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Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer Improvements Using Radiomics

DC Field Value Language
dc.contributor.authorGeewon Lee-
dc.contributor.authorSo Hyeon Bak-
dc.contributor.authorHo Yun Lee-
dc.contributor.authorJoon Young Choi-
dc.contributor.authorHyunjin Park-
dc.contributor.authorSeung-Hak Lee-
dc.contributor.authorYoshiharu Ohno-
dc.contributor.authorMizuki Nishino-
dc.contributor.authorEdwin J.R. van Beek-
dc.contributor.authorKyung Soo Lee-
dc.date.available2019-07-19T05:38:21Z-
dc.date.created2019-06-19-
dc.date.issued2019-03-
dc.identifier.issn0883-5993-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/5878-
dc.description.abstractMultimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics. © 2019 Wolters Kluwer Health, Inc. All rights reserved.-
dc.description.uri1-
dc.language영어-
dc.publisherLIPPINCOTT WILLIAMS & WILKINS-
dc.subjectmolecular targeted therapy-
dc.subjectimmunotherapy-
dc.subjectmedical oncology-
dc.subjectphenotype-
dc.subjectlung cancer response-
dc.subjectimage-
dc.subjectradiomics-
dc.titleMeasurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer Improvements Using Radiomics-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid000460363100005-
dc.identifier.scopusid2-s2.0-85060369519-
dc.identifier.rimsid68609-
dc.contributor.affiliatedAuthorHyunjin Park-
dc.identifier.doi10.1097/RTI.0000000000000390-
dc.identifier.bibliographicCitationJOURNAL OF THORACIC IMAGING, v.34, no.2, pp.103 - 115-
dc.citation.titleJOURNAL OF THORACIC IMAGING-
dc.citation.volume34-
dc.citation.number2-
dc.citation.startPage103-
dc.citation.endPage115-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusSTANDARDIZED UPTAKE VALUES-
dc.subject.keywordPlusSMALL PULMONARY NODULES-
dc.subject.keywordPlusLOW-DOSE CT-
dc.subject.keywordPlusITERATIVE RECONSTRUCTION-
dc.subject.keywordPlusVOLUME MEASUREMENT-
dc.subject.keywordPlusTUMOR VOLUME-
dc.subject.keywordPlusPERFUSION ASSESSMENT-
dc.subject.keywordPlusCHEST CT-
dc.subject.keywordPlusSEGMENTATION-
dc.subject.keywordPlusPET/CT-
dc.subject.keywordAuthormolecular targeted therapy-
dc.subject.keywordAuthorimmunotherapy-
dc.subject.keywordAuthormedical oncology-
dc.subject.keywordAuthorphenotype-
dc.subject.keywordAuthorlung cancer response-
dc.subject.keywordAuthorimage-
dc.subject.keywordAuthorradiomics-
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
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