Extracapsular extension risk assessment using an artificial intelligence prostate cancer mapping algorithm.

Objective: The objective of this study is to compare detection rates of extracapsular extension (ECE) of prostate cancer (PCa) using artificial intelligence (AI)-generated cancer maps versus MRI and conventional nomograms. Materials and methods: We retrospectively analysed data from 147 patients who received MRI-targeted biopsy and subsequent radical prostatectomy between September 2016 and May 2022. AI-based software cleared by the United States Food and Drug Administration (Unfold AI, Avenda Health) was used to map 3D cancer probability and estimate ECE risk. Conventional ECE predictors including MRI Likert scores, capsular contact length of MRI-visible lesions, PSMA T stage, Partin tables, and the "PRedicting ExtraCapsular Extension" nomogram were used for comparison.Postsurgical specimens were processed using whole-mount histopathology sectioning, and a genitourinary pathologist assessed each quadrant for ECE presence. ECE predictors were then evaluated on the patient (Unfold AI versus all comparators) and quadrant level (Unfold AI versus MRI Likert score). Receiver operator characteristic curves were generated and compared using DeLong's test. Results: Unfold AI had a significantly higher area under the curve (AUC = 0.81) than other predictors for patient-level ECE prediction. Unfold AI achieved 68% sensitivity, 78% specificity, 71% positive predictive value, and 75% negative predictive value. At the quadrant level, Unfold AI exceeded the AUC of MRI Likert scores for posterior (0.89 versus 0.82, p = 0.003), anterior (0.84 versus 0.80, p = 0.34), and all quadrants (0.89 versus 0.82, p = 0.002). The false negative rate of Unfold AI was lower than MRI in both the anterior (-60%) and posterior prostate (-40%). Conclusions: Unfold AI accurately predicted ECE risk, outperforming conventional methodologies. It notably improved ECE prediction over MRI in posterior quadrants, with the potential to inform nerve-spare technique and prevent positive margins. By enhancing PCa staging and risk stratification, AI-based cancer mapping may lead to better oncological and functional outcomes for patients.

Clinical, Pathologic, and Imaging Variables Associated with Prostate Cancer Detection by PSMA PET/CT and Multiparametric MRI.

Multiparametric MRI (mpMRI) and prostate-specific membrane antigen (PSMA) PET/CT are complementary imaging modalities used in the presurgical evaluation of patients with prostate cancer (PCa). The purpose of this study was to characterize clinically significant PCa (csPCa) detected and not detected by PSMA PET/CT and mpMRI, focusing on tumors detected solely by PSMA PET/CT and overlooked by mpMRI. Methods: We conducted a single-center, retrospective analysis of patients who underwent both PSMA PET/CT and mpMRI within 3 mo of each other and before radical prostatectomy. Two nuclear medicine physicians and 2 radiologists, in a masked manner, independently contoured PCa lesions on PSMA PET/CT and mpMRI, respectively. A consensus read was done with a third reader for each modality, and a majority rule was applied (2:1). After centralized imaging, a pathologic review was done by a genitourinary pathologist. We assessed agreement between imaging modalities and correlation with pathology. Logistic regression models explored associations between clinicopathologic variables and tumor detection on imaging. Results: In total, 132 csPCa tumors from 100 patients were identified on surgical pathology. PSMA PET/CT showed higher lesion-level (87% vs. 80%) and patient-level (98% vs. 94%) sensitivity than mpMRI. Tumors detected on both imaging modalities were larger and had higher grade groups than those not detected by one or both imaging modalities. On multivariable analysis, csPCa tumors undetected by mpMRI but detected by PSMA PET/CT were smaller than those detected by both modalities. Most tumors showing aggressive pathologic features, such as the large cribriform pattern (94.7%) and the intraductal carcinoma (96%), were correctly detected by both imaging modalities. Limitations included selection bias in a surgical cohort. Conclusion: PSMA PET/CT tends to detect smaller csPCa not detected by mpMRI. Larger tumors on pathology with higher grade groups are more likely to be correctly detected by both imaging modalities. These findings provide insights for refining presurgical evaluation strategies in PCa.

FAP and PSMA Expression by Immunohistochemistry and PET Imaging in Castration-Resistant Prostate Cancer: A Translational Pilot Study.

Prostate-specific membrane antigen (PSMA) is a theranostic target for metastatic prostate cancer (PCa). However, castration-resistant PCa (CRPC) may lose PSMA expression after systemic therapy. Fibroblast activation protein (FAP), expressed by carcinoma-associated fibroblasts in various cancer types, including PCa, has the potential to be an alternative target. In this study, we evaluated FAP expression in CRPC to assess its potential, using PSMA as a comparison. Methods: FAP expression was assessed using immunohistochemistry in 116 CRPC tumors: 78 adenocarcinomas, 11 small cell carcinomas, and 27 anaplastic carcinomas. Correlation analysis between manual scoring and automated scoring was performed on 54 whole-slide sections of metastatic CRPC. Paired FAP and PSMA stains were assessed in tissue microarray cores of CRPC (n = 62), consisting of locally advanced CRPC (n = 9) and metastatic CRPC (n = 53). FAP and PSMA positivity was defined by an immunohistochemistry score of at least 10. To explore the correlation of PSMA and FAP inhibitor (FAPi) PET imaging and immunohistochemistry, a preliminary analysis of 4 patients included in a [68Ga]-FAPi-46 imaging trial (NCT04457232) was conducted. Results: Manual and automated scoring of FAP yielded results with strong correlations. Overall, FAP expression in CRPC was notably lower than PSMA expression (median immunoscores, 14 vs. 72; P < 0.001). Different histologic subtypes of CRPC demonstrated distinct levels of PSMA expression, whereas their FAP expression levels were comparable. Among the 19 PSMA-negative tumors, 11 (58%) exhibited FAP positivity. FAP expression levels in lymph node metastases were significantly lower than those in nonnodal metastases (P = 0.021). Liver metastases showed significant enrichment of tumors with strong FAP expression compared with nonliver lesions (P = 0.016). In the 4 clinical trial patients, the biopsied metastatic lesions showed lower uptake on FAPi PET than on PSMA PET (median SUVmax, 9.6 vs. 14.5), consistent with FAP expression that was lower than PSMA expression in the corresponding tumor biopsy samples (median immunoscores, 30 vs. 160). Conclusion: Because of the low FAP expression levels in CRPC, the utility of FAPi PET imaging may be limited. Although FAPi PET imaging may be further tested in PSMA-negative CRPC, such as small cell carcinoma, other molecular imaging modalities should be evaluated as alternative choices.

Digital Volumetric Biopsy Cores Improve Gleason Grading of Prostate Cancer Using Deep Learning.

Prostate cancer (PCa) was the most frequently diagnosed cancer among American men in 2023 [1]. The histological grading of biopsies is essential for diagnosis, and various deep learning-based solutions have been developed to assist with this task. Existing deep learning frameworks are typically applied to individual 2D cross-sections sliced from 3D biopsy tissue specimens. This process impedes the analysis of complex tissue structures such as glands, which can vary depending on the tissue slice examined. We propose a novel digital pathology data source called a "volumetric core," obtained via the extraction and co-alignment of serially sectioned tissue sections using a novel morphology-preserving alignment framework. We trained an attention-based multiple-instance learning (ABMIL) framework on deep features extracted from volumetric patches to automatically classify the Gleason Grade Group (GGG). To handle volumetric patches, we used a modified video transformer with a deep feature extractor pretrained using self-supervised learning. We ran our morphology preserving alignment framework to construct 10,210 volumetric cores, leaving out 30% for pretraining. The rest of the dataset was used to train ABMIL, which resulted in a 0.958 macro-average AUC, 0.671 F1 score, 0.661 precision, and 0.695 recall averaged across all five GGG significantly outperforming the 2D baselines.

Evaluation of prostate cancer detection using micro-ultrasound versus MRI through co-registration to whole-mount pathology.

Micro-ultrasound has recently been introduced as a low-cost alternative to multi-parametric MRI for imaging prostate cancer. Early clinical studies have demonstrated promising results; however, robust validation via comparison with whole-mount pathology has yet to be achieved. Due to micro-ultrasound probe design and tissue deformation during scanning, it is difficult to accurately correlate micro-ultrasound imaging planes with ground truth whole-mount pathology slides. In this study, we developed a multi-step methodology to co-register micro-ultrasound and MRI to whole-mount pathology. The three-step process had a registration error of 3.90 ± 0.11 mm and consists of: (1) micro-ultrasound image reconstruction, (2) 3D landmark registration of micro-ultrasound to MRI, and (3) 2D capsule registration of MRI to whole-mount pathology. This process was then used in a preliminary reader study to compare the diagnostic accuracy of micro-ultrasound and MRI in 15 patients who underwent radical prostatectomy for prostate cancer. Micro-ultrasound was found to have equivalent performance to retrospective MRI review for index lesion detection (91.7% vs. 80%), while demonstrating an increased detection of tumor extent (52.5% vs. 36.7%) with similar false positive regions-of-interest (38.3% vs. 40.8%). Prospective MRI review had reduced detection of index lesions (73.3%) and tumor extent (18.9%) but improved false positive regions-of-interest (22.7%) relative to micro-ultrasound and retrospective MRI. Further evaluation is needed with a larger sample size.

ALK Inhibition With Alectinib for Refractory Metastatic Renal Cell Carcinoma With ALK Rearrangement: A Rare Case Report and Literature Review.

ALK-rearranged RCC refractory to several lines of treatment has a durable response when treated with alectinib.

Investigating MRI-Associated Biological Aspects of Racial Disparities in Prostate Cancer for African American and White Men.

BACKGROUND: Understanding the characteristics of multiparametric MRI (mpMRI) in patients from different racial/ethnic backgrounds is important for reducing the observed gaps in clinical outcomes. PURPOSE: To investigate the diagnostic performance of mpMRI and quantitative MRI parameters of prostate cancer (PCa) in African American (AA) and matched White (W) men. STUDY TYPE: Retrospective. SUBJECTS: One hundred twenty-nine patients (43 AA, 86 W) with histologically proven PCa who underwent mpMRI before radical prostatectomy. FIELD STRENGTH/SEQUENCE: 3.0 T, T2-weighted turbo spin echo imaging, a single-shot spin-echo EPI sequence diffusion-weighted imaging, and a gradient echo sequence dynamic contrast-enhanced MRI with an ultrafast 3D spoiled gradient-echo sequence. ASSESSMENT: The diagnostic performance of mpMRI in AA and W men was assessed using detection rates (DRs) and positive predictive values (PPVs) in zones defined by the PI-RADS v2.1 prostate sector map. Quantitative MRI parameters, including Ktrans and ve of clinically significant (cs) PCa (Gleason score ≥ 7) tumors were compared between AA and W sub-cohorts after matching age, prostate-specific antigen (PSA), and prostate volume. STATISTICAL TESTS: Weighted Pearson's chi-square and Mann-Whitney U tests with a statistically significant level of 0.05 were used to examine differences in DR and PPV and to compare parameters between AA and matched W men, respectively. RESULTS: A total number of 264 PCa lesions were identified in the study cohort. The PPVs in the peripheral zone (PZ) and posterior prostate of mpMRI for csPCa lesions were significantly higher in AA men than in matched W men (87.8% vs. 68.1% in PZ, and 89.3% vs. 69.6% in posterior prostate). The Ktrans of index csPCa lesions in AA men was significantly higher than in W men (0.25 ± 0.12 vs. 0.20 ± 0.08 min-1; P < 0.01). DATA CONCLUSION: This study demonstrated race-related differences in the diagnostic performances and quantitative MRI measures of csPCa that were not reflected in age, PSA, and prostate volume. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Adrenal schwannoma can be FDG-Avid on PET/CT: case report and review of historic institutional pathology.

Schwannomas are benign, generally indolent tumors of neural crest origin and comprise the most common histologic tumor of peripheral nerves. Schwannomas are a rare histology for retroperitoneal tumors and very rare histologic findings for tumors of the adrenal gland with fewer than 50 cases in the reported literature. Here we present a case report of a non-hormonally functional but metabolically active adrenal tumor with indeterminate imaging characteristics with final pathology showing a 6.1 cm adrenal schwannoma as well as historical institutional pathology review revealing two additional cases.

Trichomonas vaginalis adherence phenotypes and extracellular vesicles impact parasite survival in a novel in vivo model of pathogenesis.

Trichomonas vaginalis is a human infective parasite responsible for trichomoniasis-the most common, non-viral, sexually transmitted infection worldwide. T. vaginalis resides exclusively in the urogenital tract of both men and women. In women, T. vaginalis has been found colonizing the cervix and vaginal tract while in men it has been identified in the upper and lower urogenital tract and in secreted fluids such as semen, urethral discharge, urine, and prostatic fluid. Despite the over 270 million cases of trichomoniasis annually worldwide, T. vaginalis continues to be a highly neglected organism and thus poorly studied. Here we have developed a male mouse model for studying T. vaginalis pathogenesis in vivo by delivering parasites into the murine urogenital tract (MUT) via transurethral catheterization. Parasite burden was assessed ex-vivo using a nanoluciferase-based gene expression assay which allowed quantification of parasites pre- and post-inoculation. Using this model and read-out approach, we show that T. vaginalis can be found within MUT tissue up to 72 hrs post-inoculation. Furthermore, we also demonstrate that parasites that exhibit increased parasite adherence in vitro also have higher parasite burden in mice in vivo. These data provide evidence that parasite adherence to host cells aids in parasite persistence in vivo and molecular determinants found to correlate with host cell adherence in vitro are applicable to infection in vivo. Finally, we show that co-inoculation of T. vaginalis extracellular vesicles (TvEVs) and parasites results in higher parasite burden in vivo. These findings confirm our previous in vitro-based predictions that TvEVs assist the parasite in colonizing the host. The establishment of this pathogenesis model for T. vaginalis sets the stage for identifying and examining parasite factors that contribute to and influence infection outcomes.

Focal therapy of prostate cancer: Assessment with prostate-specific membrane antigen (PSMA) imaging.

Focal therapy of prostate cancer (PCa) is currently of great interest, but a metric of success. other than biopsy, is not yet available. In a patient with a repeatedly negative MRI and negative systematic biopsies, a scan employing the radioisotope 68Ga-PSMA-11 PET/CT identified a PSMA-avid hotspot in the prostate. PSMA-guided biopsy confirmed the diagnosis of a clinically-significant PCa. Following ablation of the lesion with high-intensity focused ultrasound (HIFU), the PSMA-avid lesion disappeared and targeted biopsy confirmed a fibrotic scar with no residual cancer. PSMA imaging may have a role in guiding diagnosis, focal ablation, and follow-up of men with PCa.

Utility of Magnetic Resonance Imaging for Localizing Prostate Cancer Near the Urethra in Men Who Are Candidates for Focal Gland Ablation.

PURPOSE: Given that treatment near the urethra is often limited to reduce side effects, in this study we aim to determine whether prostate MRI can accurately identify the distance of prostate cancer to the urethra in a cohort of men who were potential candidates for focal gland ablation. MATERIALS AND METHODS: A single-institution analysis was performed of men who underwent MRI, targeted biopsy, and radical prostatectomy from July 2012 to April 2021. Men who were candidates for focal gland ablation were identified. The ability of MRI to identify prostate cancer within 5 mm of the prostatic urethra as confirmed on whole-mount pathology was assessed. Multivariate regression was utilized to determine characteristics associated with prostate cancer within 5 mm of the urethra on whole-mount pathology. RESULTS: In 48 out of 67 men (72%), the tumor was within 5 mm of the urethra on whole-mount pathology. MRI was concordant with whole-mount pathology in 49 out of 67 men (73%). The sensitivity of MRI for identifying cancer within 5 mm of the urethra was 77% (65%-89%) and the specificity was 63% (42%-89%). The positive predictive value was 84% (range 73%-95%) and negative predictive value was 52% (32%-73%). In adjusted analysis, PSA density and Prostate Imaging-Reporting and Data System were not significantly associated with having prostate cancer within close proximity of the urethra. CONCLUSIONS: A significant number of men who are potential candidates for focal gland ablation have cancer within close proximity to the urethra that could serve as a significant source of in-field recurrence. The sensitivity of MRI for identifying these lesions is 77% and can be used to further improve patient selection for focal gland ablation.

Racial Disparities in Quantitative MRI for African American and White Men with Prostate Cancer.

The risk of prostate cancer (PCa) is strongly influenced by race and ethnicity. The purpose of this study is to investigate differences in the diagnostic performance of multiparametric MRI (mpMRI) in African American (AA) and white (W) men. 111 patients (37 AA and 74 W men) were selected from the study's initial cohort of 885 patients after matching age, prostate-specific antigen, and prostate volume. The diagnostic performance of mpMRI was assessed using detection rates (DRs) and positive predictive values (PPVs) with/without combining Ktrans (volume transfer constant) stratified by prostate zones for AA and W sub-cohorts. The DRs of mpMRI for clinically significant PCa (csPCa) lesions in AA and W sub-cohort with PI-RADS scores ≥ 3 were 67.3% vs. 80.3% in the transition zone (TZ; p=0.026) and 81.2% vs. 76.1% in the peripheral zone (PZ; p>0.9). The Ktrans of csPCa in AA men was significantly higher than in W men (0.23±0.08 min-1 vs. 0.19±0.07 min-1; p=0.022). This emphasizes that there are race-related differences in the performance of mpMRI and quantitative MRI measures that are not reflected in age, PSA, and prostate volume.

Cryotherapy for partial gland ablation of prostate cancer: Oncologic and safety outcomes.

BACKGROUND: Partial gland ablation (PGA) is a new option for treatment of prostate cancer (PCa). Cryotherapy, an early method of PGA, has had favorable evaluations, but few studies have employed a strict protocol using biopsy endpoints in men with clinically significant prostate cancer (csPCa). METHODS: 143 men with unilateral csPCa were enrolled in a prospective, observational trial of outpatient PGA-cryotherapy. Treatment was a 2-cycle freeze of the affected prostate part. Participants were evaluated with MRI-guided biopsy (MRGB) at baseline and at 6 months and 18 months after treatment. Absence of csPCa upon MRGB was the primary endpoint; quality-of-life at baseline and at 6 months after treatment was assessed by EPIC-CP questionnaires in the domains of urinary and sexual function. RESULTS: Of the 143 participants, 136 (95%) completed MRGB at 6 months after treatment. In 103/136 (76%), the biopsy revealed no csPCa. Of the 103, 71 subsequently had an 18-month comprehensive biopsy; of the 71 with 18-month biopsies, 46 (65%) were found to have no csPCa. MRI lesions became undetectable in 96/130 (74%); declines in median serum PSA levels (6.9 to 2.5 ng/mL), PSA density (0.15 to 0.07), and prostate volume (42 to 34cc) were observed (all p < 0.01). Neither lesion disappearance on MRI nor PSA decline correlated with biopsy outcome. Urinary function was affected only slightly and sexual function moderately. CONCLUSION: In the near to intermediate term, partial gland ablation with cryotherapy was found to be a safe and moderately effective treatment of intermediate-risk prostate cancer. Eradication of cancer was better determined by MRI-guided biopsy than by MRI or PSA.

Prostate cancer multiparametric magnetic resonance imaging visibility is a tumor-intrinsic phenomena.

Multiparametric magnetic resonance imaging (mpMRI) is an emerging standard for diagnosing and prognosing prostate cancer, but ~ 20% of clinically significant tumors are invisible to mpMRI, as defined by the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score of one or two. To understand the biological underpinnings of tumor visibility on mpMRI, we examined the proteomes of forty clinically significant tumors (i.e., International Society of Urological Pathology (ISUP) Grade Group 2)-twenty mpMRI-visible and twenty mpMRI-invisible, with matched histologically normal prostate. Normal prostate tissue was indistinguishable between patients with visible and invisible tumors, and invisible tumors closely resembled the normal prostate. These data indicate that mpMRI-visibility arises when tumor evolution leads to large-magnitude proteomic divergences from histologically normal prostate.

Acute interstitial nephritis observed with three different triggering agents.

A 70-year-old female patient developed acute interstitial nephritis (AIN) after treatment with non-steroidal anti-inflammatory drugs (NSAIDs), proton pump inhibitors (PPI), and Bromhexine. Renal biopsy confirmed the diagnosis, and the patient was treated with oral prednisone. Careful attention to timing of acute kidney injury (AKI) is crucial to diagnosing AIN.

Targeted Prostate Biopsy: Umbra, Penumbra, and Value of Perilesional Sampling.

BACKGROUND: Systematic prostate biopsies add to the cancer detection rate of targeted biopsies, but the explanation for that increased sensitivity is not yet clear. OBJECTIVE: To determine and quantify the utility of perilesional biopsies in the detection of clinically significant prostate cancer (csPCa). DESIGN, SETTING, AND PARTICIPANTS: Participants were 2048 men with magnetic resonance imaging (MRI) lesions (grades 3-5) who underwent targeted and systematic prostate biopsy via MRI/ultrasound fusion at University of California Los Angeles and Cornell between 2011 and 2019. The study is a retrospective examination of prospectively acquired data. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: All biopsy cores (30191), locations of which had been stored digitally in the image-fusion device, were analyzed for tissue pathology and relationship with MRI lesions. A validated Matlab script was used to determine the distance between MRI lesions and cores containing csPCa (3552 cores from 927 men). Significance of distance measurements was determined by multilevel, multivariable logistic regression to account for within patient-biopsy correlation and control for patient characteristics. RESULTS AND LIMITATIONS: Overall, 90% (95% confidence interval [CI] = 89-91) of csPCa cores (3206/3552) were located within a radius of 10 mm from the nearest lesion: 65% (95% CI = 63-67) within the region of interest (ROI) and 26% (95% CI = 24-27) outside the ROI but within the 10-mm "penumbra." The width of the penumbra or concentric band, which enclosed 90% of csPCa, was primarily related to MRI grade of lesion: grade 5, 5 mm; grade 4, 12 mm; grade 3, 16 mm. In 18% (95% CI = 15-20) of patients (166/927), csPCa was diagnosed only by sampling outside the MRI lesion, the yield decreasing with increasing distance. Limitations of MRI interpretation and fusion biopsy performance could affect the utility of these data in individual patients. CONCLUSIONS: Perilesional biopsies, that is, samples taken from a band of 10-mm radius outside MRI lesions (the penumbra), contain most cores of csPCa that are not present within the lesion. These data may help increase the performance characteristics of targeted prostate biopsy. PATIENT SUMMARY: We studied the locations of cancer within the prostate in men undergoing magnetic resonance imaging (MRI)-guided biopsy. We found that not all cancers are located within the MRI lesion, but 90% (95% confidence interval = 89-91) of the cancers arewithin 1 cm of the lesions. Biopsies taken from both within and around MRI lesions provide greater sensitivity for cancer detection than samples taken from the lesion only.

PathAL: An Active Learning Framework for Histopathology Image Analysis.

Deep neural networks, in particular convolutional networks, have rapidly become a popular choice for analyzing histopathology images. However, training these models relies heavily on a large number of samples manually annotated by experts, which is cumbersome and expensive. In addition, it is difficult to obtain a perfect set of labels due to the variability between expert annotations. This paper presents a novel active learning (AL) framework for histopathology image analysis, named PathAL. To reduce the required number of expert annotations, PathAL selects two groups of unlabeled data in each training iteration: one "informative" sample that requires additional expert annotation, and one "confident predictive" sample that is automatically added to the training set using the model's pseudo-labels. To reduce the impact of the noisy-labeled samples in the training set, PathAL systematically identifies noisy samples and excludes them to improve the generalization of the model. Our model advances the existing AL method for medical image analysis in two ways. First, we present a selection strategy to improve classification performance with fewer manual annotations. Unlike traditional methods focusing only on finding the most uncertain samples with low prediction confidence, we discover a large number of high confidence samples from the unlabeled set and automatically add them for training with assigned pseudo-labels. Second, we design a method to distinguish between noisy samples and hard samples using a heuristic approach. We exclude the noisy samples while preserving the hard samples to improve model performance. Extensive experiments demonstrate that our proposed PathAL framework achieves promising results on a prostate cancer Gleason grading task, obtaining similar performance with 40% fewer annotations compared to the fully supervised learning scenario. An ablation study is provided to analyze the effectiveness of each component in PathAL, and a pathologist reader study is conducted to validate our proposed algorithm.

A prostate cancer risk calculator: Use of clinical and magnetic resonance imaging data to predict biopsy outcome in North American men.

INTRODUCTION: A functional tool to optimize patient selection for magnetic resonance imaging (MRI)-guided prostate biopsy (MRGB) is an unmet clinical need. We sought to develop a prostate cancer risk calculator (PCRC-MRI) that combines MRI and clinical characteristics to aid decision-making for MRGB in North American men. METHODS: Two prospective registries containing 2354 consecutive men undergoing MRGB (September 2009 to April 2019) were analyzed. Patients were randomized into five groups, with one group randomly assigned to be the validation cohort against the other four groups as the discovery cohort. The primary outcome was detection of clinically significant prostate cancer (csPCa) defined as Gleason grade group ≥2. Variables included age, ethnicity, digital rectal exam (DRE), prior biopsy, prostate-specific antigen (PSA), prostate volume, PSA density, and MRI score. Odds ratios (OR) were calculated from multivariate logistic regression comparing two models: one with clinical variables only (clinical) against a second combining clinical variables with MRI data (clinical+MRI). RESULTS: csPCa was present in 942 (40%) of the 2354 men available for study. The positive and negative predictive values for csPCa in the clinical+MRI model were 57% and 89%, respectively. The area under the curve of the clinical+MRI model was superior to the clinical model in discovery (0.843 vs. 0.707, p<0.0001) and validation (0.888 vs. 0.757, p<0.0001) cohorts. Use of PCRC-MRI would have avoided approximately 16 unnecessary biopsies in every 100 men. Of all variables examined, Asian ethnicity was the most protective factor (OR 0.46, 0.29-0.75) while MRI score 5 indicated greatest risk (OR15.8, 10.5-23.9). CONCLUSIONS: A risk calculator (PCRC-MRI), based on a large North American cohort, is shown to improve patient selection for MRGB, especially in preventing unnecessary biopsies. This tool is available at https://www.uclahealth.org/urology/prostate-cancer-riskcalculator and may help rationalize biopsy decision-making.

Head-to-Head Comparison of 68Ga-PSMA-11 PET/CT and mpMRI with a Histopathology Gold Standard in the Detection, Intraprostatic Localization, and Determination of Local Extension of Primary Prostate Cancer: Results from a Prospective Single-Center Imaging Trial.

The role of prostate-specific membrane antigen (PSMA)-targeted PET in comparison to multiparametric MRI (mpMRI) in the evaluation of intraprostatic cancer foci is not well defined. The aim of our study was to compare the diagnostic performance of 68Ga-PSMA-11 PET/CT (PSMA PET/CT), mpMRI, and PSMA PET/CT + mpMRI using 3 independent masked readers for each modality and with histopathology as the gold standard in the detection, intraprostatic localization, and determination of local extension of primary prostate cancer. Methods: Patients with intermediate- or high-risk prostate cancer who underwent PSMA PET/CT as part of a prospective trial (NCT03368547) and mpMRI before radical prostatectomy were included. Each imaging modality was interpreted by 3 independent readers who were unaware of the other modality result. A central majority rule was applied (2:1). Pathologic examination of whole-mount slices was used as the gold standard. Imaging scans and whole-mount slices were interpreted using the same standardized approach on a segment level and a lesion level. A "neighboring" approach was used to define imaging-pathology correlation for the detection of individual prostate cancer foci. Accuracy in determining the location, extraprostatic extension (EPE), and seminal vesicle invasion (SVI) of prostate cancer foci was assessed using receiver-operating-characteristic curve analysis. Interreader agreement was calculated using intraclass correlation coefficient analysis. Results: The final analysis included 74 patients (14 [19%] with intermediate risk and 60 [81%] with high risk). The cancer detection rate (lesion-based analysis) was 85%, 83%, and 87% for PSMA PET/CT, mpMRI, and PSMA PET/CT + mpMRI, respectively. The change in AUC was statistically significant between PSMA PET/CT + mpMRI and the 2 imaging modalities alone for delineation of tumor localization (segment-based analysis) (P < 0.001) but not between PSMA PET/CT and mpMRI (P = 0.093). mpMRI outperformed PSMA PET/CT in detecting EPE (P = 0.002) and SVI (P = 0.001). In the segment-level analysis, intraclass correlation coefficient analysis showed moderate reliability among PSMA PET/CT and mpMRI readers using a 5-point Likert scale (range, 0.53-0.64). In the evaluation of T staging, poor reliability was found among PSMA PET/CT readers and poor to moderate reliability was found for mpMRI readers. Conclusion: PSMA PET/CT and mpMRI have similar accuracy in the detection and intraprostatic localization of prostate cancer foci. mpMRI performs better in identifying EPE and SVI. For the T-staging evaluation of intermediate to high-risk prostate cancer, mpMRI should still be considered the imaging modality of reference. Whenever available, PSMA PET/MRI or the coregistration or fusion of PSMA PET/CT and mpMRI (PSMA PET/CT + mpMRI) should be used as it improves tumor extent delineation.