Method for researching postoperative recurrence related factors of non-small cell lung cancer patient

Abstract

The invention provides a method for researching postoperative recurrence related factors of a non-small cell lung cancer patient based on multi-omics in a CT mode, and belongs to the field of computer-aided medicine. The method comprises the following steps: firstly, carrying out segmentation and image omics feature extraction on lung tumors; secondly, fusing the image omics characteristics with other omics characteristics to obtain a tumor multi-omics characteristic original data set; secondly, performing single-factor analysis on the multi-omics characteristic data and the recurrence condition of the patient by adopting an independent sample T test method to obtain recurrence related factors with statistical difference; and finally, substituting the factors with statistical difference into a Logistic regression analysis method to screen out significant characteristic factors related to recurrence of the non-small cell lung cancer, and constructing a model for verification. The invention provides a new scheme for exploring the relationship between the multi-omics characteristics under the CT mode and the postoperative recurrence condition of the patient.

Description

technical field [0001] The invention relates to the technical field of computer-aided medical treatment, in particular to a method for researching factors related to postoperative recurrence of patients with non-small cell lung cancer. Background technique [0002] The International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) recently released a new report stating that lung cancer is the malignant tumor with the fastest-growing morbidity and mortality worldwide, and it is expected to cause 1.8 million deaths in 2018, accounting for 1% of the estimated cancer deaths. 18.4% of the total population. According to histological classification, lung cancer is divided into non-small cell lung cancer and small cell lung cancer. Among them, non-small cell lung cancer (NSCLC) accounts for 80% to 85% of the total number of lung cancer patients, including squamous Cell carcinoma (squamous cell carcinoma), adenocarcinoma, large cell carcinoma. Compared wi...

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Problems solved by technology

However, this type of index has limitations: 1. There are few types of clinical information that can be used, and it cannot be accurately quantified (usually it can only be judged as 0 or 1 based on its presence or absence), and this method of judgment cannot distinguish There are subtle differences between them; 2. The indicators that can be quantified can often only be studied within a single omics, and cannot be combined with other omics information. The information used is relatively narrow, and the accuracy of its prediction and judgment is relatively low.

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