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Radiomics approach for survival prediction in chronic obstructive pulmonary disease

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Abstract
Objectives To apply radiomics analysis for overall survival prediction in chronic obstructive pulmonary disease (COPD), and evaluate the performance of the radiomics signature (RS). Methods This study included 344 patients from the Korean Obstructive Lung Disease (KOLD) cohort. External validation was performed on a cohort of 112 patients. In total, 525 chest CT-based radiomics features were semi-automatically extracted. The five most useful features for survival prediction were selected by least absolute shrinkage and selection operation (LASSO) Cox regression analysis and used to generate a RS. The ability of the RS for classifying COPD patients into high or low mortality risk groups was evaluated with the Kaplan-Meier survival analysis and Cox proportional hazards regression analysis. Results The five features remaining after the LASSO analysis were %LAA(-950), AWT_Pi10_6(th), AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA(18mm). The RS demonstrated a C-index of 0.774 in the discovery group and 0.805 in the validation group. Patients with a RS greater than 1.053 were classified into the high-risk group and demonstrated worse overall survival than those in the low-risk group in both the discovery (log-rank test, < 0.001; hazard ratio [HR], 5.265) and validation groups (log-rank test, < 0.001; HR, 5.223). For both groups, RS was significantly associated with overall survival after adjustments for patient age and body mass index. Conclusions A radiomics approach for survival prediction and risk stratification in COPD patients is feasible, and the constructed radiomics model demonstrated acceptable performance. The RS derived from chest CT data of COPD patients was able to effectively identify those at increased risk of mortality.
Author(s)
김남국서준범오연목이상도이상민이재승Choo-Khoom OngJeong Eun HwangJihye YunLi-Cher LohYoung Hoon Cho
Issued Date
2021
Type
Article
Keyword
AnalysisChestDiagnostic RadiologyImagingIntenal MedicineInterventional RadiologyLung diseasesObstructiveMedical researchMedicineMedicine &amp; Public HealthMedicineExperimentalNeuroradiologyRadiologyUltrasound
DOI
10.1007/s00330-021-07747-7
URI
https://oak.ulsan.ac.kr/handle/2021.oak/7153
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_proquest_miscellaneous_2512345068&amp;context=PC&amp;vid=ULSAN&amp;lang=ko_KR&amp;search_scope=default_scope&amp;adaptor=primo_central_multiple_fe&amp;tab=default_tab&amp;query=any,contains,Radiomics%20approach%20for%20survival%20prediction%20in%20chronic%20obstructive%20pulmonary%20disease&amp;offset=0&amp;pcAvailability=true
Publisher
EUROPEAN RADIOLOGY
Location
독일
Language
영어
ISSN
0938-7994
Citation Volume
31
Citation Number
10
Citation Start Page
7316
Citation End Page
7324
Appears in Collections:
Medicine > Medicine
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