Endometrial cancer (EC) incidence and mortality have been steadily rising globally over recent decades. The introduction of advanced molecular technologies, such as next-generation sequencing (NGS) alongside the FIGO 2023 classification, presents opportunities for refined diagnostics and risk stratification. This study aimed to analyze differences in EC classification among oncology centers in southeastern Poland.
View Article and Find Full Text PDFPurpose: Targeted prostate biopsies are increasingly being performed by urologists in the United States including those in the Pennsylvania Urologic Regional Collaborative, a physician-led data-sharing and quality improvement collaborative. To evaluate the performance of MRI guided fusion needle prostate biopsies in the collaborative, we analyzed the variability by practice in rates of detection of clinically significant prostate cancer and patient characteristics associated with detection of clinically significant prostate cancer.
Methods: We analyzed 857 first-time MRI fusion biopsy procedures performed at five practices (minimum 20 procedures) between 2015 and 2019.
Background: Myocardial infarction (MI) significantly contributes to the global mortality rate, often leading to heart failure (HF) due to left ventricular remodeling. Key factors in the pathomechanism of HF include nitrosative/oxidative stress, inflammation, and endoplasmic reticulum (ER) stress. Furthermore, while a high-fat diet (HFD) is known to exacerbate post-MI cardiac remodeling, its impact on these critical factors in the context of HF is not as well understood.
View Article and Find Full Text PDFImaging for prostate cancer defines the extent of disease. Guidelines recommend against imaging low-risk prostate cancer patients with a computed tomography (CT) scan or bone scan due to the low probability of metastasis. We reviewed imaging performed for men diagnosed with low-risk prostate cancer across the Pennsylvania Urologic Regional Collaborative (PURC), a physician-led data sharing and quality improvement collaborative.
View Article and Find Full Text PDFHistoLens is an open-source graphical user interface developed using MATLAB AppDesigner for visual and quantitative analysis of histological datasets. HistoLens enables users to interrogate sets of digitally annotated whole slide images to efficiently characterize histological differences between disease and experimental groups. Users can dynamically visualize the distribution of 448 hand-engineered features quantifying color, texture, morphology, and distribution across microanatomic sub-compartments.
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