Cryptic splice mutation in the fumarate hydratase gene in patients with clinical manifestations of Hereditary Leiomyomatosis and Renal Cell Cancer.

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is an autosomal dominant condition characterized by the development of cutaneous and uterine leiomyomas and risk for development of an aggressive form of papillary renal cell cancer. HLRCC is caused by germline inactivating pathogenic variants in the fumarate hydratase (FH) gene, which encodes the enzyme that catalyzes the interconversion of fumarate and L-malate. We utilized enzyme and protein mobility assays to evaluate the FH enzyme in a cohort of patients who showed clinical manifestations of HLRCC but were negative for known pathogenic FH gene variants. FH enzyme activity and protein levels were decreased by 50% or greater in three family members, despite normal FH mRNA expression levels as measured by quantitative PCR. Direct Nanopore RNA sequencing demonstrated 57 base pairs of retained intron sequence between exons 9 and 10 of polyadenylated FH mRNA in these patients, resulting in a truncated FH protein. Genomic sequencing revealed a heterozygous intronic alteration of the FH gene (chr1: 241498239 T/C) resulting in formation of a splice acceptor site near a polypyrimidine tract, and a uterine fibroid obtained from a patient showed loss of heterozygosity at this site. The same intronic FH variant was identified in an unrelated patient who also showed a clinical phenotype of HLRCC. These data demonstrate that careful clinical assessment as well as biochemical characterization of FH enzyme activity, protein expression, direct RNA sequencing, and genomic DNA sequencing of patient-derived cells can identify pathogenic variants outside of the protein coding regions of the FH gene.

Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results. Materials and Methods This secondary analysis of a prospective registry included consecutive patients with suspected or known PCa who underwent mpMRI, US-guided systematic biopsy, or combined systematic and MRI/US fusion-guided biopsy between April 2019 and September 2022. All lesions were prospectively evaluated using Prostate Imaging Reporting and Data System version 2.1. The lesion- and participant-level performance of a previously developed cascaded deep learning algorithm was compared with histopathologic outcomes and radiologist readings using sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC). Results A total of 658 male participants (median age, 67 years [IQR, 61-71 years]) with 1029 MRI-visible lesions were included. At histopathologic analysis, 45% (294 of 658) of participants had lesions of International Society of Urological Pathology (ISUP) grade group (GG) 2 or higher. The algorithm identified 96% (282 of 294; 95% CI: 94%, 98%) of all participants with clinically significant PCa, whereas the radiologist identified 98% (287 of 294; 95% CI: 96%, 99%; P = .23). The algorithm identified 84% (103 of 122), 96% (152 of 159), 96% (47 of 49), 95% (38 of 40), and 98% (45 of 46) of participants with ISUP GG 1, 2, 3, 4, and 5 lesions, respectively. In the lesion-level analysis using radiologist ground truth, the detection sensitivity was 55% (569 of 1029; 95% CI: 52%, 58%), and the PPV was 57% (535 of 934; 95% CI: 54%, 61%). The mean number of false-positive lesions per participant was 0.61 (range, 0-3). The lesion segmentation DSC was 0.29. Conclusion The AI algorithm detected cancer-suspicious lesions on biparametric MRI scans with a performance comparable to that of an experienced radiologist. Moreover, the algorithm reliably predicted clinically significant lesions at histopathologic examination. ClinicalTrials.gov Identifier: NCT03354416 © RSNA, 2024 Supplemental material is available for this article.

PI-RADS Version 2.0 Versus Version 2.1: Comparison of Prostate Cancer Gleason Grade Upgrade and Downgrade Rates From MRI-Targeted Biopsy to Radical Prostatectomy.

BACKGROUND. Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. OBJECTIVE. The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and downgrade from TBx to radical prostatectomy (RP). METHODS. This study entailed a retrospective post hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of three prospective clinical trials. Trial participants who underwent MRI followed by MRI/US fusion-guided TBx and RP within a 1-year interval were identified. A single genitourinary radiologist performed clinical interpretations of the MRI examinations using PI-RADS v2.0 from May 2015 to March 2019 and PI-RADS v2.1 from April 2019 to March 2023. Upgrade and downgrade rates from TBx to RP were compared using chi-square tests. Clinically significant cancer was defined as ISUP GG2 or greater. RESULTS. The final analysis included 308 patients (median age, 65 years; median PSA density, 0.16 ng/mL2). The v2.0 group (n = 177) and v2.1 group (n = 131) showed no significant difference in terms of upgrade rate (29% vs 22%, respectively; p = .15), downgrade rate (19% vs 21%, p = .76), clinically significant upgrade rate (14% vs 10%, p = .27), or clinically significant downgrade rate (1% vs 1%, p > .99). The upgrade rate and downgrade rate were also not significantly different between the v2.0 and v2.1 groups when stratifying by index lesion PI-RADS category or index lesion zone, as well as when assessed only in patients without a prior PCa diagnosis (all p > .01). Among patients with GG2 or GG3 at RP (n = 121 for v2.0; n = 103 for v2.1), the concordance rate between TBx and RP was not significantly different between the v2.0 and v2.1 groups (53% vs 57%, p = .51). CONCLUSION. Upgrade and downgrade rates from TBx to RP were not significantly different between patients whose MRI examinations were clinically interpreted using v2.0 or v2.1. CLINICAL IMPACT. Implementation of the most recent PI-RADS update did not improve the incongruence in PCa grade assessment between TBx and surgery.

Is prostatic adenocarcinoma with cribriform architecture more difficult to detect on prostate MRI?

BACKGROUND: Cribriform (CBFM) pattern on prostate biopsy has been implicated as a predictor for high-risk features, potentially leading to adverse outcomes after definitive treatment. This study aims to investigate whether the CBFM pattern containing prostate cancers (PCa) were associated with false negative magnetic resonance imaging (MRI) and determine the association between MRI and histopathological disease burden. METHODS: Patients who underwent multiparametric magnetic resonance imaging (mpMRI), combined 12-core transrectal ultrasound (TRUS) guided systematic (SB) and MRI/US fusion-guided biopsy were retrospectively queried for the presence of CBFM pattern at biopsy. Biopsy cores and lesions were categorized as follows: C0 = benign, C1 = PCa with no CBFM pattern, C2 = PCa with CBFM pattern. Correlation between cancer core length (CCL) and measured MRI lesion dimension were assessed using a modified Pearson correlation test for clustered data. Differences between the biopsy core groups were assessed with the Wilcoxon-signed rank test with clustering. RESULTS: Between 2015 and 2022, a total of 131 consecutive patients with CBFM pattern on prostate biopsy and pre-biopsy mpMRI were included. Clinical feature analysis included 1572 systematic biopsy cores (1149 C0, 272 C1, 151 C2) and 736 MRI-targeted biopsy cores (253 C0, 272 C1, 211 C2). Of the 131 patients with confirmed CBFM pathology, targeted biopsy (TBx) alone identified CBFM in 76.3% (100/131) of patients and detected PCa in 97.7% (128/131) patients. SBx biopsy alone detected CBFM in 61.1% (80/131) of patients and PCa in 90.8% (119/131) patients. TBx and SBx had equivalent detection in patients with smaller prostates (p = 0.045). For both PCa lesion groups there was a positive and significant correlation between maximum MRI lesion dimension and CCL (C1 lesions: p < 0.01, C2 lesions: p < 0.001). There was a significant difference in CCL between C1 and C2 lesions for T2 scores of 3 and 5 (p ≤ 0.01, p ≤ 0.01, respectively) and PI-RADS 5 lesions (p ≤ 0.01), with C2 lesions having larger CCL, despite no significant difference in MRI lesion dimension. CONCLUSIONS: The extent of disease for CBFM-containing tumors is difficult to capture on mpMRI. When comparing MRI lesions of similar dimensions and PIRADS scores, CBFM-containing tumors appear to have larger cancer yield on biopsy. Proper staging and planning of therapeutic interventions is reliant on accurate mpMRI estimation. Special considerations should be taken for patients with CBFM pattern on prostate biopsy.

Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection and Investigation of Multiparametric MRI-derived Markers.

Background Data regarding the prospective performance of Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 alone and in combination with quantitative MRI features for prostate cancer detection is limited. Purpose To assess lesion-based clinically significant prostate cancer (csPCa) rates in different PI-RADS version 2.1 categories and to identify MRI features that could improve csPCa detection. Materials and Methods This single-center prospective study included men with suspected or known prostate cancer who underwent multiparametric MRI and MRI/US-guided biopsy from April 2019 to December 2021. MRI scans were prospectively evaluated using PI-RADS version 2.1. Atypical transition zone (TZ) nodules were upgraded to category 3 if marked diffusion restriction was present. Lesions with an International Society of Urological Pathology (ISUP) grade of 2 or higher (range, 1-5) were considered csPCa. MRI features, including three-dimensional diameter, relative lesion volume (lesion volume divided by prostate volume), sphericity, and surface to volume ratio (SVR), were obtained from lesion contours delineated by the radiologist. Univariable and multivariable analyses were conducted at the lesion and participant levels to determine features associated with csPCa. Results In total, 454 men (median age, 67 years [IQR, 62-73 years]) with 838 lesions were included. The csPCa rates for lesions categorized as PI-RADS 1 (n = 3), 2 (n = 170), 3 (n = 197), 4 (n = 319), and 5 (n = 149) were 0%, 9%, 14%, 37%, and 77%, respectively. csPCa rates of PI-RADS 4 lesions were lower than PI-RADS 5 lesions (P < .001) but higher than PI-RADS 3 lesions (P < .001). Upgraded PI-RADS 3 TZ lesions were less likely to harbor csPCa compared with their nonupgraded counterparts (4% [one of 26] vs 20% [20 of 99], P = .02). Predictors of csPCa included relative lesion volume (odds ratio [OR], 1.6; P < .001), SVR (OR, 6.2; P = .02), and extraprostatic extension (EPE) scores of 2 (OR, 9.3; P < .001) and 3 (OR, 4.1; P = .02). Conclusion The rates of csPCa differed between consecutive PI-RADS categories of 3 and higher. MRI features, including lesion volume, shape, and EPE scores of 2 and 3, predicted csPCa. Upgrading of PI-RADS category 3 TZ lesions may result in unnecessary biopsies. ClinicalTrials.gov registration no. NCT03354416 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Goh in this issue.

Deep Learning-Based T2-weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates.

BACKGROUND: Image quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis. PURPOSE: To examine the impact of image quality on prostate cancer detection using an in-house previously developed artificial intelligence (AI) algorithm. STUDY TYPE: Retrospective. SUBJECTS: 615 consecutive patients (median age 67 [interquartile range [IQR]: 61-71] years) with elevated serum PSA (median PSA 6.6 [IQR: 4.6-9.8] ng/mL) prior to prostate biopsy. FIELD STRENGTH/SEQUENCE: 3.0T/T2-weighted turbo-spin-echo MRI, high b-value echo-planar diffusion-weighted imaging, and gradient recalled echo dynamic contrast-enhanced. ASSESSMENTS: Scans were prospectively evaluated during clinical readout using PI-RADSv2.1 by one genitourinary radiologist with 17 years of experience. For each patient, T2-weighted images (T2WIs) were classified as high-quality or low-quality based on evaluation of both general distortions (eg, motion, distortion, noise, and aliasing) and perceptual distortions (eg, obscured delineation of prostatic capsule, prostatic zones, and excess rectal gas) by a previously developed in-house AI algorithm. Patients with PI-RADS category 1 underwent 12-core ultrasound-guided systematic biopsy while those with PI-RADS category 2-5 underwent combined systematic and targeted biopsies. Patient-level cancer detection rates (CDRs) were calculated for clinically significant prostate cancer (csPCa, International Society of Urological Pathology Grade Group ≥2) by each biopsy method and compared between high- and low-quality images in each PI-RADS category. STATISTICAL TESTS: Fisher's exact test. Bootstrap 95% confidence intervals (CI). A P value <0.05 was considered statistically significant. RESULTS: 385 (63%) T2WIs were classified as high-quality and 230 (37%) as low-quality by AI. Targeted biopsy with high-quality T2WIs resulted in significantly higher clinically significant CDR than low-quality images for PI-RADS category 4 lesions (52% [95% CI: 43-61] vs. 32% [95% CI: 22-42]). For combined biopsy, there was no significant difference in patient-level CDRs for PI-RADS 4 between high- and low-quality T2WIs (56% [95% CI: 47-64] vs. 44% [95% CI: 34-55]; P = 0.09). DATA CONCLUSION: Higher quality T2WIs were associated with better targeted biopsy clinically significant cancer detection performance for PI-RADS 4 lesions. Combined biopsy might be needed when T2WI is lower quality. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

A diagnosis of Birt-Hogg-Dubé syndrome in individuals with Smith-Magenis syndrome: Recommendation for cancer screening.

We report a series of four unrelated adults with Smith-Magenis syndrome (SMS) and concomitant features of Birt-Hogg-Dubé (BHD) syndrome based upon haploinsufficiency for FLCN and characteristic renal cell carcinomas and/or evidence of cutaneous fibrofolliculomas. Three of the cases constitute the first known association of histopathologically verified characteristic BHD-associated renal tumors in adults with SMS; the fourth was identified to have histologically confirmed skin fibrofolliculomas. Molecular analysis documented second-hit FLCN mutations in two of the three cases with confirmed BHD renal pathology. These cases suggest the need to expand management recommendations for SMS to include kidney cancer surveillance starting at 20 years of age, as per the screening recommendations for BHD syndrome.

Comparison of MRI-Based Staging and Pathologic Staging for Predicting Biochemical Recurrence of Prostate Cancer After Radical Prostatectomy.

BACKGROUND. Currently most clinical models for predicting biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) incorporate staging information from RP specimens, creating a gap in preoperative risk assessment. OBJECTIVE. The purpose of our study was to compare the utility of presurgical staging information from MRI and postsurgical staging information from RP pathology in predicting BCR in patients with PCa. METHODS. This retrospective study included 604 patients (median age, 60 years) with PCa who underwent prostate MRI before RP from June 2007 to December 2018. A single genitourinary radiologist assessed MRI examinations for extraprostatic extension (EPE) and seminal vesicle invasion (SVI) during clinical interpretations. The utility of EPE and SVI on MRI and RP pathology for BCR prediction was assessed through Kaplan-Meier and Cox proportional hazards analyses. Established clinical BCR prediction models, including the University of California San Francisco Cancer of the Prostate Risk Assessment (UCSF-CAPRA) model and the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) model, were evaluated in a subset of 374 patients with available Gleason grade groups from biopsy and RP pathology; two CAPRA-MRI models (CAPRA-S model with modifications to replace RP pathologic staging features with MRI staging features) were also assessed. RESULTS. Univariable predictors of BCR included EPE on MRI (HR = 3.6), SVI on MRI (HR = 4.4), EPE on RP pathology (HR = 5.0), and SVI on RP pathology (HR = 4.6) (all p < .001). Three-year BCR-free survival (RFS) rates for patients without versus with EPE were 84% versus 59% for MRI and 89% versus 58% for RP pathology, and 3-year RFS rates for patients without versus with SVI were 82% versus 50% for MRI and 83% versus 54% for RP histology (all p < .001). For patients with T3 disease on RP pathology, 3-year RFS rates were 67% and 41% for patients without and with T3 disease on MRI. AUCs of CAPRA models, including CAPRA-MRI models, ranged from 0.743 to 0.778. AUCs were not significantly different between CAPRA-S and CAPRA-MRI models (p > .05). RFS rates were significantly different between low- and intermediate-risk groups for only CAPRA-MRI models (80% vs 51% and 74% vs 44%; both p < .001). CONCLUSION. Presurgical MRI-based staging features perform comparably to postsurgical pathologic staging features for predicting BCR. CLINICAL IMPACT. MRI staging can preoperatively identify patients at high BCR risk, helping to inform early clinical decision-making. TRIAL REGISTRATION. ClinicalTrials.gov NCT00026884 and NCT02594202.

Magnetic Resonance Imaging-Guided Biopsy in Active Surveillance of Prostate Cancer.

PURPOSE: The underlying premise of prostate cancer active surveillance (AS) is that cancers likely to metastasize will be recognized and eliminated before cancer-related disease can ensue. Our study was designed to determine the prostate cancer upgrading rate when biopsy guided by magnetic resonance imaging (MRGBx) is used before entry and during AS. MATERIALS AND METHODS: The cohort included 519 men with low- or intermediate-risk prostate cancer who enrolled in prospective studies (NCT00949819 and NCT00102544) between February 2008 and February 2020. Subjects were preliminarily diagnosed with Gleason Grade Group (GG) 1 cancer; AS began when subsequent MRGBx confirmed GG1 or GG2. Participants underwent confirmatory MRGBx (targeted and systematic) followed by surveillance MRGBx approximately every 12 to 24 months. The primary outcome was tumor upgrading to ≥GG3. RESULTS: Upgrading to ≥GG3 was found in 92 men after a median followup of 4.8 years (IQR 3.1-6.5) after confirmatory MRGBx. Upgrade-free probability after 5 years was 0.85 (95% CI 0.81-0.88). Cancer detected in a magnetic resonance imaging lesion at confirmatory MRGBx increased risk of subsequent upgrading during AS (HR 2.8; 95% CI 1.3-6.0), as did presence of GG2 (HR 2.9; 95% CI 1.1-8.2) In men who upgraded ≥GG3 during AS, upgrading was detected by targeted cores only in 27%, systematic cores only in 25% and both in 47%. In 63 men undergoing prostatectomy, upgrading from MRGBx was found in only 5 (8%). CONCLUSIONS: When AS begins and follows with MRGBx (targeted and systematic), upgrading rate (≥GG3) is greater when tumor is initially present within a magnetic resonance imaging lesion or when pathology is GG2 than when these features are absent.

Characterization of genetically defined sporadic and hereditary type 1 papillary renal cell carcinoma cell lines.

Renal cell carcinoma (RCC) is not a single disease but is made up of several different histologically defined subtypes that are associated with distinct genetic alterations which require subtype specific management and treatment. Papillary renal cell carcinoma (pRCC) is the second most common subtype after conventional/clear cell RCC (ccRCC), representing ~20% of cases, and is subcategorized into type 1 and type 2 pRCC. It is important for preclinical studies to have cell lines that accurately represent each specific RCC subtype. This study characterizes seven cell lines derived from both primary and metastatic sites of type 1 pRCC, including the first cell line derived from a hereditary papillary renal carcinoma (HPRC)-associated tumor. Complete or partial gain of chromosome 7 was observed in all cell lines and other common gains of chromosomes 16, 17, or 20 were seen in several cell lines. Activating mutations of MET were present in three cell lines that all demonstrated increased MET phosphorylation in response to HGF and abrogation of MET phosphorylation in response to MET inhibitors. CDKN2A loss due to mutation or gene deletion, associated with poor outcomes in type 1 pRCC patients, was observed in all cell line models. Six cell lines formed tumor xenografts in athymic nude mice and thus provide in vivo models of type 1 pRCC. These type 1 pRCC cell lines provide a comprehensive representation of the genetic alterations associated with pRCC that will give insight into the biology of this disease and be ideal preclinical models for therapeutic studies.

Prognostic Features of Biochemical Recurrence of Prostate Cancer Following Radical Prostatectomy Based on Multiparametric MRI and Immunohistochemistry Analysis of MRI-guided Biopsy Specimens.

Background Although prostate MRI is routinely used for the detection and staging of localized prostate cancer, imaging-based assessment and targeted molecular sampling for risk stratification are an active area of research. Purpose To evaluate features of preoperative MRI and MRI-guided biopsy immunohistochemistry (IHC) findings associated with biochemical recurrence (BCR) of prostate cancer after surgery. Materials and Methods In this retrospective case-control study, patients underwent multiparametric MRI before MRI-guided biopsy followed by radical prostatectomy between 2008 and 2016. Lesions were retrospectively scored with the Prostate Imaging Reporting and Data System (PI-RADS) (version 2) by radiologists who were blinded to the clinical-pathologic results. The IHC staining, including stains for the ETS-related gene, phosphatase and tensin homolog, androgen receptor, prostate specific antigen, and p53, was performed with targeted biopsy specimens of the index lesion (highest suspicion at MRI and pathologic grade) and scored by pathologists who were blinded to clinical-pathologic outcomes. Cox proportional hazards regression analysis was used to evaluate associations with recurrence-free survival (RFS). Results The median RFS was 31.7 months (range, 1-101 months) for 39 patients (median age, 62 years; age range, 47-76 years) without BCR and 14.6 months (range, 1-61 months) for 40 patients (median age, 59 years; age range, 47-73 years) with BCR. MRI features that showed a significant relationship with the RFS interval included an index lesion with a PI-RADS score of 5 (hazard ratio [HR], 2.10; 95% CI: 1.05, 4.21; P = .04); index lesion burden, defined as ratio of index lesion volume to prostate volume (HR, 1.55; 95% CI: 1.2, 2.1; P = .003); and suspicion of extraprostatic extension (EPE) (HR, 2.18; 95% CI: 1.1, 4.2; P = .02). Presurgical multivariable analysis indicated that suspicion of EPE at MRI (adjusted HR, 2.19; 95% CI: 1.1, 4.3; P = .02) and p53 stain intensity (adjusted HR, 2.22; 95% CI: 1.0, 4.7; P = .04) were significantly associated with RFS. Conclusion MRI features, including Prostate Imaging Reporting and Data System score, index lesion burden, extraprostatic extension, and preoperative guided biopsy p53 immunohistochemistry stain intensity are associated with biochemical relapse of prostate cancer after surgery. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Costa in this issue.

Magnetic Resonance Imaging-Targeted and Systematic Biopsy for Detection of Grade Progression in Patients on Active Surveillance for Prostate Cancer.

PURPOSE: Active surveillance for patients with low and intermediate risk prostate cancers is becoming a more utilized option in recent years. However, the use of magnetic resonance imaging and imaging-targeted biopsy for monitoring grade progression has been poorly studied in this population. We aim to define the utility of magnetic resonance imaging-targeted biopsy and systematic biopsy in an active surveillance population. MATERIALS AND METHODS: Between July 2007 and January 2020, patients with diagnosed prostate cancer who elected active surveillance were monitored with prostate magnetic resonance imaging, imaging-targeted biopsy and standard systematic biopsy. Patients were eligible for surveillance if diagnosed with any volume Gleason grade 1 disease and select Gleason grade 2 disease. Grade progression (Gleason grade 1 to ≥2 disease and Gleason grade 2 to ≥3 disease) for each biopsy modality was measured at 2 years, 4 years and 6+ years. RESULTS: In total, 369 patients had both magnetic resonance imaging-targeted and systematic biopsy and were surveilled for at least 1 year. At 2 years, systematic biopsy, magnetic resonance imaging-targeted biopsy and combined biopsy (systematic+imaging-targeted) detected grade progression in 44 patients (15.9%), 73 patients (26.4%) and 90 patients (32.5%), respectively. Magnetic resonance imaging-targeted biopsy detected more cancer grade progression compared to systematic biopsy in both the low and intermediate risk populations (p <0.001). Of all 90 grade progressions at the 2-year time point 46 (51.1%) were found by magnetic resonance imaging-targeted biopsy alone and missed by systematic biopsy. CONCLUSIONS: Magnetic resonance imaging-targeted biopsy detected significantly more grade progressions in our active surveillance cohort compared to systematic biopsy at 2 years. Our results provide compelling evidence that prostate magnetic resonance imaging and imaging-targeted biopsy should be included in contemporary active surveillance protocols.

The Risk of Prostate Cancer Progression in Active Surveillance Patients with Bilateral Disease Detected by Combined Magnetic Resonance Imaging-Fusion and Systematic Biopsy.

PURPOSE: We sought to evaluate whether bilateral prostate cancer detected at active surveillance (AS) enrollment is associated with progression to Grade Group (GG) ≥2 and to compare the efficacy of combined targeted biopsy plus systematic biopsy (Cbx) vs systematic biopsy (Sbx) or targeted biopsy alone to detect bilateral disease. MATERIALS AND METHODS: A prospectively maintained database of patients referred to our institution from 2007-2020 was queried. The study cohort included all AS patients with GG1 on confirmatory Cbx and followup of at least 1 year. Cox proportional hazard analysis identified baseline characteristics associated with progression to ≥GG2 at any point throughout followup. RESULTS: Of 579 patients referred, 103 patients had GG1 on Cbx and were included in the study; 49/103 (47.6%) patients progressed to ≥GG2, with 30/72 (41.7%) patients with unilateral disease progressing and 19/31 (61.3%) patients with bilateral disease progressing. Median time to progression was 68 months vs 52 months for unilateral and bilateral disease, respectively (p=0.006). Both prostate specific antigen density (HR 1.72, p=0.005) and presence of bilateral disease (HR 2.21, p=0.012) on confirmatory biopsy were associated with AS progression. At time of progression, GG and risk group were significantly higher in patients with bilateral versus unilateral disease. Cbx detected 16% more patients with bilateral disease than Sbx alone. CONCLUSIONS: Bilateral disease and prostate specific antigen density at confirmatory Cbx conferred greater risk of earlier AS progression. Cbx was superior to Sbx for identifying bilateral disease. AS risk-stratification protocols may benefit from including presence of bilateral disease and should use Cbx to detect bilateral disease.

Novel renal medullary carcinoma cell lines, UOK353 and UOK360, provide preclinical tools to identify new therapeutic treatments.

Renal medullary carcinoma (RMC) is a rare, aggressive disease that predominantly afflicts individuals of African or Mediterranean descent with sickle cell trait. RMC comprises 1% of all renal cell carcinoma diagnoses with a median overall survival of 13 months. Patients are typically young (median age-22) and male (male:female ratio of 2:1) and tumors are characterized by complete loss of expression of the SMARCB1 tumor suppressor protein. Due to the low incidence of RMC and the disease's aggressiveness, treatment decisions are often based on case reports. Thus, it is critical to develop preclinical models of RMC to better understand the pathogenesis of this disease and to identify effective forms of therapy. Two novel cell line models, UOK353 and UOK360, were derived from primary RMCs that both demonstrated the characteristic SMARCB1 loss. Both cell lines overexpressed EZH2 and other members of the polycomb repressive complex and EZH2 inhibition in RMC tumor spheroids resulted in decreased viability. High throughput drug screening of both cell lines revealed several additional candidate compounds, including bortezomib that had both in vitro and in vivo antitumor activity. The activity of bortezomib was shown to be partially dependent on increased oxidative stress as addition of the N-acetyl cysteine antioxidant reduced the effect on cell proliferation. Combining bortezomib and cisplatin further decreased cell viability both in vitro and in vivo that single agent bortezomib treatment. The UOK353 and UOK360 cell lines represent novel preclinical models for the development of effective forms of therapy for RMC patients.

Cabozantinib in patients with platinum-refractory metastatic urothelial carcinoma: an open-label, single-centre, phase 2 trial.

BACKGROUND: Cabozantinib is a multikinase inhibitor of MET, VEGFR, AXL, and RET, which also has an effect on the tumour immune microenvironment by decreasing regulatory T cells and myeloid-derived suppressor cells. In this study, we examined the activity of cabozantinib in patients with metastatic platinum-refractory urothelial carcinoma. METHODS: This study was an open-label, single-arm, three-cohort phase 2 trial done at the National Cancer Institute (Bethesda, MD, USA). Eligible patients were 18 years or older, had histologically confirmed urothelial carcinoma or rare genitourinary tract histologies, Karnofsky performance scale index of 60% or higher, and documented disease progression after at least one previous line of platinum-based chemotherapy (platinum-refractory). Cohort one included patients with metastatic urothelial carcinoma with measurable disease as defined by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Two additional cohorts that enrolled in parallel (patients with bone-only urothelial carcinoma metastases and patients with rare histologies of the genitourinary tract) were exploratory. Patients received cabozantinib 60 mg orally once daily in 28-day cycles until disease progression or unacceptable toxicity. The primary endpoint was investigator-assessed objective response rate by RECIST in cohort one. Response was assessed in all patients who met the eligibility criteria and who received at least 8 weeks of therapy. All patients who received at least one dose of cabozantinib were included in the safety analysis. This completed study is registered with ClinicalTrials.gov, NCT01688999. FINDINGS: Between Sept 28, 2012, and Oct, 20, 2015, 68 patients were enrolled on the study (49 in cohort one, six in cohort two, and 13 in cohort three). All patients received at least one dose of cabozantinib. The median follow-up was 61·2 months (IQR 53·8-70·0) for the 57 patients evaluable for response. In the 42 evaluable patients in cohort one, there was one complete response and seven partial responses (objective response rate 19%, 95% CI 9-34). The most common grade 3-4 adverse events were fatigue (six [9%] patients), hypertension (five [7%]), proteinuria (four [6%]), and hypophosphataemia (four [6%]). There were no treatment-related deaths. INTERPRETATION: Cabozantinib has single-agent clinical activity in patients with heavily pretreated, platinum-refractory metastatic urothelial carcinoma with measurable disease and bone metastases and is generally well tolerated. Cabozantinib has innate and adaptive immunomodulatory properties providing a rationale for combining cabozantinib with immunotherapeutic strategies. FUNDING: National Cancer Institute Intramural Program and the Cancer Therapy Evaluation Program.

PI-RADS® Category as a Predictor of Progression to Unfavorable Risk Prostate Cancer in Men on Active Surveillance.

PURPOSE: We identified baseline imaging and clinical characteristics of patients that may improve risk stratification among patients being evaluated for active surveillance. MATERIALS AND METHODS: From July 2007 to January 2020 patients referred to our institution for prostate cancer were evaluated and those who remained on active surveillance were identified. Men underwent multiparametric magnetic resonance imaging upon entry into our active surveillance protocol during which baseline demographic and imaging data were documented. Patients were then followed and outcomes, specifically progression to Gleason Grade Group (GG)3 or greater disease, were recorded. RESULTS: Of the men placed on active surveillance 344 had at least 1 PI-RADS score documented. For those with an index lesion PI-RADS category of 5, 33% (17/51) had progression to GG3 or greater on active surveillance with a median time to progression of 31 months. When comparing the progression-free survival times and progression rates in each category, PI-RADS category was found to be associated with progression to GG3 or greater on active surveillance (p <0.01). On univariable analysis factors associated with progression included an index lesion PI-RADS category of 5, prostate specific antigen density and the size of the largest lesion. On multivariable analysis only PI-RADS category of 5 and prostate specific antigen density were associated with progression on active surveillance. CONCLUSIONS: PI-RADS lesion categories at baseline multiparametric magnetic resonance imaging during active surveillance enrollment can be used to predict cancer progression to GG3 or greater on active surveillance. This information, along with other clinical data, can better assist urologists in identifying and managing patients appropriate for active surveillance.

Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study.

BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) provides guidelines for risk stratification of lesions detected on multiparametric MRI (mpMRI) of the prostate but suffers from high intra/interreader variability. PURPOSE: To develop an artificial intelligence (AI) solution for PI-RADS classification and compare its performance with an expert radiologist using targeted biopsy results. STUDY TYPE: Retrospective study including data from our institution and the publicly available ProstateX dataset. POPULATION: In all, 687 patients who underwent mpMRI of the prostate and had one or more detectable lesions (PI-RADS score >1) according to PI-RADSv2. FIELD STRENGTH/SEQUENCE: T2 -weighted, diffusion-weighted imaging (DWI; five evenly spaced b values between b = 0-750 s/mm2 ) for apparent diffusion coefficient (ADC) mapping, high b-value DWI (b = 1500 or 2000 s/mm2 ), and dynamic contrast-enhanced T1 -weighted series were obtained at 3.0T. ASSESSMENT: PI-RADS lesions were segmented by a radiologist. Bounding boxes around the T2 /ADC/high-b value segmentations were stacked and saved as JPEGs. These images were used to train a convolutional neural network (CNN). The PI-RADS scores obtained by the CNN were compared with radiologist scores. The cancer detection rate was measured from a subset of patients who underwent biopsy. STATISTICAL TESTS: Agreement between the AI and the radiologist-driven PI-RADS scores was assessed using a kappa score, and differences between categorical variables were assessed with a Wald test. RESULTS: For the 1034 detection lesions, the kappa score for the AI system vs. the expert radiologist was moderate, at 0.40. However, there was no significant difference in the rates of detection of clinically significant cancer for any PI-RADS score in 86 patients undergoing targeted biopsy (P = 0.4-0.6). DATA CONCLUSION: We developed an AI system for assignment of a PI-RADS score on segmented lesions on mpMRI with moderate agreement with an expert radiologist and a similar ability to detect clinically significant cancer. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection.

OBJECTIVE. The purpose of this study was to prospectively evaluate Prostate Imaging Reporting and Data and System version 2.1 (PI-RADSv2.1), which was released in March 2019 to update version 2.0, for prostate cancer detection with transrectal ultrasound-MRI fusion biopsy and 12-core systematic biopsy. SUBJECTS AND METHODS. This prospective study included 110 consecutively registered patients who underwent multiparametric MRI evaluated with PI-RADSv2.1 criteria followed by fusion biopsy and systematic biopsy between April and September 2019. Lesion-based cancer detection rates (CDRs) were calculated for prostate cancer (Gleason grade group, > 0) and clinically significant prostate cancer (Gleason grade group, > 1). RESULTS. A total of 171 lesions (median size, 1.1 cm) in 110 patients were detected and evaluated with PI-RADSv2.1. In 16 patients no lesion was detected, and only systematic biopsy was performed. Lesions were categorized as follows: PI-RADS category 1, 1 lesion; PI-RADS category 2, 34 lesions; PI-RADS category 3, 54 lesions; PI-RADS category 4, 52 lesions; and PI-RADS category 5, 30 lesions. Histopathologic analysis revealed prostate cancer in 74 of 171 (43.3%) lesions and clinically significant prostate cancer in 57 of 171 (33.3%) lesions. The CDRs of prostate cancer for PI-RADS 2, 3, 4, and 5 lesions were 20.0%, 24.1%, 51.9%, and 90.0%. The CDRs of clinically significant prostate cancer for PI-RADS 1, 2, 3, 4, and 5 lesions were 0%, 5.7%, 14.8%, 44.2%, and 80.0%. In 16 patients with normal multiparametric MRI findings (PI-RADS 1), the CDRs were 50.0% for PCa and 18.8% for clinically significant prostate cancer. CONCLUSION. This investigation yielded CDRs assessed with prospectively assigned PI-RADSv2.1 scores. CDRs increased with higher PI-RADSv2.1 scores. These results can be compared with previously published outcomes derived with PI-RADS version 2.0.

Prospective Evaluation of 18F-DCFPyL PET/CT in Detection of High-Risk Localized Prostate Cancer: Comparison With mpMRI.

OBJECTIVE. The purpose of this study was to assess the utility of PET with (2S)-2-[[(1S)-1-carboxy-5-[(6-(18F)fluoranylpyridine-3-carbonyl)amino]pentyl]carbamoylamino]pentanedioic acid (18F-DCFPyL), a prostate-specific membrane antigen (PSMA)-targeted radiotracer, in the detection of high-risk localized prostate cancer as compared with multiparametric MRI (mpMRI). SUBJECTS AND METHODS. This HIPAA-compliant prospective study included 26 consecutive patients with localized high-risk prostate cancer (median age, 69.5 years [range, 53-81 years]; median prostate-specific antigen [PSA] level, 18.88 ng/mL [range, 1.03-20.00 ng/mL]) imaged with 18F-DCFPyL PET/CT and mpMRI. Images from PET/CT and mpMRI were evaluated separately, and suspicious areas underwent targeted biopsy. Lesion-based sensitivity and tumor detection rate were compared for PSMA PET and mpMRI. Standardized uptake value (SUV) and PSMA PET parameters were correlated with histopathology score, and uptake in tumor was compared with that in nonmalignant tissue. On a patient level, SUV and PSMA tumor volume were correlated with PSA density. RESULTS. Forty-four tumors (one in Gleason grade [GG] group 1, 12 in GG group 2, seven in GG group 3, nine in GG group 4, and 15 in GG group 5) were identified at histopathology. Sensitivity and tumor detection rate of 18F-DCFPyL PET/CT and mpMRI were similar (PET/CT, 90.9% and 80%; mpMRI, 86.4% and 88.4%; p = 0.58/0.17). Total lesion PSMA and PSMA tumor volume showed a relationship with GG (τ = 0.27 and p = 0.08, τ = 0.30 and p = 0.06, respectively). Maximum SUV in tumor was significantly higher than that in nonmalignant tissue (p < 0.05). Tumor burden density moderately correlated with PSA density (r = 0.47, p = 0.01). Five true-positive tumors identified on 18F-DCFPyL PET/CT were not identified on mpMRI. CONCLUSION. In patients with high-risk prostate cancer, 18F-DCFPyL PET/CT is highly sensitive in detecting intraprostatic tumors and can detect tumors missed on mpMRI. Measured uptake is significantly higher in tumor tissue, and PSMA-derived tumor burden is associated with severity of disease.

Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI.

OBJECTIVE. The purpose of this study was to evaluate in a multicenter dataset the performance of an artificial intelligence (AI) detection system with attention mapping compared with multiparametric MRI (mpMRI) interpretation in the detection of prostate cancer. MATERIALS AND METHODS. MRI examinations from five institutions were included in this study and were evaluated by nine readers. In the first round, readers evaluated mpMRI studies using the Prostate Imaging Reporting and Data System version 2. After 4 weeks, images were again presented to readers along with the AI-based detection system output. Readers accepted or rejected lesions within four AI-generated attention map boxes. Additional lesions outside of boxes were excluded from detection and categorization. The performances of readers using the mpMRI-only and AI-assisted approaches were compared. RESULTS. The study population included 152 case patients and 84 control patients with 274 pathologically proven cancer lesions. The lesion-based AUC was 74.9% for MRI and 77.5% for AI with no significant difference (p = 0.095). The sensitivity for overall detection of cancer lesions was higher for AI than for mpMRI but did not reach statistical significance (57.4% vs 53.6%, p = 0.073). However, for transition zone lesions, sensitivity was higher for AI than for MRI (61.8% vs 50.8%, p = 0.001). Reading time was longer for AI than for MRI (4.66 vs 4.03 minutes, p < 0.001). There was moderate interreader agreement for AI and MRI with no significant difference (58.7% vs 58.5%, p = 0.966). CONCLUSION. Overall sensitivity was only minimally improved by use of the AI system. Significant improvement was achieved, however, in the detection of transition zone lesions with use of the AI system at the cost of a mean of 40 seconds of additional reading time.