Evidence map›Paper›PMID 42658410›Full record

ArticleInfection2026

Postoperative CT-derived spleen volumetry for recurrence risk stratification after curative-intent surgery for hepatic alveolar echinococcosis.

Lukas Endrös, Jochen Schneider, Marc Martignoni, Christian Brückner, Markus Mergen, Daniel Spitzl, Felianty Teresa, Manuel Nickel, Mara Goetz, Daniel Martinez Heinemann and 4 more

Abstract read
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Article in Infection, 2026. 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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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Lukas EndrösDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany. l.endroes@uke.de.ORCID https://orcid.org/0009-0007-1817-2598
Jochen SchneiderDepartment of Internal Medicine II, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Marc MartignoniDepartment of Surgery, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Christian BrücknerDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Markus MergenDepartment of Internal Medicine II, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Daniel SpitzlDepartment of Internal Medicine II, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Felianty TeresaDepartment of Diagnostic and Interventional Radiology, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Manuel NickelChair for AI in Healthcare and Medicine, Joint Appointment of TUM School of Medicine and Health und TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Mara GoetzDepartment of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Daniel Martinez HeinemannDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Christian MaegerleinDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Jan S KirschkeDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Rickmer BrarenDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Lisa SteinhelferDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate automated CT-derived spleen volumetry as an opportunistic imaging biomarker for postoperative risk stratification in patients with surgically treated hepatic alveolar echinococcosis (AE) and to compare its prognostic performance with clinical and laboratory parameters.

methodsThis retrospective single-center cohort study included consecutive patients undergoing curative-intent R0 resection for hepatic AE. Baseline was defined as the immediate postoperative CT. Automated spleen segmentation was performed on baseline and 12-month CT using TotalSegmentator, and relative spleen volume change was calculated. The primary endpoint was imaging-defined disease recurrence within 24 months. Clinical, laboratory, serological (indirect hemagglutination assay [IHA], total IgE), and imaging variables were analyzed using univariate logistic regression; significant predictors entered multivariate analysis. ROC analysis assessed discriminatory performance.

results62 patients were included; 21 developed recurrence within 24 months. In univariate analysis, 4 features were significant, with relative spleen volume change showing the strongest association with recurrence (OR 1.158; 95% CI 1.082-1.239; p < 0.001). In multivariate analysis, only relative spleen volume change remained independently associated with recurrence (OR 1.152; 95% CI 1.056-1.255; p = 0.001). Relative spleen volume change showed excellent discrimination (AUC 0.926; 95% CI 0.851-0.978); a 24.3% increase yielded sensitivity of 0.81 and specificity of 0.90. Total IgE and IHA titers, including longitudinal changes, were not associated with recurrence.

conclusionsAutomated postoperative CT-derived spleen volumetry may provide an objective imaging biomarker for postoperative risk stratification after curative-intent surgery for hepatic AE, independently predicting recurrence, whereas routinely available clinical, serological and laboratory markers showed no significant association in this cohort.

Indexed as

alveolar echinococcosisautomated spleen volumetrycomputed tomographyimaging biomarkerpostoperative risk stratificationrecurrence

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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.