{"id":5633,"date":"2023-09-04T03:14:04","date_gmt":"2023-09-04T03:14:04","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/hcc-tace-seg\/"},"modified":"2023-09-13T12:00:45","modified_gmt":"2023-09-13T12:00:45","slug":"hcc-tace-seg","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/hcc-tace-seg\/","title":{"rendered":"HCC-TACE-SEG"},"featured_media":0,"template":"","citation-tax":[],"cancer_types":["Hepatocellular Carcinoma"],"citations":[4538,4539,2925],"collection_doi":"10.7937\/TCIA.5FNA-0924","collection_download_info":"Click the Versions tab for more info about data releases.","collection_downloads":[5131,5132],"full_export":"<h1 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-Summary\">Summary<\/h1>Hepatocellular carcinoma (HCC) is the most common primary liver cancer with incidences doubled over the past two decades due to increasing risk factors. Despite surveillance, the majority of HCC cases are diagnosed at advanced stages that can be treated only using (Transarterial chemoembolization) TACE, or systemic therapy. TACE failure can occur to 60% of patients receiving the procedure, with subsequent financial and emotional burden. Radiomics have emerged as a new tool capable of predicting tumor response to TACE from pre-procedural CT study.<\/p><p>This retrospectively acquired data collection includes pre- and post-procedure CT imaging studies of 105\u00a0confirmed HCC patients who underwent TACE between 2002 and 2012 with an available treatment outcome, in the form of time-to-progression and overall survival. Baseline imaging includes multiphasic contrast-enhanced CT with no image artifacts (e.g. surgical clip) and was obtained 1-12 weeks (average 3 weeks) prior to the first TACE session. Semiautomatic segmentation of liver, tumor, and blood vessels created using <a href=\"https:\/\/assets.thermofisher.com\/TFS-Assets\/MSD\/Product-Guides\/users-guide-amira-software-2019.pdf\" class=\"external-link\" rel=\"nofollow\">AMIRA <\/a>was manually clinically curated. These segmentations of each pre-procedural CT study were done for the purpose of algorithm training for prediction and automatic liver tumor segmentation, and are provided here (NIfTI converted to DICOM-SEG format).<h3 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-Acknowledgements\"><span>Acknowledgements<\/span><\/h3><p>We would like to acknowledge the individuals and institutions that have provided data for this collection:<\/p><ul><li><p>The <strong>University of Texas MD Anderson Cancer Center<\/strong>, Departments of Imaging Physics, Body Imaging, Gastrointestinal Oncology, Epidemiology, and Interventional Radiology.<\/p><\/li><li><p>Harmonization of the components of this dataset, including into standard DICOM representation, was supported in part by the NCI Imaging Data Commons consortium. NCI Imaging Data Commons consortium is supported by the contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI.<\/p><\/li><\/ul><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=\"#702302294297f56b2c9149338e7439e0a99f98ae\"><strong>Data Access<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#70230229b0f67f5753794847910bfc98b107f8f8\"><strong>Detailed Description<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#70230229f913ce205fbf4acd9b85688c69669a3c\"><strong>Citations &amp; Data Usage Policy<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#70230229fdd3964706c34713afaeeeae34d64be6\"><strong>Versions<\/strong><\/a> <\/li><\/ul><div class=\"tabs-pane  active-pane \" id=\"702302294297f56b2c9149338e7439e0a99f98ae\" active=\"true\" name=\"Data Access\" ><h3 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-DataAccess\">Data Access<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup><col\/><col\/><col\/><\/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\"><p><span style=\"color: rgb(0,0,0);\">Images and Segmentations (DICOM, 26.6 GB)<\/span><\/p><\/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\/70230229\/HCC-TACE-Seg_v1_202201.tcia?api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/nbia.cancerimagingarchive.net\/nbia-search\/?MinNumberOfStudiesCriteria=1&amp;CollectionCriteria=HCC-TACE-Seg\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-search-color\"><i class=\"fa fa-search\" \/> Search<\/button><\/a>\u00a0\n<\/span><span style=\"color: rgb(33,37,41);text-decoration: none;\"><br\/>(Download requires\u00a0<\/span><span style=\"color: rgb(33,37,41);text-decoration: none;\">the<span>\u00a0<\/span><\/span><a style=\"text-decoration: none;text-align: left;\" rel=\"nofollow\" href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a>)<\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 4.0<\/a><\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\"><span style=\"color: rgb(0,0,0);\">Clinical data with description (XLSX)<\/span><\/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\/70230229\/HCC-TACE-Seg_clinical_data-V2.xlsx\" 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\/4.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 4.0<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p class=\"auto-cursor-target\">Click the Versions tab for more info about data releases.<\/p><h3 class=\"auto-cursor-target\" id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-AdditionalResourcesforthisDataset\">Additional Resources for this Dataset<\/h3><p style=\"text-align: left;\">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.<\/p><ul style=\"text-align: left;\"><li>Source code is publicly available on Github at <a href=\"https:\/\/github.com\/fuentesdt\/livermask\" class=\"external-link\" rel=\"nofollow\">https:\/\/github.com\/fuentesdt\/livermask<\/a><\/li><li>Multiple open-source software can be used to visualize the DICOM-Seg files; the authors of this Collection highly recommend using the latest stable version of 3D-Slicer for data visualization after installing the \u201cquantitative reporting\u201d extension. Step-by-step installation and guidance can be found in: \u00a0<a href=\"https:\/\/qiicr.gitbook.io\/quantitativereporting-guide\/\" class=\"external-link\" rel=\"nofollow\">https:\/\/qiicr.gitbook.io\/quantitativereporting-guide\/<\/a>. For the full list of the available software, please visit dcmqi documentation for instructions at: <a href=\"https:\/\/dicom4qi.readthedocs.io\/en\/latest\/results\/seg\/\" class=\"external-link\" rel=\"nofollow\">https:\/\/dicom4qi.readthedocs.io\/en\/latest\/results\/seg\/<\/a><\/li><\/ul><p class=\"auto-cursor-target\"><span style=\"color: rgb(33,37,41);\">The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.<\/span><\/p><ul style=\"text-align: left;\"><li class=\"auto-cursor-target\"><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=hcc_tace_seg\" class=\"external-link\" rel=\"nofollow\">Imaging Data Commons (IDC)<\/a><span>\u00a0<\/span>(Imaging Data)<\/li><\/ul><p><br\/><\/p><\/div><div class=\"tabs-pane \" id=\"70230229b0f67f5753794847910bfc98b107f8f8\" name=\"Detailed Description\" ><h3 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-DetailedDescription\">Detailed Description<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup><col\/><col\/><\/colgroup><tbody><tr><th class=\"confluenceTh\"><p>Image Statistics<\/p><\/th><th class=\"confluenceTh\"><br\/><\/th><\/tr><tr><td class=\"confluenceTd\"><p>Modalities<\/p><\/td><td style=\"text-align: center;\" class=\"confluenceTd\"><p>CT, SEG<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Patients<\/p><\/td><td style=\"text-align: center;\" class=\"confluenceTd\"><p>105<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Studies<\/p><\/td><td style=\"text-align: center;\" class=\"confluenceTd\"><p>214<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Series<\/p><\/td><td style=\"text-align: center;\" class=\"confluenceTd\"><p>677<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Images<\/p><\/td><td style=\"text-align: center;\" class=\"confluenceTd\"><p>51,968<\/p><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Images Size (GB)<\/td><td style=\"text-align: center;\" colspan=\"1\" class=\"confluenceTd\">26.6<\/td><\/tr><\/tbody><\/table><\/div><p><strong>These SEG were originally created as NIfTI format files (<span style=\"color: rgb(32,33,36);\"><a href=\"https:\/\/assets.thermofisher.com\/TFS-Assets\/MSD\/Product-Guides\/users-guide-amira-software-2019.pdf\" class=\"external-link\" rel=\"nofollow\">Amira Software, ThermoFisher 2019<\/a><\/span><span style=\"color: rgb(32,33,36);\">)\u00a0<\/span>, and converted to DICOM. <\/strong><\/p><p>Github link for the NN code:\u00a0<a href=\"https:\/\/urldefense.proofpoint.com\/v2\/url?u=https-3A__github.com_fuentesdt_livermask&amp;d=DwMFaQ&amp;c=27AKQ-AFTMvLXtgZ7shZqsfSXu-Fwzpqk4BoASshREk&amp;r=aq1HkYBvkUpcOMwNkL5Y4w&amp;m=obPEcQ6UABV0hPU9H_uUgg1bYf2QYJajWbPjU029GfE&amp;s=t4bcHiioZa-P-cW0H2dQ7NE1yhTZiBIlbpAvilY8v0Q&amp;e=\" class=\"external-link\" rel=\"nofollow\">https:\/\/github.com\/fuentesdt\/livermask<\/a><\/p><p>Note - the mask on Patient ID HCC_001 (SEG file Series UID 1.2.276.0.7230010.3.1.3.8323329.719.1600928570.399942) has a slightly different dimension than the CT (Series UI <span class=\"iceOutTxt\">1.3.6.1.4.1.14519.5.2.1.1706.8374.302065206690360709343725942120)\u00a0<\/span>. This difference is is far from the interesting features and the masks, so clinical interpretation should be unaffected by this discrepancy.<\/p><\/div><div class=\"tabs-pane \" id=\"70230229f913ce205fbf4acd9b85688c69669a3c\" name=\"Citations BITVOODOO_ANDamp; Data Usage Policy\" ><h3 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-Citations&amp;DataUsagePolicy\">Citations &amp; Data Usage Policy<\/h3><p><span>\nUsers of this data must abide by the <a href=\"https:\/\/wiki.cancerimagingarchive.net\/x\/c4hF\" class=\"external-link\" re=\"nofollow\" rel=\"nofollow\">TCIA Data Usage Policy<\/a> and the <a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" class=\"external-link\" rel=\"nofollow\">Creative Commons Attribution 4.0 International License<\/a> under which it has been published. Attribution should include references to the following citations:<\/span><\/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>Moawad, A. W., Fuentes, D., Morshid, A., Khalaf, A. M., Elmohr, M. M., Abusaif, A., Hazle, J. D., Kaseb, A. O., Hassan, M., Mahvash, A., Szklaruk, J., Qayyom, A., &amp; Elsayes, K. (2021). <strong>Multimodality annotated HCC cases with and without advanced imaging segmentation<\/strong> [Data set]. The Cancer Imaging Archive. <a href=\"https:\/\/doi.org\/10.7937\/TCIA.5FNA-0924\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.7937\/TCIA.5FNA-0924<\/a><\/p><\/div><\/div><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>Morshid, A., Elsayes, K. M., Khalaf, A. M., Elmohr, M. M., Yu, J., Kaseb, A. O., Hassan, M., Mahvash, A., Wang, Z., Hazle, J. D., &amp; Fuentes, D. (2019). <strong>A Machine Learning Model to Predict Hepatocellular Carcinoma Response to Transcatheter Arterial Chemoembolization.<\/strong> Radiology: Artificial Intelligence, 1(5), e180021. <a href=\"https:\/\/doi.org\/10.1148\/ryai.2019180021\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1148\/ryai.2019180021<\/a>\u00a0<\/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><h3 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-OtherPublicationsUsingThisData\">Other Publications Using This Data<\/h3><p><span>TCIA maintains\u00a0<\/span><a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\" class=\"external-link\" rel=\"nofollow\">a list of publications<\/a><span> which leverage TCIA data. <\/span> If you have a manuscript you'd like to add please<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\" class=\"external-link\" rel=\"nofollow\"> contact the TCIA Helpdesk<\/a>.<\/p><ol><li>Moawad, A. W., Morshid, A., Khalaf, A. M., Elmohr, M. M., Hazle, J. D., Fuentes, D., Badawy, M., Kaseb, A. O., Hassan, M., Mahvash, A., Szklaruk, J., Qayyum, A., Abusaif, A., Bennett, W. C., Nolan, T. S., Camp, B., &amp; Elsayes, K. M. (2023). <strong>Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation<\/strong>. In Scientific Data (Vol. 10, Issue 1).\u00a0 <a href=\"https:\/\/doi.org\/10.1038\/s41597-023-01928-3\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1038\/s41597-023-01928-3<\/a><\/li><\/ol><\/div><div class=\"tabs-pane \" id=\"70230229fdd3964706c34713afaeeeae34d64be6\" name=\"Versions\" ><h3 id=\"MultimodalityannotatedHCCcaseswithandwithoutadvancedimagingsegmentation(HCCTACESeg)-Version1(Current):Updated2022\/08\/17\">Version 1 (Current): Updated 2022\/08\/17<\/h3><div class=\"table-wrap\"><table class=\"wrapped fixed-width confluenceTable\" style=\"width: 57.8195%;\"><colgroup><col style=\"width: 32.0446%;\"\/><col style=\"width: 46.9019%;\"\/><col style=\"width: 21.0535%;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\"><span>Data Type<\/span><\/th><th class=\"confluenceTh\"><span>Download all or Query\/Filter<\/span><\/th><th class=\"confluenceTh\"><span>License<\/span><\/th><\/tr><tr><td class=\"confluenceTd\"><p><span style=\"color: rgb(0,0,0);\">Images and Segmentations (DICOM, 26.6 GB)<\/span><\/p><\/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\/70230229\/HCC-TACE-Seg_v1_202201.tcia?api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/nbia.cancerimagingarchive.net\/nbia-search\/?MinNumberOfStudiesCriteria=1&amp;CollectionCriteria=HCC-TACE-Seg\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-search-color\"><i class=\"fa fa-search\" \/> Search<\/button><\/a>\u00a0\n<\/span><br\/><\/p><p><span style=\"color: rgb(33,37,41);text-decoration: none;\">(Download requires\u00a0<\/span><span style=\"color: rgb(33,37,41);text-decoration: none;\">the<span>\u00a0<\/span><\/span><a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\" rel=\"nofollow\" style=\"text-decoration: none;text-align: left;\">NBIA Data Retriever<\/a>)<\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 4.0<\/a><\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\"><span style=\"color: rgb(0,0,0);\">Clinical data with description (XLSX)<\/span><\/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\/70230229\/HCC-TACE-Seg_clinical_data-V2.xlsx\" 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\/4.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 4.0<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/div><\/div><p><br\/><\/p><p><br\/><\/p>","versions":false,"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.\n<ul><li>Source code is publicly available on Github at <a href=\"https:\/\/github.com\/fuentesdt\/livermask\">https:\/\/github.com\/fuentesdt\/livermask<\/a><\/li><li>Multiple open-source software can be used to visualize the DICOM-Seg files; the authors of this Collection highly recommend using the latest stable version of 3D-Slicer for data visualization after installing the \u201cquantitative reporting\u201d extension. Step-by-step installation and guidance can be found in: \u00a0<a href=\"https:\/\/qiicr.gitbook.io\/quantitativereporting-guide\/\">https:\/\/qiicr.gitbook.io\/quantitativereporting-guide\/<\/a>. For the full list of the available software, please visit dcmqi documentation for instructions at: <a href=\"https:\/\/dicom4qi.readthedocs.io\/en\/latest\/results\/seg\/\">https:\/\/dicom4qi.readthedocs.io\/en\/latest\/results\/seg\/<\/a><\/li><\/ul>\nThe NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.\n<ul><li><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=hcc_tace_seg\">Imaging Data Commons (IDC)<\/a>\u00a0(Imaging Data)<\/li><\/ul>\n<br\/>","cancer_locations":["Liver"],"collection_page_accessibility":"Public","publications_related":"","version_change_log":"","version_change_log_archived":"","analysis_results":"","collection_status":"Complete","publications_using":"TCIA maintains\u00a0<a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\">a list of publications<\/a> which 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>.\n<ol><li>Moawad, A. W., Morshid, A., Khalaf, A. M., Elmohr, M. M., Hazle, J. D., Fuentes, D., Badawy, M., Kaseb, A. O., Hassan, M., Mahvash, A., Szklaruk, J., Qayyum, A., Abusaif, A., Bennett, W. C., Nolan, T. S., Camp, B., &amp; Elsayes, K. M. (2023). <strong>Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation<\/strong>. In Scientific Data (Vol. 10, Issue 1).\u00a0 <a href=\"https:\/\/doi.org\/10.1038\/s41597-023-01928-3\">https:\/\/doi.org\/10.1038\/s41597-023-01928-3<\/a><\/li><\/ol>","species":["Human"],"collection_title":"Multimodality annotated HCC cases with and without advanced imaging segmentation","detailed_description":"<strong>These SEG were originally created as NIfTI format files (<a href=\"https:\/\/assets.thermofisher.com\/TFS-Assets\/MSD\/Product-Guides\/users-guide-amira-software-2019.pdf\">Amira Software, ThermoFisher 2019<\/a>)\u00a0, and converted to DICOM. <\/strong>\nGithub link for the NN code:\u00a0<a href=\"https:\/\/urldefense.proofpoint.com\/v2\/url?u=https-3A__github.com_fuentesdt_livermask&amp;d=DwMFaQ&amp;c=27AKQ-AFTMvLXtgZ7shZqsfSXu-Fwzpqk4BoASshREk&amp;r=aq1HkYBvkUpcOMwNkL5Y4w&amp;m=obPEcQ6UABV0hPU9H_uUgg1bYf2QYJajWbPjU029GfE&amp;s=t4bcHiioZa-P-cW0H2dQ7NE1yhTZiBIlbpAvilY8v0Q&amp;e=\">https:\/\/github.com\/fuentesdt\/livermask<\/a>\nNote - the mask on Patient ID HCC_001 (SEG file Series UID 1.2.276.0.7230010.3.1.3.8323329.719.1600928570.399942) has a slightly different dimension than the CT (Series UI 1.3.6.1.4.1.14519.5.2.1.1706.8374.302065206690360709343725942120)\u00a0. This difference is is far from the interesting features and the masks, so clinical interpretation should be unaffected by this discrepancy.","related_analysis_results":false,"subjects":"105","collection_short_title":"HCC-TACE-Seg","data_types":["CT","SEG"],"date_updated":"2023-09-13","collection_browse_title":"","supporting_data":["Clinical","Image Analyses"],"collection_featured_image":false,"collection_summary":"Hepatocellular carcinoma (HCC) is the most common primary liver cancer with incidences doubled over the past two decades due to increasing risk factors. Despite surveillance, the majority of HCC cases are diagnosed at advanced stages that can be treated only using (Transarterial chemoembolization) TACE, or systemic therapy. TACE failure can occur to 60% of patients receiving the procedure, with subsequent financial and emotional burden. Radiomics have emerged as a new tool capable of predicting tumor response to TACE from pre-procedural CT study.<p>This retrospectively acquired data collection includes pre- and post-procedure CT imaging studies of 105\u00a0confirmed HCC patients who underwent TACE between 2002 and 2012 with an available treatment outcome, in the form of time-to-progression and overall survival. Baseline imaging includes multiphasic contrast-enhanced CT with no image artifacts (e.g. surgical clip) and was obtained 1-12 weeks (average 3 weeks) prior to the first TACE session. Semiautomatic segmentation of liver, tumor, and blood vessels created using <a href=\"https:\/\/assets.thermofisher.com\/TFS-Assets\/MSD\/Product-Guides\/users-guide-amira-software-2019.pdf\">AMIRA <\/a>was manually clinically curated. These segmentations of each pre-procedural CT study were done for the purpose of algorithm training for prediction and automatic liver tumor segmentation, and are provided here (NIfTI converted to DICOM-SEG format).<\/p>","collection_acknowledgements":"We would like to acknowledge the individuals and institutions that have provided data for this collection:\n<ul><li><p>The <strong>University of Texas MD Anderson Cancer Center<\/strong>, Departments of Imaging Physics, Body Imaging, Gastrointestinal Oncology, Epidemiology, and Interventional Radiology.<\/p><\/li><li><p>Harmonization of the components of this dataset, including into standard DICOM representation, was supported in part by the NCI Imaging Data Commons consortium. NCI Imaging Data Commons consortium is supported by the contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI.<\/p><\/li><\/ul>","collection_funding":"","hide_from_browse_table":[],"_links":{"self":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections\/5633"}],"collection":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections"}],"about":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/types\/tcia_collection"}],"wp:attachment":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/media?parent=5633"}],"wp:term":[{"taxonomy":"tcia_citation_tax","embeddable":true,"href":"https:\/\/cm.vastapps.dev\/api\/v1\/citation-tax?post=5633"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}