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OBJECTIVE. The purpose of this study was to evaluate the rate of detection of clinically significant prostate cancer (csPCa), as assessed on the basis of Prostate Imaging Reporting and Data System version 2.1 (PI-RADSv2.1) guidelines, using 3-T in-bore MR-guided biopsy (MRGB) for a cohort of patients suspected of having csPCa despite having a history of recent negative transrectal ultrasound-guided biopsy results. MATERIALS AND METHODS. The cohort in this retrospective, single-center study was derived from a database of 330 patients who underwent multiparametric MRI (mpMRI) followed by in-bore transrectal 3-T MRGB. Seventy-nine patients (mean [± SD] age, 64.1 ± 8.6 years) with prior negative transrectal ultrasound-guided biopsy results and positive pre-MRGB mpMRI results (PI-RADS score ≥ 3) composed the final cohort. The rate of detection of PCa and csPCa (the latter of which was defined by a Gleason score of 3 + 4 or higher) was stratified according to updated PI-RADSv2.1 assessment. RESULTS. MRGB detected PCa in 36 patients (45.6%), 30 (83.3%) of whom had csPCa. The PI-RADSv2.1 score was a strong predictor (odds ratio, 3.97; 95% CI, 1.93-7.47) of csPCa detection. We found two benign transition zone target lesions that were downgraded from PI-RADSv2 category 3 to PI-RADSv2.1 category 2. PCa was detected in 18.4% (7/38), 65.2% (15/23), and 87.5% (14/16) of individuals with PI-RADSv2.1 category 3, 4, and 5 lesions, respectively, with 85.7% (6/7), 86.7% (13/15), and 78.6% (11/14) of these cases found to be csPCa, respectively. Of the seven PI-RADSv2.1 category 3 csPCa lesions, six had prostate-specific antigen density greater than 0.10 ng/mL/cc. CONCLUSION. With the use of 3-T in-bore MRGB, csPCa was detected in 38% of individuals with prior negative transrectal ultrasound-guided biopsy results. PI-RADSv2.1 was a strong predictor of csPCa detection. On the basis of our results, patients with PI-RADSv2.1 category 4 or 5 lesions and patients with PI-RADSv2.1 category 3 lesions and a prostate-specific antigen density greater than or equal to 0.10 ng/mL/cc may benefit from in-bore MRGB.

Background Microstructural MRI has the potential to improve diagnosis and characterization of prostate cancer (PCa), but validation with histopathology is lacking. Purpose To validate ex vivo diffusion-relaxation correlation spectrum imaging (DR-CSI) in the characterization of microstructural tissue compartments in prostate specimens from men with PCa by using registered whole-mount digital histopathology (WMHP) as the reference standard. Materials and Methods Men with PCa who underwent 3-T MRI and robotic-assisted radical prostatectomy between June 2018 and January 2019 were prospectively studied. After prostatectomy, the fresh whole prostate specimens were imaged in patient-specific three-dimensionally printed molds by using 3-T MRI with DR-CSI and were then sliced to create coregistered WMHP slides. The DR-CSI spectral signal component fractions ( f A , f B , f C ) were compared with epithelial, stromal, and luminal area fractions ( f epithelium , f stroma , f lumen ) quantified in PCa and benign tissue regions. A linear mixed-effects model assessed the correlations between ( f A , f B , f C ) and ( f epithelium , f stroma , f lumen ), and the strength of correlations was evaluated by using Spearman correlation coefficients. Differences between PCa and benign tissues in terms of DR-CSI signal components and microscopic tissue compartments were assessed using two-sided t tests. Results Prostate specimens from nine men (mean age, 65 years ± 7 [standard deviation]) were evaluated; 20 regions from 17 PCas, along with 20 benign tissue regions of interest, were analyzed. Three DR-CSI spectral signal components (spectral peaks) were consistently identified. The f A , f B , and f C were correlated with f epithelium , f stroma , and f lumen (all P < .001), with Spearman correlation coefficients of 0.74 (95% confidence interval [CI]: 0.62, 0.83), 0.80 (95% CI: 0.66, 0.89), and 0.67 (95% CI: 0.51, 0.81), respectively. PCa exhibited differences compared with benign tissues in terms of increased f A (PCa vs benign, 0.37 ± 0.05 vs 0.27 ± 0.06; P < .001), decreased f C (PCa vs benign, 0.18 ± 0.06 vs 0.31 ± 0.13; P = .01), increased f epithelium (PCa vs benign, 0.44 ± 0.13 vs 0.26 ± 0.16; P < .001), and decreased f lumen (PCa vs benign, 0.14 ± 0.08 vs 0.27 ± 0.18; P = .004). Conclusion Diffusion-relaxation correlation spectrum imaging signal components correlate with microscopic tissue compartments in the prostate and differ between cancer and benign tissue. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Lee and Hectors in this issue.

Multi-parametric MRI (mp-MRI) is considered the best non-invasive imaging modality for diagnosing prostate cancer (PCa). However, mp-MRI for PCa diagnosis is currently limited by the qualitative or semi-quantitative interpretation criteria, leading to inter-reader variability and a suboptimal ability to assess lesion aggressiveness. Convolutional neural networks (CNNs) are a powerful method to automatically learn the discriminative features for various tasks, including cancer detection. We propose a novel multi-class CNN, FocalNet, to jointly detect PCa lesions and predict their aggressiveness using Gleason score (GS). FocalNet characterizes lesion aggressiveness and fully utilizes distinctive knowledge from mp-MRI. We collected a prostate mp-MRI dataset from 417 patients who underwent 3T mp-MRI exams prior to robotic-assisted laparoscopic prostatectomy. FocalNet was trained and evaluated in this large study cohort with fivefold cross validation. In the free-response receiver operating characteristics (FROC) analysis for lesion detection, FocalNet achieved 89.7% and 87.9% sensitivity for index lesions and clinically significant lesions at one false positive per patient, respectively. For the GS classification, evaluated by the receiver operating characteristics (ROC) analysis, FocalNet received the area under the curve of 0.81 and 0.79 for the classifications of clinically significant PCa (GS ≥ 3 + 4) and PCa with GS ≥ 4 + 3, respectively. With the comparison to the prospective performance of radiologists using the current diagnostic guideline, FocalNet demonstrated comparable detection sensitivity for index lesions and clinically significant lesions, only 3.4% and 1.5% lower than highly experienced radiologists without statistical significance.

Background: Hemiablation is a less morbid treatment alternative for appropriately selected patients with unilateral prostate cancer (PCa). However, to the authors' knowledge, traditional diagnostic techniques inadequately identify appropriate candidates. In the current study, the authors quantified the accuracy for identifying hemiablation candidates using contemporary diagnostic techniques, including multiparametric magnetic resonance imaging (mpMRI) and MRI-fusion with complete systematic template biopsy., Methods: A retrospective analysis of patients undergoing MRI and MRI-fusion prostate biopsy, including full systematic template biopsy, prior to radical prostatectomy in a single tertiary academic institution between June 2010 and February 2018 was performed. Hemiablation candidates had unilateral intermediate-risk PCa (Gleason score [GS] of 3+4 or 4+3, clinical T classification ≤T2, and prostate-specific antigen level <20 ng/dL) on MRI-fusion biopsy and 2) no contralateral highly or very highly suspicious Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) MRI lesions. Hemiablation candidates were inappropriately selected if pathologists identified contralateral GS ≥3+4 or high-risk ipsilateral PCa on prostatectomy. The authors tested a range of hemiablation inclusion criteria and performed multivariable analysis of preoperative predictors of undetected contralateral disease., Results: Of 665 patients, 92 met primary hemiablation criteria. Of these 92 patients, 44 (48%) were incorrectly identified due to ipsilateral GS ≥3+4 tumors crossing the midline (21 patients), undetected distinct contralateral GS ≥3+4 tumors (20 patients), and/or ipsilateral high-risk PCa (3 patients) on prostatectomy. The rate of undetected contralateral disease ranged from 41% to 48% depending on inclusion criteria. On multivariable analysis, men with anterior index tumors were found to be 2.4 times more likely to harbor undetected contralateral GS ≥3+4 PCa compared with men with posterior lesions (P < .05)., Conclusions: Clinicians and patients must weigh the risk of inadequate oncologic treatment against the functional benefits of hemiablation. Further investigation into methods for improving patient selection for hemiablation is necessary., (© 2019 American Cancer Society.)

OBJECTIVE. The purpose of this article is to evaluate restriction spectrum imaging (RSI) in men undergoing MRI-ultrasound fusion biopsy for suspected prostate cancer (PCa) and to compare the performance of RSI with that of conventional DWI. MATERIALS AND METHODS. One hundred ninety-eight biopsy-naïve men enrolled in a concurrent prospective clinical trial evaluating MRI-targeted prostate biopsy underwent multiparametric MRI with RSI. Clinical and imaging features were compared between men with and without clinically significant (CS) PCa (MRI-ultrasound fusion biopsy Gleason score ≥ 3 + 4). RSI z score and apparent diffusion coefficient (ADC) were correlated, and their diagnostic performances were compared. RESULTS. CS PCa was detected in 109 of 198 men (55%). Using predefined thresholds of ADC less than or equal to 1000 μm 2 /s and RSI z score greater than or equal to 3, sensitivity and specificity for CS PCa were 86% and 38%, respectively, for ADC and 61% and 70%, respectively, for RSI. In the transition zone ( n = 69), the sensitivity and specificity were 94% and 17%, respectively, for ADC and 59% and 69%, respectively, for RSI. Among lesions with CS PCa, RSI z score and ADC were significantly inversely correlated in the peripheral zone (ρ = -0.4852; p < 0.01) but not the transition zone (ρ = -0.2412; p = 0.17). Overall diagnostic accuracies of RSI and DWI were 0.70 and 0.68, respectively ( p = 0.74). CONCLUSION. RSI and DWI achieved equivalent diagnostic performance for PCa detection in a large population of men undergoing first-time prostate biopsy for suspected PCa, but RSI had superior specificity for transition zone lesions.

Purpose: The purpose of the study was to propose a deep transfer learning (DTL)-based model to distinguish indolent from clinically significant prostate cancer (PCa) lesions and to compare the DTL-based model with a deep learning (DL) model without transfer learning and PIRADS v2 score on 3 Tesla multi-parametric MRI (3T mp-MRI) with whole-mount histopathology (WMHP) validation., Methods: With IRB approval, 140 patients with 3T mp-MRI and WMHP comprised the study cohort. The DTL-based model was trained on 169 lesions in 110 arbitrarily selected patients and tested on the remaining 47 lesions in 30 patients. We compared the DTL-based model with the same DL model architecture trained from scratch and the classification based on PIRADS v2 score with a threshold of 4 using accuracy, sensitivity, specificity, and area under curve (AUC). Bootstrapping with 2000 resamples was performed to estimate the 95% confidence interval (CI) for AUC., Results: After training on 169 lesions in 110 patients, the AUC of discriminating indolent from clinically significant PCa lesions of the DTL-based model, DL model without transfer learning and PIRADS v2 score ≥ 4 were 0.726 (CI [0.575, 0.876]), 0.687 (CI [0.532, 0.843]), and 0.711 (CI [0.575, 0.847]), respectively, in the testing set. The DTL-based model achieved higher AUC compared to the DL model without transfer learning and PIRADS v2 score ≥ 4 in discriminating clinically significant lesions in the testing set., Conclusion: The DeLong test indicated that the DTL-based model achieved comparable AUC compared to the classification based on PIRADS v2 score (p = 0.89).

Purpose: We investigated the performance of 3 Tesla multiparametric magnetic resonance imaging with and without an endorectal coil to detect prostate cancer with a whole mount histopathology reference., Materials and Methods: This retrospective HIPAA (Health Insurance Portability and Accountability Act) compliant, institutional review board approved, case-control study included patients who underwent 3 Tesla multiparametric magnetic resonance imaging with and without an endorectal coil from July 2009 to December 2016 prior to prostatectomy. The tumor detection rate was calculated for total and index lesions. Lesion magnetic resonance imaging and histopathology features were compared between the 2 groups. Using SPSS®, version 24 p <0.05 was considered significant., Results: A total of 871 whole mount histopathology lesions in 429 patients with a mean ± SD age of 61.8 ± 7 years were included in analysis. The subcohorts with and without an endorectal coil comprised 260 and 169 patients with a total of 529 and 342 lesions, respectively. The overall tumor detection rates in all patients, and in the endorectal coil and nonendorectal coil subcohorts were 49.6% (432 of 871 patients), 50.5% (267 of 529) and 48.2% (165 of 342), respectively. The index tumor detection rates overall, and in the endorectal coil and nonendorectal coil subcohorts were 77.6% (333 of 429 patients), 78.5% (204 of 260) and 76.3% (129 of 169), respectively. In the endorectal coil and nonendorectal coil subcohorts we detected 35.9% (66 of 184) and 48.4% (76 of 157) of anterior lesions (p = 0.019), 58% (200 of 345) and 48.1% (89 of 185) of posterior lesions (p = 0.025), 37.3% (41 of 110) and 54.4% (62 of 114) of transition zone lesions (p = 0.010), and 53.7% (225 of 419) and 45.2% (103 of 228) of peripheral lesions (p = 0.033), respectively. After adjusting for clinical and pathological factors the endorectal coil group only showed higher detection of peripheral and posterior prostate cancer., Conclusions: We found that 3 Tesla multiparametric magnetic resonance imaging with and without an endorectal coil had similar detection of overall and index prostate cancer. However, the endorectal coil subcohort had significantly higher detection of posterior and peripheral prostate cancer, and lower detection of anterior and transition zone prostate cancer.

Purpose: To determine the characteristics of missed prostate cancer (PCa) lesions on 3T multiparametric-MRI (mpMRI) based on PI-RADSv2 with whole-mount histopathology (WMHP) correlation., Materials and Methods: This IRB-approved, HIPAA-compliant study, included 614 consecutive men with 3T mpMRI prior to prostatectomy at a single tertiary center between 12/2009 and 4/2017. Clinical, mpMRI, and pathologic features were obtained. PI-RADSv2-based MRI detected lesions were matched with previously finalized WMHP by a genitourinary (GU) radiologist and a GU pathologist. Patients with no mpMRI detected PCa lesion, but with at least one lesion ≥ 1 cm on WMHP, were reviewed retrospectively and assigned a PI-RADSv2 score. Tumor characteristics were compared between missed and detected lesions., Result: The final cohort included 518 patients with 1085 WMHP lesions. 51.9% (563/1085) of lesions were missed on 3T mpMRI. 71.4% (402/563), 21.7% (122/563), 4.4% (25/563), and 2.5% (14/563) of the missed lesions were Gleason scores (GS) 3 + 3, 3 + 4, 4 + 3, and 8 - 10, respectively. Missed PCa lesions had significantly lower proportion of GS ≥ 7 (p < 0.001) and smaller size for overall (p < 0.001) and index subcohorts (p < 0.001), as compared to detected lesions. 34.5% (194) of overall and 71.2% (79) index missed lesions were larger than 1 cm. In 13.7% (71/518) of patients without MR detected PCa, 149 lesions were detected on WMHP, with 70 (47%) lesions ≥ 1 cm. In retrospective review of these lesions, 42.9% (30), 18.6% (13), 21.5% (15), 10% (7), and 7% (5) were PI-RADSv2 1, 2, 3, 4, and 5, respectively., Conclusion: 3T mpMRI has an excellent per patients diagnostic performance for PCa and majority of missed lesions are clinically nonsignificant.

Background: Patient-specific 3D-printed molds and ex vivo MRI of the resected prostate have been two important strategies to align MRI with whole-mount histopathology (WMHP) for prostate cancer (PCa) research, but the combination of these two strategies has not been systematically evaluated., Purpose: To develop and evaluate a system that combines patient-specific 3D-printed molds with ex vivo MRI (ExV) to spatially align in vivo MRI (InV), ExV, and WMHP in PCa patients., Study Type: Prospective cohort study., Population: Seventeen PCa patients who underwent 3T MRI and robotic-assisted laparoscopic radical prostatectomy (RALP)., Field Strength/sequences: T 2 -weighted turbo spin-echo sequences at 3T., Assessment: Immediately after RALP, the fresh whole prostate specimens were imaged in patient-specific 3D-printed molds by 3T MRI and then sectioned to create WMHP slides. The time required for ExV was measured to assess impact on workflow. InV, ExV, and WMHP images were registered. Spatial alignment was evaluated using: slide offset (mm) between ExV slice locations and WMHP slides; overlap of the 3D prostate contour on InV versus ExV using Dice's coefficient (0 to 1); and 2D target registration error (TRE, mm) between corresponding landmarks on InV, ExV, and WMHP. Data are reported as mean ± standard deviation (SD)., Statistical Testing: Differences in 2D TRE before versus after registration were compared using the Wilcoxon signed-rank test (P < 0.05 considered significant)., Results: ExV (duration 115 ± 15 min) was successfully incorporated into the workflow for all cases. Absolute slide offset was 1.58 ± 1.57 mm. Dice's coefficient was 0.865 ± 0.035. 2D TRE was significantly reduced after registration (P < 0.01) with mean (±SD of per patient means) of 1.9 ± 0.6 mm for InV versus ExV, 1.4 ± 0.5 mm for WMHP versus ExV, and 2.0 ± 0.5 mm for WMHP versus InV., Data Conclusion: The proposed system combines patient-specific 3D-printed molds with ExV to achieve spatial alignment between InV, ExV, and WMHP with mean 2D TRE of 1-2 mm., Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:270-279., (© 2018 International Society for Magnetic Resonance in Medicine.)

Background: Prostate specific antigen (PSA) has been used as a screening test for the early detection of prostate cancer (PC) for many years. Although the introduction of PSA test led to a considerable increase in reported prostate cancer cases, there is still some controversy over the sensitivity and specificity of this marker in distinguishing PC patients from those with benign prostate hyperplasia (BPH), the most common benign prostate condition., Objective: An attempt is made to elucidate if the plasma level of Interleukin 8 (IL-8) could be used effectively as a marker for the detection of prostate cancer., Methods: Plasma levels of IL-8 and PSA were measured in two groups of 40 BPH and PC patients using enzyme-linked immunosorbent (ELISA) and radioimmunoassay (RIA) techniques, respectively. In addition IL-8 levels in PC3 and DU145 cell line supernatants were measured by ELISA technique., Results: The concentration of IL-8 in the plasma of PC patients was not significantly higher than the BPH subjects. Although, a correlation between plasma IL-8 concentration and the Gleason score of PC patients was found, no indicated correlation was detected between the concentration of IL-8 or PSA and age of the patients in both groups. DU145 and PC3 cell lines produced and secreted IL-8 in the media., Conclusion: Data of this investigation collectively conclude no correlation between IL-8 concentration in PC and BPH patients.