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Quality assessment of meningioma radiomics studies: Bridging the gap between exploratory research and clinical applications
DC Field | Value | Language |
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dc.contributor.author | 강석구 | - |
dc.contributor.author | 김세훈 | - |
dc.contributor.author | 김의현 | - |
dc.contributor.author | 문주형 | - |
dc.contributor.author | 박예원 | - |
dc.contributor.author | 안성수 | - |
dc.contributor.author | 이승구 | - |
dc.contributor.author | 장종희 | - |
dc.date.accessioned | 2021-09-29T00:58:24Z | - |
dc.date.available | 2021-09-29T00:58:24Z | - |
dc.date.issued | 2021-05 | - |
dc.identifier.issn | 0720-048X | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/184129 | - |
dc.description.abstract | Purpose: To evaluate the quality of radiomics studies on meningiomas, using a radiomics quality score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD), and the Image Biomarker Standardization Initiative (IBSI). Methods: PubMed MEDLINE and Embase were searched to identify radiomics studies on meningiomas. Of 138 identified articles, 25 relevant original research articles were included. Studies were scored according to the RQS, TRIPOD guidelines, and items in IBSI. Results: Only four studies (16 %) performed external validation. The mean RQS was 5.6 out of 36 (15.4 %), and the basic adherence rate was 26.8 %. The adherence rate was low for stating biological correlation (4%), conducting calibration statistics (12 %), multiple segmentation (16 %), and stating potential clinical utility (16 %). None of the studies conducted a test‒retest or phantom study, stated a comparison to a 'gold standard', conducted prospective studies or cost-effectivity analysis, or opened code and data to the public, resulting in low RQS. The overall adherence rate for TRIPOD was 54.1 %, with low scores for reporting the title (4%), abstract (0%), blind assessment of the outcome (8%), and explaining the sample size (0%). According to IBSI items, only 6 (24 %), 6 (24 %), and 3 (12 %) studies performed N4 bias-field correction, isovoxel resampling, and grey-level discretization, respectively. No study performed skull stripping. Conclusion: The quality of radiomics studies for meningioma is insufficient. Acknowledgement of RQS, TRIPOD, and IBSI reporting guidelines may improve the quality of meningioma radiomics studies and enable their clinical application. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Elsevier Science Ireland Ltd | - |
dc.relation.isPartOf | EUROPEAN JOURNAL OF RADIOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Meningeal Neoplasms* / diagnostic imaging | - |
dc.subject.MESH | Meningioma* / diagnostic imaging | - |
dc.subject.MESH | Prognosis | - |
dc.subject.MESH | Prospective Studies | - |
dc.subject.MESH | Research Design | - |
dc.title | Quality assessment of meningioma radiomics studies: Bridging the gap between exploratory research and clinical applications | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Neurosurgery (신경외과학교실) | - |
dc.contributor.googleauthor | So Yeon Won | - |
dc.contributor.googleauthor | Yae Won Park | - |
dc.contributor.googleauthor | Sung Soo Ahn | - |
dc.contributor.googleauthor | Ju Hyung Moon | - |
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 | 10.1016/j.ejrad.2021.109673 | - |
dc.contributor.localId | A00036 | - |
dc.contributor.localId | A00610 | - |
dc.contributor.localId | A00837 | - |
dc.contributor.localId | A01383 | - |
dc.contributor.localId | A05330 | - |
dc.contributor.localId | A02234 | - |
dc.contributor.localId | A02912 | - |
dc.contributor.localId | A03470 | - |
dc.relation.journalcode | J00845 | - |
dc.identifier.eissn | 1872-7727 | - |
dc.identifier.pmid | 33774441 | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0720048X21001534 | - |
dc.subject.keyword | Machine learning | - |
dc.subject.keyword | Meningioma | - |
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 | 문주형 | - |
dc.contributor.affiliatedAuthor | 박예원 | - |
dc.contributor.affiliatedAuthor | 안성수 | - |
dc.contributor.affiliatedAuthor | 이승구 | - |
dc.contributor.affiliatedAuthor | 장종희 | - |
dc.citation.volume | 138 | - |
dc.citation.startPage | 109673 | - |
dc.identifier.bibliographicCitation | EUROPEAN JOURNAL OF RADIOLOGY, Vol.138 : 109673, 2021-05 | - |
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