{"id":5747,"date":"2023-09-04T03:35:21","date_gmt":"2023-09-04T03:35:21","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/tcga-gbm-qi-radiogenomics\/"},"modified":"2023-09-13T12:08:18","modified_gmt":"2023-09-13T12:08:18","slug":"tcga-gbm-qi-radiogenomics","status":"publish","type":"tcia_analysis_result","link":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/tcga-gbm-qi-radiogenomics\/","title":{"rendered":"TCGA-GBM-QI-RADIOGENOMICS"},"featured_media":0,"template":"","cancer_types":["Glioblastoma"],"citations":[4746,4747,2925],"full_export":"<h2 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-Description\">Description<\/h2><h4 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-PURPOSE:\">PURPOSE:<\/h4><p>To derive\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">quantitative<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0from magnetic resonance (MR) images that characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to create\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">radiogenomic<\/span>\u00a0maps associating these\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0with various molecular data.<\/p><h4 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-MATERIALSANDMETHODS:\">MATERIALS AND METHODS:<\/h4><p>Clinical, molecular, and MR imaging data for GBMs in 55 patients were obtained from the\u00a0<a href=\"https:\/\/wiki.cancerimagingarchive.net\/pages\/viewpage.action?pageId=1966258\">The Cancer Genome Atlas Glioblastoma Multiforme Collection (TCGA-GBM)<\/a> collection after local ethics committee and institutional review board approval. Regions of interest (ROIs) corresponding to enhancing necrotic portions of tumor and peritumoral edema were drawn and saved in <a href=\"https:\/\/rubinlab.stanford.edu\/node\/319\" class=\"external-link\" rel=\"nofollow\">AIM format<\/a>. Q<span class=\"highlight\" style=\"color: rgb(0,0,0);\">uantitative<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0were derived from these ROIs. Robust\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">quantitative<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0were defined on the basis of an intraclass correlation coefficient of 0.6 for a digital algorithmic modification and a test-retest\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">analysis<\/span>. The robust\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0were visualized by using hierarchic clustering and were correlated with survival by using Cox proportional hazards modeling. Next, these robust\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0were correlated with manual radiologist annotations from the Visually Accessible Rembrandt Images (VASARI) feature set and GBM molecular subgroups by using nonparametric statistical tests. A bioinformatic algorithm was used to create gene expression modules, defined as a set of coexpressed genes together with a multivariate model of cancer driver genes predictive of the module's expression pattern. Modules were correlated with robust\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0by using the Spearman correlation test to create\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">radiogenomic<\/span>\u00a0maps and to link robust\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0with molecular pathways.<\/p><h4 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-RESULTS:\">RESULTS:<\/h4><p>Eighteen\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0passed the robustness\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">analysis<\/span>\u00a0and were further analyzed for the three types of ROIs, for a total of 54\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>. Three enhancement\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0were significantly correlated with survival, 77 significant correlations were found between robust\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">quantitative<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0and the VASARI feature set, and seven\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0were correlated with molecular subgroups (P &lt; .05 for all). A radiogenomics map was created to link\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0with gene expression modules and allowed linkage of 56% (30 of 54) of the\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">image<\/span>\u00a0<span class=\"highlight\" style=\"color: rgb(0,0,0);\">features<\/span>\u00a0with biologic processes.<\/p><h4 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-CONCLUSION:\">CONCLUSION:<\/h4><p><span class=\"highlight\" style=\"color: rgb(0,0,0);\">Radiogenomic<\/span>\u00a0approaches in GBM have the potential to predict clinical and molecular characteristics of tumors noninvasively.<\/p><div class=\"tab-style-builtin\"><div class=\"localtabs-macro\"><div class=\"aui-tabs horizontal-tabs\" role=\"application\" data-aui-responsive=\"true\"><ul class=\"tabs-menu\"><li class=\"menu-item bv-localtab  active-tab \"><a href=\"#167117674562d3a220b14d9c8b70f19d0bc84680\"><strong>Data Access<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#167117673d6775b20da5467baf51ebbe7833a4f6\"><strong>Detailed Description<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#167117670c5df5c865ae4a3aa540e03ff8a64560\"><strong>Citations &amp; Data Usage Policy<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#16711767ecfb11b846544bf985fc59ca402dcb41\"><strong>Versions<\/strong><\/a> <\/li><\/ul><div class=\"tabs-pane  active-pane \" id=\"167117674562d3a220b14d9c8b70f19d0bc84680\" active=\"true\" name=\"Data Access\" ><h3 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-DataAccess\"><span>Data Access<\/span><\/h3><div class=\"table-wrap\"><table class=\"fixed-table wrapped confluenceTable\"><colgroup><col style=\"width: 278.0px;\"\/><col style=\"width: 303.0px;\"\/><col style=\"width: 303.0px;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><th class=\"confluenceTh\">License<\/th><\/tr><tr><td class=\"confluenceTd\">Segmentations (ZIP, 597kB)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><br\/>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/SupplementaryDataZIP_AIMfiles.zip?api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/3.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 3.0<\/a><\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\">Segmentation Summary (XLS, 123kB)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><br\/>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/tcga-gbm%20segmentation%20summary.xls?api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/3.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 3.0<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p class=\"auto-cursor-target\"><span style=\"color: rgb(33,37,41);\">Click the Versions tab for more info about data releases.<\/span><\/p><h4 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-CollectionsUsedinthisThirdPartyAnalysis\"><strong><span style=\"color: rgb(29,28,29);text-decoration: none;\">Collections Used in this Third Party Analysis<\/span><\/strong><\/h4><p><br\/><span style=\"color: rgb(29,28,29);text-decoration: none;\">Below is a list of the Collections used in these analyses:<\/span><\/p><div class=\"table-wrap\"><table class=\"fixed-table wrapped confluenceTable\"><colgroup><col style=\"width: 278.0px;\"\/><col style=\"width: 303.0px;\"\/><col style=\"width: 303.0px;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Source Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><th class=\"confluenceTh\">License<\/th><\/tr><tr><td class=\"confluenceTd\"><p><span style=\"color: rgb(33,37,41);\">Corresponding Original Images from <\/span><span style=\"color: rgb(29,28,29);text-decoration: none;\"><a href=\"https:\/\/doi.org\/10.7937\/K9\/TCIA.2016.RNYFUYE9\" class=\"external-link\" rel=\"nofollow\">TCGA-GBM<\/a> <\/span><span style=\"color: rgb(33,37,41);\">(DICOM, 1.73 GB)<\/span><\/p><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/TCGA-GBM_4fewer_for_RJEFTJBU.tcia?api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p>(Requires<span>\u00a0<a rel=\"nofollow\" href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\" style=\"text-decoration: underline;\">NBIA Data Retriever<\/a><\/span>)<p><br\/><\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/4556915\/TCIA%20Restricted%20License%2020220519.pdf?version=1&amp;modificationDate=1652964581655&amp;api=v2\" class=\"external-link\" rel=\"nofollow\">TCIA Restricted<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p><br\/><\/p><p><span style=\"color: rgb(29,28,29);text-decoration: none;\"><span style=\"color: rgb(23,43,77);\">Please contact <a href=\"mailto:help@cancerimagingarchive.net\" class=\"external-link\" rel=\"nofollow\">help@cancerimagingarchive.net<\/a>\u00a0 with any questions regarding usage.<\/span><\/span><\/p><\/div><div class=\"tabs-pane \" id=\"167117673d6775b20da5467baf51ebbe7833a4f6\" name=\"Detailed Description\" ><h3 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-DetailedDescription\">Detailed Description<\/h3><p>Image Segmentation summary spreadsheet: <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/tcga-gbm%20segmentation%20summary.xls?version=1&amp;modificationDate=1414698995529&amp;api=v2\" data-linked-resource-id=\"19103937\" data-linked-resource-version=\"1\" data-linked-resource-type=\"attachment\" data-linked-resource-default-alias=\"tcga-gbm segmentation summary.xls\" data-nice-type=\"Excel Spreadsheet\" data-linked-resource-content-type=\"application\/vnd.ms-excel\" data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\">tcga-gbm segmentation summary.xls<\/a><\/p><\/div><div class=\"tabs-pane \" id=\"167117670c5df5c865ae4a3aa540e03ff8a64560\" name=\"Citations BITVOODOO_ANDamp; Data Usage Policy\" ><h3 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-Citations&amp;DataUsagePolicy\">Citations &amp; Data Usage Policy\u00a0<\/h3><p class=\"auto-cursor-target\">\n<p>\nUsers must abide by the <a href=\"https:\/\/wiki.cancerimagingarchive.net\/x\/c4hF\" class=\"external-link\" rel=\"nofollow\">TCIA Data Usage Policy and Restrictions<\/a>. Attribution should include references to the following citations:\n<\/p><\/p><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Data Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p><span style=\"color: rgb(102,102,102);\">Gevaert O, Mitchell LA, Achrol AS, Xu J, Echegaray S, Steinberg GK, Cheshier SH, Napel S, Zaharchuk G, Plevritis SK. (2014). <strong>Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features<\/strong>. The Cancer Imaging Archive. <a href=\"https:\/\/doi.org\/10.7937\/K9\/TCIA.2014.RJEFTJBU\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.7937\/K9\/TCIA.2014.RJEFTJBU<\/a> <\/span><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">TCIA Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., &amp; Prior, F. (2013). <strong>The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository<\/strong>. Journal of Digital Imaging, 26(6), 1045\u20131057. <a href=\"https:\/\/doi.org\/10.1007\/s10278-013-9622-7\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/s10278-013-9622-7<\/a><\/p><\/div><\/div><p><span> <strong>In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:<\/strong> <\/span><\/p><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p><span style=\"color: rgb(102,102,102);\">Gevaert, O., Mitchell, L. A., Achrol, A. S., Xu, J., Echegaray, S., Steinberg, G. K., Cheshier, S. H., Napel, S., Zaharchuk, G., &amp; Plevritis, S. K. (2014). <strong>Glioblastoma Multiforme: Exploratory Radiogenomic Analysis by Using Quantitative Image Features<\/strong>. Radiology, 273(1), 168\u2013174. <a href=\"https:\/\/doi.org\/10.1148\/radiol.14131731\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1148\/radiol.14131731<\/a> <\/span><\/p><\/div><\/div><h3 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-OtherPublicationsUsingThisData\">Other Publications Using This Data<\/h3><p>TCIA maintains <a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\" class=\"external-link\" rel=\"nofollow\"> a list of publications<\/a> that leverage TCIA data. If you have a manuscript you'd like to add please<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\" rel=\"nofollow\" class=\"external-link\"> contact the TCIA Helpdesk<\/a>.<\/p><\/div><div class=\"tabs-pane \" id=\"16711767ecfb11b846544bf985fc59ca402dcb41\" name=\"Versions\" ><h3 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-Version2(Current):2020\/10\/07\">Version 2 (Current): 2020\/10\/07<\/h3><div class=\"table-wrap\"><table class=\"fixed-table wrapped confluenceTable\"><colgroup><col style=\"width: 278.0px;\"\/><col style=\"width: 303.0px;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><\/tr><tr><td class=\"confluenceTd\">Image Data (DICOM, 1.73 GB)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/TCGA-GBM_4fewer_for_RJEFTJBU.tcia?version=1&amp;modificationDate=1602095434102&amp;api=v2\" data-linked-resource-id=\"70229707\" data-linked-resource-version=\"1\" data-linked-resource-type=\"attachment\" data-linked-resource-default-alias=\"TCGA-GBM_4fewer_for_RJEFTJBU.tcia\" data-linked-resource-content-type=\"application\/x-nbia-manifest-file\" data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\"><span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image confluence-thumbnail\" draggable=\"false\" height=\"30\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/DOI\/Glioblastoma%20multiforme:%20exploratory%20radiogenomic%20analysis%20by%20using%20quantitative%20image%20features%20(TCGA-GBM-QI-Radiogenomics)\/tcia_wiki_download_button.png?api=v2\"><\/span><\/a><br\/><br\/>(Requires<span>\u00a0<a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\" rel=\"nofollow\" style=\"text-decoration: underline;\">NBIA Data Retriever<\/a><\/span>)<\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Segmentations (ZIP, 597kB)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p><a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/SupplementaryDataZIP_AIMfiles.zip?version=1&amp;modificationDate=1411651374580&amp;api=v2\" data-linked-resource-id=\"19103789\" data-linked-resource-version=\"1\" data-linked-resource-type=\"attachment\" data-linked-resource-default-alias=\"SupplementaryDataZIP_AIMfiles.zip\" data-nice-type=\"Zip Archive\" data-linked-resource-content-type=\"application\/zip\" data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\"><span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image confluence-thumbnail\" draggable=\"false\" height=\"30\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/DOI\/Glioblastoma%20multiforme:%20exploratory%20radiogenomic%20analysis%20by%20using%20quantitative%20image%20features%20(TCGA-GBM-QI-Radiogenomics)\/tcia_wiki_download_button.png?api=v2\"><\/span><\/a><\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Segmentation Summary (XLS, 123kB)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p><a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/tcga-gbm%20segmentation%20summary.xls?version=1&amp;modificationDate=1414698995529&amp;api=v2\" data-linked-resource-id=\"19103937\" data-linked-resource-version=\"1\" data-linked-resource-type=\"attachment\" data-linked-resource-default-alias=\"tcga-gbm segmentation summary.xls\" data-nice-type=\"Excel Spreadsheet\" data-linked-resource-content-type=\"application\/vnd.ms-excel\" data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\"><span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image confluence-thumbnail\" draggable=\"false\" height=\"30\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/DOI\/Glioblastoma%20multiforme:%20exploratory%20radiogenomic%20analysis%20by%20using%20quantitative%20image%20features%20(TCGA-GBM-QI-Radiogenomics)\/tcia_wiki_download_button.png?api=v2\"><\/span><\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p>4 <a href=\"https:\/\/wiki.cancerimagingarchive.net\/pages\/viewpage.action?pageId=1966258\">The Cancer Genome Atlas Glioblastoma Multiforme Collection (TCGA-GBM)<\/a> patients were removed from the collection, which had been previously analyzed by this group.\u00a0 Since the images are no longer available this Analysis Result dataset was updated accordingly.\u00a0<\/p><h3 id=\"Glioblastomamultiforme:exploratoryradiogenomicanalysisbyusingquantitativeimagefeatures(TCGAGBMQIRadiogenomics)-Version1:2014\/11\/05\">Version 1: 2014\/11\/05<\/h3><div class=\"table-wrap\"><table class=\"fixed-table wrapped confluenceTable\"><colgroup><col style=\"width: 278.0px;\"\/><col style=\"width: 303.0px;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><\/tr><tr><td class=\"confluenceTd\">Image Data (DICOM)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>No longer available. See v2 note.<\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Segmentations (ZIP)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p><a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/SupplementaryDataZIP_AIMfiles.zip?version=1&amp;modificationDate=1411651374580&amp;api=v2\" data-linked-resource-id=\"19103789\" data-linked-resource-version=\"1\" data-linked-resource-type=\"attachment\" data-linked-resource-default-alias=\"SupplementaryDataZIP_AIMfiles.zip\" data-nice-type=\"Zip Archive\" data-linked-resource-content-type=\"application\/zip\" data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\"><span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image confluence-thumbnail\" draggable=\"false\" height=\"30\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/DOI\/Glioblastoma%20multiforme:%20exploratory%20radiogenomic%20analysis%20by%20using%20quantitative%20image%20features%20(TCGA-GBM-QI-Radiogenomics)\/tcia_wiki_download_button.png?api=v2\"><\/span><\/a><\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Segmentation Summary (XLS)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p><a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/16711767\/tcga-gbm%20segmentation%20summary.xls?version=1&amp;modificationDate=1414698995529&amp;api=v2\" data-linked-resource-id=\"19103937\" data-linked-resource-version=\"1\" data-linked-resource-type=\"attachment\" data-linked-resource-default-alias=\"tcga-gbm segmentation summary.xls\" data-nice-type=\"Excel Spreadsheet\" data-linked-resource-content-type=\"application\/vnd.ms-excel\" data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\"><span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image confluence-thumbnail\" draggable=\"false\" height=\"30\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/DOI\/Glioblastoma%20multiforme:%20exploratory%20radiogenomic%20analysis%20by%20using%20quantitative%20image%20features%20(TCGA-GBM-QI-Radiogenomics)\/tcia_wiki_download_button.png?api=v2\"><\/span><\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/div><\/div>","make_new_version_button":"","related_collections":["TCGA-GBM"],"result_doi":"10.7937\/K9\/TCIA.2014.RJEFTJBU","versions":false,"cancer_locations":["Brain"],"publications_related":"","result_download_info":"Click the Versions tab for more info about data releases.","result_downloads":[5362,5363],"result_page_accessibility":"Public","version_change_log_archived":"","additional_resources":"","date_updated":"2014-11-05","publications_using":"TCIA maintains <a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\"> a list of publications<\/a> that leverage TCIA data. If you have a manuscript you'd like to add please<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\"> contact the TCIA Helpdesk<\/a>.","result_title":"Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features","subjects":"55","detailed_description":"Image Segmentation summary spreadsheet: <a data-linked-resource-container-id=\"16711767\" data-linked-resource-container-version=\"26\" data-linked-resource-content-type=\"application\/vnd.ms-excel\" data-linked-resource-default-alias=\"tcga-gbm segmentation summary.xls\" data-linked-resource-id=\"19103937\" data-linked-resource-type=\"attachment\" data-linked-resource-version=\"1\" data-nice-type=\"Excel Spreadsheet\" download=\"\" href=\"\/wp-content\/uploads\/tcga-gbm-segmentation-summary.xls\" target=\"_blank\">tcga-gbm segmentation summary.xls<\/a>","result_short_title":"TCGA-GBM-QI-Radiogenomics","supporting_data":["Tumor segmentations"],"version_change_log":"","collections":"<br\/>Below is a list of the Collections used in these analyses:\n<table><colgroup><col\/><col\/><col\/><\/colgroup><tbody><tr><th>Source Data Type<\/th><th>Download all or Query\/Filter<\/th><th>License<\/th><\/tr><tr><td><p>Corresponding Original Images from <a href=\"https:\/\/doi.org\/10.7937\/K9\/TCIA.2016.RNYFUYE9\">TCGA-GBM<\/a> (DICOM, 1.73 GB)<\/p><\/td><td><div><p>\n<a download=\"\" href=\"\/wp-content\/uploads\/TCGA-GBM_4fewer_for_RJEFTJBU.tcia\" target=\"_blank\"><button><i> <\/i> Download<\/button><\/a>\u00a0\n<\/p>(Requires\u00a0<a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a>)<\/div><\/td><td><div><p>\n<a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/4556915\/TCIA%20Restricted%20License%2020220519.pdf?version=1&amp;modificationDate=1652964581655&amp;api=v2\">TCIA Restricted<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table>\n<br\/>\nPlease contact <a href=\"mailto:help@cancerimagingarchive.net\">help@cancerimagingarchive.net<\/a>\u00a0 with any questions regarding usage.","result_browse_title":"","version_number":[],"collection_downloads":[5840],"result_summary":"<h4>PURPOSE:<\/h4>\nTo derive\u00a0quantitative\u00a0image\u00a0features\u00a0from magnetic resonance (MR) images that characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to create\u00a0radiogenomic\u00a0maps associating these\u00a0features\u00a0with various molecular data.\n<h4>MATERIALS AND METHODS:<\/h4>\nClinical, molecular, and MR imaging data for GBMs in 55 patients were obtained from the\u00a0<a href=\"\/pages\/viewpage.action?pageId=1966258\">The Cancer Genome Atlas Glioblastoma Multiforme Collection (TCGA-GBM)<\/a> collection after local ethics committee and institutional review board approval. Regions of interest (ROIs) corresponding to enhancing necrotic portions of tumor and peritumoral edema were drawn and saved in <a href=\"https:\/\/rubinlab.stanford.edu\/node\/319\">AIM format<\/a>. Quantitative\u00a0image\u00a0features\u00a0were derived from these ROIs. Robust\u00a0quantitative\u00a0image\u00a0features\u00a0were defined on the basis of an intraclass correlation coefficient of 0.6 for a digital algorithmic modification and a test-retest\u00a0analysis. The robust\u00a0features\u00a0were visualized by using hierarchic clustering and were correlated with survival by using Cox proportional hazards modeling. Next, these robust\u00a0image\u00a0features\u00a0were correlated with manual radiologist annotations from the Visually Accessible Rembrandt Images (VASARI) feature set and GBM molecular subgroups by using nonparametric statistical tests. A bioinformatic algorithm was used to create gene expression modules, defined as a set of coexpressed genes together with a multivariate model of cancer driver genes predictive of the module's expression pattern. Modules were correlated with robust\u00a0image\u00a0features\u00a0by using the Spearman correlation test to create\u00a0radiogenomic\u00a0maps and to link robust\u00a0image\u00a0features\u00a0with molecular pathways.\n<h4>RESULTS:<\/h4>\nEighteen\u00a0image\u00a0features\u00a0passed the robustness\u00a0analysis\u00a0and were further analyzed for the three types of ROIs, for a total of 54\u00a0image\u00a0features. Three enhancement\u00a0features\u00a0were significantly correlated with survival, 77 significant correlations were found between robust\u00a0quantitative\u00a0features\u00a0and the VASARI feature set, and seven\u00a0image\u00a0features\u00a0were correlated with molecular subgroups (P &lt; .05 for all). A radiogenomics map was created to link\u00a0image\u00a0features\u00a0with gene expression modules and allowed linkage of 56% (30 of 54) of the\u00a0image\u00a0features\u00a0with biologic processes.\n<h4>CONCLUSION:<\/h4>\nRadiogenomic\u00a0approaches in GBM have the potential to predict clinical and molecular characteristics of tumors noninvasively.","result_featured_image":false,"result_acknowledgements":"","hide_from_browse_table":[],"_links":{"self":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/analysis-results\/5747"}],"collection":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/analysis-results"}],"about":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/types\/tcia_analysis_result"}],"wp:attachment":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/media?parent=5747"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}