{"id":45529,"date":"2023-11-20T05:18:35","date_gmt":"2023-11-20T11:18:35","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/analysis-result\/radiomics-tumor-phenotypes\/"},"modified":"2024-11-07T12:23:00","modified_gmt":"2024-11-07T18:23:00","slug":"radiomics-tumor-phenotypes","status":"publish","type":"tcia_analysis_result","link":"https:\/\/stage.cancerimagingarchive.net\/analysis-result\/radiomics-tumor-phenotypes\/","title":{"rendered":"RADIOMICS-TUMOR-PHENOTYPES"},"featured_media":7119,"template":"","class_list":["post-45529","tcia_analysis_result","type-tcia_analysis_result","status-publish","has-post-thumbnail"],"cancer_types":["Lung Cancer","Head and Neck Cancer"],"citations":[45509,45511,9225],"result_doi":"10.7937\/K9\/TCIA.2014..UA0JGPDG","result_download_info":"","result_downloads":[45513],"version_change_log_archived":"Version 2 (Current): 2020\/03\/23\r\nAdded links to the recently published TCIA collections which reflect the additional arms of the study described in Nature Communications (http:\/\/doi.org\/10.1038\/ncomms5006).\r\n\r\nData TypeDownload all or Query\/FilterImage Data (DICOM) and Clinical DataPlease refer to each Collection page to download available images and clinical data:NSCLC-Radiomics\u00a0(Lung1)NSCLC-Radiomics-Genomics\u00a0(Lung3)Head-Neck-Radiomics-HN1\u00a0(H&amp;N1)NSCLC-Radiomics-Interobserver1 (Multiple delineation)RIDER Lung CT Segmentation Labels from: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach\u00a0(RIDER test\/retest)NSCLC-Radiomics-Genomics\u00a0(Lung3)Gene Expression Datahttp:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE58661Version 1 : 2016\/08\/02\r\nData TypeDownload all or Query\/FilterImage Data (DICOM)Clinical Data (CSV, XLS)Gene Expression Data","versions":[45527],"additional_resources":"The following external resources have been made available by the data submitters.\u00a0 These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.\r\n<ul>\r\n \t<li><a href=\"http:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE58661\">Genomics data<\/a> in Gene Expression Omnibus for <a href=\"https:\/\/cancerimagingarchive.net\/collection\/nsclc-radiomics-genomics\/\" target=\"_blank\" rel=\"noopener\">NSCLC-Radiomics-Genomics<\/a> (Lung3) Gene Expression Data<\/li>\r\n<\/ul>","cancer_locations":["Lung","Head-Neck"],"publications_related":"","result_page_accessibility":"Public","detailed_description":"","publications_using":"TCIA maintains\u00a0<a href=\"https:\/\/commons.datacite.org\/doi.org\/10.7937\/K9\/TCIA.2014..UA0JGPDG\">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":"Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach","species":false,"version_number":"2","date_updated":"2020-03-23","related_collections":[43039,43015,42417,43005],"result_short_title":"Radiomics-Tumor-Phenotypes","subjects":"1019","related_analysis_results":false,"result_browse_title":"Radiomics-Tumor-Phenotypes","supporting_data":["Genomics"],"version_change_log":"Added links to the recently published TCIA collections which reflect the additional arms of the study described <span style=\"color: #172b4d;\">in Nature Communications (<\/span><a class=\"external-link\" style=\"text-decoration: underline; text-align: left;\" href=\"http:\/\/doi.org\/10.1038\/ncomms5006\" rel=\"nofollow\">http:\/\/doi.org\/10.1038\/ncomms5006<\/a><span style=\"color: #172b4d;\">).<\/span>","collections":"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\u00a0<a href=\"\/wp-content\/uploads\/TCIA-License-for-Limited-Access-Collections-w-NC-Final20220121.pdf\" download=\"TCIA-License-for-Limited-Access-Collections-w-NC-Final20220121.pdf\">TCIA No Commercial Limited Access License<\/a>\u00a0to\u00a0<a href=\"mailto:help@cancerimagingarchive.net\">help@cancerimagingarchive.net<\/a>\u00a0before accessing this portion of the data.\r\n<table><colgroup> <col \/> <col \/> <col \/><\/colgroup>\r\n<thead>\r\n<tr>\r\n<th>Source Data Type<\/th>\r\n<th>\r\n<div>\r\n\r\nDownload\r\n\r\n<\/div><\/th>\r\n<th>License<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>Corresponding Original Images from Head-Neck-Radiomics-HN1 (H&amp;N1) (DICOM)<\/td>\r\n<td>\r\n<div><\/div>\r\n<a href=\"\/wp-content\/uploads\/Head-Neck-Radiomics-HN1-Version-2-Sept-2019-NBIA-manifest.tcia\" download=\"Head-Neck-Radiomics-HN1-Version-2-Sept-2019-NBIA-manifest.tcia\"><button><i><\/i> Download<\/button><\/a>\r\n\r\n<a href=\"https:\/\/nbia.cancerimagingarchive.net\/nbia-search\/?MinNumberOfStudiesCriteria=1&amp;CollectionCriteria=HEAD-NECK-RADIOMICS-HN1\"><button><i><\/i> Search<\/button><\/a>\r\n(Download requires <a href=\"\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a>)<\/td>\r\n<td>\r\n<div>\r\n\r\n<a href=\"\/wp-content\/uploads\/TCIA-License-for-Limited-Access-Collections-w-NC-Final20220121.pdf\" download=\"TCIA-License-for-Limited-Access-Collections-w-NC-Final20220121.pdf\">TCIA No Commercial Limited<\/a>\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Corresponding Original Images from NSCLC-Radiomics (Lung1), NSCLC-Radiomics-Genomics (Lung3),\u00a0NSCLC-Radiomics-Interobserver1 (Multiple delineation)\u00a0(DICOM)<\/td>\r\n<td>\r\n<div>\r\n\r\n<a href=\"\/wp-content\/uploads\/manifest-20230519_CC3-NC.tcia\" download=\"manifest-20230519_CC3-NC.tcia\"><button><i><\/i> Download<\/button><\/a>\r\n\r\n<a href=\"https:\/\/nbia.cancerimagingarchive.net\/nbia-search\/?MinNumberOfStudiesCriteria=1&amp;CollectionCriteria=NSCLC-Radiomics,NSCLC-Radiomics-Interobserver1,NSCLC-Radiomics-Genomics\"><button><i><\/i> Search<\/button><\/a>\r\n\r\n(Download requires <a href=\"\/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:\/\/creativecommons.org\/licenses\/by-nc\/3.0\/\">CC BY-NC 3.0<\/a>\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Corresponding Original Images from RIDER-LungCT-Seg (RIDER test\/retest)\u00a0\u00a0(DICOM)<\/td>\r\n<td>\r\n<div>\r\n\r\n<a href=\"\/wp-content\/uploads\/RIDER-Lung-CT-RTSTRUCTS-DICOM-SEGS-Leonard-Wee-Feb-10-2020.tcia\" download=\"RIDER-Lung-CT-RTSTRUCTS-DICOM-SEGS-Leonard-Wee-Feb-10-2020.tcia\"><button><i><\/i> Download<\/button><\/a>\r\n\r\n(Download requires <a href=\"\/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:\/\/creativecommons.org\/licenses\/by\/3.0\/\">CC BY 3.0<\/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:\/\/cancerimagingarchive.net\/collection\/nsclc-radiomics\/\" target=\"_blank\" rel=\"noopener\">NSCLC-Radiomics<\/a><\/li>\r\n \t<li><a href=\"https:\/\/cancerimagingarchive.net\/collection\/nsclc-radiomics-genomics\/\" target=\"_blank\" rel=\"noopener\">NSCLC-Radiomics-Genomics<\/a><\/li>\r\n \t<li><a href=\"https:\/\/cancerimagingarchive.net\/collection\/head-neck-radiomics-hn1\/\" target=\"_blank\" rel=\"noopener\">HEAD-NECK-RADIOMICS-HN1<\/a><\/li>\r\n \t<li><a href=\"https:\/\/cancerimagingarchive.net\/collection\/nsclc-radiomics-interobserver1\/\" target=\"_blank\" rel=\"noopener\">NSCLC-Radiomics-Interobserver1<\/a><\/li>\r\n \t<li><a href=\"https:\/\/cancerimagingarchive.net\/analysis-result\/rider-lungct-seg\/\" target=\"_blank\" rel=\"noopener\">RIDER-LungCT-Seg<\/a><\/li>\r\n<\/ul>","result_summary":"This data applies a radiomic approach to computed tomography data of 1,019 patients with lung or head-and-neck cancer which are described in Nature Communications (<a href=\"http:\/\/doi.org\/10.1038\/ncomms5006\">http:\/\/doi.org\/10.1038\/ncomms5006<\/a>).\u00a0 The various arms of the study are represented in TCIA as distinct Collections including\u00a0<a href=\"https:\/\/www.cancerimagingarchive.net\/collection\/nsclc-radiomics\">NSCLC-Radiomics<\/a>\u00a0(Lung1),\u00a0<a href=\"https:\/\/cancerimagingarchive.net\/collection\/nsclc-radiomics-genomics\/\" target=\"_blank\" rel=\"noopener\">NSCLC-Radiomics-Genomics<\/a>\u00a0(Lung3),\u00a0<a href=\"https:\/\/www.cancerimagingarchive.net\/collection\/head-neck-radiomics-hn1\/\">Head-Neck-Radiomics-HN1<\/a>\u00a0(H&amp;N1),\u00a0<a href=\"https:\/\/cancerimagingarchive.net\/collection\/nsclc-radiomics-interobserver1\/\" target=\"_blank\" rel=\"noopener\">NSCLC-Radiomics-Interobserver1<\/a> (Multiple delineation), and <a href=\"https:\/\/cancerimagingarchive.net\/analysis-result\/rider-lungct-seg\/\" target=\"_blank\" rel=\"noopener\">RIDER-LungCT-Seg<\/a>\u00a0(RIDER test\/retest).\r\n\r\nRadiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features. In present analysis 440 features quantifying tumour image intensity, shape and texture, were extracted. We found that a large number of radiomic features have prognostic power in independent data sets, many of which were not identified as significant before. Radiogenomics analysis revealed that a prognostic radiomic signature, capturing intra-tumour heterogeneity, was associated with underlying gene-expression patterns. These data suggest that radiomics identifies a general prognostic phenotype existing in both lung and head-and-neck cancer. This may have a clinical impact as imaging is routinely used in clinical practice, providing an unprecedented opportunity to improve decision-support in cancer treatment at low cost.","collection_downloads":[45515,45517,45519],"result_featured_image":{"ID":"7119","post_author":"29","post_date":"2023-09-13 09:32:26","post_date_gmt":"2023-09-13 14:32:26","post_content":"","post_title":"NSCLC-RADIOMICS-GRAPHIC","post_excerpt":"","post_status":"inherit","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"nsclc-radiomics-graphic","to_ping":"","pinged":"","post_modified":"2023-12-04 12:50:07","post_modified_gmt":"2023-12-04 18:50:07","post_content_filtered":"","post_parent":"42417","guid":"https:\/\/stage.cancerimagingarchive.net\/wp-content\/uploads\/NSCLC-RADIOMICS-GRAPHIC.jpg","menu_order":"0","post_type":"attachment","post_mime_type":"image\/jpeg","comment_count":"0","pod_item_id":"7119"},"result_acknowledgements":"","hide_from_browse_table":"1","program":["Community"],"_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/analysis-results\/45529","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\/45529\/revisions"}],"predecessor-version":[{"id":47467,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/analysis-results\/45529\/revisions\/47467"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media\/7119"}],"wp:attachment":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media?parent=45529"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}