Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer.

Objective: To establish a radiomics nomogram by integrating clinical risk factors and radiomics features extracted from digital mammography (MG) images for pre-operative prediction of axillary lymph node (ALN) metastasis in breast cancer.

Methods: 216 patients with breast cancer lesions confirmed by surgical excision pathology were divided into the primary cohort ( = 144) and validation cohort ( = 72). Radiomics features were extracted from craniocaudal (CC) view of mammograms, and radiomics features selection were performed using the methods of ANOVA F-value and least absolute shrinkage and selection operator; then a radiomics signature was constructed with the method of support vector machine.

Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics.

Purpose: To develop and validate an effective model to differentiate NF-pNET from PDAC.

Materials And Methods: Between July 2014 and December 2017, 147 patients (80 patients with PDAC and 67 patients with atypical NF-pNET) with pathology results and enhanced CT were consecutively enrolled and chronologically divided into primary and validation cohorts. Three models were built to differentiate atypical NF-pNET from PDAC, including a model based on radiomic signature alone, one based on clinicoradiological features alone and one that integrated the two.