Evidence map›Paper›PMID 36653372›Full record

ArticleScientific data2023

Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation.

Ahmed W Moawad, Ali Morshid, Ahmed M Khalaf, Mohab M Elmohr, John D Hazle, David Fuentes, Mohamed Badawy, Ahmed O Kaseb, Manal Hassan, Armeen Mahvash and 7 more

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 3 institutions in 1 country.

Ahmed W MoawadDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. awmoawad@gmail.com.ORCID 0000-0001-6860-1513
Ali MorshidDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. alimorshid@gmail.com.
Ahmed M KhalafDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.ORCID 0000-0002-0355-1516
Mohab M ElmohrDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. mohab.elmohr@gmail.com.
John D HazleDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. jhazle@mdanderson.org.
David FuentesDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. DTFuentes@mdanderson.org.
Mohamed BadawyDepartments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Ahmed O KasebDepartments of Gastrointestinal Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. akaseb@mdanderson.org.
Manal HassanDepartments of Gastrointestinal Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. mhassan@mdanderson.org.
Armeen MahvashDepartments of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Janio SzklarukDepartments of Body Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. JSzklaru@mdanderson.org.
Aliyya QayyumDepartments of Body Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Abdelrahman AbusaifDepartments of Body Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
William C BennettDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA. WCBennett@uams.edu.
Tracy S NolanDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA. TNolan@uams.edu.ORCID 0000-0002-7023-7586
Brittney CampDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA. BCamp@uams.edu.
Khaled M ElsayesDepartments of Body Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. KMElsayes@mdanderson.org.
The University of Texas MD Anderson Cancer Center · USUniversity of Arkansas for Medical Sciences · USCatholic Medical Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
TCIA Sustainment and Scalability - Platforms for Quantitative Imaging Informatics in Precision MedicineU24CA215109 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI BANERJEE, IMON, PRIOR, FRED WILLIAM · 2017 to 2021
$8.5M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENCI NIH HHS P30 CA016672NCI NIH HHS U24 CA215109
6 · The paper itself

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.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsChemoembolization, TherapeuticHumansTreatment Outcome

Identifiers

PMID36653372
PMCPMC9849450
OpenAlexW4317209201

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.