Sub-regional Radiomics Analysis for Predicting Metastasis Risk in Clear Cell Renal Cell Carcinoma: A Multicenter Retrospective Study.

Rationale And Objectives: Clear cell renal cell carcinoma (ccRCC) is the most common malignant neoplasm affecting the kidney, exhibiting a dismal prognosis in metastatic instances. Elucidating the composition of ccRCC holds promise for the discovery of highly sensitive biomarkers. Our objective was to utilize habitat imaging techniques and integrate multimodal data to precisely predict the risk of metastasis, ultimately enabling early intervention and enhancing patient survival rates.

Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre study.

Purpose: To develop and validate a predictive combined model for metastasis in patients with clear cell renal cell carcinoma (ccRCC) by integrating multimodal data.

Materials And Methods: In this retrospective study, the clinical and imaging data (CT and ultrasound) of patients with ccRCC confirmed by pathology from three tertiary hospitals in different regions were collected from January 2013 to January 2023. We developed three models, including a clinical model, a radiomics model, and a combined model.

[Diffusion tensor imaging of elderly leukoaraiosis and its correlation with cognitive function].

Objective: To apply diffusion tensor imaging (DTI) for investigating the correlation between leukoaraiosis (LA) lesion's fraction anisotropy (FA) as well as average diffusion coefficient (DCavg) and LA severity, so as to explore DTI changes in microstructure of white marrow with normal ordinary MRI and its correlation with cognitive function.

Methods: Sixty LA patients and 30 healthy elderly people accepted DTI examination to detect the value of DCavg and FA of LA lesion and normal white marrow. The Mini-Mental State Examination (MMSE) was used for assessing cognitive function.