Navigating Management of Localized Prostate Cancer in the Geriatric Population.

Prostate cancer (PCa) is highly prevalent among aging men and a significant contributor to global mortality. Balancing early detection and treatment of "clinically significant" disease with avoiding over-detection and overtreatment of slow-growing tumors is challenging, especially for elderly patients with competing health risks and potentially aggressive disease phenotypes. This review emphasizes the importance of individualized approaches for diagnosing and treating PCa in geriatric patients.

Student Urology Conference Increases Participant Knowledge of Urology Match and Confidence in Research.

Objective: To study the impact of a student-specific urology conference for students considering a career in urology. The first symposium specifically for medical students interested in urology was designed to provide an opportunity to present their research, explore urological subspecialties, and network with faculty members, residents, and other students.

Methods: Medical students and faculty at a US medical school organized the inaugural New England Student Urology Symposium (NESUS).

Lower urinary tract symptoms in elderly men: Considerations for prostate cancer testing.

Purpose: Both lower urinary tract symptoms (LUTS) and prostate cancer (PCa) are common in elderly men. While LUTS are generally due to a benign etiology, they may provoke an evaluation with prostate-specific antigen (PSA), which can lead to a cascade of further testing and possible overdiagnosis in patients with competing risks. There is limited patient and provider understanding of the relationship between LUTS and PCa risk, and a lack of clarity in how to evaluate these men to balance appropriate diagnosis of aggressive PCa with avoidance of overdiagnosis.

Consistent predictive ability of prostate-specific antigen density prediction model for clinically significant prostate cancer across age strata.

Background: Prebiopsy prostate-specific antigen density (PSAD) is a well-known predictor of clinically significant prostate cancer (csPCa). Since prostate-specific antigen (PSA) and prostate volume (PV) increase normally with aging, PSAD thresholds may vary. The purpose of the study was to determine if PSAD was predictive of csPCa in different age strata.

Optimising postoperative care: Same-day discharge after transurethral resection of the prostate.

Introduction: This study aims to assess the feasibility and safety of same-day discharge after transurethral resection of the prostate.

Materials And Methods: Five years of records were retrospectively analysed. Length of stay categorised patients into Groups 1 (same-day discharge) and 2 (standard-length discharge).

Harnessing artificial intelligence for prostate cancer management.

Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging enable the application of artificial intelligence (AI) in pathology.

Ductal, intraductal, and cribriform carcinoma of the prostate: Molecular characteristics and clinical management.

Prostatic acinar adenocarcinoma accounts for approximately 95% of prostate cancer (CaP) cases. The remaining 5% of histologic subtypes of CaP are known to be more aggressive and have recently garnered substantial attention. These histologic subtypes - namely, prostatic ductal adenocarcinoma (PDA), intraductal carcinoma of the prostate (IDC-P), and cribriform carcinoma of the prostate (CC-P) - typically exhibit distinct growth characteristics, genomic features, and unique oncologic outcomes.

Less qualitative multiparametric magnetic resonance imaging in prostate cancer can underestimate extraprostatic extension in higher grade tumors.

Background: Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for risk stratification and preoperative staging of prostate cancer. It remains unclear how Grade Group (GG) interacts with the ability of mpMRI to determine the presence of extraprostatic extension (EPE) on surgical pathology.

Methods: A retrospective review of a robotic assisted laparoscopic radical prostatectomy (RALP) database from 2016-2020 was performed.

"Shared decision-making" for prostate cancer screening: Is it a marker of quality preventative healthcare?

Background: "Shared decision-making" (SDM) is a cornerstone of prostate cancer (PCa) screening guidelines due to tradeoffs between clinical benefits and concerns for over-diagnosis and over-treatment. SDM requires effort by primary-care-providers (PCP) in an often busy clinical setting to understand patient preferences with the backdrop of patient risk factors. We hypothesized that SDM for PCa screening, given its prominence in guidelines and practical challenges, may be associated with quality preventative healthcare in terms of other appropriate cancer screening and encouragement of other preventative health behaviors.

The Surgical Management of Urolithiasis: A Review of the Literature.

The incidence of stone disease has increased significantly in the past 30 years, with a reported prevalence of 11% of the U.S. population in 2022, up from 9% in 2012 and 5.

Renal Imaging in Stone Disease: Which Modality to Choose?

Numerous imaging modalities are available to the provider when diagnosing or surveilling kidney stones. The decision to order one over the other can be nuanced and especially confusing to non-urologic practitioners. This manuscript reviews the main modalities used to image stones in the modern era - renal bladder ultrasound, Kidney Ureter Bladder plain film radiography (KUB), magnetic resonance imaging (MRI), and non-contrast computerized tomography (NCCT).

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report.

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2.

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans.

Background: The previous COVID-19 lung diagnosis system lacks both scientific validation and the role of explainable artificial intelligence (AI) for understanding lesion localization. This study presents a cloud-based explainable AI, the “COVLIAS 2.0-cXAI” system using four kinds of class activation maps (CAM) models.

Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine.

Radiogenomics, a combination of "Radiomics" and "Genomics," using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes.

COVLIAS 1.0 vs. MedSeg: An Artificial Intelligence Framework for Automated Lesion Segmentation in COVID-19 Lung Computed Tomography Scans.

Background: COVID-19 is a disease with multiple variants, and is quickly spreading throughout the world. It is crucial to identify patients who are suspected of having COVID-19 early, because the vaccine is not readily available in certain parts of the world. Methodology: Lung computed tomography (CT) imaging can be used to diagnose COVID-19 as an alternative to the RT-PCR test in some cases.

Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction-A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review.

Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients.

COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts.

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020-2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.