Comparison of preoperative CT- and MRI-based multiparametric radiomics in the prediction of lymph node metastasis in rectal cancer

Yue Niu; Xiaoping Yu; Lu Wen; Feng Bi; Lian Jian; Siye Liu; Yanhui Yang; Yi Zhang; Qiang Lu

doi:10.3389/fonc.2023.1230698

Comparison of preoperative CT- and MRI-based multiparametric radiomics in the prediction of lymph node metastasis in rectal cancer

Front Oncol. 2023 Nov 24:13:1230698. doi: 10.3389/fonc.2023.1230698. eCollection 2023.

Authors

Yue Niu^{1

2}, Xiaoping Yu^{1

2}, Lu Wen², Feng Bi², Lian Jian², Siye Liu², Yanhui Yang^{1

2}, Yi Zhang^{1

2}, Qiang Lu²

Affiliations

¹ Department of Diagnostic Radiology, Graduate Collaborative Training Base of Hunan Cancer Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
² Department of Diagnostic Radiology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China.

Abstract

Objective: To compare computed tomography (CT)- and magnetic resonance imaging (MRI)-based multiparametric radiomics models and validate a multi-modality, multiparametric clinical-radiomics nomogram for individual preoperative prediction of lymph node metastasis (LNM) in rectal cancer (RC) patients.

Methods: 234 rectal adenocarcinoma patients from our retrospective study cohort were randomly selected as the training (n = 164) and testing (n = 70) cohorts. The radiomics features of the primary tumor were extracted from the non-contrast enhanced computed tomography (NCE-CT), the enhanced computed tomography (CE-CT), the T2-weighted imaging (T2WI) and the gadolinium contrast-enhanced T1-weighted imaging (CE-TIWI) of each patient. Three kinds of models were constructed based on training cohort, including the Clinical model (based on the clinical features), the radiomics models (based on NCE-CT, CE-CT, T2WI, CE-T1WI, CT, MRI, CT combing with MRI) and the clinical-radiomics models (based on CT or MRI radiomics model combing with clinical data) and Clinical-IMG model (based on CT and MRI radiomics model combing with clinical data). The performances of the 11 models were evaluated via the area under the receiver operator characteristic curve (AUC), accuracy, sensitivity, and specificity in the training and validation cohort. Differences in the AUCs among the 11 models were compared using DeLong's test. Finally, the optimal model (Clinical-IMG model) was selected to create a radiomics nomogram. The performance of the nomogram to evaluate clinical efficacy was verified by ROC curves and decision curve analysis (DCA).

Results: The MRI radiomics model in the validation cohort significantly outperformed than CT radiomics model (AUC, 0.785 vs. 0.721, p<0.05). The Clinical-IMG nomogram had the highest prediction efficiency than all other predictive models (p<0.05), of which the AUC was 0.947, the sensitivity was 0.870 and the specificity was 0.884.

Conclusion: MRI radiomics model performed better than both CT radiomics model and Clinical model in predicting LNM of RC. The clinical-radiomics nomogram that combines the radiomics features obtained from both CT and MRI along with preoperative clinical characteristics exhibits the best diagnostic performance.

Keywords: computed tomography (CT); lymph nodes; magnetic resonance imaging (MRI); radiomics; rectal cancer.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by Hunan Provincial Natural Science Foundation of China (Project Number: 2023JJ60038), the Scientific Research Project of Hunan Provincial Health Commission (Project Number 20201028), and the National Natural Science Foundation of Hunan (Project Number 2021JJ70104).