Utilization of Texture Analysis in Differentiating Benign and Malignant Breast Masses: Comparison of Grayscale Ultrasound, Shear Wave Elastography, and Radiomic Features.

Autor: Mannina D; Department of Radiology, McMaster University, Hamilton, ON, Canada., Kulkarni A; Department of Radiology, McMaster University, Juravinski Hospital, Hamilton, ON, Canada., van der Pol CB; Department of Radiology, McMaster University, Juravinski Hospital, Hamilton, ON, Canada., Al Mazroui R; Department of Radiology, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat, Oman., Abdullah P; Department of Kinesiology, York University, Toronto, ON, Canada., Joshi S; Hospital for Sick Children, IMS-University of Toronto, Toronto, ON, Canada., Alabousi A; Department of Radiology, McMaster University, St. Joseph's Healthcare, Hamilton, ON, Canada.
Jazyk: angličtina
Zdroj: Journal of breast imaging [J Breast Imaging] 2024 Sep 11; Vol. 6 (5), pp. 513-519.
DOI: 10.1093/jbi/wbae037
Abstrakt: Objective: This study aims to determine which qualitative and quantitative US features are independently associated with malignancy, including those derived from grayscale imaging morphology, shear wave elastography (SWE), and texture analysis.
Methods: This single-center retrospective study was approved by the institutional research ethics board. Consecutive breast US studies performed between January and December 2020 were included. Images were acquired using a Canon Aplio i800 US unit (Canon Medical Systems, Inc., CA) and i18LX5 wideband linear matrix transducer. Grayscale US features, SWE mean, and median elasticity were obtained. Single representative grayscale images were analyzed using dedicated software (LIFEx, version 6.30). First-order and gray-level co-occurrence matrix second-order texture features were extracted. Multivariate logistic regression was performed to assess for predictors of malignancy (STATA v16.1).
Results: One hundred forty-seven cases with complete SWE data were selected for analysis (mean age 54.3, range 21-92). The following variables were found to be independently associated with malignancy: age (P <.001), family history (P = .013), irregular mass shape (P = .024), and stiffness on SWE (mean SWE ≥40 kPa; P <.001). Remaining variables (including texture features) were not found to be independently associated with malignancy (P >.05).
Conclusion: US texture analysis features were not associated with malignancy independent of other qualitative and quantitative US characteristics currently utilized in clinical practice. This suggests texture analysis may not be warranted when differentiating benign and malignant breast masses on US. In contrast, irregular mass shape on grayscale imaging and increased stiffness on SWE were found to be independent predictors of malignancy.
(© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Breast Imaging.)
Databáze: MEDLINE