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Computed tomography-based radiomics nomogram for the preoperative prediction of perineural invasion in colorectal cancer: a multicentre study

  • Special Section: Quantitative Imaging
  • Published:
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Abstract

Purpose

To develop and validate a computed tomography (CT) radiomics nomogram from multicentre datasets for preoperative prediction of perineural invasion (PNI) in colorectal cancer.

Methods

A total of 299 patients with histologically confirmed colorectal cancer from three hospitals were enrolled in this retrospective study. Radiomic features were extracted from the whole tumour volume. The least absolute shrinkage and selection operator logistic regression was applied for feature selection and radiomics signature construction. Finally, a radiomics nomogram combining the radiomics score and clinical predictors was established. The receiver operating characteristic curve and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomics nomogram in the training cohort, internal validation and external validation cohorts.

Results

Twelve radiomics features extracted from the whole tumour volume were used to construct the radiomics model. The area under the curve (AUC) values of the radiomics model in the training cohort, internal validation cohort, external validation cohort 1, and external validation cohort 2 were 0.82 (0.75–0.90), 0.77 (0.62–0.92), 0.71 (0.56–0.85), and 0.73 (0.60–0.85), respectively. The nomogram, which combined the radiomics score with T category and N category by CT, yielded better performance in the training cohort (AUC = 0.88), internal validation cohort (AUC = 0.80), external validation cohort 1 (AUC = 0.75), and external validation cohort 2 (AUC = 0.76). DCA confirmed the clinical utility of the nomogram.

Conclusions

The CT-based radiomics nomogram has the potential to accurately predict PNI in patients with colorectal cancer.

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Funding

This study was funded by Nantong Science and Technology Bureau (grant No. MS22021047) and Wu Jieping Medical Foundation (Grant No. 320.6750).

Author information

Author notes

  1. First authors: Qiaoling Chen and Yanfen Cui have contributed equally to the work.

  2. The corresponding authors: Feng Feng and Hongmei Gu have contributed equally to the work.

Authors and Affiliations

  1. Nantong University, Nantong, 226001, Jiangsu Province, China

    Qiaoling Chen, Ting Xue, Hui Peng & Manman Li

  2. Department of Radiology, Shanxi Tumor Hospital, Shanxi, 030013, Shanxi Province, China

    Yanfen Cui

  3. Department of Pathology, Affiliated Tumor Hospital of Nantong University, Nantong, 226001, Jiangsu Province, China

    Xinghua Zhu

  4. GE Healthcare China, Shanghai City, 210000, China

    Shaofeng Duan

  5. Department of Radiology, Affiliated Hospital of Nantong University, Nantong, 226001, Jiangsu Province, China

    Hongmei Gu

  6. Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, 226001, Jiangsu Province, China

    Feng Feng

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  1. Qiaoling Chen
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Correspondence to Hongmei Gu or Feng Feng.

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The studies involving human participants were reviewed and approved the ethics committee of Affiliated Tumor Hospital of Nantong University, Affiliated Hospital of Nantong University, Shanxi Province Cancer Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

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Chen, Q., Cui, Y., Xue, T. et al. Computed tomography-based radiomics nomogram for the preoperative prediction of perineural invasion in colorectal cancer: a multicentre study. Abdom Radiol 47, 3251–3263 (2022). https://doi.org/10.1007/s00261-022-03620-3

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