CT Volumetry and Hepatic Vascular Deformation Mapping to Predict Post-Hepatectomy Liver Failure
This is not medical advice. AI-assisted translation — inaccuracies may occur. Always verify the original and consult your oncologist before taking any steps.
About the trial
Removing a large part of the liver (major hepatectomy) can cure primary and secondary liver cancers, but it carries the risk of post-hepatectomy liver failure (PHLF), a serious complication in which the liver left behind - the future liver remnant (FLR) - cannot meet the body's metabolic needs. PHLF occurs after roughly 5% to 15% of major hepatectomies and is the leading cause of postoperative death. Before surgery, surgeons routinely use CT scans to measure how much liver will remain (CT volumetry). Volume alone does not tell the whole story. After a large resection the remaining liver can rotate and shift into the empty space left behind, kinking or compressing the veins that drain it. The resulting congestion can make an apparently adequate remnant fail. This prospective, multicenter, observational cohort study tests whether adding two elements to standard CT volumetry improves the preoperative prediction of liver failure: 1. Hepatic vascular deformation mapping (VDM), a three-dimensional image-analysis technique that quantifies the geometry and displacement of the hepatic veins and the portal vein; and 2. A set of simple, reproducible measurements that any radiologist can make on a standard CT scan (hepatic vein diameters, congestion index, spleen volume, liver attenuation, and the distances from the veins to the planned resection plane). Consecutive adults undergoing major hepatic resection (three or more Couinaud segments) at several tertiary hepatobiliary centers will be enrolled. The preoperative CT scans already performed as part of routine care are analyzed centrally by a core imaging laboratory. There is no additional imaging, no extra hospital visit, and no study-specific intervention: every patient receives standard surgical care. Participants are followed for at least 30 days after surgery to record liver failure (International Study Group of Liver Surgery criteria, operationalized by the "50-50" rule on postoperative day 5) and radiologic evidence of hepatic congestion. Three nested prediction models are compared - volumetry alone; volumetry plus VDM; and volumetry plus VDM plus the simple radiology parameters - and the best-performing model is converted into a practical risk score. Because the study runs across several centers, the model can be validated by leaving one center out at a time, which gives an honest estimate of how well it would perform at a new hospital. The goal is a generalizable, easy-to-use tool that tells surgeons, before the operation, which patients are genuinely at risk of post-hepatectomy liver failure.
Original English text from ClinicalTrials.gov
Who can (and can't) join
✓ Qualifies
- •Wiek 18 lat lub więcej
- •Planowana operacja usunięcia dużej części wątroby (co najmniej trzy segmenty)
- •Wykonane badanie CT piersi sprzed operacji wystarczającej jakości do analizy
- •Możliwość uczestnictwa w obserwacji przez co najmniej 30 dni po operacji
- •Podpisana zgoda na udział w badaniu
✗ Disqualifies
- •Planowana operacja usunięcia małej części wątroby (mniej niż trzy segmenty)
- •Poważne wady lub choroby naczyń krwionośnych wątroby (np. skrzepnięcie żyły)
- •Nagła operacja z powodu urazu
- •Badanie obrazowe niezadowalającej jakości
- •Brak danych z okresu obserwacji po operacji
Simplified criteria — AI translation
Trial details
- Minimum age
- 18 Years
- Last updated (source)
- August 18, 2026
- Sex
- No restrictions
Therapies / drugs in trial
Locations (3)
Liver and GIT Hospital, Faculty of Medicine, Minia University
Minya, Egypt
Maadi Armed Forces Medical Compound - Department of Liver and Pancreas Surgery and Liver Transplantation
Maadi, Egypt
National Liver Institute, Menoufia University
Shibīn al Kawm, Egypt
Trial contact
Saleh K Saleh, MD
Contact information from ClinicalTrials.gov. Contact in English.
Share this trial
Data from ClinicalTrials.gov. AI-assisted translation, last sync: 8/19/2026.
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