Evidence map›Paper›PMID 38660703›Full record

ArticleTechnology in cancer research & treatment

Feasibility Study of Computed Tomographic Radiomics Model for the Prediction of Early and Intermediate Stage Hepatocellular Carcinoma Using BCLC Staging.

Han Dong, Lu Yang, Duan Shaofeng, Guo Lili

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Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Han DongThe Affiliated Huai'an First People's Hospital of Nanjing Medical University, Huai'an, Jiangsu Province, China.ORCID 0000-0002-8737-8254
Lu YangThe Affiliated Huai'an First People's Hospital of Nanjing Medical University, Huai'an, Jiangsu Province, China.
Duan ShaofengGE Healthcare, Shanghai, China.ORCID 0000-0001-9413-7574
Guo LiliThe Affiliated Huai'an First People's Hospital of Nanjing Medical University, Huai'an, Jiangsu Province, China.ORCID 0000-0002-4034-6968

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is a serious health concern because of its high morbidity and mortality. The prognosis of HCC largely depends on the disease stage at diagnosis. Computed tomography (CT) image textural analysis is an image analysis technique that has emerged in recent years.

objectiveTo probe the feasibility of a CT radiomic model for predicting early (stages 0, A) and intermediate (stage B) HCC using Barcelona Clinic Liver Cancer (BCLC) staging.

methodsA total of 190 patients with stages 0, A, or B HCC according to CT-enhanced arterial and portal vein phase images were retrospectively assessed. The lesions were delineated manually to construct a region of interest (ROI) consisting of the entire tumor mass. Consequently, the textural profiles of the ROIs were extracted by specific software. Least absolute shrinkage and selection operator dimensionality reduction was used to screen the textural profiles and obtain the area under the receiver operating characteristic curve values.

resultsWithin the test cohort, the area under the curve (AUC) values associated with arterial-phase images and BCLC stages 0, A, and B disease were 0.99, 0.98, and 0.99, respectively. The overall accuracy rate was 92.7%. The AUC values associated with portal vein phase images and BCLC stages 0, A, and B disease were 0.98, 0.95, and 0.99, respectively, with an overall accuracy of 90.9%.

conclusionThe CT radiomic model can be used to predict the BCLC stage of early-stage and intermediate-stage HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsNeoplasm StagingAdultAgedArea Under CurveFeasibility StudiesFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesROC CurveBCLC staging systemcomputed tomographyhepatocellular carcinomaradiomics

Identifiers

PMID38660703
PMCPMC11044781

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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.