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뇌과학이미징연구단
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Imaging Phenotyping Using Radiomics to Predict Micropapillary Pattern within Lung Adenocarcinoma

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dc.contributor.authorSo Hee Song-
dc.contributor.authorHyunjin Park-
dc.contributor.authorGeewon Lee-
dc.contributor.authorHo Yun Lee-
dc.contributor.authorInsuk Sohn-
dc.contributor.authorHye Seung Kim-
dc.contributor.authorSeung Hak Lee-
dc.contributor.authorJi Yun Jeong-
dc.contributor.authorJhingook Kim-
dc.contributor.authorKyung Soo Lee-
dc.contributor.authorYoung Mog Shim-
dc.date.available2017-09-05T05:20:43Z-
dc.date.created2017-04-24-
dc.date.issued2017-04-
dc.identifier.issn1556-0864-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/3729-
dc.description.abstractIntroduction Lung adenocarcinomas (ADCs) with a micropapillary pattern have been reported to have a poor prognosis. However, few studies have reported on the imaging-based identification of a micropapillary component, and all of them have been subjective studies dealing with qualitative computed tomography variables. We aimed to explore imaging phenotyping using a radiomics approach for predicting a micropapillary pattern within lung ADC. Methods We enrolled 339 patients who underwent complete resection for lung ADC. Histologic subtypes and grades of the ADC were classified. The amount of micropapillary component was determined. Clinical features and conventional imaging variables such as tumor disappearance rate and maximum standardized uptake value on positron emission tomography were assessed. Quantitative computed tomography analysis was performed on the basis of histogram, size and shape, Gray level co-occurrence matrix–based features, and intensity variance and size zone variance–based features. Results Higher tumor stage (OR = 3.270, 95% confidence interval [CI]: 1.483–7.212), intermediate grade (OR = 2.977, 95% CI: 1.066–8.316), lower value of the minimum of the whole pixel value (OR = 0.725, 95% CI: 0.527–0.98800), and lower value of the variance of the positive pixel value (OR = 0.961, 95% CI: 0.927–0.997) were identified as being predictive of a micropapillary component within lung ADC. On the other hand, maximum standardized uptake value and tumor disappearance rate were not significantly different in groups with a micropapillary pattern constituting at least 5% or less than 5% of the entire tumor. Conclusion A radiomics approach can be used to interrogate an entire tumor in a noninvasive manner. Combining imaging parameters with clinical features can provide added diagnostic value to identify the presence of a micropapillary component and thus, can influence proper treatment planning. © 2016 International Association for the Study of Lung Cance-
dc.description.uri1-
dc.language영어-
dc.publisherELSEVIER SCIENCE INC-
dc.subjectComputed tomography-
dc.subjectLung adenocarcinoma-
dc.subjectMicropapillary-
dc.subjectQuantitative imaging-
dc.subjectRadiomics-
dc.titleImaging Phenotyping Using Radiomics to Predict Micropapillary Pattern within Lung Adenocarcinoma-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid000399063900007-
dc.identifier.scopusid2-s2.0-85015919834-
dc.identifier.rimsid59278ko
dc.date.tcdate2018-10-01-
dc.contributor.affiliatedAuthorHyunjin Park-
dc.identifier.doi10.1016/j.jtho.2016.11.2230-
dc.identifier.bibliographicCitationJOURNAL OF THORACIC ONCOLOGY, v.12, no.4, pp.624 - 632-
dc.citation.titleJOURNAL OF THORACIC ONCOLOGY-
dc.citation.volume12-
dc.citation.number4-
dc.citation.startPage624-
dc.citation.endPage632-
dc.date.scptcdate2018-10-01-
dc.description.wostc3-
dc.description.scptc3-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusRESPIRATORY SOCIETY CLASSIFICATION-
dc.subject.keywordPlusSIGNIFICANTLY POOR-PROGNOSIS-
dc.subject.keywordPlusLEARNING HEALTH-CARE-
dc.subject.keywordPlusINTERNATIONAL-ASSOCIATION-
dc.subject.keywordPlusPULMONARY ADENOCARCINOMA-
dc.subject.keywordPlusTUMOR RECURRENCE-
dc.subject.keywordPlusPATIENT SURVIVAL-
dc.subject.keywordPlusFDG-PET-
dc.subject.keywordPlusRESECTION-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordAuthorLung adenocarcinoma-
dc.subject.keywordAuthorMicropapillary-
dc.subject.keywordAuthorComputed tomography-
dc.subject.keywordAuthorQuantitative imaging-
dc.subject.keywordAuthorRadiomics-
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
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