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.

Evaluation of Surgical Improvement of Clinical Knowledge Ops (SICKO), an Interactive Training Platform.

Over the past two decades, there have been numerous attempts at using surgical simulation software for training purposes. There has been extensive prior success at using digital laparoscopic tools and virtual and augmented reality in strengthening specific surgical techniques, but clinical decision-making simulation has been limited to multiple choice question banks. Surgical Improvement of Clinical Knowledge Ops (SICKO) is a web-based educational application that takes users through various aspects of clinical decision-making in the field of surgery.App SpecsApp name: Surgical Improvement of Clinical Knowledge Ops (SICKO)App developer: James Lau M.D., Dana Lin M.D., Julia Park M.D.App website/URL*: http://med.stanford.edu/sm/archive/sicko/game/SICKOTitle.html App price: The website is free to use and has no microtransactionsCategory: educational, surgery simulation, clinical decision makingTags: web-based app, surgical simulation, learning, healthcare, gamificationWorks offline: noBrowsers: Works on Google Chrome, Mozilla Firefox, Safari, and Microsoft EdgeFDA approval: N/A*It should be noted that although the URL leads to a website with a tab header that reads "SEPTRIS," an older iteration of the game, the interactive experience is actually SICKO, which the user can clearly see from the webpage itself.Quick Review (1 star, lowest; 5 stars, highest)Overall Rating (1-5): 4.5Content (1-5): 5Usability (1-5): 5Design (1-5): 4Ratings Disclosure: The SICKO application was reviewed by two independent medical student authors of this article, as well as a resident physician. The reviews were done anonymously through each reviewer's own input and were blinded to each other's ratings until completion of the simulation. Each reviewer completed full renditions of the game from beginning to end to experience a situation where the patient expired, as well as one where the patient was saved in order to observe the full user experience. Both authors felt that the game was remarkably useful, with the only criticism being the simple graphical design of the application. No reviewers or authors of this paper have any connection to the software content or development team of SICKO.

Role of Race and Insurance Status in Prostate Cancer Diagnosis-to-Treatment Interval.

INTRODUCTION: Numerous studies have shown that both race and insurance status may affect prostate cancer (PCa) workup and treatment. Preliminary investigations have shown that these factors may be associated with treatment delays, which may indicate inequitable care and increase risk of tumor progression. This investigation aimed to assess whether race and insurance impacted the interval between multiparametric MRI (mpMRI)-to-biopsy, and biopsy-to-prostatectomy. MATERIALS AND METHODS: A single-institution analysis of 261 patients with recorded race and insurance data was performed using an Institutional Review Board-compliant database with information spanning from 2016 to 2022. Race was self-reported during intake, and insurance status was retrieved from the electronic medical record. Insurance was sub-divided into private, Medicare, and Medicaid. Diagnostic or treatment latency was defined as time between mpMRI-to-biopsy, or biopsy-to-surgery. RESULTS: Stratified by race, there was no difference in either latency period when comparing African American (AA) and white patients. Stratified by insurance status, there was no difference in time from mpMRI-to-biopsy (P = .50), but there was a significantly longer interval from biopsy-to-prostatectomy for patients with Medicaid insurance (P = .02). Patients with Medicaid waited on average 168 days to receive surgery, in contrast to 92 days for private and 87 for Medicare. Notably, 82% of Medicaid patients were AA. CONCLUSION: Insurance status, which is inherently linked to race and social determinants of health, portended a significantly increased interval between biopsy and surgery. Physicians should be aware of the relationship between insurance status and treatment delay, as well as its potential downstream consequences.

Urologic dermatology: a comprehensive foray into the noninfectious etiologies of balanitis.

Balanitis is classically defined as inflammation of the glans penis, often also encompassing the prepuce (balanoposthitis). Several investigations have found that a sizable proportion of urology clinic visits are due to balanitis or related complaints. Balanitis can have numerous complications, including severe pain, urethral stenosis, phimosis, sexual dysfunction, and if untreated, malignancy. Unfortunately, there is no recent or comprehensive review that describes the various etiologies, clinical workup, and treatments for balanitis. Herein this review, we attempt to provide the reader with a complete and updated guide to balanitis in an attempt to improve clinical outcomes.