Cited 0 times in
Efficacy of Radiomics in Predicting Oncologic Outcome of Liver-Directed Combined Radiotherapy in Locally Advanced Hepatocellular Carcinoma
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 성진실 | - |
dc.contributor.author | 박종원 | - |
dc.date.accessioned | 2023-11-28T03:30:37Z | - |
dc.date.available | 2023-11-28T03:30:37Z | - |
dc.date.issued | 2023-11 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/196832 | - |
dc.description.abstract | Purpose: We investigated whether radiomic features extracted from three-phase dynamic contrast-enhanced computed tomography (CECT) can be used to predict clinical outcomes, including objective treatment response (OR) and in-field failure-free survival rate (IFFR), in patients with hepatocellular carcinoma (HCC) who received liver-directed combined radiotherapy (LD-CRT). Methods: We included 409 patients, and they were randomly divided into training (n = 307) and validation (n = 102) cohorts. For radiomics models, we extracted 116 radiomic features from the region of interest on the CECT images. Significant clinical prognostic factors are identified to predict the OR and IFFR in the clinical models. We developed clinical models, radiomics models, and a combination of both features (CCR model). Results: Among the radiomic models evaluated for OR, the OR-PVP-Peri-1cm model showed favorable predictive performance with an area under the curve (AUC) of 0.647. The clinical model showed an AUC of 0.729, whereas the CCR model showed better performance (AUC 0.759). For the IFFR, the IFFR-PVP-Peri-1cm model showed an AUC of 0.673, clinical model showed 0.687, and the CCR model showed 0.736. We also developed and validated a prognostic nomogram based on CCR models. Conclusion: In predicting the OR and IFFR in patients with HCC undergoing LD-CRT, CCR models performed better than clinical and radiomics models. Moreover, the constructed nomograms based on these models may provide valuable information on the prognosis of these patients. | - |
dc.description.statementOfResponsibility | open | - |
dc.format | application/pdf | - |
dc.language | English | - |
dc.publisher | MDPI | - |
dc.relation.isPartOf | CANCERS | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Efficacy of Radiomics in Predicting Oncologic Outcome of Liver-Directed Combined Radiotherapy in Locally Advanced Hepatocellular Carcinoma | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Radiation Oncology (방사선종양학교실) | - |
dc.contributor.googleauthor | Jong Won Park | - |
dc.contributor.googleauthor | Hansang Lee | - |
dc.contributor.googleauthor | Helen Hong | - |
dc.contributor.googleauthor | Jinsil Seong | - |
dc.identifier.doi | 10.3390/cancers15225405 | - |
dc.contributor.localId | A01956 | - |
dc.relation.journalcode | J03449 | - |
dc.identifier.eissn | 2072-6694 | - |
dc.subject.keyword | hepatocellular carcinoma | - |
dc.subject.keyword | liver-directed combined radiotherapy | - |
dc.subject.keyword | radiomics | - |
dc.subject.keyword | treatment response | - |
dc.subject.keyword | in-field failure-free survival rate | - |
dc.contributor.alternativeName | Seong, Jin Sil | - |
dc.contributor.affiliatedAuthor | 성진실 | - |
dc.citation.volume | 15 | - |
dc.citation.number | 22 | - |
dc.citation.startPage | 5405 | - |
dc.identifier.bibliographicCitation | CANCERS, Vol.15(22) : 5405, 2023-11 | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.