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Correlation between MR Image-Based Radiomics Features and Risk Scores Associated with Gene Expression Profiles in Breast Cancer

DC FieldValueLanguage
dc.contributor.author김가람-
dc.contributor.author김은경-
dc.date.accessioned2020-09-28T11:30:12Z-
dc.date.available2020-09-28T11:30:12Z-
dc.date.issued2020-05-
dc.identifier.issn1738-2637-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/179210-
dc.description.abstractPurpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008–0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.-
dc.description.statementOfResponsibilityopen-
dc.languageKorean-
dc.publisher대한영상의학회-
dc.relation.isPartOfJournal of the Korean Society of Radiology (대한영상의학회지)-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleCorrelation between MR Image-Based Radiomics Features and Risk Scores Associated with Gene Expression Profiles in Breast Cancer-
dc.title.alternative유방암에서 자기공명영상 근거 영상표현형과 유전자 발현 프로파일 근거 위험도의 관계-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiology (영상의학교실)-
dc.contributor.googleauthorGa Ram Kim-
dc.contributor.googleauthorYou Jin Ku-
dc.contributor.googleauthorJun Ho Kim-
dc.contributor.googleauthorEun-Kyung Kim-
dc.identifier.doi10.3348/jksr.2020.81.3.632-
dc.contributor.localIdA00284-
dc.contributor.localIdA00801-
dc.contributor.localIdA00801-
dc.relation.journalcodeJ01843-
dc.identifier.eissn2288-2928-
dc.subject.keywordBreast Neoplasms-
dc.subject.keywordMagnetic Resonance Imaging-
dc.subject.keywordGene Expression Profiling-
dc.contributor.alternativeNameKim, Ga Ram-
dc.contributor.affiliatedAuthor김가람-
dc.contributor.affiliatedAuthor김은경-
dc.contributor.affiliatedAuthor김은경-
dc.citation.volume81-
dc.citation.number3-
dc.citation.startPage632-
dc.citation.endPage643-
dc.identifier.bibliographicCitationJournal of the Korean Society of Radiology (대한영상의학회지), Vol.81(3) : 632-643, 2020-05-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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