Radiomics approach for survival prediction in chronic obstructive pulmonary disease.
Young Hoon ChoJoon Beom SeoSang Min LeeNamkug KimJihye YunJeong Eun HwangJae Seung LeeYeon-Mok OhSang Do LeeLi-Cher LohChoo-Khoom OngPublished in: European radiology (2021)
• A total of 525 chest CT-based radiomics features were extracted and the five radiomics features of %LAA-950, AWT_Pi10_6th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA18mm were selected to generate a radiomics model. • A radiomics model for predicting survival of COPD patients demonstrated reliable performance with a C-index of 0.774 in the discovery group and 0.805 in the validation group. • Radiomics approach was able to effectively identify COPD patients with an increased risk of mortality, and patients assigned to the high-risk group demonstrated worse overall survival in both the discovery and validation groups.
Keyphrases
- end stage renal disease
- lymph node metastasis
- contrast enhanced
- chronic kidney disease
- ejection fraction
- newly diagnosed
- chronic obstructive pulmonary disease
- small molecule
- peritoneal dialysis
- type diabetes
- squamous cell carcinoma
- single cell
- cardiovascular disease
- free survival
- cardiovascular events
- air pollution