Integration of MRI-Based Radiomics Features, Clinicopathological Characteristics, and Blood Parameters: A Nomogram Model for Predicting Clinical Outcome in Nasopharyngeal Carcinoma.

Purpose: This study aimed to develop a nomogram model based on multiparametric magnetic resonance imaging (MRI) radiomics features, clinicopathological characteristics, and blood parameters to predict the progression-free survival (PFS) of patients with nasopharyngeal carcinoma (NPC).

Methods: A total of 462 patients with pathologically confirmed nonkeratinizing NPC treated at Sichuan Cancer Hospital were recruited from 2015 to 2019 and divided into training and validation cohorts at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used for radiomics feature dimension reduction and screening in the training cohort.

Prognostic value of non-contrast myocardial T1 mapping in cardiovascular diseases: a systematic review and meta-analysis.

Myocardial fibrosis predisposes the development of main adverse cardiovascular events (MACEs) in various cardiac disorders. Native T1 derived from cardiac magnetic resonance allows the quantitative assessment of myocardial fibrosis without the use of contrast media. However, the prognostic value of native T1 in risk stratification remains uncertain.