A5017537265- Renal cell carcinoma treatment
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Prostate Cancer Diagnosis and Treatment
- Renal and related cancers
- Prostate Cancer Treatment and Research
- Pediatric Urology and Nephrology Studies
- Radiology practices and education
- Radiation Dose and Imaging
- Urologic and reproductive health conditions
- Renal and Vascular Pathologies
- Advanced X-ray and CT Imaging
- Artificial Intelligence in Healthcare and Education
- Surgical Simulation and Training
- Esophageal and GI Pathology
- Pancreatic and Hepatic Oncology Research
- Urological Disorders and Treatments
- Anatomy and Medical Technology
- Appendicitis Diagnosis and Management
- Bladder and Urothelial Cancer Treatments
- Genetic and Kidney Cyst Diseases
- Adrenal and Paraganglionic Tumors
- Vascular anomalies and interventions
- Urinary and Genital Oncology Studies
- Cardiac, Anesthesia and Surgical Outcomes
Princess Margaret Cancer Centre
2024-2025
University Health Network
2018-2025
University of Toronto
2018-2025
Mount Sinai Hospital
2018-2025
Toronto General Hospital
2019-2025
Ottawa Hospital
2016-2025
Gujarat Kidney Foundation
2025
Women's College Hospital
2019-2025
Sinai Health System
2022-2025
York University
2025
Background ChatGPT is a powerful artificial intelligence large language model with great potential as tool in medical practice and education, but its performance radiology remains unclear. Purpose To assess the of on board-style examination questions without images to explore strengths limitations. Materials Methods In this exploratory prospective study performed from February 25 March 3, 2023, 150 multiple-choice designed match style, content, difficulty Canadian Royal College American...
Supplemental material is available for this article. See also the article by Bhayana et al and editorial Lourenco in issue.
Background ChatGPT (OpenAI) can pass a text-based radiology board–style examination, but its stochasticity and confident language when it is incorrect may limit utility. Purpose To assess the reliability, repeatability, robustness, confidence of GPT-3.5 GPT-4 (ChatGPT; OpenAI) through repeated prompting with examination. Materials Methods In this exploratory prospective study, 150 multiple-choice questions, previously used to benchmark ChatGPT, were administered default versions (GPT-3.5...
Background Structured radiology reports for pancreatic ductal adenocarcinoma (PDAC) improve surgical decision-making over free-text reports, but radiologist adoption is variable. Resectability criteria are applied inconsistently. Purpose To evaluate the performance of large language models (LLMs) in automatically creating PDAC synoptic from original and to explore categorizing tumor resectability. Materials Methods In this institutional review board–approved retrospective study, 180...
GPT-4 identified incidental adrenal nodules, pancreatic cystic lesions, and vascular calcifications in radiology reports with F1 scores of 1.00, 0.91, 0.99, respectively. The findings indicate a potential role for large language models to help improve recognition management imaging be applied flexibly medical context.
Large language models enabled accurate automated clinical histories for oncologic imaging that were markedly more complete than original requisition and preferred by radiologists image interpretation safety.
A hybrid large language model (LLM)–based application, optimized by combining LLM feature classification with deterministic elements, accurately assigned Ovarian-Adnexal Reporting and Data System MRI scores from adnexal lesion descriptions outperformed originally reporting radiologists.
To assess the ability of magnetic resonance imaging (MRI) to diagnose extraprostatic extension (EPE) in prostate cancer.With Institutional Review Board (IRB) approval, 149 men with 170 ≥0.5 mL tumors underwent preoperative 3T MRI followed by radical prostatectomy (RP) between 2012-2015. Two blinded radiologists (R1/R2) assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2, subjectively evaluated for presence EPE, measured tumor size, length capsular contact (LCC). A third...
See also the editorial by Forghani in this issue.
Accurate regional segmentation of the prostate boundaries on magnetic resonance (MR) images is a fundamental requirement before automated cancer diagnosis can be achieved. In this paper, we describe novel methodology to segment whole gland (WG), central (CG), and peripheral zone (PZ), where PZ + CG = WG, from T2W apparent diffusion coefficient (ADC) map MR images.We designed two similar models each made up U-Nets delineate CG, ADC images, separately. The U-Net, which modified version fully...
Background The limitation of diagnosis transition zone (TZ) prostate cancer (PCa) using subjective assessment multiparametric (mp) MRI with PI‐RADS v2 is related to overlapping features between cancers and stromal benign prostatic hyperplasia (BPH) nodules, particularly in small lesions. Purpose To evaluate modeling quantitative apparent diffusion coefficient (ADC), texture, shape logistic regression (LR) support vector machine (SVM) models for the PCa. Study Type Retrospective. Population...
Cystic renal masses are commonly encountered in clinical practice. In 2019, the Bosniak classification of cystic masses, originally developed for CT, underwent a major revision to incorporate MRI and is referred as Classification, version 2019. The proposed changes attempt (a) define (ie, tumors with less than 25% enhancing tissue) which should be applied; (b) emphasize specificity diagnosis cancers, thereby decreasing number benign indolent that unnecessarily treated or imaged further; (c)...
Diagnostic Accuracy of Unenhanced CT Analysis to Differentiate Low-Grade From High-Grade Chromophobe Renal Cell CarcinomaNicola Schieda1, Robert S. Lim2, Satheesh Krishna1, Matthew D. F. McInnes1, Trevor A. Flood2 and Rebecca E. Thornhill1Audio Available | Share
Penile cancer is one of the male‐specific cancers. Accurate pretreatment staging crucial due to a plethora treatment options currently available. The 8 th edition American Joint Committee on Cancer‐Tumor Node and Metastasis (AJCC‐TNM) revised for penile cancers, with invasion corpora cavernosa upstaged from T2 T3 urethra downstaged being not separately relevant. With this revision, MRI more relevant in local because accurate identifying cavernosa, while accuracy lower detection urethral...