{"id":45543,"date":"2023-11-20T05:19:25","date_gmt":"2023-11-20T11:19:25","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/analysis-result\/gbm-mr-ner-outcomes\/"},"modified":"2024-11-07T12:19:42","modified_gmt":"2024-11-07T18:19:42","slug":"gbm-mr-ner-outcomes","status":"publish","type":"tcia_analysis_result","link":"https:\/\/stage.cancerimagingarchive.net\/analysis-result\/gbm-mr-ner-outcomes\/","title":{"rendered":"GBM-MR-NER-OUTCOMES"},"featured_media":0,"template":"","class_list":["post-45543","tcia_analysis_result","type-tcia_analysis_result","status-publish"],"cancer_types":["Glioblastoma"],"citations":[45531,45533,9225],"result_doi":"10.7937\/K9\/TCIA.2014.FAB7YRPZ","result_download_info":"Some data in this collection contains images that could potentially be used to reconstruct a human face. To safeguard the privacy of participants, users must sign and submit a <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/4556915\/TCIA%20Restricted%20License%2020220519.pdf?version=1&amp;modificationDate=1652964581655&amp;api=v2\">TCIA Restricted License Agreement<\/a> to <a href=\"mailto:help@cancerimagingarchive.net\">help@cancerimagingarchive.net<\/a> before accessing the data.\r\n\r\n&nbsp;","result_downloads":[45537,45539],"version_change_log_archived":"Version 1 (Current): 2014\/07\/24\r\n   Data TypeDownload all or Query\/FilterImage Data (DICOM)Supplemental Data (XLS)","versions":false,"additional_resources":"","cancer_locations":["Brain"],"publications_related":"","result_page_accessibility":"Limited","detailed_description":"Please see <a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/DSC+T2*+MR+Perfusion+Analysis\">DSC T2* MR Perfusion Analysis<\/a> for more information about the authors' perfusion analysis.","publications_using":"TCIA maintains\u00a0<a href=\"https:\/\/commons.datacite.org\/doi.org\/10.7937\/K9\/TCIA.2014.FAB7YRPZ\">a list of publications<\/a>\u00a0that leveraged this dataset. If you have a manuscript you\u2019d like to add please\u00a0<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\">contact TCIA\u2019s Helpdesk<\/a>.","result_title":"Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor","species":false,"version_number":"1","date_updated":"2014-07-24","related_collections":[43903],"result_short_title":"GBM-MR-NER-Outcomes","subjects":"45","related_analysis_results":false,"result_browse_title":"Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor (GBM-MR-NER-Outcomes)","supporting_data":false,"version_change_log":"","collections":"Below is a list of the Collections used in these analyses:\r\n<table><colgroup> <col \/> <col \/> <col \/><\/colgroup>\r\n<tbody>\r\n<tr>\r\n<th>Source Data Type<\/th>\r\n<th>Download all or Query\/Filter<\/th>\r\n<th>License<\/th>\r\n<\/tr>\r\n<tr>\r\n<td>Original Data from TCGA-GBM (DICOM, 45 subjects, 46 studies, 488 series, 67730 images, 6.81 GB )<\/td>\r\n<td>\r\n<div>\r\n\r\n<a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/18514300\/manifest-tcga-gbm-gbm-ner-outcomes.tcia?api=v2\"><button><i><\/i> Download<\/button><\/a>(Download requires <a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a>)\r\n\r\n<\/div><\/td>\r\n<td>\r\n<div>\r\n\r\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>\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<ul>\r\n \t<li><a href=\"https:\/\/doi.org\/10.7937\/K9\/TCIA.2016.RNYFUYE9\">TCGA-GBM<\/a><\/li>\r\n<\/ul>","result_summary":"This manuscript correlates patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along with clinical and genomic markers. Forty-five patients with GBM underwent baseline imaging with contrast material-enhanced magnetic resonance (MR) imaging and dynamic susceptibility contrast-enhanced T2*-weighted perfusion MR imaging.\u00a0 See <a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/DSC+T2*+MR+Perfusion+Analysis\">DSC T2* MR Perfusion Analysis<\/a> for more information about the authors' perfusion analysis.\u00a0 Molecular and clinical predictors of survival were obtained. Single and multivariable models of overall survival (OS) and progression-free survival (PFS) were explored with Kaplan-Meier estimates, Cox regression, and random survival forests.\r\n\r\nWorsening OS (log-rank test, P = .0103) and PFS (log-rank test, P = .0223) were associated with increasing relative cerebral blood volume of NER (rCBV NER ), which was higher with deep white matter involvement (t test, P = .0482) and poor NER margin definition (t test, P = .0147). NER crossing the midline was the only morphologic feature of NER associated with poor survival (log-rank test, P = .0125). Preoperative Karnofsky performance score (KPS) and resection extent (n = 30) were clinically significant OS predictors (log-rank test, P = .0176 and P = .0038, respectively). No genomic alterations were associated with survival, except patients with high rCBV NER \u00a0and wild-type epidermal growth factor receptor (EGFR) mutation had significantly poor survival (log-rank test, P = .0306; area under the receiver operating characteristic curve = 0.62). Combining resection extent with rCBV NER \u00a0marginally improved prognostic ability (permutation, P = .084). Random forest models of presurgical predictors indicated rCBV NER \u00a0as the top predictor; also important were KPS, age at diagnosis, and NER crossing the midline. A multivariable model containing rCBV NER , age at diagnosis, and KPS can be used to group patients with more than 1 year of difference in observed median survival (0.49-1.79 years). Conclusion Patients with high rCBV NER \u00a0and NER crossing the midline and those with high rCBV NER \u00a0and wild-type EGFR mutation showed poor survival. In multivariable survival models, however, rCBV NER \u00a0provided unique prognostic information that went above and beyond the assessment of all NER imaging features, as well as clinical and genomic features.","collection_downloads":[45541],"result_featured_image":false,"result_acknowledgements":"","hide_from_browse_table":"0","program":["TCGA"],"_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/analysis-results\/45543","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/analysis-results"}],"about":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/types\/tcia_analysis_result"}],"version-history":[{"count":1,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/analysis-results\/45543\/revisions"}],"predecessor-version":[{"id":47043,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/analysis-results\/45543\/revisions\/47043"}],"wp:attachment":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media?parent=45543"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}