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Breast cancer liver metastasis anti-HER-2 treatment curative effect prediction method, system, equipment and medium

A HER-2, prediction method technology, applied in the medical field, to achieve the best effect of classification efficiency

Pending Publication Date: 2022-05-27
SHANDONG UNIV QILU HOSPITAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it has not been reported in the literature whether radiomics can discover some potential features that cannot be obtained from visual basis in breast cancer liver metastases to predict the efficacy of anti-HER-2 therapy in patients

Method used

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  • Breast cancer liver metastasis anti-HER-2 treatment curative effect prediction method, system, equipment and medium
  • Breast cancer liver metastasis anti-HER-2 treatment curative effect prediction method, system, equipment and medium
  • Breast cancer liver metastasis anti-HER-2 treatment curative effect prediction method, system, equipment and medium

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068] Materials and Methods

[0069] 1. Research objects

[0070] This study was approved by the Clinical Research Center of Qilu Hospital, Shandong University. Collected from January 1, 2011 to November 20, 2021 in the central campus of Qilu Hospital of Shandong University and the east campus of Qilu Hospital of Shandong University, patients with liver metastases from breast cancer who were treated with anti-HER-2 therapy were collected. All cases were collected. After the pathological diagnosis of the primary tumor or metastatic tumor, the abdominal contrast CT images of the enrolled patients were retrospectively analyzed. A total of 61 patients (0 males and 61 females; aged 31-71 years) were enrolled in this study. All patients regularly used anti-HER-2 drugs after liver metastasis (49 cases of trastuzumab, 6 cases of pyrotinib, and 6 cases of lapatinib), and then the enrolled 61 patients were based on the existing important clinical Trial conclusions (median PFS of 7.4...

Embodiment 2

[0116] A curative effect prediction system for anti-HER-2 treatment for breast cancer liver metastases, the curative effect prediction system may include:

[0117] The data acquisition module is used to acquire the abdominal enhanced CT image to be identified of the subject, namely, the patient with liver metastases from breast cancer treated with anti-HER-2 therapy;

[0118] Data processing and output module: used to input the enhanced CT image of the abdomen to be identified into the efficacy prediction model, the efficacy prediction model performs quantitative analysis of the enhanced CT image of the abdomen to be identified, and outputs the subject's breast cancer liver metastasis anti-HER-2 treatment efficacy prediction results.

[0119] Wherein, in the data processing and output module, the efficacy prediction model is obtained by using a machine learning algorithm to perform model training on the pre-collected radiomics-related feature data of patients with liver metast...

Embodiment 3

[0133] An electronic device, comprising a memory, a processor, and computer instructions stored in the memory and running on the processor, when the computer instructions are executed by the processor, each operation in the method of Embodiment 1 is completed. For brevity, here No longer.

[0134] The electronic device can be a mobile terminal and a non-mobile terminal, the non-mobile terminal includes a desktop computer, and the mobile terminal includes a smart phone (Smart Phone, such as an Android phone, an IOS phone, etc.), smart glasses, smart watches, smart bracelets, and tablet computers. , notebook computers, personal digital assistants and other mobile Internet devices that can communicate wirelessly.

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Abstract

The invention provides a curative effect prediction method, system and device for breast cancer liver metastasis anti-HER-2 treatment and a medium, and belongs to the technical field of medicine. The method comprises the following steps: acquiring a to-be-recognized abdomen enhanced CT image of a subject, namely an anti-HER-2 treated breast cancer liver metastasis patient; and inputting a to-be-identified abdomen-enhanced CT image to the curative effect prediction model, and performing quantitative analysis operation on the to-be-identified abdomen-enhanced CT image by the curative effect prediction model to obtain a curative effect prediction result of the breast cancer liver metastasis anti-HER-2 treatment of the subject. According to the method, the value of the radiomics characteristics based on the abdominal enhanced CT in predicting the anti-HER-2 treatment effect of the BCLM is researched for the first time, so that reference information and related clinical guidance opinions are provided for predicting the anti-HER-2 treatment effect of an HER-2 positive BCLM patient and a total treatment scheme.

Description

technical field [0001] The invention belongs to the technical field of medicine, and in particular relates to a method, system, equipment and medium for predicting the curative effect of anti-HER-2 therapy for breast cancer liver metastasis. Background technique [0002] The information disclosed in this Background section is only for enhancement of understanding of the general background of the invention and should not necessarily be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person of ordinary skill in the art. [0003] Breast cancer is currently the most common malignant tumor in women worldwide, and its various treatment methods have been attracting attention. Studies have shown that about one-third of breast cancer patients will have distant non-lymph node metastasis. Once distant metastasis occurs, The 5-year survival rate dropped to 23%. The common metastatic sites of breast cancer are bone, lung...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06V10/25G06V10/54G06V10/774G06K9/62G16H70/40
CPCG06T7/0012G16H70/40G06T2207/10081G06T2207/30068G06T2207/30096G06F18/214
Inventor 扈煜彭志国王冬冬何淼于德新王秀问张冉孟迎旭黎莉
Owner SHANDONG UNIV QILU HOSPITAL
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