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Application of radiomics in precision prediction of diagnosis and treatment of gastric cancer

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Abstract

Gastric cancer is one of the most common malignant tumors. Although some progress has been made in chemotherapy and surgery, it is still one of the highest mortalities in the world. Therefore, early detection, diagnosis and treatment are very important to improve the prognosis of patients. In recent years, with the proposal of the concept of radiomics, it has been gradually applied to histopathological grading, differential diagnosis, therapeutic efficacy and prognosis evaluation of gastric cancer, whose advantage is to comprehensively quantify the tumor phenotype using a large number of quantitative image features, so as to predict and diagnose the lesion area of gastric cancer early. The purpose of this review is to evaluate the research status and progress of radiomics in gastric cancer, and reviewed the workflow and clinical application of radiomics. The 27 original studies on the application of radiomics in gastric cancer were included from web of science database search results from 2017 to 2021, the number of patients included ranged from 30 to 1680, and the models used were based on the combination of radiomics signature and clinical factors. Most of these studies showed positive results, the median radiomics quality score (RQS) for all studies was 36.1%, and the development prospect and challenges of radiomics development were prospected. In general, radiomics has great potential in improving the early prediction and diagnosis of gastric cancer, and provides an unprecedented opportunity for clinical practice to improve the decision support of gastric cancer treatment at a low cost.

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Acknowledgements

This work was supported, in part, by the National Natural Science Foundation of China under Grant Nos. 11727813, 32001074, 32171173, the Open Funding Project of National Key Laboratory of Human Factors Engineering: SYFD061908K, the Natural Science Basic Research Plan in Ningxia Province of China (Program No.2021AAC03319), and the Key Research and Development Program in Ningxia Province of China (NO. 2022BEG03080).

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  1. Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, 710071, Shaanxi, China

    Getao Du, Yun Zeng, Dan Chen & Yonghua Zhan

  2. Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, 750004, China

    Wenhua Zhan

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  1. Getao Du
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Du, G., Zeng, Y., Chen, D. et al. Application of radiomics in precision prediction of diagnosis and treatment of gastric cancer. Jpn J Radiol 41, 245–257 (2023). https://doi.org/10.1007/s11604-022-01352-4

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