Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography

doi:10.4251/wjgo.v17.i12.112873

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastrointest Oncol. Dec 15, 2025; 17(12): 112873
Published online Dec 15, 2025. doi: 10.4251/wjgo.v17.i12.112873

Table 6 Summary of all final selected clinical, body composition analysis, and radiomic features across feature subsets 1 to 4

	Feature subset 1	Feature subset 2	Feature subset 3	Feature subset 4
Clinical	clinical_T, clinical_N, clinical_M, ECOG	clinical_T, clinical_M	clinical_T, clinical_M	clinical_T, clinical_M
BOA	delta_SAT, TAT/SMI, sarco0
Radiomics (pretreatment)		MUSCLE_original_shape_Sphericity0, VAT_shape_Elongation0, VAT_shape_Sphericity0, VAT_shape_SurfaceVolumeRatio0, VAT_firstorder_Mean0, VAT_glcm_ClusterShade0		MUSCLE_original_shape_Sphericity0, VAT_shape_SurfaceVolumeRatio0, SAT_firstorder_Skewness0
Radiomics (f/u)			MUSCLE_original_glszm_LargeAreaEmphasis1, VAT_firstorder_10Percentile1, VAT_firstorder_90Percentile1, VAT_firstorder_Mean1, VAT_firstorder_Minimum1, VATl_glcm_JointEnergy1, VAT_glcm_JointEntropy1, VAT_gldm_DependenceVariance1, VAT_glrlm_LongRunLowGrayLevelEmphasis1, VAT_glrlm_RunEntropy1, VAT_glszm_GrayLevelNonUniformityNormalized1, VAT_glszm_SizeZoneNonUniformity1	MUSCLE_glszm_LargeAreaEmphasis1, VAT_firstorder_10Percentile1, VAT_firstorder_90Percentile1, VAT_firstorder_Mean1, VAT_glcm_JointEnergy1, VAT_gldm_DependenceVariance1, VAT_glrlm_LongRunLowGrayLevelEmphasis1, VAT_glrlm_RunEntropy1, VAT_glszm_GrayLevelNonUniformityNormalized1, delta_VAT_shape_Sphericity1

ECOG: Eastern Cooperative Oncology Group; sarco: Sarcopenia; 0: Pretreatment; TATSMR1: Total adipose tissue index/skeletal muscle index ratio; SAT: Subcutaneous adipose tissue; 1: Follow-up; VAT: Visceral adipose tissue; glcm: Gray-level co-occurrence matrix; glszm: Gray-level size zone matrix; glrlm: Gray-level run length matrix; Gldm: Gray-level dependence matrix; f/u: Follow-up; BOA: Body organ analysis.

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Citation: Liu MC, Cheng YY, Lin SC, Lin CH, Chuang CY, Chen WH, Liao CH, Hsieh CH, Hsieh MF, Liu YJ. Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography. World J Gastrointest Oncol 2025; 17(12): 112873
URL: https://www.wjgnet.com/1948-5204/full/v17/i12/112873.htm
DOI: https://dx.doi.org/10.4251/wjgo.v17.i12.112873

Liu MC, Cheng YY, Lin SC, Lin CH, Chuang CY, Chen WH, Liao CH, Hsieh CH, Hsieh MF, Liu YJ. Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography. World J Gastrointest Oncol 2025; 17(12): 112873 [PMID: 41480227 DOI: 10.4251/wjgo.v17.i12.112873]

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