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Liver Planning Software Accurately Predicts Postoperative Liver Volume and Measures Early Regeneration

Abstract

Background: Postoperative or remnant liver volume (RLV) after hepatic resection is a critical predictor of perioperative outcomes. This study investigates whether the accuracy of liver surgical planning software for predicting postoperative RLV and assessing early regeneration.

Study Design: Patients eligible for hepatic resection were approached for participation in the study from June 2008 to 2010. All patients underwent cross-sectional imaging (CT or MRI) before and early after resection. Planned remnant liver volume (pRLV) (based on the planned resection on the preoperative scan) and postoperative actual remnant liver volume (aRLV) (determined from early postoperative scan) were measured using Scout Liver software (Pathfinder Therapeutics Inc.). Differences between pRLV and aRLV were analyzed, controlling for timing of postoperative imaging. Measured total liver volume (TLV) was compared with standard equations for calculating volume.

Results: Sixty-six patients were enrolled in the study from June 2008 to June 2010 at 3 treatment centers. Correlation was found between pRLV and aRLV (r = 0.941; p < 0.001), which improved when timing of postoperative imaging was considered (r = 0.953; p < 0.001). Relative volume deviation from pRLV to aRLV stratified cases according to timing of postoperative imaging showed evidence of measurable regeneration beginning 5 days after surgery, with stabilization at 8 days (p < 0.01). For patients at the upper and lower extremes of liver volumes, TLV was poorly estimated using standard equations (up to 50% in some cases).

Conclusions: Preoperative virtual planning of future liver remnant accurately predicts postoperative volume after hepatic resection. Early postoperative liver regeneration is measureable on imaging beginning at 5 days after surgery. Measuring TLV directly from CT scans rather than calculating based on equations accounts for extremes in TLV.

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References
1.
Nagino M, Ando M, Kamiya J, Uesaka K, Sano T, Nimura Y . Liver regeneration after major hepatectomy for biliary cancer. Br J Surg. 2001; 88(8):1084-91. DOI: 10.1046/j.0007-1323.2001.01832.x. View

2.
Vauthey J, Chaoui A, Do K, Bilimoria M, Fenstermacher M, Charnsangavej C . Standardized measurement of the future liver remnant prior to extended liver resection: methodology and clinical associations. Surgery. 2000; 127(5):512-9. DOI: 10.1067/msy.2000.105294. View

3.
Du Bois D, Du Bois E . A formula to estimate the approximate surface area if height and weight be known. 1916. Nutrition. 1989; 5(5):303-11; discussion 312-3. View

4.
Hermoye L, Laamari-Azjal I, Cao Z, Annet L, Lerut J, Dawant B . Liver segmentation in living liver transplant donors: comparison of semiautomatic and manual methods. Radiology. 2004; 234(1):171-8. DOI: 10.1148/radiol.2341031801. View

5.
Urata K, Kawasaki S, Matsunami H, Hashikura Y, Ikegami T, Ishizone S . Calculation of child and adult standard liver volume for liver transplantation. Hepatology. 1995; 21(5):1317-21. View