ReviewSurgical endoscopy2026
Liver volumetry software: a narrative review of technical performance and clinical utility.
Review in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Comparing the reliability of three software programmes for manual and (semi-)automatic volumetry in healthy livers.World journal of radiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLiver volumetry (LV) is essential in preoperative planning for liver resection and living donor liver transplantation, particularly in extended resections, where minimizing the risk of post-hepatectomy liver failure (PHLF) and ensuring donor safety are pivotal. Several software platforms have been developed to support LV, employing different segmentation techniques, from manual to semi-automated and fully automated, based on contrast-enhanced computed tomography (CT) or, less frequently, magnetic resonance imaging. MAIN
findingsManual tracing remains the reference standard but it is limited by high operator dependency, long execution times, and low reproducibility. Semi-automated tools reduce user variability and shorten processing time. Synapse has shown no evident learning curve, while Syngo.via requires user training. Hermes, integrating functional data from SPECT, offers superior prediction of PHLF but less precise correlation with actual graft weight in living donor liver transplantation. Automated platforms such as LiverVision, Myrian XP-Liver, and Vitrea have demonstrated strong agreement with manual or graft weight references and shorter execution times. However, most tools still require manual contouring, particularly for anatomical delineation and exclusion of vessels or biliary structures. Fully automated tools such as LISA remain experimental and lack clinical validation. Software comparison remains challenging and limited due to the absence of standardized validation protocols, metrics variations across studies, and the predominance of proprietary conditions.
conclusionThe aim of this narrative review is to summarize the available features, performances and clinical applicability of 11 widely used LV tools. While emerging evidence supports their clinical utility, further multicenter studies using standardized methodologies are needed to clarify their relative advantages and promote consistent use in surgical practice.
Indexed as
Identifiers
42151462What OpenQuestion holds
Registered trials
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.