Computed tomography-based radiomics nomogram for prediction of lympho-vascular and perineural invasion in esophageal squamous cell cancer patients: a retrospective cohort study

作者：Bin Tang, Fan Wu, Lin Peng, Xuefeng Leng, Yongtao Han, Qifeng Wang, Junxiang Wu, L.C. Orlandini · 发表于：Cancer Imaging · 年份：2024 · DOI：10.1186/s40644-024-00781-w · 被引用次数：6 · 研究领域：Esophageal Cancer Research and Treatment、Radiomics and Machine Learning in Medical Imaging、Pancreatic and Hepatic Oncology Research

PURPOSE: Lympho-vascular invasion (LVI) and perineural invasion (PNI) have been established as prognostic factors in various types of cancers. The preoperative prediction of LVI and PNI has the potential to guide personalized medicine strategies for patients with esophageal squamous cell cancer (ESCC). This study investigates whether radiomics features derived from preoperative contrast-enhanced CT could predict LVI and PNI in ESCC patients. METHODS AND MATERIALS: A retrospective cohort of 544 ESCC patients who underwent esophagectomy were included in this study. Preoperative contrast-enhanced CT images, pathological results of PNI and LVI, and clinical characteristics were collected. For each patient, the gross tumor volume (GTV-T) and lymph nodes volume (GTV-N) were delineated and four categories of radiomics features (first-order, shape, textural and wavelet) were extracted from GTV-T and GTV-N. The Mann-Whitney U test was used to select significant features associated with LVI and PNI in turn. Subsequently, radiomics signatures for LVI and PNI were constructed using LASSO regression with ten-fold cross-validation. Significant clinical characteristics were combined with radiomics signature to develop two nomogram models for predicting LVI and PNI, respectively. The area under the curve (AUC) and calibration curve were used to evaluate the predictive performance of the models. RESULTS: The radiomics signature for LVI prediction consisted of 28 features, while the PNI radiom...