Accurate preoperative prediction of lymphovascular and perineural invasion status in gastric cancer patients is crucial for identifying high-risk individuals. This study developed and tested a machine learning model that successfully combines spectral CT parameters and clinical indicators to accurately predict LVI/PNI status. The integration of portal venous and ep spectral CT parameters significantly enhances the detection of LVI/PNI, with CT stage, N status, and EMVI status also playing important roles in predicting invasion status.
Journal Article by Ge HT, Chen JW (…) Lin WW et 5 al. in World J Gastroenterol
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