Prostate Cancer

Interpretable machine learning for individualized survival prediction in node-positive, non-metastatic prostate cancer: a population-based study.

BACKGROUND: Prostate cancer with regional lymph node involvement but no distant metastasis (N1M0) has heterogeneous prognosis. This study aimed to develop and validate an interpretable machine learning model for predicting cancer-specific survival (CSS). METHODS: Data from 18,287 N1M0 patients (2000-2022) in the SEER database were divided into training (n = 4780), internal testing (n = 1193), and ...

Deep learning auto-contouring of target and organs-at-risk on post-catheter implant CT images for prostate HDR brachytherapy.

BACKGROUND: Accurate delineation of the prostate and surrounding organs-at-risk (OARs) is essential for HDR prostate brachytherapy. Manual contouring on post-catheter CT images is time-consuming and prone to variability due to artifacts and anatomical deformation from the implanted brachytherapy catheters. PURPOSE: To develop and validate a 3D deep learning autosegmentation model for prostate and ...

Machine learning-based classification model to distinguish tumor and tumor-free samples using synthetic plasma proteomic dataset.

BACKGROUND: Tumor-Specific Peptides (TSPs) and Tumor-associated Overexpressed Proteins (TOPs) are promising biomarkers for cancer diagnosis and monito...

Apparent diffusion coefficient radiomics for differentiating benign and malignant PI-RADS 3-5 prostate lesions: external validation.

PURPOSE: To develop and externally validate a simplified apparent diffusion coefficient (ADC)-based MRI radiomics model for differentiating benign and...

Multimodal artificial intelligence in prostate cancer: integrating multiparametric MRI with clinicopathological, molecular, and functional imaging data.

Multimodal artificial intelligence (AI) is reshaping prostate cancer imaging by moving beyond MRI-only algorithms toward models that integrate multipa...

Automatic treatment planning using reinforcement learning for high-dose-rate prostate brachytherapy.

Purpose.In high-dose-rate (HDR) prostate brachytherapy procedures, needle placement solely relies on physician experience. We investigated the feasibi...

A comprehensive framework for multi-class prostate cancer classification using biparametric MRI: a multi-center retrospective study.

OBJECTIVES: Accurate pre-biopsy or preoperative diagnosis and risk stratification of prostate cancer remain challenging. This study aimed to develop a...

Accurate and noninvasive prostate cancer detection using plasma-derived extracellular vesicle RNA.

Prostate cancer (PCa) is the most commonly diagnosed noncutaneous malignancy in men and a leading cause of cancer-related death worldwide. Its clinica...

Machine learning-based clinical models for prediction of urinary incontinence after robot-assisted laparoscopic radical prostatectomy.

OBJECTIVE: To investigate risk factors for urinary incontinence (UI) after robot-assisted laparoscopic radical prostatectomy (RARP) using interpretabl...

Artificial Intelligence Versus Conventional Methods for NCCN Risk Stratification in Localized Prostate Cancer (2020-2025): A Systematic Review.

BACKGROUND AND OBJECTIVE: Accurate risk stratification in localized prostate cancer is essential for guiding treatment decisions. Conventional Nationa...

A serum-clinical composite model for prostate cancer diagnosis: multicenter validation and CRISPR/Cas13a-based detection.

BACKGROUND: Avoidable prostate biopsies remain a persistent weakness of prostate specific antigen (PSA)- and imaging-led prostate cancer (PCa) diagnos...

Evaluating Risk Factors Associating With Late Recurrence After Low-Dose-Rate Brachytherapy for Prostate Cancer Using Machine Learning.

BACKGROUND: The Phoenix definition is widely used to define biochemical recurrence (BCR) after radiation therapy for prostate cancer; however, a defin...

Development of a predictive marker panel for the individualised bDMARD therapy of psoriatic arthritis: protocol for a prospective observational study (Integrate-PsA).

INTRODUCTION: Psoriatic arthritis is a chronic inflammatory disease that can affect the axial skeleton as well as the joints and enthesis. Following t...

fAI-BRO: a multimodal AI decision-support system to address diagnostic delay in fibromyalgia syndrome.

OBJECTIVE: To evaluate the diagnostic accuracy and patient acceptability of fAI-BRO (Fibromyalgia AI-Based Rheumatology Observer), a multimodal artifi...

Response to letter to editor "Radiomics-based machine-learning approach to predict response at brachytherapy using pretreatment magnetic resonance imaging in locally advanced cervical cancer".

Clinical-Radiomics Model Based on T2-Weighted and Diffusion-Weighted Magnetic Resonance Images on Predicting "Double Gray Zone" Prostate Cancer of PSA and PI-RADS.

OBJECTIVES: This study aimed to develop a clinical-radiomics model based on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) to improve...

Artificial intelligence-enabled MRI surveillance of prostate cancer: integrating PRECISE v2, PI-QUAL, and longitudinal biomarkers-a narrative review.

Active surveillance (AS) is widely used for men with low-risk and selected favorable intermediate-risk prostate cancer, but pathways remain heterogene...

Intraoperative technological advances and new frontiers in precision glioma surgery.

BACKGROUND: Diffuse gliomas remain among the most surgically challenging tumors, characterized by their infiltrative nature, proximity to eloquent bra...

Evolving role of biomarkers beyond prostate‑specific antigen in refining prostate cancer screening: From blood‑based tests to urinary and genetic markers (Review).

Prostate‑specific antigen (PSA) screening reduces prostate cancer (PCa) mortality but is limited by overdiagnosis and poor specificity for clinically ...

Clinical Variable-Based Machine Learning for Predicting Early mCRPC Using Exclusively Clinical Variables: Development and Multicenter External Validation.

BACKGROUND AND OBJECTIVE: Metastatic hormone-sensitive prostate cancer (mHSPC) exhibits heterogeneous progression patterns, with early progression to ...