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Habitat and Peritumoral Radiomics with Clinical Variables for Predicting Lymphovascular Invasion in Gastric Cancer: A Cross-Sectional Study
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DOI：10.1016/j.acra.2026.05.006.png)
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Abstract
En 中文
To construct radiomics models based on various spatial feature strategies for the preoperative prediction of Lymphovascular invasion (LVI) in gastric cancer, to compare the predictive performance of intratumoral, peritumoral, and habitat-based modeling approaches, and to explore the incremental value of integrating radiomics models with clinical factors.
Keywords:
AUC
Area under the curve
CH
Calinski-Harabasz
CT
Computed tomography
CTPA
Contrast-enhanced CT perfusion analysis
DCA
Decision curve analysis
DFS
Disease-free survival
F
Integrated discrimination improvement
GLCM
Gray-level co-occurrence matrix
GLRLM
Gray-level run length matrix
GLSZM
Gray-level size zone matrix
LASSO
Least absolute shrinkage and selection operator
LR
Logistic regression
LVI
Lymphovascular invasion
MLP
Multilayer perceptron
NGTDM
Neighborhood gray-tone difference matrix
NRI
Net reclassification index
OS
Overall survival
PCA
Principal component analysis
RFS
Recurrence-free survival
ROI
Region of interest
SVM
Support vector machine
VOI
Volume of interest
Gastric cancer
Lymphovascular invasion
Radiomics
Habitat imaging
Preoperative prediction
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