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BACKGROUND AND AIMS: Successful aging is a worldwide aim, but its related factors and instruments of measurement are currently hotly debated. To investigate the relationship between muscle strength and functional capacity, and its association with successful aging. METHODS: A population-based cross-sectional study was performed in Mataró (Spain). Included in the study were 313 subjects (153 men, 160 women) aged 70 years and over. Physical and cognitive functions were assessed, as well as muscle strength, nutritional status, lifestyle factors, and associated morbidities. RESULTS: A state of successful aging (SA), defined as optimal functional and cognitive capacities with absence of cancer, stroke, cardiovascular or pulmonary chronic diseases, was found in 20% of women and 32% of men. SA was associated with higher muscle strength in comparison with the non-SA condition. Muscle strength measurements were higher in men, and decreased with age, poor balance, decreased functional capacity, and impaired cognitive status. It was also associated with higher academic level, regular exercise, and nutritional status in both genders. Multivariate analysis showed that independent variables related to SA were: hand grip, arthrosis, deafness and unipodal balance test, but not age or gender. CONCLUSIONS: Muscle strength is positively associated with the successful aging condition, and may be one of its functional links, reflecting the integrated health status of old men and women. The systematic inclusion of the measurement of muscle strength may be helpful in clinical evaluation of the elderly. [ABSTRACT FROM AUTHOR]

Purpose To evaluate the performance of an artificial intelligence (AI) model in detecting overall and clinically significant prostate cancer (csPCa)-positive lesions on paired external and in-house biparametric MRI (bpMRI) scans and assess performance differences between each dataset. Materials and Methods This single-center retrospective study included patients who underwent prostate MRI at an external institution and were rescanned at the authors' institution between May 2015 and May 2022. A genitourinary radiologist performed prospective readouts on in-house MRI scans following the Prostate Imaging Reporting and Data System (PI-RADS) version 2.0 or 2.1 and retrospective image quality assessments for all scans. A subgroup of patients underwent an MRI/US fusion-guided biopsy. A bpMRI-based lesion detection AI model previously developed using a completely separate dataset was tested on both MRI datasets. Detection rates were compared between external and in-house datasets with use of the paired comparison permutation tests. Factors associated with AI detection performance were assessed using multivariable generalized mixed-effects models, incorporating features selected through forward stepwise regression based on the Akaike information criterion. Results The study included 201 male patients (median age, 66 years [IQR, 62-70 years]; prostate-specific antigen density, 0.14 ng/mL 2 [IQR, 0.10-0.22 ng/mL 2 ]) with a median interval between external and in-house MRI scans of 182 days (IQR, 97-383 days). For intraprostatic lesions, AI detected 39.7% (149 of 375) on external and 56.0% (210 of 375) on in-house MRI scans ( P < .001). For csPCa-positive lesions, AI detected 61% (54 of 89) on external and 79% (70 of 89) on in-house MRI scans ( P < .001). On external MRI scans, better overall lesion detection was associated with a higher PI-RADS score (odds ratio [OR] = 1.57; P = .005), larger lesion diameter (OR = 3.96; P < .001), better diffusion-weighted MRI quality (OR = 1.53; P = .02), and fewer lesions at MRI (OR = 0.78; P = .045). Better csPCa detection was associated with a shorter MRI interval between external and in-house scans (OR = 0.58; P = .03) and larger lesion size (OR = 10.19; P < .001). Conclusion The AI model exhibited modest performance in identifying both overall and csPCa-positive lesions on external bpMRI scans. Keywords: MR Imaging, Urinary, Prostate Supplemental material is available for this article. © RSNA, 2024.

von Hippel-Lindau (VHL) is an autosomal-dominant hereditary tumour susceptibility disease associated with pathogenic germline variants in the VHL tumour suppressor gene. VHL patients are at increased risk of developing multiple benign and malignant tumours. Current CLIA-based genetic tests demonstrate a very high detection rate of germline VHL variants in patients with clinical manifestations of VHL. In this report, we describe a large family with canonical VHL manifestations, for which no germline alteration had been detected by conventional germline testing. We identified a novel 291 kb chromosomal inversion involving chromosome 3p in affected family members. This inversion disrupts the VHL gene between exon 2 and exon 3 and is thereby responsible for the disease observed in this family., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Rationale and Objectives: The increasing use of focal therapy (FT) in localized prostate cancer (PCa) management requires a standardized MRI interpretation system to detect recurrent clinically significant PCa (csPCa). This pilot study evaluates the novel Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) and compares its performance to that of the Prostate Imaging after Focal Ablation (PI-FAB) system., Materials and Methods: This retrospective study included 38 patients who underwent primary FT for localized PCa, with follow-up multiparametric MRI (mpMRI) and biopsy. Two radiologists assessed the mpMRIs using both PI-FAB and TARGET independently. Diagnostic performance metrics and area under the receiver operating characteristic curve (AUC) were calculated. Inter-reader and intrareader agreement were assessed using Cohen's κ and Kendall's τ., Results: 14 patients had recurrent csPCa. PI-FAB showed high sensitivity (92.9% for both readers) and NPV (reader 1: 93.8%, reader 2: 92.9%) but moderate specificity (reader 1: 62.5%, reader 2: 54.2%). TARGET demonstrated lower sensitivity for one reader (reader 1: 78.6%, reader 2: 92.9%) but higher specificity (reader 1: 79.2%, reader 2: 62.5%) for both readers. Both systems displayed moderate inter-reader agreement (κ = 0.56 for PI-FAB, 0.57 for TARGET)., Conclusion: PI-FAB and TARGET exhibit similar performances in post-FT MRI. While PI-FAB had consistently high sensitivity, TARGET offered higher specificity for one reader. Moderate agreement levels demonstrate the viability of these systems in clinical settings and a promise for improvement., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: B. J. Wood receives support as part of a cooperative research and development agreement (CRADA) between NIH and Philips Healthcare, receives royalties from NIH related to a licensing agreement with Philips Healthcare, and is party to patents or potential patents related to this work. P. L. Choyke receives royalties for MRI/ultrasound fusion biopsy patents licensed to Philips Medical. P. A. Pinto receives royalties from NIH related to a Philips licensing agreement and support as part of a CRADA between NIH and Philips Healthcare. B. Turkbey receives support as part of a CRADA between NIH and NVDIA and between NIH and Philips Healthcare, receives royalties from NIH, and is party to patents or potential patents related to this work. The remaining authors declare that there are no other disclosures relevant to the subject matter of this article. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government., (Published by Elsevier Inc.)

Germplasm banking is a fundamental tool for the preservation of autochthonous breeds. Semen cryopreservation is effective for this task, but protocols are adapted to commercial species, and post-thawing sperm quality could be sensitive to environmental cues. We compared the post-thawing sperm quality in doses from the CBA-SERIDA bank in northern Spain for the Asturiana de la Montaña (AM) and Asturiana de los Valles (AV) autochthonous cattle breeds. Doses from 23 AM and 16 AV bulls (ejaculates from at least three different seasons) were assessed for motility (computer-assisted sperm analysis), physiology and chromatin status (flow cytometry) after thawing and after 5 h at 38°C. Data were analysed using linear mixed-effects and cosinor models for seasonal and breed effects and by correlations with the association of sperm quality with temperature-humidity index (THI), considering the interval of spermatogenesis plus maturation. The breed affected sperm quality, with higher motility for AV and higher apoptotic ratio, mitochondrial activity, reactive oxygen species, DNA fragmentation and chromatin immaturity for AM. However, seasonality effects were minimal, and THI was not associated with sperm quality. In summary, the season seems to be a minor factor in the post-thawing quality of the AM and AV autochthonous breeds, well-adapted to their local environment., (© 2024 The Authors. Reproduction in Domestic Animals published by Wiley‐VCH GmbH.)

Rationale and Objectives: Extraprostatic extension (EPE) is well established as a significant predictor of prostate cancer aggression and recurrence. Accurate EPE assessment prior to radical prostatectomy can impact surgical approach. We aimed to utilize a deep learning-based AI workflow for automated EPE grading from prostate T2W MRI, ADC map, and High B DWI., Material and Methods: An expert genitourinary radiologist conducted prospective clinical assessments of MRI scans for 634 patients and assigned risk for EPE using a grading technique. The training set and held-out independent test set consisted of 507 patients and 127 patients, respectively. Existing deep-learning AI models for prostate organ and lesion segmentation were leveraged to extract area and distance features for random forest classification models. Model performance was evaluated using balanced accuracy, ROC AUCs for each EPE grade, as well as sensitivity, specificity, and accuracy compared to EPE on histopathology., Results: A balanced accuracy score of .390 ± 0.078 was achieved using a lesion detection probability threshold of 0.45 and distance features. Using the test set, ROC AUCs for AI-assigned EPE grades 0-3 were 0.70, 0.65, 0.68, and 0.55 respectively. When using EPE≥ 1 as the threshold for positive EPE, the model achieved a sensitivity of 0.67, specificity of 0.73, and accuracy of 0.72 compared to radiologist sensitivity of 0.81, specificity of 0.62, and accuracy of 0.66 using histopathology as the ground truth., Conclusion: Our AI workflow for assigning imaging-based EPE grades achieves an accuracy for predicting histologic EPE approaching that of physicians. This automated workflow has the potential to enhance physician decision-making for assessing the risk of EPE in patients undergoing treatment for prostate cancer due to its consistency and automation., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: B. J. Wood receives support as part of a cooperative research and development agreement (CRADA) between NIH and Philips Healthcare, receives royalties from NIH related to a licensing agreement with Philips Healthcare, and is party to patents or potential patents related to this work. P. L. Choyke receives royalties for MRI/ultrasound fusion biopsy patents licensed to Philips Medical. P. A. Pinto receives royalties from NIH related to a Philips licensing agreement and support as part of a CRADA between NIH and Philips Healthcare. B. Turkbey receives support as part of a CRADA between NIH and NVDIA and between NIH and Philips Healthcare, receives royalties from NIH, and is party to patents or potential patents related to this work. Jesse Tetreault: employee of NVIDIA Corporation. The remaining authors declare that there are no other disclosures relevant to the subject matter of this article. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government., (Published by Elsevier Inc.)

Purpose: Cabozantinib and nivolumab (CaboNivo) alone or with ipilimumab (CaboNivoIpi) have shown promising efficacy and safety in patients with metastatic urothelial carcinoma (mUC), metastatic renal cell carcinoma (mRCC), and rare genitourinary (GU) tumors in a dose-escalation phase I study. We report the final data analysis of the safety, overall response rate (ORR), progression-free survival (PFS), and overall survival (OS) of the phase I patients and seven expansion cohorts., Methods: This is an investigator-initiated, multicenter, phase I trial. CaboNivo doublet expansion cohorts included (1) mUC, (2) mRCC, and (3) adenocarcinoma of the bladder/urachal; CaboNivoIpi triplet expansion cohorts included (1) mUC, (2) mRCC, (3) penile cancer, and (4) squamous cell carcinoma of the bladder and other rare GU tumors (ClinicalTrials.gov identifier: NCT02496208)., Results: The study enrolled 120 patients treated with CaboNivo (n = 64) or CaboNivoIpi (n = 56), with a median follow-up of 49.2 months. In 108 evaluable patients (CaboNivo n = 59; CaboNivoIpi n = 49), the ORR was 38% (complete response rate 11%) and the median duration of response was 20 months. The ORR was 42.4% for mUC, 62.5% for mRCC (n = 16), 85.7% for squamous cell carcinoma of the bladder (n = 7), 44.4% for penile cancer (n = 9), and 50.0% for renal medullary carcinoma (n = 2). Grade ≥ 3 treatment-related adverse events occurred in 84% of CaboNivo patients and 80% of CaboNivoIpi patients., Conclusion: CaboNivo and CaboNivoIpi demonstrated clinical activity and safety in patients with multiple GU malignancies, especially clear cell RCC, urothelial carcinoma, and rare GU tumors such as squamous cell carcinoma of the bladder, small cell carcinoma of the bladder, adenocarcinoma of the bladder, renal medullary carcinoma, and penile cancer.

Objective: To assess impact of image quality on prostate cancer extraprostatic extension (EPE) detection on MRI using a deep learning-based AI algorithm., Materials and Methods: This retrospective, single institution study included patients who were imaged with mpMRI and subsequently underwent radical prostatectomy from June 2007 to August 2022. One genitourinary radiologist prospectively evaluated each patient using the NCI EPE grading system. Each T2WI was classified as low- or high-quality by a previously developed AI algorithm. Fisher's exact tests were performed to compare EPE detection metrics between low- and high-quality images. Univariable and multivariable analyses were conducted to assess the predictive value of image quality for pathological EPE., Results: A total of 773 consecutive patients (median age 61 [IQR 56-67] years) were evaluated. At radical prostatectomy, 23% (180/773) of patients had EPE at pathology, and 41% (131/318) of positive EPE calls on mpMRI were confirmed to have EPE. The AI algorithm classified 36% (280/773) of T2WIs as low-quality and 64% (493/773) as high-quality. For EPE grade ≥ 1, high-quality T2WI significantly improved specificity for EPE detection (72% [95% CI 67-76%] vs. 63% [95% CI 56-69%], P = 0.03), but did not significantly affect sensitivity (72% [95% CI 62-80%] vs. 75% [95% CI 63-85%]), positive predictive value (44% [95% CI 39-49%] vs. 38% [95% CI 32-43%]), or negative predictive value (89% [95% CI 86-92%] vs. 89% [95% CI 85-93%]). Sensitivity, specificity, PPV, and NPV for EPE grades ≥ 2 and ≥ 3 did not show significant differences attributable to imaging quality. For NCI EPE grade 1, high-quality images (OR 3.05, 95% CI 1.54-5.86; P < 0.001) demonstrated a stronger association with pathologic EPE than low-quality images (OR 1.76, 95% CI 0.63-4.24; P = 0.24)., Conclusion: Our study successfully employed a deep learning-based AI algorithm to classify image quality of prostate MRI and demonstrated that better quality T2WI was associated with more accurate prediction of EPE at final pathology., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Drug repurposing aims to find new therapeutic applications for existing drugs in the pharmaceutical market, leading to significant savings in time and cost. The use of artificial intelligence and knowledge graphs to propose repurposing candidates facilitates the process, as large amounts of data can be processed. However, it is important to pay attention to the explainability needed to validate the predictions. We propose a general architecture to understand several explainable methods for graph completion based on knowledge graphs and design our own architecture for drug repurposing. We present XG4Repo (eXplainable Graphs for Repurposing), a framework that takes advantage of the connectivity of any biomedical knowledge graph to link compounds to the diseases they can treat. Our method allows methapaths of different types and lengths, which are automatically generated and optimised based on data. XG4Repo focuses on providing meaningful explanations to the predictions, which are based on paths from compounds to diseases. These paths include nodes such as genes, pathways, side effects, or anatomies, so they provide information about the targets and other characteristics of the biomedical mechanism that link compounds and diseases. Paths make predictions interpretable for experts who can validate them and use them in further research on drug repurposing. We also describe three use cases where we analyse new uses for Epirubicin, Paclitaxel, and Predinisone and present the paths that support the predictions., (© 2024. The Author(s).)

Introduction: Renal cell carcinoma is one of the ten more common malignant tumors worldwide, with a high incidence and mortality rate. Kidney cancer frequently presents at an advanced stage, and it is almost invariably fatal. Much progress has been made in identifying molecular targets for therapy in the hope of improving survival rates, but still, we have no good markers for early detection or progression of the disease. Von Hippel Lindau syndrome (VHL) is an autosomal dominant cancer hereditary syndrome in which affected individuals are at risk of developing bilateral and multifocal renal cell carcinomas (RCC) as well as other tumors. These patients provide an ideal platform to investigate the potential of urinary exosomal miRNA biomarkers in the early development of ccRCC, as these patients are regularly imaged and tumors are actively monitored until the tumor reaches 3 cm before surgical excision. This allows for pre- and post-surgical urine collection and comparison to excised tumor tissues. Studying different biomarkers in urine can provide comprehensive molecular profiling available to patients and physicians and can be a great source of additional tumor genetic information., Methods: Pre- and postoperative urine samples were obtained from a cohort of VHL patients undergoing surveillance and surgical excision of ccRCCs, and exosomes were extracted. MicroRNA-Seq analysis was performed on miRNA extracted from both urine-derived exosomes and FFPE material from excised ccRCCs., Results: MicroRNA-Seq analysis highlighted a significant difference in the urinary exosome-derived miRNA expression profiles between VHL patients and normal control individuals. This included decreased expression of the miR-320 family, such as miR-320a, known to be decreased in sporadic ccRCC and suppressed by the HIF1α transcription factor activated by the loss of the VHL gene. MiR-542-5p represented a potential marker of VHL-associated ccRCC that was lowly expressed in normal control urinary exosomes, significantly increased in the preoperative urinary exosomes of tumor-bearing VHL patients, and subsequently reduced to normal levels of expression after tumor excision. In concordance with this, the expression of miR-542-5p was increased in the VHL-associated ccRCC in comparison to the normal kidney., Conclusions: This study shows the potential for miRNA profiling of exosomes from readily available biofluids to both distinguish VHL patient urine from normal control urine microRNAs and to provide biomarkers for the presence of VHL syndrome-associated ccRCC. Further validation studies are necessary to demonstrate the utility of urinary exosome-derived miRNAs as biomarkers in kidney cancer.

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., (© 2023 International Society for Magnetic Resonance in Medicine. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Competing Interests: The authors declare no conflict of interest.

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.

Introduction: Nosocomial infectious ventriculitis caused by multidrug-resistant (MDR) Gram-negative bacilli associated with external ventricular drainage (EVD) placement poses a significant mortality burden and hospital costs., Objectives: This study aims to analyze the characteristics, ventriculitis evolution, treatment, and outcomes of patients with ventriculitis due to MDR Gram-negative bacilli associated with EVD placement., Methods: A retrospective cohort study focusing on patients with nosocomial infection caused by MDR Gram-negative bacilli while on EVD was conducted from 2019 to 2022. Medical, laboratory, and microbiological records were collected. The antibiotic resistance of the Gram-negative bacilli isolated in the cerebrospinal fluid (CSF) of patients was analyzed. The risk factors were identified using univariate risk models and were analyzed using survival curves (Cox regression). An adjusted Cox proportional hazards model was also constructed., Results: Among 530 patients with suspected EVD-associated ventriculitis, 64 patients with isolation of Gram-negative bacilli in CSF were included. The estimated mortality was 78.12%. Hemorrhages (intracranial, subarachnoid, and intraventricular) were observed in 69.8% of patients. Acinetobacter baumannii, Klebsiella pneumoniae , and Pseudomonas aeruginosa were the most frequently isolated bacilli. In the univariate analysis, significant risk factors for mortality included arterial hypertension, a Glasgow Coma Scale (GCS) score of ≤ 8, invasive mechanical ventilation (IMV) upon hospital admission and during hospitalization, septic shock, and ineffective treatment. The adjusted Cox proportional hazards model revealed that septic shock (HR = 3.3, 95% CI = 1.5-7.2; p = 0.003) and ineffective treatment (HR = 3.2, 1.6-6.5, 0.001) were significant predictors. A high resistance to carbapenems was found for A. baumannii (91.3%) and P. aeruginosa (80.0%). Low resistance to colistin was found for A. baumannii (4.8%) and P. aeruginosa (12.5%)., Conclusion: Ineffective treatment was an independent hazard factor for death in patients with ventriculitis caused by MDR Gram-negative bacilli associated with EVD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Corona-Nakamura, Arias-Merino, Ávila-Esparza, Tolentino-Corona, Cañedo-Castañeda, Flores-Salinas, Corona-Macías and Vázquez-Arias.)

This is the second article in a two-part series published in this journal, in which we examine the histopathological characteristics, as well as the differential diagnosis, of the main entities that present as cystic and pseudocystic structures in cutaneous biopsy. In this second article, we address ciliated cutaneous cysts, branchial cysts, Bartholin's cysts, omphalomesenteric cysts, thymic cysts, thyroglossal duct cysts, synovial cysts, and median raphe cysts, as well as mucocele, ganglion, and auricular and digital myxoid pseudocysts., (Copyright © 2024. Publicado por Elsevier España, S.L.U.)

Background and Objective: Focal therapy (FT) is increasingly recognized as a promising approach for managing localized prostate cancer (PCa), notably reducing treatment-related morbidities. However, post-treatment anatomical changes present significant challenges for surveillance using current imaging techniques. This study aimed to evaluate the inter-reader agreement and efficacy of the Prostate Imaging after Focal Ablation (PI-FAB) scoring system in detecting clinically significant prostate cancer (csPCa) on post-FT multiparametric magnetic resonance imaging (mpMRI)., Methods: A retrospective cohort study was conducted involving patients who underwent primary FT for localized csPCa between 2013 and 2023, followed by post-FT mpMRI and a prostate biopsy. Two expert genitourinary radiologists retrospectively evaluated post-FT mpMRI using PI-FAB. The key measures included inter-reader agreement of PI-FAB scores, assessed by quadratic weighted Cohen's kappa ( κ ), and the system's efficacy in predicting in-field recurrence of csPCa, with a PI-FAB score cutoff of 3. Additional diagnostic metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy were also evaluated., Key Findings and Limitations: Scans from 38 patients were analyzed, revealing a moderate level of agreement in PI-FAB scoring ( κ  = 0.56). Both radiologists achieved sensitivity of 93% in detecting csPCa, although specificity, PPVs, NPVs, and accuracy varied., Conclusions and Clinical Implications: The PI-FAB scoring system exhibited high sensitivity with moderate inter-reader agreement in detecting in-field recurrence of csPCa. Despite promising results, its low specificity and PPV necessitate further refinement. These findings underscore the need for larger studies to validate the clinical utility of PI-FAB, potentially aiding in standardizing post-treatment surveillance., Patient Summary: Focal therapy has emerged as a promising approach for managing localized prostate cancer, but limitations in current imaging techniques present significant challenges for post-treatment surveillance. The Prostate Imaging after Focal Ablation (PI-FAB) scoring system showed high sensitivity for detecting in-field recurrence of clinically significant prostate cancer. However, its low specificity and positive predictive value necessitate further refinement. Larger, more comprehensive studies are needed to fully validate its clinical utility.

Cystic structures represent one of the most common findings in dermatopathology. These encompass both cystic tumors and pseudocysts resulting from the accumulation of certain substances, such as mucin. In a two-part series (of which this is the first part), we have reviewed the principal types of cysts and pseudocysts that may be observed in cutaneous biopsies, examining their histopathological features and primary differential diagnoses. This first part encompasses infundibular cysts, eruptive dermoid cysts, pigmented follicular cysts, pilonidal cysts, tricholemmal cysts, milium cysts, hybrid cysts, bronchogenic cysts, as well as steatocystoma, hydrocystoma, and comedones., (Copyright © 2023 Sociedad Española de Anatomía Patológica. Publicado por Elsevier España, S.L.U. All rights reserved.)

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/mL 2 ). 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.

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.

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., (Published 2023. This article is a U.S. Government work and is in the public domain in the USA.)

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., (Published by Oxford University Press 2023.)

Objective: To evaluate a biparametric MRI (bpMRI)-based artificial intelligence (AI) model for the detection of local prostate cancer (PCa) recurrence in patients with radiotherapy history., Materials and Methods: This study included post-radiotherapy patients undergoing multiparametric MRI and subsequent MRI/US fusion-guided and/or systematic biopsy. Histopathology results were used as ground truth. The recurrent cancer detection sensitivity of a bpMRI-based AI model, which was developed on a large dataset to primarily identify lesions in treatment-naïve patients, was compared to a prospective radiologist assessment using the Wald test. Subanalysis was conducted on patients stratified by the treatment modality (external beam radiation treatment [EBRT] and brachytherapy) and the prostate volume quartiles., Results: Of the 62 patients included (median age = 70 years; median PSA = 3.51 ng/ml; median prostate volume = 27.55 ml), 56 recurrent PCa foci were identified within 46 patients. The AI model detected 40 lesions in 35 patients. The AI model performance was lower than the prospective radiology interpretation (Rad) on a patient-(AI: 76.1% vs. Rad: 91.3%, p = 0.02) and lesion-level (AI: 71.4% vs. Rad: 87.5%, p = 0.01). The mean number of false positives per patient was 0.35 (range: 0-2). The AI model performance was higher in EBRT group both on patient-level (EBRT: 81.5% [22/27] vs. brachytherapy: 68.4% [13/19]) and lesion-level (EBRT: 79.4% [27/34] vs. brachytherapy: 59.1% [13/22]). In patients with gland volumes >34 ml (n = 25), detection sensitivities were 100% (11/11) and 94.1% (16/17) on patient- and lesion-level, respectively., Conclusion: The reported bpMRI-based AI model detected the majority of locally recurrent prostate cancer after radiotherapy. Further testing including external validation of this model is warranted prior to clinical implementation., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Bradford J. Wood: Principal investigator on cooperative research and development agreement (CRADA) between National Institutes of Health (NIH) and Philips and CRADAs with industry partners unrelated to this work; travel support related to CRADAs; royalties from NIH related to Philips licensing agreement; patents planned, issued, or pending. Peter L. Choyke: Receives payment from royalties paid to the U.S. government for patents on MRI US fusion biopsy licensed to Philips Medical. Peter A. Pinto: Institutional CRADA with Philips; royalties from NIH related to Philips licensing agreement; NIH-related patents planned, issued, or pending (U.S. patent nos. 8 447 384 and 10 215 830). Baris Turkbey: CRADAs with NVIDIA and Philips; royalties from NIH; patents planned, issued, or pending in the field of artificial intelligence., (Published by Elsevier B.V.)

Objective: To report an initial experience with a novel, "fully" transperineal (TP) prostate fusion biopsy using an unconstrained ultrasound transducer placed on the perineal skin to guide biopsy needles inserted via a TP approach., Methods: Conventional TP prostate biopsies for detection of prostate cancer have been performed with transrectal ultrasound, requiring specialized hardware, imposing limitations on needle trajectory, and contributing to patient discomfort. Seventy-six patients with known or suspected prostate cancer underwent 78 TP biopsy sessions in an academic center between June 2018 and April 2022 and were included in this study. These patients underwent TP prostate fusion biopsy using a grid or freehand device with transrectal ultrasound as well as TP prostate fusion biopsy using TP ultrasound in the same session. Per-session and per-lesion cancer detection rates were compared for conventional and fully TP biopsies using Fisher exact and McNemar's tests., Results: After a refinement period in 30 patients, 92 MRI-visible prostate lesions were sampled in 46 subsequent patients, along with repeat biopsies in 2 of the 30 patients from the refinement period. Grade group ≥2 cancer was diagnosed in 24/92 lesions (26%) on conventional TP biopsy (17 lesions with grid, 7 with freehand device), and in 25/92 lesions (27%) on fully TP biopsy (P = 1.00), with a 73/92 (79%) rate of agreement for grade group ≥2 cancer between the two methods., Conclusion: Fully TP biopsy is feasible and may detect prostate cancer with detection rates comparable to conventional TP biopsy., Competing Interests: Declaration of Competing Interest Peter Pinto Institutional CRADA with Philips; royalties from NIH related to Philips licensing agreement; NIH-related patents planned, issued, or pending (U.S. patent nos. 8 447 384 and 10 215830). Peter L. Choyke Receives payment from royalties paid to the U.S. government for patents on MRI US fusion biopsy licensed to Philips Medical. Baris Turkbey CRADAs with NVIDIA and Philips; royalties from NIH; patents planned, issued, or pending in the field of artificial intelligence. Nicole Varble employee of Philips. Bradford J. Wood Principal investigator on cooperative research and development agreement (CRADA) between National Institutes of Health (NIH) and Philips and CRADAs with industry partners unrelated to this work; travel support related to CRADAs; royalties from NIH related to Philips licensing agreement; patents planned, issued, or pending. The other authors have no conflict of interest to declare., (Published by Elsevier Inc.)

Renal cell carcinoma with fibromyomatous stroma (RCCFMS) include ELOC/TCEB1 -mutated renal cell carcinoma (RCC) and those with TSC1/2 / MTOR alterations. Besides morphologic similarity, most of these tumors is known to be diffusely positive for carbonic anhydrase IX and cytokeratin 7 by immunohistochemistry. We previously showed strong and diffuse expression of GPNMB (glycoprotein nonmetastatic B) in translocation RCC and eosinophilic renal neoplasms with known TSC1/2/MTOR alterations. We retrospectively identified molecularly confirmed cases of TCEB1/ELOC -mutated RCC (7 tumors from 7 patients), and RCCFMS with alterations in TSC1/2/MTOR (6 tumors from 5 patients, 1 patient with tuberous sclerosis syndrome). In addition, we included 7 clear cell papillary renal cell tumors (CCPRCTs) and 8 clear cell RCC, as they can also present morphologic overlap with RCCFMS. Morphologically, RCCs with TSC1/2/MTOR alterations and those with TCEB1/ELOC mutations were indistinguishable and characterized by papillary, nested, or tubular architecture, with tumor cells with clear cytoplasm and low nuclear grade. By immunohistochemistry, cytokeratin 7 was positive in 5/7 (71%) of TCEB1/ELOC -mutated RCCs, 6/6 (100%) of RCCs with TSC1/2/mTOR alterations, and 7/7 (100%) of CCPRCTs ( P =not significant). Carbonic anhydrase IX was positive in 7/7 TCEB1/ELOC -mutated RCCs, 6/6 (100%) of RCCs with TSC1/2/MTOR alterations, and 7/7 (100%) of CCPRCTs ( P =NS). GPNMB was strongly and diffusely positive in all tumors with TSC1/2/MTOR alterations (6/6), while negative in all TCEB1/ELOC -mutated RCCs (0/6), or CCPRCTs (0/7) ( P =0.002). Two of 8 clear cell RCC showed focal weak staining, while 6/8 were negative. In conclusion, the results support the use of GPNMB to distinguish RCCFMS with TSC1/2/MTOR alterations from others with similar morphology., Competing Interests: Conflicts of Interest and Source of Funding: The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To characterize the clinical manifestations and genetic basis of a familial cancer syndrome in patients with lipomas and Birt-Hogg-Dubé-like clinical manifestations including fibrofolliculomas and trichodiscomas and kidney cancer., Methods: Genomic analysis of blood and renal tumor DNA was performed. Inheritance pattern, phenotypic manifestations, and clinical and surgical management were documented. Cutaneous, subcutaneous, and renal tumor pathologic features were characterized., Results: Affected individuals were found to be at risk for a highly penetrant and lethal form of bilateral, multifocal papillary renal cell carcinoma. Whole genome sequencing identified a germline pathogenic variant in PRDM10 (c.2029 T>C, p.Cys677Arg), which cosegregated with disease. PRDM10 loss of heterozygosity was identified in kidney tumors. PRDM10 was predicted to abrogate expression of FLCN, a transcriptional target of PRDM10, which was confirmed by tumor expression of GPNMB, a TFE3/TFEB target and downstream biomarker of FLCN loss. In addition, a sporadic papillary RCC from the TCGA cohort was identified with a somatic PRDM10 mutation., Conclusion: We identified a germline PRDM10 pathogenic variant in association with a highly penetrant, aggressive form of familial papillary RCC, lipomas, and fibrofolliculomas/trichodiscomas. PRDM10 loss of heterozygosity and elevated GPNMB expression in renal tumors indicate that PRDM10 alteration leads to reduced FLCN expression, driving TFE3-induced tumor formation. These findings suggest that individuals with Birt-Hogg-Dubé-like manifestations and subcutaneous lipomas, but without a germline pathogenic FLCN variant, should be screened for germline PRDM10 variants. Importantly, kidney tumors identified in patients with a pathogenic PRDM10 variant should be managed with surgical resection instead of active surveillance., Competing Interests: Declaration of Competing Interest The authors have nothing to declare., (Published by Elsevier Inc.)