Evidence map›Paper›PMID 38782785›Full record

ArticleAbdominal radiology (New York)2024

Quantitative radiomics and qualitative LI-RADS imaging descriptors for non-invasive assessment of β-catenin mutation status in hepatocellular carcinoma.

Dooman Arefan, Nicholas M D'Ardenne, Negaur Iranpour, Roberta Catania, Jacob Yousef, Kalina Chupetlovska, Akshata Moghe, Biatta Sholosh, Senthur Thangasamy, Amir A Borhani and 4 more

Abstract read
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In one paragraph

Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. [Hepatobiliary phase image manifestation classification and pathological features of nodules in nodules accompanied by hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024
    Article
  5. Review
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

14 authors.

Dooman Arefan *Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA.
Nicholas M D'Ardenne *Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA.
Negaur IranpourDepartment of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
Roberta CataniaDepartment of Radiology, Northwestern University Feinberg School of Medicine, 676 N. Saint Clair Street, Suite 800, Chicago, IL, 60611, USA.
Jacob YousefDepartment of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA.
Kalina ChupetlovskaDiagnostic Imaging Department, University Hospital "Saint Ivan Rilski", Sofia, Bulgaria.
Akshata MogheDivision of Gastroenterology and Hepatology, Department of Medicine, University of Texas Medical Branch, Galveston, TX, USA.
Biatta SholoshDepartment of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA.
Senthur ThangasamyDepartment of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA.
Amir A BorhaniDepartment of Radiology, Northwestern University Feinberg School of Medicine, 676 N. Saint Clair Street, Suite 800, Chicago, IL, 60611, USA.
Aatur D SinghiPittsburgh Liver Research Center, University of Pittsburgh Medical Center and University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Satdarshan P MongaPittsburgh Liver Research Center, University of Pittsburgh Medical Center and University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Alessandro FurlanDepartment of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA.
Shandong WuDepartment of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Suite 200, Pittsburgh, PA, 15213, USA. wus3@upmc.edu.

Funding

Pittsburgh Liver Research CenterP30DK120531 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Shuchang Silvia Liu · 2019 to 2026
$10.9M
Targeting tumor metabolism and immune environment via beta-catenin: Towards precision medicine in HCCR01CA251155 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LUJAMBIO, AMAIA, MONGA, SATDARSHAN SINGH · 2020 to 2024
$3.1M
Investigating Multifactorial Beta-catenin Activation in Hepatocellular CancersR01CA250227 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Xin Chen, Satdarshan Singh Monga · 2021 to 2026
$3.0M
Foundation for the National Institutes of Health P30DK120531Foundation for the National Institutes of Health R01CA250227Foundation for the National Institutes of Health R01CA251155NCI NIH HHS R01 CA250227NCI NIH HHS R01 CA251155NIDDK NIH HHS P30 DK120531
6 · The paper itself

Abstract

purposeGain-of-function mutations in CTNNB1, gene encoding for β-catenin, are observed in 25-30% of hepatocellular carcinomas (HCCs). Recent studies have shown β-catenin activation to have distinct roles in HCC susceptibility to mTOR inhibitors and resistance to immunotherapy. Our goal was to develop and test a computational imaging-based model to non-invasively assess β-catenin activation in HCC, since liver biopsies are often not done due to risk of complications.

methodsThis IRB-approved retrospective study included 134 subjects with pathologically proven HCC and available β-catenin activation status, who also had either CT or MR imaging of the liver performed within 1 year of histological assessment. For qualitative descriptors, experienced radiologists assessed the presence of imaging features listed in LI-RADS v2018. For quantitative analysis, a single biopsy proven tumor underwent a 3D segmentation and radiomics features were extracted. We developed prediction models to assess the β-catenin activation in HCC using both qualitative and quantitative descriptors.

resultsThere were 41 cases (31%) with β-catenin mutation and 93 cases (69%) without. The model's AUC was 0.70 (95% CI 0.60, 0.79) using radiomics features and 0.64 (0.52, 0.74; p = 0.468) using qualitative descriptors. However, when combined, the AUC increased to 0.88 (0.80, 0.92; p = 0.009). Among the LI-RADS descriptors, the presence of a nodule-in-nodule showed a significant association with β-catenin mutations (p = 0.015). Additionally, 88 radiomics features exhibited a significant association (p < 0.05) with β-catenin mutations.

conclusionCombination of LI-RADS descriptors and CT/MRI-derived radiomics determine β-catenin activation status in HCC with high confidence, making precision medicine a possibility.

Indexed as

beta CateninCarcinoma, HepatocellularLiver NeoplasmsMagnetic Resonance ImagingTomography, X-Ray ComputedAdultAgedFemaleHumansLiverMaleMiddle AgedMutationRadiology Information SystemsRadiomicsRetrospective Studiesbeta CateninCTNNB1 protein, humanBeta cateninHepatocellular carcinomaLI-RADS descriptorsMedical imagingRadiogenomicsRadiomics

Identifiers

PMID38782785

What Socratic holds

Textmetadata
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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 Socratic graph.