AI Article Synopsis
- A nomogram-based survival prediction model was developed for esophageal squamous cell carcinoma (ESCC) patients treated with chemoradiotherapy, using features from CT and PET scans alongside clinical factors.
- The model involved analyzing data from 81 training patients and validating it with additional patients from the same and a different institution, applying LASSO regression for feature selection.
- Results showed that the dosiomics features were superior predictors of overall survival compared to CT and PET radiomics features, with significant distinctions between high- and low-risk patient groups.
Article Abstract
Objectives: To propose a nomogram-based survival prediction model for esophageal squamous cell carcinoma (ESCC) treated with definitive chemoradiotherapy using pretreatment computed tomography (CT), positron emission tomography (PET) radiomics and dosiomics features, and common clinical factors.
Methods: Radiomics and dosiomics features were extracted from CT and PET images and dose distribution from 2 institutions. The least absolute shrinkage and selection operator (LASSO) with logistic regression was used to select radiomics and dosiomics features by calculating the radiomics and dosiomics scores (Rad-score and Dos-score), respectively, in the training model. The model was trained in 81 patients and validated in 35 patients at Center 1 using 10-fold cross validation. The model was externally tested in 26 patients at Center 2. The predictive clinical factors, Rad-score, and Dos-score were identified to develop a nomogram model.
Results: Using LASSO Cox regression, 13, 11, and 19 CT, PET-based radiomics, and dosiomics features, respectively, were selected. The clinical factors T-stage, N-stage, and clinical stage were selected as significant prognostic factors by univariate Cox regression. In the external validation cohort, the C-index of the combined model of CT-based radiomics, PET-based radiomics, and dosiomics features with clinical factors were 0.74, 0.82, and 0.92, respectively. Significant differences in overall survival (OS) in the combined model of CT-based radiomics, PET-based radiomics, and dosiomics features with clinical factors were observed between the high- and low-risk groups (P = 0.019, 0.038, and 0.014, respectively).
Conclusion: The dosiomics features have a better predicter for OS than CT- and PET-based radiomics features in ESCC treated with radiotherapy.
Clinical Relevance Statement: The current study predicted the overall survival for esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy. The dosiomics features have a better predicter for overall survival than CT- and PET-based radiomics features.
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| http://dx.doi.org/10.1016/j.ejso.2024.108450 | DOI Listing |
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