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• Clinical Article •
Preoperative prediction of vascular invasion in rectal cancer patients without lymph node metastasis based on multimodal MRI imaging features combined with clinical risk factors
YANG Yan  WEI Huanhuan  FU Fangfang  WEI Wei  WU Yaping  JI Xiang  WANG Meiyun 

Cite this article as: YANG Y, WEI H H, FU F F, et al. Preoperative prediction of vascular invasion in rectal cancer patients without lymph node metastasis based on multimodal MRI imaging features combined with clinical risk factors[J]. Chin J Magn Reson Imaging, 2023, 14(1): 94-99, 110. DOI:10.12015/issn.1674-8034.2023.01.017.


[Abstract] Objective To explore the application value of the clinical-radiomics model based on axial fat suppression T2-weighted imaging (FS-T2WI) and T1-weighted contrast-enhanced (T1CE) sequences combined with clinical predictors in the prediction of preoperative lymphovascular invasion (LVI) in patients with rectal cancer without lymph node metastasis.Materials and Methods The cases and imaging data of 221 patients with rectal cancer who underwent MRI scan and were confirmed by postoperative pathology in Henan Provincial People's Hospital from December 2016 to December 2021 were retrospectively included. Univariate and multivariate logistic regression were used to analyze the clinical data of the LVI positive group and the LVI negative group to determine the independent predictors of LVI. The full-layer region of interest (ROI) of tumor was manually delineated by ITK-SNAP software , and the open source software PyRadiomics was used to extract the radiomics features. Patients were divide into the training set (177 cases) and the test set (44 cases) according to the ratio of 8∶2 by SPSS random number table method, and the radiomics signature was constructed after feature dimension reduction. Four prediction models were constructed based on whether clinical predictors were included in the image omics model. The diagnostic efficacy of different prediction models was evaluated according to the area under curve (AUC) of receiver operating characteristic (ROC), sensitivity and specificity.Results Maximum tumor diameter was independent predictors of LVI in patients with rectal cancer (P＜0.05). The AUC of FS-T2WI, T1CE and their combination (FS-T2WI+T1CE) was 0.757, 0.802 and 0.869, respectively. The FS-T2WI+T1CE combined with clinical predictors clinical-radiomics model had the best diagnostic performance, with an AUC of 0.898 (95% CI: 0.769, 0.968) in the test set.Conclusions The clinical-radiomics model constructed in this study has a high diagnostic efficiency, which can assist the clinical prediction of preoperative individualized LVI in rectal cancer patients without lymph node metastasis and improve the treatment plan.
[Keywords] rectal cancer；lymphovascular invasion；radiomics；magnetic resonance imaging；logistic regression

YANG Yan1   WEI Huanhuan1   FU Fangfang1, 2   WEI Wei1, 2   WU Yaping1, 2   JI Xiang3   WANG Meiyun1, 2*  

1 Department of Medical Imaging, the People's Hospital of Zhengzhou University, Zhengzhou 450003, China

2 Henan Provincial People's Hospital, Henan Key Laboratory of Neurological Imaging, Zhengzhou 450003, China

3 School of Computers and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, China

Corresponding author: Wang MY, E-mail: mywang@ha.edu.cn

Conflicts of interest   None.

ACKNOWLEDGMENTS Henan Provincial Science and Technology Research Project (No. 212102310689); Joint Construction Project of Henan Medical Science and Technology Research Project (No. LHGJ20210001, LHGJ20210005).
Received  2022-08-29
Accepted  2022-12-05
DOI: 10.12015/issn.1674-8034.2023.01.017
Cite this article as: YANG Y, WEI H H, FU F F, et al. Preoperative prediction of vascular invasion in rectal cancer patients without lymph node metastasis based on multimodal MRI imaging features combined with clinical risk factors[J]. Chin J Magn Reson Imaging, 2023, 14(1): 94-99, 110. DOI:10.12015/issn.1674-8034.2023.01.017.

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