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. 2021 Sep 22:11:689176.
doi: 10.3389/fonc.2021.689176. eCollection 2021.

Development of a Nomogram Combining Clinical Risk Factors and Dual-Energy Spectral CT Parameters for the Preoperative Prediction of Lymph Node Metastasis in Patients With Colorectal Cancer

Yuntai Cao  1   2   3   4   5 , Jing Zhang  6 , Haihua Bao  1 , Guojin Zhang  7 , Xiaohong Yan  8 , Zhan Wang  9 , Jialiang Ren  10 , Yanjun Chai  3 , Zhiyong Zhao  2   3   4   5 , Junlin Zhou  3   4   5
Affiliations

Development of a Nomogram Combining Clinical Risk Factors and Dual-Energy Spectral CT Parameters for the Preoperative Prediction of Lymph Node Metastasis in Patients With Colorectal Cancer

Yuntai Cao et al. Front Oncol. .

Abstract

Objective: This study aimed to develop a dual-energy spectral computed tomography (DESCT) nomogram that incorporated both clinical factors and DESCT parameters for individual preoperative prediction of lymph node metastasis (LNM) in patients with colorectal cancer (CRC).

Material and methods: We retrospectively reviewed 167 pathologically confirmed patients with CRC who underwent enhanced DESCT preoperatively, and these patients were categorized into training (n = 117) and validation cohorts (n = 50). The monochromatic CT value, iodine concentration value (IC), and effective atomic number (Eff-Z) of the primary tumors were measured independently in the arterial phase (AP) and venous phase (VP) by two radiologists. DESCT parameters together with clinical factors were input into the prediction model for predicting LNM in patients with CRC. Logistic regression analyses were performed to screen for significant predictors of LNM, and these predictors were presented as an easy-to-use nomogram. The receiver operating characteristic curve and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the nomogram.

Results: The logistic regression analysis showed that carcinoembryonic antigen, carbohydrate antigen 199, pericolorectal fat invasion, ICAP, ICVP, and Eff-ZVP were independent predictors in the predictive model. Based on these predictors, a quantitative nomogram was developed to predict individual LNM probability. The area under the curve (AUC) values of the nomogram were 0.876 in the training cohort and 0.852 in the validation cohort, respectively. DCA showed that our nomogram has outstanding clinical utility.

Conclusions: This study presents a clinical nomogram that incorporates clinical factors and DESCT parameters and can potentially be used as a clinical tool for individual preoperative prediction of LNM in patients with CRC.

Keywords: X-ray computed; colorectal cancer; lymph node metastasis; nomogram; tomography.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
A flow diagram of patient recruitment, including inclusion and exclusion criteria.
Figure 2
Figure 2
An example of dual-energy spectral computed tomography (DESCT) images with regions of interest (ROIs) for evaluating quantitative measurements in a 63-year-old man with ascending colon cancer that was pathologically confirmed to have lymph node metastasis (LNM). ROIs were placed in the arterial phase (A) and the venous phase (D) of the 70-keV monochromatic images. Concurrently, ROIs were copied to the arterial phase (B) and the venous phase (E) of iodine-based material decomposition images and the arterial phase (C) and the venous phase (F) of the effective atomic number images. Local lymphadenopathy is presented in front of the right psoas major (white arrow) at both the arterial phase and venous phase (A–F).
Figure 3
Figure 3
An example of DESCT images with ROIs for evaluating quantitative measurements in a 75-year-old man with ascending colon cancer that was pathologically confirmed to have non-metastatic lymph nodes. ROIs were placed in the arterial phase (A) and the venous phase (D) of the 70-keV monochromatic images. At the same time, ROIs were copied to the arterial phase (B) and the venous phase (E) of iodine-based material decomposition images and the arterial phase (C) and venous phase (F) of the effective atomic number images.
Figure 4
Figure 4
Comparison of the different spectrum models for the identification of LNM in patients with colorectal cancer in the training cohort (A) and validation cohort (B).
Figure 5
Figure 5
A multiparametric clinical–DESCT nomogram for predicting the probability of LNM in CRC patients (A). Decision curve analysis (DCA) of the clinical–DESCT nomogram, clinicoradiological model, and spectrum-combined model in the training cohort (B) and validation cohort (C).
Figure 6
Figure 6
ROC curves of the clinical–DESCT nomogram, clinicoradiological model, and spectrum-combined model for preoperative prediction of LNM in patients with colorectal cancer in the training cohort (A) and validation cohort (B).
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