Rationale And Objectives: To investigate the effectiveness of machine learning-based clinical, radiomics, and combined models in differentiating idiopathic granulomatous mastitis (IGM) from malignancy, both presenting as non-mass enhancement (NME) lesions on magnetic resonance imaging (MRI), and to compare these models with radiological evaluation.
Material And Methods: A total of 178 patients (69 IGM and 109 breast cancer patients) with NME on breast MRI evaluated between March 2018 and April 2022, were included in this two-center study. Age, skin changes, presence of fistula, and abscess were recorded from hospital records.
This study aims to evaluate the role of shearwave elastography (SWE) and superb microvascular imaging (SMI) for preoperative prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 214 women with breast cancer, B-Mode ultrasonography (US), SMIvascular-index (SMIvi), and SWE (E-mean, E-ratio) values were recorded before tru-cut biopsy. Axillary fine-needle aspiration biopsy (FNAB) and sentinel lymph node sampling results were collected.
View Article and Find Full Text PDFObjectives: The aim of this study was to investigate the role of superb microvascular imaging (SMI) and shear wave elastography (SWE) in the prediction of malignancy and invasiveness of isolated microcalcifications (MC) that can be visualized by ultrasonography (US).
Material And Methods: Sixty-seven women with MC, who were considered suspicious on mammography were evaluated. Only those lesions that could be visualized by US and presented as non-mass lesion were included.