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Clinico-Radiologic Nomogram Using Multiphase CT to Predict Lymph Node Metastasis in Colon Cancer.

Authors :
Cheng, Yuan
Yu, Qing
Meng, Weiyu
Jiang, Wenyan
Source :
Molecular Imaging & Biology; Oct2022, Vol. 24 Issue 5, p798-806, 9p
Publication Year :
2022

Abstract

<bold>Purpose: </bold>To evaluate the value of multiphase computed tomography (CT)-based radiomics for predicting lymph node metastasis in patients with colorectal cancer (CRC).<bold>Methods: </bold>This study included 191 patients enrolled in our hospital who underwent non-contrast, arterial, and portal venous phase CT scans between June 2017 and December 2019. Segmented regions of interest in each slice of CT images were used to extract radiomics features. Redundant features were ruled out using the least absolute shrinkage and selection operator (LASSO) regression. The multiphase CT-combined radiomics signature (Com-RS) was constructed based on the selected radiomics features from the three CT phases weighted by the respective LASSO coefficients. The nomogram was created by combining the Com-RS with key clinical parameters. The performance of the nomogram was evaluated using receiver operating characteristics, calibration, and decision curve analyses (DCA).<bold>Results: </bold>Nine features were demonstrated to be the most significant and used to build the Com-RS: two from non-contrast CT, four from arterial CT, and three from portal venous CT. Tumor length has been identified as a key clinical parameter. A radiomics nomogram was constructed by integrating the Com-RS with tumor length and generated good performance with areas under the curve of 0.830 (95% confidence interval [CI], 0.758 - 0.902) and 0.712 (95% CI, 0.585 - 0.839) in the training and validation cohorts, respectively. Calibration and DCA confirmed the potential clinical relevance and applicability of the nomogram.<bold>Conclusions: </bold>The developed multiphase CT-based radiomics nomogram can potentially serve as an effective tool for the preoperative prediction of lymph node status in CRC. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15361632
Volume :
24
Issue :
5
Database :
Complementary Index
Journal :
Molecular Imaging & Biology
Publication Type :
Academic Journal
Accession number :
159759417
Full Text :
https://doi.org/10.1007/s11307-022-01730-4