BROWSE

Related Scientist

cnir's photo.

cnir
뇌과학이미징연구단
more info

ITEM VIEW & DOWNLOAD

Clustering approach to identify intratumour heterogeneity combining FDG PET and diffusion-weighted MRI in lung adenocarcinoma

DC Field Value Language
dc.contributor.authorJonghoon Kim-
dc.contributor.authorSeong-Yoon Ryu-
dc.contributor.authorSeung-Hak Lee-
dc.contributor.authorHo Yun Lee-
dc.contributor.authorHyunjin Park-
dc.date.available2019-01-30T01:57:40Z-
dc.date.created2018-07-23-
dc.date.issued2019-01-
dc.identifier.issn0938-7994-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/5346-
dc.description.abstractObjectives: Malignant tumours consist of biologically heterogeneous components; identifying and stratifying those various subregions is an important research topic. We aimed to show the effectiveness of an intratumour partitioning method using clustering to identify highly aggressive tumour subregions, determining prognosis based on pre-treatment PET and DWI in stage IV lung adenocarcinoma. Methods: Eighteen patients who underwent both baseline PET and DWI were recruited. Pre-treatment imaging of SUV and ADC values were used to form intensity vectors within manually specified ROIs. We applied k-means clustering to intensity vectors to yield distinct subregions, then chose the subregion that best matched the criteria for high SUV and low ADC to identify tumour subregions with high aggressiveness. We stratified patients into high- and low-risk groups based on subregion volume with high aggressiveness and conducted survival analyses. This approach is referred to as the partitioning approach. For comparison, we computed tumour subregions with high aggressiveness without clustering and repeated the described procedure; this is referred to as the voxel-wise approach. Results: The partitioning approach led to high-risk (median SUVmax = 14.25 and median ADC = 1.26x10-3 mm2/s) and low-risk (median SUVmax = 14.64 and median ADC = 1.09x10-3 mm2/s) subgroups. Our partitioning approach identified significant differences in survival between high- and low-risk subgroups (hazard ratio, 4.062, 95% confidence interval, 1.21 – 13.58, p-value: 0.035). The voxel-wise approach did not identify significant differences in survival between high- and low-risk subgroups (p-value: 0.325). Conclusion: Our partitioning approach identified intratumour subregions that were predictors of survival. Key Points: • Multimodal imaging of PET and DWI is useful for assessing intratumour heterogeneity.• Data-driven clustering identified subregions which might be highly aggressive for lung adenocarcinoma.• The data-driven partitioning results might be predictors of survival. © 2018 European Society of Radiolog c European Society of Radiology 2018-
dc.description.uri1-
dc.language영어-
dc.publisherSPRINGER-
dc.subjectAdenocarcinoma of lung-
dc.subjectClustering analysis-
dc.subjectIntratumour heterogeneity-
dc.subjectMultimodal imaging-
dc.subjectSurvival analysis-
dc.titleClustering approach to identify intratumour heterogeneity combining FDG PET and diffusion-weighted MRI in lung adenocarcinoma-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid000453471200054-
dc.identifier.scopusid2-s2.0-85048798160-
dc.identifier.rimsid64150-
dc.contributor.affiliatedAuthorHyunjin Park-
dc.identifier.doi10.1007/s00330-018-5590-0-
dc.identifier.bibliographicCitationEUROPEAN RADIOLOGY, v.29, no.1, pp.468 - 475-
dc.citation.titleEUROPEAN RADIOLOGY-
dc.citation.volume29-
dc.citation.number1-
dc.citation.startPage468-
dc.citation.endPage475-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorAdenocarcinoma of lung-
dc.subject.keywordAuthorClustering analysis-
dc.subject.keywordAuthorIntratumour heterogeneity-
dc.subject.keywordAuthorMultimodal imaging-
dc.subject.keywordAuthorSurvival analysis-
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
Files in This Item:
38_박현진_Clustering approach to identify intratumour heterogeneity combining FDG PET and diffusion-weighted MRI in lung adenocarcinoma.pdfDownload

qrcode

  • facebook

    twitter

  • Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
해당 아이템을 이메일로 공유하기 원하시면 인증을 거치시기 바랍니다.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse