Classification of intrinsic subtypes and histological grade for breast cancers by multimodality images

Chisako Muramatsu; Takumi Iwasaki; Mikinao Oiwa; Tomonori Kawasaki; Hiroshi Fujita

doi:10.1117/12.2625871

13 July 2022 Classification of intrinsic subtypes and histological grade for breast cancers by multimodality images

Chisako Muramatsu, Takumi Iwasaki, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita

Proceedings Volume 12286, 16th International Workshop on Breast Imaging (IWBI2022); 122860Y (2022) https://doi.org/10.1117/12.2625871
Event: Sixteenth International Workshop on Breast Imaging, 2022, Leuven, Belgium

Abstract

Success of breast cancer treatment is subject to various factors, including cancer stage and cancer grade. The best treatment is selected based on the characteristic of cancer. It is desirable to predict the cancer characteristics and prognostic factors accurately and promptly by diagnostic imaging. The purpose of the study is to investigate the use of multimodality diagnostic images in predicting breast cancer subtypes to assist diagnosis and treatment planning. In this study, we classify lesions into molecular subtypes and simultaneously predict histological grades and invasiveness of the cancers by mammography and breast ultrasound images. Models with different architectures including single input and multi-input layers with single head and multiple head models are compared. The results indicate that use of multimodality images is more predictive than using single modalities. The automatic subtype classification using multimodality images may support a prompt treatment planning and proper patient care.

Citation Download Citation

Chisako Muramatsu, Takumi Iwasaki, Mikinao Oiwa, Tomonori Kawasaki, and Hiroshi Fujita "Classification of intrinsic subtypes and histological grade for breast cancers by multimodality images", Proc. SPIE 12286, 16th International Workshop on Breast Imaging (IWBI2022), 122860Y (13 July 2022); https://doi.org/10.1117/12.2625871

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