Ultrasound GLCM texture analysis of radiation-induced acute toxicity following breast cancer radiotherapy

Boran Zhou; Mingquan Lin; Xiaofeng Yang; Simone Henry; Jolinta Lin; Karen Godette; Shannon T. Kahn; Walter J. Curran; Mylin A. Torres; Tian Liu

doi:10.1117/12.2581139

15 February 2021 Ultrasound GLCM texture analysis of radiation-induced acute toxicity following breast cancer radiotherapy

Boran Zhou, Mingquan Lin, Xiaofeng Yang, Simone Henry, Jolinta Lin, Karen Godette, Shannon T. Kahn, Walter J. Curran, Mylin A. Torres, Tian Liu

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Proceedings Volume 11602, Medical Imaging 2021: Ultrasonic Imaging and Tomography; 1160205 (2021) https://doi.org/10.1117/12.2581139
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

The aim of this study is to identify ultrasound texture features to characterize radiation-associated acute breast toxicity in women following radiotherapy treatment for breast cancer. We investigated a series of sonographic features obtained from the gray level co-occurrence matrix (GLCM) – a second order statistical method of texture analysis. These features were tested in a pilot study of 42 postradiotherapy patients. The mean follow-up time for the postradiotherapy patients was 6 weeks. Each participant underwent an ultrasound study in which ultrasound scans were performed on the bilateral breast, generating a total of 42 post irradiation and 42 contralateral normal breasts exams. The ultrasound scans of the irradiated breasts were graded as either mild (n=27) or severe (n=15). After specifying the region of interest on the B-mode images and computing the sonographic features based off the severity grading, we observed statistically significant differences in the quantification of

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Boran Zhou, Mingquan Lin, Xiaofeng Yang, Simone Henry, Jolinta Lin, Karen Godette, Shannon T. Kahn, Walter J. Curran, Mylin A. Torres, and Tian Liu "Ultrasound GLCM texture analysis of radiation-induced acute toxicity following breast cancer radiotherapy", Proc. SPIE 11602, Medical Imaging 2021: Ultrasonic Imaging and Tomography, 1160205 (15 February 2021); https://doi.org/10.1117/12.2581139

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