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A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer

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Abstract

Purpose

To develop and validate a nomogram for the preoperative diagnosis of T2 and T3 stage rectal cancer using MRI radiomics features of mesorectal fat.

Methods

The data of 288 patients with T2 and T3 stage rectal cancer were retrospectively collected. Radiomics features were extracted from the lesion region of interest (ROI) in the MRI high-resolution T2WI, apparent diffusion coefficient (ADC), and diffusion-weighted imaging (DWI) sequences. After using ICC inter-group consistency analysis and Pearson correlation analysis to reduce dimensions, LASSO regression analysis was performed to select features and calculate Rad-score for each sequence. Then, Combined_Radscore and nomogram were constructed based on the LASSO-selected features and clinical data for each sequence. Receiver operating characteristic curve (ROC) area under the curve (AUC) was used to evaluate the performance of the Rad-score model and nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical usability of the radiomics nomogram, which were combined with calibration curves to evaluate the prediction accuracy.

Results

The nomogram based on MRI-report T status and Combined_Radscore achieved AUCs of 0.921 and 0.889 in the training and validation cohorts, respectively.

Conclusion

The nomogram can be stated that the radiomics nomogram based on multi-sequence MRI imaging of the mesorectal fat has excellent diagnosing performance for preoperative differentiation of T2 and T3 stage rectal cancer.

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Author information

Author notes

  1. Bo Deng and Qian Wang have contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Shanghai Fifth Rehabilitation Hospital, Shanghai, China

    Bo Deng & Qian Wang

  2. Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, China

    Bo Deng, Yuanqing Liu & Hui Dai

  3. Magnetic Resonance Room of Orthopedics Department, First Affiliated Hospital of Soochow University, Suzhou, China

    Yanwei Yang

  4. Department of Radiology, Luodian Hospital, Shanghai University Medical College, Baoshan District, Shanghai, China

    Xiaolong Gao

Authors
  1. Bo Deng
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  2. Qian Wang
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  3. Yuanqing Liu
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  4. Yanwei Yang
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  5. Xiaolong Gao
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  6. Hui Dai
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Correspondence to Xiaolong Gao or Hui Dai.

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Deng, B., Wang, Q., Liu, Y. et al. A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer. Abdom Radiol (2024). https://doi.org/10.1007/s00261-023-04164-w

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  • DOI: https://doi.org/10.1007/s00261-023-04164-w

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