MRI-based radiomics machine learning model to differentiate non-clear cell renal cell carcinoma from benign renal tumors.

Purpose: We aim to develop an MRI-based radiomics model to improve the accuracy of differentiating non-ccRCC from benign renal tumors preoperatively.

Methods: The retrospective study included 195 patients with pathologically confirmed renal tumors (134 non-ccRCCs and 61 benign renal tumors) who underwent preoperative renal mass protocol MRI examinations. The patients were divided into a training set (n = 136) and test set (n = 59).

Potential of quantitative T1 mapping to serve as a novel prognostic predictor of clear cell renal cell carcinoma after nephrectomy.

Background: Accurate preoperative risk stratification methods are important for clear cell renal cell carcinoma (ccRCC) patients to enable personalized treatment. However, there are still no accurate and quantitative prognostic factors. This study aimed to investigate the effectiveness of T1 mapping in predicting the progression-free survival (PFS) of ccRCC after nephrectomy.

Imaging Characteristics of Clear Cell Papillary Renal Cell Carcinoma: Identifying the Sheep in Wolf's Clothing.

Objective: This study aimed to describe the characteristics of computed tomography (CT) and magnetic resonance imaging (MRI) of clear cell papillary renal cell carcinoma (CCPRCC).

Methods: This retrospective study comprised 27 patients diagnosed with 29 tumors of CCPRCC. The study was approved by the Medical Ethics Committee and the requirement for the informed consent was waived.