• F-Fluciclovine PET/MRI has high specificity for detection of lymph node metastasis. •F-Fluciclovine PET/MRI lacks sensitivity to replace ePLND. • F-Fluciclovine PET/MRI may be used to aid surgery and select adjuvant therapy. •F-Fluciclovine PET-positive patients have more extensive disease than PET-negative patients. • Size of metastatic lymph nodes is an important factor for detection.

ObjectiveSimultaneous 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.MethodsPatients 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.ResultsAmong 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.ConclusionCombined 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.

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.

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.

ObjectivesThis 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.MethodsThe 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.ResultsA 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.ConclusionsmpMRI, 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.