AI Article Synopsis
- The study evaluates the use of preoperative radiomics to predict outcomes for patients with esophageal squamous cell cancer (ESCC) by analyzing data from 931 patients, split into training and validation groups.
- Researchers identified 12 key radiomic features that significantly correlated with overall survival (OS), constructing a radiomics index that outperformed traditional clinical staging methods in predicting patient prognosis.
- An integrated model combining the radiomics index with other clinical factors showed improved predictive capability compared to existing methods, indicating it can be a valuable tool in clinical practice for managing ESCC.
Article Abstract
Objective: This study aimed to evaluate the prognostic value of preoperative radiomics and establish an integrated model for esophageal squamous cell cancer (ESCC).
Methods: A total of 931 patients were retrospectively enrolled in this study (training cohort, n=624; validation cohort, n=307). Radiomics features were obtained by contrast-enhanced computed tomography (CT) before esophagectomy. A radiomics index was set based on features of tumor and reginal lymph nodes by using the least absolute shrinkage and selection operator (LASSO) Cox regression. Prognostic nomogram was built based on radiomics index and other independent risk factors. The prognostic value was assessed by using Harrell's concordance index, time-dependent receiver operating characteristics and Kaplan-Meier curves.
Results: Twelve radiomic features from tumor and lymph node regions were identified to build a radiomics index, which was significantly associated with overall survival (OS) in both training cohort and validation cohort. The radiomics index was highly correlated with clinical tumor-node-metastasis (cTNM) and pathologic TNM (pTNM) stages, but it demonstrated a better prognostic value compared with cTNM stage and was almost comparable with pTNM stage. Multivariable Cox regression showed that the radiomics index was an independent prognostic factor. An integrated model was constructed based on gender, preoperative serum sodium concentration, pTNM and the radiomics index for clinical usefulness. The integrated model demonstrated discriminatory ability better compared with the traditional clinical-pathologic model and pTNM alone, indicating incremental value for prognosis.
Conclusions: CT-based radiomics for primary tumor and reginal lymph nodes was sufficient in predicting OS for patients with ESCC. The integrated model demonstrated incremental value for prognosis and was robust for clinical applications.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9086572 | PMC |
| http://dx.doi.org/10.21147/j.issn.1000-9604.2022.02.02 | DOI Listing |
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