Evidence map›Paper›PMID 39658716›Full record

ArticleAnnals of surgical oncology2025

Development and External Validation of a Combined Clinical-Radiomic Model for Predicting Insufficient Hypertrophy of the Future Liver Remnant following Portal Vein Embolization.

Qiang Wang, Torkel B Brismar, Dennis Björk, Erik Baubeta, Gert Lindell, Bergthor Björnsson, Ernesto Sparrelid

Abstract readValidation StudyMulticenter Study
In one paragraph

Article in Annals of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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.

Qiang WangDepartment of Clinical Science, Intervention and Technology (CLINTEC), Division of Medical Imaging and Technology, Karolinska Institutet, Stockholm, Sweden. qiang.wang@ki.se.ORCID http://orcid.org/0000-0001-6686-6630
Torkel B BrismarDepartment of Clinical Science, Intervention and Technology (CLINTEC), Division of Medical Imaging and Technology, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-3409-1938
Dennis BjörkDepartment of Surgery, Linköping University Hospital, Linköping, Sweden.ORCID http://orcid.org/0009-0002-1568-2481
Erik BaubetaDepartment of Imaging and Functional Medicine, Skåne University Hospital, Lund, Sweden.ORCID http://orcid.org/0000-0001-9177-7322
Gert LindellDepartment of Surgery, Skåne University Hospital Comprehensive Cancer Center, Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden.
Bergthor BjörnssonDepartment of Surgery, Linköping University Hospital, Linköping, Sweden.ORCID http://orcid.org/0000-0001-9704-1260
Ernesto SparrelidDivision of Surgery and Oncology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-0259-8328

Funding

Karolinska Ruth and Richard Julin Foundation 2023-00474
6 · The paper itself

Abstract

objectivesThis study aimed to develop and externally validate a model for predicting insufficient future liver remnant (FLR) hypertrophy after portal vein embolization (PVE) based on clinical factors and radiomics of pretreatment computed tomography (CT) PATIENTS AND

methodsClinical information and CT scans of 241 consecutive patients from three Swedish centers were retrospectively collected. One center (120 patients) was applied for model development, and the other two (59 and 62 patients) as test cohorts. Logistic regression analysis was adopted for clinical model development. A FLR radiomics signature was constructed from the CT images using the support vector machine. A model combining clinical factors and FLR radiomics signature was developed. Area under the curve (AUC) was adopted for predictive performance evaluation

resultsThree independent clinical factors were identified for model construction: pretreatment standardized FLR (odds ratio (OR): 1.12, 95% confidence interval (CI): 1.04-1.20), alanine transaminase (ALT) level (OR: 0.98, 95% CI: 0.97-0.99), and PVE material (OR: 0.27, 95% CI: 0.08-0.87). This clinical model showed an AUC of 0.75, 0.71, and 0.68 in the three cohorts, respectively. A total of 833 radiomics features were extracted, and after feature dimension reduction, 16 features were selected for FLR radiomics signature construction. When adding it to the clinical model, the AUC of the combined model increased to 0.80, 0.76, and 0.72, respectively. However, the increase was not significant.

conclusionsPretreatment CT radiomics showed added value to the clinical model for predicting FLR hypertrophy following PVE. Although not reaching statistically significant, the evolving radiomics holds a potential to supplement traditional predictors of FLR hypertrophy.

Indexed as

Carcinoma, HepatocellularEmbolization, TherapeuticLiverLiver NeoplasmsPortal VeinTomography, X-Ray ComputedAdultAgedFemaleFollow-Up StudiesHumansHypertrophyLiver RegenerationMaleMiddle AgedPrognosisFuture liver remnantLiver cancerMachine learningPortal vein embolizationRadiomics

Identifiers

PMID39658716
PMCPMC11811440

What Socratic holds

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LicenceCC BY
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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.