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Performance of the FORD Versus Other Available Models for the Noninvasive Prediction of Pulmonary Hypertension in Patients with Interstitial Lung Disease.
Lung
January 2025
Advanced Lung Disease and Transplant Program, Inova Heart and Vascular Institute, Inova Fairfax Hospital, 3300 Gallows Road, Falls Church, VA, 22042, USA.
Purpose: Pulmonary hypertension (PH) is associated with morbidity and mortality in patients with interstitial lung disease (ILD). Several prediction models have been proposed to predict PH in ILD patients. We sought to discern how previously described prediction models perform in predicting PH in patients with ILD.
View Article and Find Full Text PDFCT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.
Abdom Radiol (NY)
January 2025
Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
Background: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced CT, and integrated clinical characteristics to create a radiomics-clinical nomogram for prognostic prediction.
Methods: In this retrospective study, data were collected from 124 PDAC patients treated surgically at a single center, from January 2017 to March 2023.
Radiomics for prediction of perineural invasion in colorectal cancer: a systematic review and meta-analysis.
Abdom Radiol (NY)
January 2025
The General Hospital of Western Theater Command, Chengdu, Sichuan 610083, China, Chengdu, China.
Background: Perineural invasion (PNI) in colorectal cancer (CRC) is a significant prognostic factor associated with poor outcomes. Radiomics, which involves extracting quantitative features from medical imaging, has emerged as a potential tool for predicting PNI. This systematic review and meta-analysis aimed to evaluate the diagnostic accuracy of radiomics models in predicting PNI in CRC.
View Article and Find Full Text PDFMulti-parametric MRI combined with radiomics for the diagnosis and grading of endometrial fibrosis.
Abdom Radiol (NY)
January 2025
Department of Radiology, Nanjing Drum Tower Hospital, Clinical College of Nanjing University of Chinese Medicine, No. 321 Zhongshan Road, Nanjing, 210008, China.
Purpose: To evaluate the application of multi-parametric MRI (MP-MRI) combined with radiomics in diagnosing and grading endometrial fibrosis (EF).
Methods: A total of 74 patients with severe endometrial fibrosis (SEF), 41 patients with mild to moderate fibrosis (MMEF) confirmed by hysteroscopy, and 40 healthy women of reproductive age were prospectively enrolled. The enrolled data were randomly stratified and divided into a train set (108 cases: 28 healthy women, 29 with MMEF, and 51 with SEF) and a test set (47 cases: 12 healthy women, 12 MMEF and 23 SEF) at a ratio of 7:3.
Clinical significance of stratifying prostate cancer patients through specific circulating genes.
Mol Oncol
January 2025
Urologic Oncology Research Group, Cancer Research Program, Research Institute of the McGill University Health Center, Montreal, Canada.
Patient stratification remains a challenge for optimal treatment of prostate cancer (PCa). This clinical heterogeneity implies intra-tumoural heterogeneity, with different prostate epithelial cell subtypes not all targeted by current treatments. We reported that such cell subtypes are traceable in liquid biopsies through representative transcripts.
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