{"id":45407,"date":"2023-11-20T05:11:32","date_gmt":"2023-11-20T11:11:32","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/collection\/b-mode-and-ceus-liver\/"},"modified":"2023-11-20T05:11:32","modified_gmt":"2023-11-20T11:11:32","slug":"b-mode-and-ceus-liver","status":"publish","type":"tcia_collection","link":"https:\/\/stage.cancerimagingarchive.net\/collection\/b-mode-and-ceus-liver\/","title":{"rendered":"B-MODE-AND-CEUS-LIVER"},"featured_media":8533,"template":"","class_list":["post-45407","tcia_collection","type-tcia_collection","status-publish","has-post-thumbnail"],"cancer_types":["Liver Cancer"],"citations":[45395,9225],"collection_doi":"10.7937\/TCIA.2021.v4z7-tc39","collection_download_info":"","collection_downloads":[45397,45399],"versions":[45405],"additional_resources":"<p>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.<\/p>\n<li><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=b_mode_and_ceus_liver\">Imaging Data Commons (IDC)<\/a>\u00a0(Imaging Data)<\/li>","cancer_locations":["Liver"],"collection_page_accessibility":"Public","publications_related":"","version_change_log_archived":"<h3>Version 2 (Current): Updated 2022\/02\/18<\/h3>\n<table><colgroup> <col\/> <col\/> <\/colgroup><tbody><tr><th>Data Type<\/th><th>Download all or Query\/Filter<\/th><\/tr><tr><td colspan=\"1\">Images (DICOM, 253 GB)<\/td><td colspan=\"1\"><div><p><br\/>\n<a download=\"B-mode-and-CEUS-Liver_20220218.tcia\" href=\"\/wp-content\/uploads\/B-mode-and-CEUS-Liver_20220218.tcia\"><button><i><\/i> Download<\/button><\/a>\u00a0\n<\/p>\u00a0 \u00a0<p>\n<a href=\"https:\/\/www.cancerimagingarchive.net\/nbia-search\/?CollectionCriteria=B-mode-and-CEUS-Liver\"><button><i><\/i> Search<\/button><\/a>\u00a0\n<br\/><\/p><p>(Download requires <a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a> app)<\/p><\/div><\/td><\/tr><tr><td>Clinical data (XLSX, 24KB)<\/td><td><div><p><a data-linked-resource-container-id=\"61080617\" data-linked-resource-container-version=\"42\" data-linked-resource-content-type=\"application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet\" data-linked-resource-default-alias=\"B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\" data-linked-resource-id=\"95224080\" data-linked-resource-type=\"attachment\" data-linked-resource-version=\"1\" data-nice-type=\"Excel Spreadsheet\" download=\"B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\" href=\"\/wp-content\/uploads\/B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\">\u00a0<\/a>\n<a download=\"B-mode-and-CEUS-Liver_ReferenceStandards_v2_20220218.xlsx\" href=\"\/wp-content\/uploads\/B-mode-and-CEUS-Liver_ReferenceStandards_v2_20220218.xlsx\"><button><i><\/i> Download<\/button><\/a>\u00a0\n<\/p><\/div><\/td><\/tr><\/tbody><\/table>\n<p>Added 45 new participants and a new spreadsheet version.<\/p><h3>Version 1: Updated 2021\/08\/04<\/h3>\n<table><colgroup> <col\/> <col\/> <\/colgroup><tbody><tr><th>Data Type<\/th><th>Download all or Query\/Filter<\/th><\/tr><tr><td colspan=\"1\">Images (DICOM, 208 GB)<\/td><td colspan=\"1\"><div><p><br\/>\n<a download=\"B-mode-and-CEUS-Liver_20210728.tcia\" href=\"\/wp-content\/uploads\/B-mode-and-CEUS-Liver_20210728.tcia\"><button><i><\/i> Download<\/button><\/a>\u00a0\n<\/p>\u00a0 \u00a0<p>(Download requires <a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a> app)<\/p><\/div><\/td><\/tr><tr><td>Clinical data (XLSX, 19KB)<\/td><td><div><p><a data-linked-resource-container-id=\"61080617\" data-linked-resource-container-version=\"42\" data-linked-resource-content-type=\"application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet\" data-linked-resource-default-alias=\"B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\" data-linked-resource-id=\"95224080\" data-linked-resource-type=\"attachment\" data-linked-resource-version=\"1\" data-nice-type=\"Excel Spreadsheet\" download=\"B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\" href=\"\/wp-content\/uploads\/B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\">\u00a0<\/a>\n<a download=\"B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\" href=\"\/wp-content\/uploads\/B-mode-and-CEUS-Liver_ReferenceStandards_v1_20210804.xlsx\"><button><i><\/i> Download<\/button><\/a>\u00a0\n<\/p><\/div><\/td><\/tr><\/tbody><\/table>\n<p>7\/28\/21 Added new participants.<br\/>8\/4\/21 Added spreadsheet.<br\/><\/p>","collection_status":"Complete","publications_using":"<p>TCIA maintains <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>.<\/p>","related_analysis_results":false,"species":["Human"],"version_number":"2","collection_title":"Ultrasound data of a variety of liver masses","date_updated":"2022-02-18","related_collection":false,"subjects":"120","analysis_results":"","collection_short_title":"B-mode-and-CEUS-Liver","data_types":["US"],"version_change_log":"<p>Added 45 new participants and a new spreadsheet version.<\/p>","collection_browse_title":"B-mode-and-CEUS-Liver","detailed_description":"","supporting_data":["Clinical"],"collection_featured_image":{"ID":"8533","post_author":"29","post_date":"2023-09-14 00:50:01","post_date_gmt":"2023-09-14 05:50:01","post_content":"","post_title":"ceus","post_excerpt":"","post_status":"inherit","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ceus","to_ping":"","pinged":"","post_modified":"2023-11-20 05:11:32","post_modified_gmt":"2023-11-20 11:11:32","post_content_filtered":"","post_parent":"45407","guid":"https:\/\/stage.cancerimagingarchive.net\/wp-content\/uploads\/ceus.png","menu_order":"0","post_type":"attachment","post_mime_type":"image\/png","comment_count":"0","pod_item_id":"8533"},"collection_summary":"<p><\/p>\nData were generated as part of two ongoing clinical trials investigating the use of <u><strong>c<\/strong><\/u>ontrast-<u><strong>e<\/strong><\/u>nhanced <u><strong>u<\/strong><\/u>ltra<u><strong>s<\/strong><\/u>ound to a) characterize indeterminate liver lesions and b) monitor treatment response to loco regional therapy. Ultrasound data was obtained on a variety of state of the art ultrasound scanners with curvilinear probes. Gain, dynamic range, focus position and depth were optimized for image quality by the performing sonographer. Images of the mass in both sagittal and transverse planes were obtained and saved in DICOM format. Full cine-loops of the contrast enhanced ultrasound are also saved in DICOM format. The reference standard used for lesion characterization included tissue pathology and contrast-enhanced cross-sectional imaging within 1 month of the ultrasound exam. The initial treatment response to transarterial chemoembolization is also available for many hepatocellular carcinoma (HCC) cases and uses pathology, retreatment angiography, or longer-term tumor response on cross-sectional imaging as a reference standard.<p>We expect these images can be used in a wide variety of image processing application. We are currently exploring a variety of automated intelligence algorithms for AI-based lesion characterization. Algorithms for object detection and segmentation may also be of interest. As the studies that have generated this data are also ongoing, it is expected that we can add volumetric data, contrast-enhanced ultrasound cine loops, and longer-term treatment response data to this data set in the future.<\/p>","collection_acknowledgements":"<p>We would like to acknowledge the individuals and institutions that have provided data for this collection:<\/p>\n<ul><li><p><em>Thomas Jefferson University, Philadelphia, PA, USA - Special thanks to John Eisenbrey, PhD from the Department of Radiology, Andrej Lyshchik, MD, PhD from the Department of Radiology, Corinne Wessner, MBA from the Department of Radiology<\/em><\/p><\/li><li>This work was supported in whole or in part under R01 CA194307 ; R01 CA215520 .<\/li><\/ul>","collection_funding":"","hide_from_browse_table":"0","program":["Community"],"_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections\/45407","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections"}],"about":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/types\/tcia_collection"}],"version-history":[{"count":0,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections\/45407\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media\/8533"}],"wp:attachment":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media?parent=45407"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}