defined as Gleason score ≥ 3 + 4. The evaluation metric was the area under the curve (AUC)., Results: IMPROD bpMRI Likert demonstrated the highest TLPOCV AUC of 0.92. The tested clinical variables had AUC 0.56-0.73, while the mRNA and additional IMPROD bpMRI parameters had AUC 0.50-0.67 and 0.65-0.89 respectively. The combination of clinical and mRNA biomarkers produced TLPOCV AUC of 0.87, the highest TLPOCV performance without including IMPROD bpMRI Likert., Data Conclusion: The qualitative IMPROD bpMRI Likert score demonstrated the highest accuracy for SPCa detection compared with the tested clinical variables and mRNA biomarkers., Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1540-1553., (© 2019 International Society for Magnetic Resonance in Medicine.)

Background: Prostate MRI is increasingly being used in men with a clinical suspicion of prostate cancer (PCa). However, development and validation of methods for focal therapy planning are still lagging., Purpose: To evaluate the diagnostic accuracy on lesion, region-of-interest (ROI), and voxel level of IMPROD biparametric prostate MRI (bpMRI) for PCa detection in men with a clinical suspicion of PCa who subsequently underwent radical prostatectomy., Study Type: Prospective single-institution clinical trial (NCT01864135)., Population: Sixty-four men who underwent radical prostatectomy after IMPROD bpMRI performed in prebiopsy settings., Field Strength/sequence: IMPROD bpMRI consisted of T 2 -weighted imaging (T 2 w) and three separate diffusion-weighted imaging acquisitions with an average acquisition time of 15 minutes., Assessment: The diagnostic accuracy of prospectively reported manual cancer delineations and regions increased with 3D dilation were evaluated on the voxel level (volume of 1.17 mm 3 , 1 mm 3 , 125 mm 3 ) as well as the 36 ROI level. Only PCa lesions with a diameter ≥ 5 mm or any Gleason Grade 4 were analyzed. All data and protocols are freely available at: http://petiv.utu.fi/improd STATISTICAL TESTS: Sensitivity, specificity, accuracy., Results: In total, 99 PCa lesions were identified. Forty (40%, 40/99) had a Gleason score (GS) of >3 + 4. Twenty-eight PCa lesions (28%, 28/99) were missed by IMPROD bpMRI, three (7.5%, 3/40) with GS >3 + 4. 3D dilation of manual cancer delineations in all directions by ~10-12 mm (corresponding to the Hausdorff distance) was needed to achieve sensitivity approaching 100% on a voxel level., Data Conclusion: IMPROD bpMRI had a high sensitivity on lesion level for PCa with GS >3 + 4. Increasing 3D lesion delineations by ~10-12 mm (corresponding to the Hausdorff distance) was needed to achieve high sensitivity on the voxel level. Such information may help in planning ablation therapies., Level of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1641-1650., (© 2019 International Society for Magnetic Resonance in Medicine.)

Purpose: To evaluate the role of a 3T biparametric magnetic resonance imaging (bpMRI), T 2 -weighted imaging, and three separate diffusion-weighted imaging acquisitions combined with targeted biopsy (TB) for improving risk stratification of men with elevated prostate-specific antigen (PSA)., Materials and Methods: Between March 2013 and February 2015, 175 men with a clinical suspicion of prostate cancer (PCa) were offered bpMRI (NCT01864135) based on a suspicion of PCa (two repeated PSA measurements in the range 2.5-20.0 ng/ml and/or abnormal digital rectal examination). Men with an equivocal to high suspicion of PCa had two TBs of the dominant lesion using cognitive ultrasound guidance, followed by systematic biopsy (SB). Men with a low to very low suspicion had only SB. In total, 161 (161/175, 92%) prospectively enrolled men completed the trial and were included in the final analyses. The primary endpoint of the trial was the cancer detection rate (CDR) of TB and SB. Clinically significant cancer (SPCa) was defined as Gleason score ≥3 + 4., Results: TB compared with SB had higher CDR for SPCa (45%, 72/161 vs. 39%, 63/161, respectively; P > 0.05) and a lower CDR for Gleason score 3 + 3 (8%, 15/161 vs. 16%, 30/161; P < 0.05). Restricting biopsy to men with equivocal to highly suspicious bpMRI findings would have resulted in a 24% (38/161) reduction in the number of men undergoing biopsy, while missing 4 (2%) with SPCa. All anonymized datasets, including bpMRI reports and follow up information, are freely available on the trial server., Conclusion: Prebiopsy bpMRI and TB in men with a clinical suspicion of PCa improved risk stratification., Level of Evidence: 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2017;46:1089-1095., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: To evaluate in a multi-institutional study whether radiomic features useful for prostate cancer (PCa) detection from 3 Tesla (T) multi-parametric MRI (mpMRI) in the transition zone (TZ) differ from those in the peripheral zone (PZ)., Materials and Methods: 3T mpMRI, including T2-weighted (T2w), apparent diffusion coefficient (ADC) maps, and dynamic contrast-enhanced MRI (DCE-MRI), were retrospectively obtained from 80 patients at three institutions. This study was approved by the institutional review board of each participating institution. First-order statistical, co-occurrence, and wavelet features were extracted from T2w MRI and ADC maps, and contrast kinetic features were extracted from DCE-MRI. Feature selection was performed to identify 10 features for PCa detection in the TZ and PZ, respectively. Two logistic regression classifiers used these features to detect PCa and were evaluated by area under the receiver-operating characteristic curve (AUC). Classifier performance was compared with a zone-ignorant classifier., Results: Radiomic features that were identified as useful for PCa detection differed between TZ and PZ. When classification was performed on a per-voxel basis, a PZ-specific classifier detected PZ tumors on an independent test set with significantly higher accuracy (AUC = 0.61-0.71) than a zone-ignorant classifier trained to detect cancer throughout the entire prostate (P < 0.05). When classifiers were evaluated on MRI data from multiple institutions, statistically similar AUC values (P > 0.14) were obtained for all institutions., Conclusion: A zone-aware classifier significantly improves the accuracy of cancer detection in the PZ., Level of Evidence: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:184-193., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ)., Materials and Methods: This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of K trans between normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for K trans and v e for every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed., Results: Significant differences (P < 0.05) in PBM K trans between PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based K trans occurred in 26/27 and 30/38 patients, respectively. The 75 th and 100 th percentiles of K trans and v e estimated using PBM positively correlated with lesion size (P < 0.05)., Conclusion: Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. J. Magn. Reson. Imaging 2016;44:1405-1414., (© 2016 International Society for Magnetic Resonance in Medicine.)