Prediction method of breast cancer HER2 state and related equipment

Abstract

The invention discloses a breast cancer HER2 state prediction method and related equipment, and the method comprises the steps: inputting a to-be-predicted breast MR image into a first classification model and a second classification model, and controlling the first classification model and the second classification model to determine that the HER2 category corresponding to the mammary gland MR image is an HER2 high expression category, an HER2 low expression category or an HER2 zero expression category. According to the application, the first classification model and the second classification model are adopted to learn the mammary gland MR image carrying mammary gland lesion features in different aspects, so that lesion information mined in different aspects is associated, and the HER2 category is determined to be an HER2 high expression category, an HER2 low expression category or an HER2 zero expression category through the associated lesion information. Therefore, the accuracy of identifying the HER2 category as an HER2 high expression category, an HER2 low expression category or an HER2 zero expression category is improved.

Description

technical field [0001] The present application relates to the technical field of biomedical engineering, in particular to a method for predicting the HER2 status of breast cancer and related equipment. Background technique [0002] Breast cancer (Breast Cancer, BC) is a heterogeneous disease, which has surpassed lung cancer to become the largest cancer in the world, and breast cancer is also the leading cause of cancer death in women. Human Epidermal Growth Factor Receptor 2 (Human Epidermal Growth Factor Receptor 2, HER2) is a proto-oncogene encoding tyrosine kinase active epidermal growth factor receptor, and is the only predictive marker for breast cancer targeted therapy. HER2 status is in Breast cancer treatment options and prognosis evaluation play a vital role. According to the definition of ASCO / CAP guidelines, BC is divided into HER2 high expression and HER2 negative. Through standardized central pathology, HER2 negative can be divided into HER2 low expression and ...

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Problems solved by technology

[0004] For this reason, the existing technology uses traditional radiomics to evaluate the HER2 status, which cannot fully explore the internal relationship between the data, and cannot accurately predict the HER2 status, resulting in the problem of prediction errors

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