Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma

Abstract

ObjectivesTo develop a radiomics model based on contrast-enhanced CT (CECT) to predict the lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC) and provide decision-making support for clinicians.Patients and MethodsThis retrospective study enrolled 334 patients with surgically resected and pathologically confirmed ESCC, including 96 patients with LVI and 238 patients without LVI. All enrolled patients were randomly divided into a training cohort and a testing cohort at a ratio of 7:3, with the training cohort containing 234 patients (68 patients with LVI and 166 without LVI) and the testing cohort containing 100 patients (28 patients with LVI and 72 without LVI). All patients underwent preoperative CECT scans within 2 weeks before operation. Quantitative radiomics features were extracted from CECT images, and the least absolute shrinkage and selection operator (LASSO) method was applied to select radiomics features. Logistic regression (Logistic), support vector machine (SVM), and decision tree (Tree) methods were separately used to establish radiomics models to predict the LVI status in ESCC, and the best model was selected to calculate Radscore, which combined with two clinical CT predictors to build a combined model. The clinical model was also developed by using logistic regression. The receiver characteristic curve (ROC) and decision curve (DCA) analysis were used to evaluate the model performance in predicting the LVI status in ESCC.ResultsIn the radiomics model, Sphericity and gray-level non-uniformity (GLNU) were the most significant radiomics features for predicting LVI. In the clinical model, the maximum tumor thickness based on CECT (cThick) in patients with LVI was significantly greater than that in patients without LVI (P<0.001). Patients with LVI had higher clinical N stage based on CECT (cN stage) than patients without LVI (P<0.001). The ROC analysis showed that both the radiomics model (AUC values were 0.847 and 0.826 in the training and testing cohort, respectively) and the combined model (0.876 and 0.867, respectively) performed better than the clinical model (0.775 and 0.798, respectively), with the combined model exhibiting the best performance.ConclusionsThe combined model incorporating radiomics features and clinical CT predictors may potentially predict the LVI status in ESCC and provide support for clinical treatment decisions.

18F-fluorodeoxyglucose positron emission tomography/computed tomography parameters are associated with histological outcomes in superficial esophageal squamous cell carcinoma

“…However, lymphovascular invasion can be diagnosed only via postoperative histopathology, and preoperative prediction is extremely di cult [22]. A previous report also indicated that enhanced CT is a potential candidate for predicting lymphovascular invasion, although the study subject was not limited to super cial SCC but also included advanced SCC [22]. The bene t of FDG PET/CT for predicting lymphovascular invasion has been described in lung cancer, hepatocellular carcinoma, and colon cancer; [23][24][25] however, it has been poorly studied in super cial ESCC.…”

The Potential Value of Texture Analysis Based on Dynamic Contrast-Enhanced MR Images in the Grading of Breast Phyllode Tumors

“…Many texture features are unstable in different reconstruction algorithms, while GLevNonU is one of the most repetitive radiomics features showing good stability. The GLevNonU value increases with the tumor heterogeneity, which is related to tumor invasion, treatment response, and prognosis ( 28 ). In this study, we found that the Z_GLevNonU, 45dgr_GLevNonU, and 135dr_GLevNonU values of the BMPTs were statistically larger than those of the BPTs, indicating that the gray-level distribution was more heterogeneous in BMPTs on DCE-MR images, compared with BPTs.…”

Could tumour volume and major and minor axis based on CTA statistical anatomy improve the pre‐operative T‐stage in oesophageal cancer?

“…All patients who participated in this study underwent appropriate breathing exercises, and a 64‐bit multi‐detector spiral CTA scanner was used to scan all images. All patients were placed in the supine position with the head facing forward and the hands above the head, and either the chest or the upper abdomen was scanned during the CTA examination 22 . Typically, a traditional CTA scan is performed first, followed by intravenous injection of contrast medium using a syringe pump 23 .…”