Cited 17 times in
Quality of Radiomics Research on Brain Metastasis: A Roadmap to Promote Clinical Translation
DC Field | Value | Language |
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dc.contributor.author | 강석구 | - |
dc.contributor.author | 김세훈 | - |
dc.contributor.author | 김의현 | - |
dc.contributor.author | 박예원 | - |
dc.contributor.author | 박채정 | - |
dc.contributor.author | 안성수 | - |
dc.contributor.author | 이승구 | - |
dc.contributor.author | 장종희 | - |
dc.date.accessioned | 2022-03-11T05:59:06Z | - |
dc.date.available | 2022-03-11T05:59:06Z | - |
dc.date.issued | 2022-01 | - |
dc.identifier.issn | 1229-6929 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/187892 | - |
dc.description.abstract | Objective: Our study aimed to evaluate the quality of radiomics studies on brain metastases based on the radiomics quality score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist, and the Image Biomarker Standardization Initiative (IBSI) guidelines. Materials and methods: PubMed MEDLINE, and EMBASE were searched for articles on radiomics for evaluating brain metastases, published until February 2021. Of the 572 articles, 29 relevant original research articles were included and evaluated according to the RQS, TRIPOD checklist, and IBSI guidelines. Results: External validation was performed in only three studies (10.3%). The median RQS was 3.0 (range, -6 to 12), with a low basic adherence rate of 50.0%. The adherence rate was low in comparison to the "gold standard" (10.3%), stating the potential clinical utility (10.3%), performing the cut-off analysis (3.4%), reporting calibration statistics (6.9%), and providing open science and data (3.4%). None of the studies involved test-retest or phantom studies, prospective studies, or cost-effectiveness analyses. The overall rate of adherence to the TRIPOD checklist was 60.3% and low for reporting title (3.4%), blind assessment of outcome (0%), description of the handling of missing data (0%), and presentation of the full prediction model (0%). The majority of studies lacked pre-processing steps, with bias-field correction, isovoxel resampling, skull stripping, and gray-level discretization performed in only six (20.7%), nine (31.0%), four (3.8%), and four (13.8%) studies, respectively. Conclusion: The overall scientific and reporting quality of radiomics studies on brain metastases published during the study period was insufficient. Radiomics studies should adhere to the RQS, TRIPOD, and IBSI guidelines to facilitate the translation of radiomics into the clinical field. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Korean Society of Radiology | - |
dc.relation.isPartOf | KOREAN JOURNAL OF RADIOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Biomarkers | - |
dc.subject.MESH | Brain Neoplasms* / diagnostic imaging | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Prognosis | - |
dc.subject.MESH | Prospective Studies | - |
dc.title | Quality of Radiomics Research on Brain Metastasis: A Roadmap to Promote Clinical Translation | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Neurosurgery (신경외과학교실) | - |
dc.contributor.googleauthor | Chae Jung Park | - |
dc.contributor.googleauthor | Yae Won Park | - |
dc.contributor.googleauthor | Sung Soo Ahn | - |
dc.contributor.googleauthor | Dain Kim | - |
dc.contributor.googleauthor | Eui Hyun Kim | - |
dc.contributor.googleauthor | Seok-Gu Kang | - |
dc.contributor.googleauthor | Jong Hee Chang | - |
dc.contributor.googleauthor | Se Hoon Kim | - |
dc.contributor.googleauthor | Seung-Koo Lee | - |
dc.identifier.doi | 10.3348/kjr.2021.0421 | - |
dc.contributor.localId | A00036 | - |
dc.contributor.localId | A00610 | - |
dc.contributor.localId | A00837 | - |
dc.contributor.localId | A05330 | - |
dc.contributor.localId | A04942 | - |
dc.contributor.localId | A02234 | - |
dc.contributor.localId | A02912 | - |
dc.contributor.localId | A03470 | - |
dc.relation.journalcode | J02884 | - |
dc.identifier.eissn | 2005-8330 | - |
dc.identifier.pmid | 34983096 | - |
dc.subject.keyword | Brain metastasis | - |
dc.subject.keyword | Machine learning | - |
dc.subject.keyword | Quality improvement | - |
dc.subject.keyword | Radiomics | - |
dc.subject.keyword | Radiomics quality score | - |
dc.contributor.alternativeName | Kang, Seok Gu | - |
dc.contributor.affiliatedAuthor | 강석구 | - |
dc.contributor.affiliatedAuthor | 김세훈 | - |
dc.contributor.affiliatedAuthor | 김의현 | - |
dc.contributor.affiliatedAuthor | 박예원 | - |
dc.contributor.affiliatedAuthor | 박채정 | - |
dc.contributor.affiliatedAuthor | 안성수 | - |
dc.contributor.affiliatedAuthor | 이승구 | - |
dc.contributor.affiliatedAuthor | 장종희 | - |
dc.citation.volume | 23 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 77 | - |
dc.citation.endPage | 88 | - |
dc.identifier.bibliographicCitation | KOREAN JOURNAL OF RADIOLOGY, Vol.23(1) : 77-88, 2022-01 | - |
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