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ORIGINAL ARTICLES: ELDERLY PATIENTS

Pre-treatment CT radiomics to predict 3-year overall survival following chemoradiotherapy of esophageal cancer

ORCID Icon, , , , , , , ORCID Icon, , & show all
Pages 1475-1481 | Received 02 Nov 2017, Accepted 30 May 2018, Published online: 01 Aug 2018

Figures & data

Table 1. Patient characteristics.

Figure 1. ROC-curves for the AMC cohort (training) and Maastro cohort (validation) for the random forest models based on (a) 40 radiomic features and (b) 6 clinical variables.

Figure 1. ROC-curves for the AMC cohort (training) and Maastro cohort (validation) for the random forest models based on (a) 40 radiomic features and (b) 6 clinical variables.

Figure 2. Survival curves of the (a) AMC cohort (training) and (b) Maastro cohort (validation). Division in risk groups was based on the predictions by the random forest model with radiomics features.

Figure 2. Survival curves of the (a) AMC cohort (training) and (b) Maastro cohort (validation). Division in risk groups was based on the predictions by the random forest model with radiomics features.

Figure 3. Survival curves of the (a) AMC cohort (training) and (b) Maastro cohort (validation). Division in risk groups was based on the predictions by the random forest model with clinical variables.

Figure 3. Survival curves of the (a) AMC cohort (training) and (b) Maastro cohort (validation). Division in risk groups was based on the predictions by the random forest model with clinical variables.

Figure 4. Survival curves of the (a) AMC cohort (training) and (b) Maastro cohort (validation). Division in risk groups was based on the pathological response in the primary tumor.

Figure 4. Survival curves of the (a) AMC cohort (training) and (b) Maastro cohort (validation). Division in risk groups was based on the pathological response in the primary tumor.
Supplemental material

Supplemental Material

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