@article{a9b93c76f33d44e49afa9bcc3d6d7745,
title = "Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation",
abstract = "Hepatocellular carcinoma (HCC) is the most common primary liver neoplasm, and its incidence has doubled over the past two decades owing to increasing risk factors. Despite surveillance, most HCC cases are diagnosed at advanced stages and can only be treated using transarterial chemo-embolization (TACE) or systemic therapy. TACE failure may occur with incidence reaching up to 60% of cases, leaving patients with a financial and emotional burden. Radiomics has emerged as a new tool capable of predicting tumor response to TACE from pre-procedural computed tomography (CT) studies. This data report defines the HCC-TACE data collection of confirmed HCC patients who underwent TACE and have pre- and post-procedure CT imaging studies and available treatment outcomes (time-to-progression and overall survival). Clinically curated segmentation of pre-procedural CT studies was done for the purpose of algorithm training for prediction and automatic liver tumor segmentation.",
author = "Moawad, {Ahmed W.} and Ali Morshid and Khalaf, {Ahmed M.} and Elmohr, {Mohab M.} and Hazle, {John D.} and David Fuentes and Mohamed Badawy and Kaseb, {Ahmed O.} and Manal Hassan and Armeen Mahvash and Janio Szklaruk and Aliyya Qayyum and Abdelrahman Abusaif and Bennett, {William C.} and Nolan, {Tracy S.} and Brittney Camp and Elsayes, {Khaled M.}",
note = "Funding Information: Work was supported by the NIH/NCI under award number P30 CA016672 and U24CA215109 and also by the MD Anderson QIAC Partnership in Research Grants. The TCIA and POSDA Tools portions of this project have been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Under this contract the University of Arkansas is funded by Leidos Biomedical Research subcontract 16 × 011. Support was also provided by U24CA215109. Funding Information: Work was supported by the NIH/NCI under award number P30 CA016672 and U24CA215109 and also by the MD Anderson QIAC Partnership in Research Grants. The TCIA and POSDA Tools portions of this project have been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Under this contract the University of Arkansas is funded by Leidos Biomedical Research subcontract 16 × 011. Support was also provided by U24CA215109. We thank Dawn Chalaire at the Scientific Publication Department at the University of Texas MD Anderson Cancer Center for her contribution to this article. Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
month = dec,
doi = "10.1038/s41597-023-01928-3",
language = "English (US)",
volume = "10",
journal = "Scientific Data",
issn = "2052-4463",
publisher = "Nature Publishing Group",
number = "1",
}