Evidence map›Paper›PMID 31677071›Full record

ArticleDigestive diseases and sciences2020

Morphomic Signatures Derived from Computed Tomography Predict Hepatocellular Carcinoma Occurrence in Cirrhotic Patients.

Kung-Hao Liang, Peng Zhang, Chih-Lang Lin, Stewart C Wang, Tsung-Hui Hu, Chau-Ting Yeh, Grace L Su

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Digestive diseases and sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

7 authors.

Kung-Hao LiangDepartment of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.
Peng ZhangDepartment of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.
Chih-Lang LinLiver Research Center, Chang Gung Memorial Hospital, Linkou, Taiwan.
Stewart C WangDepartment of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.
Tsung-Hui HuDivision of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
Chau-Ting YehLiver Research Center, Chang Gung Memorial Hospital, Linkou, Taiwan.
Grace L SuMorphomic Analysis Group, University of Michigan Medical School, Ann Arbor, MI, USA. gsu@umich.edu.ORCID 0000-0002-8701-774X

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DAVID P OLSON · 2013 to 2026
$24.3M
Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
NOVEL STRATEGIES TO IMPROVE LIVER CANCER SURVEILLANCE UPTAKE AND EARLY DETECTIONU01CA230669 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LOK, ANNA S.F., SU, GRACE L. · 2018 to 2022
$3.3M
Developing Personalized Treatment for Diabetes Through Novel Imaging MethodsK01DK106296 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, PENG · 2016 to 2018
$465k
NCI NIH HHS U01 CA230669NIDDK NIH HHS K01 DK106296NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

BACKGROUND AND

aimsComputed tomography (CT) provides scans of the human body from which digitized features can be extracted. The aim of this study was to examine the role of these digital biomarkers for predicting subsequent occurrence of hepatocellular carcinoma (HCC) in cirrhotic patients.

methodsA cohort of 269 patients with cirrhosis were recruited and prospectively followed for the occurrence of HCC in Taiwan. CT scans were retrospectively retrieved and computationally processed using analytic morphomics. A predictive score was constructed using Cox regression and the generalized iterative modeling method, maximizing the log likelihood of the time to HCC development. An independent cohort of 274 patients from University of Michigan was utilized to examine the predictive validity of this score in a Western population.

resultsOf the 27 digitized features at the 12th thoracic vertebral level, six features were significantly associated with HCC occurrence. Two digitized features (fascia eccentricity and the bone mineral density) were able to stratify patients into high- and low-risk groups with distinct cumulative incidence of HCC in both the training and validation cohorts (P = 0.015 and 0.044, respectively). When the two digitized features were tested in the Michigan cohort, only bone mineral density remained an effective predictor.

conclusionDigitized features derived from the CT were effective in predicting subsequent occurrence of HCC in cirrhosis patients. The bone mineral density measured on CT was an effective predictor for patients in both Taiwan and USA.

Indexed as

Agedalpha-FetoproteinsBone and BonesBone DensityCarcinoma, HepatocellularFasciaFemaleHepatitis B, ChronicHepatitis C, ChronicHumansImage Processing, Computer-AssistedIncidenceKaplan-Meier EstimateLiver CirrhosisLiver NeoplasmsMalealpha-FetoproteinsBone mineral densityFascia eccentricityPrognosisRetrospective–prospective design

Identifiers

PMID31677071
PMCPMC7195221

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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.