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Radiomics based on preoperative rectal cancer MRI to predict the metachronous liver metastasis

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Abstract

Purpose

At present, there are few effective method to predict metachronous liver metastasis (MLM) from rectal cancer. We aim to investigate the efficacy of radiomics based on multiparametric MRI of first diagnosed rectal cancer in predicting MLM from rectal cancer.

Methods

From 301 consecutive histopathologically confirmed rectal cancer patients, 130 patients who have no distant metastasis detected at the time of diagnosis were enrolled and divided into MLM group (n = 49) and non-MLM group (n = 81) according to whether liver metastasis be detected later than 6 month after the first diagnosis of rectal cancer within 3 years’ follow-up. The 130 patients were divided into a training set (n = 91) and a testing set (n = 39) at a ratio of 7:3 by stratified sampling using SPSS 24.0 software. The DWI model, HD T2WI model, and DWI + HD T2WI model were constructed respectively. The best performing model was selected and combined with the screened clinical features (including non-radiomics MRI features) to construct a fusion model. The testing set was used to evaluate the performance of the models, and the area under the curve (AUC) of receiver operating characteristics (ROC) was calculated for both the training set and the testing set.

Results

The AUC of the DWI + HD T2WI model in the testing set was higher than that of the DWI or the HD T2 model alone with statistically significance (P < 0.05). The screened clinical features were extramural vascular invasion (EMVI), T and N stages in MRI (mrT, mrN), and the distance from the lower edge of the tumor to the anal verge. The AUC of the fusion model in the testing set was 0.911. Decision curves and nomogram also showed that the fusion model had excellent clinical performance.

Conclusion

The fusion model of primary rectal cancer MRI based radiomics combing clinical features can effectively predict MLM from rectal cancer, which may assist clinicians in formulating individualized monitoring and treatment plans.

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Funding

This work was supported by Key Research and Development Plan Guidance Project of Cangzhou City (Grant No. 213106017).

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Authors and Affiliations

  1. Department of Magnetic Resonance Imaging, Cangzhou Central Hospital, No. 16 Xinhua Western Road, Yunhe District, Cangzhou, 061000, China

    Zhuo-fu Li, Li-qing Kang, Feng-hai Liu, Meng Zhao, Su-yin Guo & Shan Lu

  2. GE HealthCare China (Shanghai), Shanghai, 210000, China

    Shuai Quan

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Z-fL. The first draft of the manuscript was written by Z-fL and all authors commented on previous versions of the manuscript. The manuscript was modified and finalized by L-qK. All authors have approved the final manuscript.

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Correspondence to Li-qing Kang.

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All authors report there are no competing interests to declare. The authors have no relevant financial or non-financial interests to disclose.

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The study complied with the standards of the declaration of the Helsinki and current ethical guidelines, and was approved by ethics review committee at Cangzhou Central Hospital.

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Informed consent was obtained from all patients.

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Li, Zf., Kang, Lq., Liu, Fh. et al. Radiomics based on preoperative rectal cancer MRI to predict the metachronous liver metastasis. Abdom Radiol 48, 833–843 (2023). https://doi.org/10.1007/s00261-022-03773-1

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