Multiparametric Prostate MRI in Biopsy-Naïve Men: A Prospective Evaluation of Performance and Biopsy Strategies

Objectives: This study aims to prospectively estimate the diagnostic performance of multiparametric prostate MRI (mpMRI) and compare the detection rates of prostate cancer using cognitive targeted transrectal ultrasound (TRUS) guided biopsies, targeted MR-guided in-bore biopsies (MRGB), or both methods combined in biopsy-naïve men. Methods: The biopsy-naïve men referred for mpMRI (including T2-weighted, diffusion-weighted and dynamic contrast enhanced MRI) due to prostate cancer suspicion (elevated prostate-specific antigen or abnormal digital rectal examination) were eligible for inclusion. The images were scored according to Prostate Imaging Reporting and Data System (PI-RADS) v2, and men with PI-RADS 1–2 lesions were referred for routine systematic TRUS, while those with PI-RADS 3–5 lesions were randomized to MRGB or cognitive targeted TRUS. Men randomized to MRGB were referred to a secondary TRUS 2 weeks after MRGB. Gleason grade group ≥2 was defined as clinically significant prostate cancer. The performance of mpMRI was estimated using prostate cancer detected by any biopsy method as the reference test. Results: A total of 210 men were included. There was no suspicion of prostate cancer after mpMRI (PI-RADS 1–2) in 48% of the men. Among these, significant and insignificant prostate cancer was diagnosed in five and 11 men, respectively. Thirty-five men who scored as PI-RADS 1–2 did not undergo biopsy and were therefore excluded from the calculation of diagnostic accuracy. The overall sensitivity, specificity, negative predictive value, and positive predictive value of mpMRI for the detection of significant prostate cancer were 0.94, 0.63, 0.92, and 0.67, respectively. In patients with PI-RADS 3–5 lesions, the detection rates for significant prostate cancer were not significantly different between cognitive targeted TRUS (68.4%), MRGB (57.7%), and the combination of the two biopsy methods (64.4%). The median numbers of biopsy cores taken per patient undergoing systematic TRUS, cognitive targeted TRUS, and MRGB were 14 [8-16], 12 [6-17], and 2 [1-4] respectively. Conclusions: mpMRI, in a cohort of biopsy-naïve men, has high negative predictive value, and our results support that it is safe to avoid biopsy after negative mpMRI. Furthermore, MRGB provides a similar diagnosis to the cognitive targeted TRUS but with fewer biopsies

Prostate-Specific Membrane Antigen PET/Magnetic Resonance Imaging for the Planning of Salvage Radiotherapy in Patients with Prostate Cancer with Biochemical Recurrence After Radical Prostatectomy

Prostate-specific membrane antigen (PSMA) PET/magnetic resonance (MR) imaging can help distinguish between patients with prostate cancer with locoregional recurrence and those with distant metastases, even at low prostate-specific antigen levels. PSMA PET/MR imaging may have advantages compared with PET/computed tomography for the detection of local recurrence and anatomic correlates to PET-positive lymph node and bone lesions. PSMA PET/MR imaging can help in making informed treatment decisions in patients with biochemical recurrence after radical prostatectomy. PSMA PET/MR imaging enables dose-escalated and metastases-directed salvage radiotherapy in patients with biochemical recurrence after radical prostatectomy

The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images

Volume of interest segmentation is an essential step in computer-aided detection and diagnosis (CAD) systems. Deep learning (DL)-based methods provide good performance for prostate segmentation, but little is known about the reproducibility of these methods. In this work, an in-house collected dataset from 244 patients was used to investigate the intra-patient reproducibility of 14 shape features for DL-based segmentation methods of the whole prostate gland (WP), peripheral zone (PZ), and the remaining prostate zones (non-PZ) on T2-weighted (T2W) magnetic resonance (MR) images compared to manual segmentations. The DL-based segmentation was performed using three different convolutional neural networks (CNNs): V-Net, nnU-Net-2D, and nnU-Net-3D. The two-way random, single score intra-class correlation coefficient (ICC) was used to measure the inter-scan reproducibility of each feature for each CNN and the manual segmentation. We found that the reproducibility of the investigated methods is comparable to manual for all CNNs (14/14 features), except for V-Net in PZ (7/14 features). The ICC score for segmentation volume was found to be 0.888, 0.607, 0.819, and 0.903 in PZ; 0.988, 0.967, 0.986, and 0.983 in non-PZ; 0.982, 0.975, 0.973, and 0.984 in WP for manual, V-Net, nnU-Net-2D, and nnU-Net-3D, respectively. The results of this work show the feasibility of embedding DL-based segmentation in CAD systems, based on multiple T2W MR scans of the prostate, which is an important step towards the clinical implementation

A comparison of Generative Adversarial Networks for automated prostate cancer detection on T2-weighted MRI

Generative Adversarial Networks (GANs) have shown potential in medical imaging. In this study, several previously developed GANs were investigated for prostate cancer (PCa) detection on T2-weighted (T2W) magnetic resonance images (MRI).T2W MRI from an in-house collected dataset (N=961) were used to train, validate, and test an automated computer-aided detection (CAD) pipeline. The open-access PROSTATEx training dataset (N=199) was used as an external test set. The CAD pipeline consisted of normalization, prostate segmentation, quality control, prostate gland cropping, and a GAN model. Six GANs (f-AnoGAN, HealthyGAN, StarGAN, StarGAN-v2, Fixed-Point-GAN and DeScarGAN) were evaluated for PCa detection on the patient-level using the area under the receiver operating characteristic curve (AUC). The best performing GAN (validation set) was trained with five different initializations and evaluated on the internal and external test sets to assess its robustness.Fixed-Point-GAN performed best (validation, AUC 0.76) and was selected for further assessment. The highest performance on the internal and external test sets were an AUC of 0.73 (95% CI: 0.68-0.79) and 0.77 (95% CI: 0.70-0.83), respectively. The average AUCs ± standard deviation across all runs corresponded to 0.71 ± 0.01 and 0.71 ± 0.04, respectively.Fixed-Point-GAN was identified as a promising GAN for the detection of PCa on T2W MRI. This model needs to be further investigated and trained on a larger dataset of multiparametric or biparametric MR images to assess its full potential as a support tool for radiologists

Relative Enhanced Diffusivity in Prostate Cancer: Protocol Optimization and Diagnostic Potential

Background Relative enhanced diffusivity (RED) is a potential biomarker for indirectly measuring perfusion in tissue using diffusion‐weighted magnetic resonance imaging (MRI) with 3 b values. Purpose To optimize the RED MRI protocol for the prostate, and to investigate its potential for prostate cancer (PCa) diagnosis. Study Type Prospective. Population Ten asymptomatic healthy volunteers and 35 patients with clinical suspicion of PCa. Sequence 3T T2‐ and diffusion‐weighted MRI with b values: b = 0, 50, [100], 150, [200], 250, [300], 400, 800 s/mm2 (values in brackets were only used for patients). Assessment Monte Carlo simulations were performed to assess noise sensitivity of RED as a function of intermediate b value. Volunteers were scanned 3 times to assess repeatability of RED. Patient data were used to investigate RED's potential for discriminating between biopsy‐confirmed cancer and healthy tissue, and between true and false positive radiological findings. Statistical Tests Within‐subject coefficient of variation (WCV) to assess repeatability and receiver‐operating characteristic curve analysis and logistic regression to assess diagnostic performance of RED. Results The repeatability was acceptable (WCV = 0.2‐0.3) for all intermediate b values tested, apart from b = 50 s/mm2 (WCV = 0.3‐0.4). The simulated RED values agreed well with the experimental data, showing that an intermediate b value between 150‐250 s/mm2 minimizes noise sensitivity in both peripheral zone (PZ) and transition zone (TZ). RED calculated with the b values 0, 150 and 800 s/mm2 was significantly higher in tumors than in healthy tissue in both PZ (P < 0.001, area under the curve [AUC] = 0.85) and PZ + TZ (P < 0.001, AUC = 0.84). RED was shown to aid apparent diffusion coefficient (ADC) in differentiating between false‐positive findings and true‐positive PCa in the PZ (AUC; RED = 0.71, ADC = 0.74, RED+ADC = 0.77). Data Conclusion RED is a repeatable biomarker that may have value for prostate cancer diagnosis. An intermediate b value in the range of 150‐250 s/mm2 minimizes the influence of noise and maximizes repeatability. Level of Evidence: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019

Pseudo-T2 mapping for normalization of T2-weighted prostate MRI

Objective Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that normalizes transversal prostate T2W MRI by creating a pseudo-T2 map. The aim of this study was to evaluate the accuracy of pseudo-T2s and multicenter standardization performance for AutoRef with three pairs of reference tissues: fat/muscle (AutoRefF), femoral head/muscle (AutoRefFH) and pelvic bone/muscle (AutoRefPB). Materials and methods T2s measured by multi-echo spin echo (MESE) were compared to AutoRef pseudo-T2s in the whole prostate (WP) and zones (PZ and TZ/CZ/AFS) for seven asymptomatic volunteers with a paired Wilcoxon signed-rank test. AutoRef normalization was assessed on T2W images from a multicenter evaluation set of 1186 prostate cancer patients. Performance was measured by inter-patient histogram intersections of voxel intensities in the WP before and after normalization in a selected subset of 80 cases. Results AutoRefFH pseudo-T2s best approached MESE T2s in the volunteer study, with no significant difference shown (WP: p = 0.30, TZ/CZ/AFS: p = 0.22, PZ: p = 0.69). All three AutoRef versions increased inter-patient histogram intersections in the multicenter dataset, with median histogram intersections of 0.505 (original data), 0.738 (AutoRefFH), 0.739 (AutoRefF) and 0.726 (AutoRefPB). Discussion All AutoRef versions reduced variation in the multicenter data. AutoRefFH pseudo-T2s were closest to experimentally measured T2s

Detection of recurrent prostate cancer with 18F-Fluciclovine PET/MRI

Objective: Simultaneous PET/MRI combines soft-tissue contrast of MRI with high molecular sensitivity of PET in one session. The aim of this prospective study was to evaluate detection rates of recurrent prostate cancer by 18F-fluciclovine PET/MRI. Methods: Patients with biochemical recurrence (BCR) or persistently detectable prostate specific antigen (PSA), were examined with simultaneous 18F-fluciclovine PET/MRI. Multiparametric MRI (mpMRI) and PET/MRI were scored on a 3-point scale (1-negative, 2-equivocal, 3-recurrence/metastasis) and detection rates (number of patients with suspicious findings divided by total number of patients) were reported. Detection rates were further stratified based on PSA level, PSA doubling time (PSAdt), primary treatment and inclusion criteria (PSA persistence, European Association of Urology (EAU) Low-Risk BCR and EAU High-Risk BCR). A detailed investigation of lesions with discrepancy between mpMRI and PET/MRI scores was performed to evaluate the incremental value of PET/MRI to mpMRI. The impact of the added PET acquisition on further follow-up and treatment was evaluated retrospectively. Results: Among patients eligible for analysis (n=84), 54 lesions were detected in 38 patients by either mpMRI or PET/MRI. Detection rates were 41.7% for mpMRI and 39.3% for PET/MRI (score 2 and 3 considered positive). There were no significant differences in detection rates for mpMRI versus PET/MRI. Disease detection rates were higher in patients with PSA≥1ng/mL than in patients with lower PSA levels but did not differ between patients with PSAdt above versus below 6 months. Detection rates in patients with primary radiation therapy were higher than in patients with primary surgery. Patients categorized as EAU Low-Risk BCR had a detection rate of 0% both for mpMRI and PET/MRI. For 15 lesions (27.8% of all lesions) there was a discrepancy between mpMRI score and PET/MRI score. Of these, 10 lesions scored as 2-equivocal by mpMRI were changed to a more definite score (n=4 score 1 and n=6 score 3) based on the added PET acquisition. Furthermore, for 4 of 10 patients with discrepancy between mpMRI and PET/MRI scores, the added PET acquisition had affected the treatment choice. Conclusion: Combined 18F-fluciclovine PET/MRI can detect lesions suspicious for recurrent prostate cancer in patients with a range of PSA levels. Combined PET/MRI may be useful to select patients for appropriate treatment, but is of limited use at low PSA values or in patients classified as EAU Low-Risk BCR, and the clinical value of 18F-fluciclovine PET/MRI in this study was too low to justify routine clinical use