Journal of Clinical Interventional Radiology ISVIR (Dec 2020)

A Validation Study of Liver Volumetry Estimation by a Semiautomated Software in Patients Undergoing Hepatic Resections

  • Suyash S. Kulkarni,
  • Nitin Sudhakar Shetty,
  • Kunal B. Gala,
  • Shraddha Patkar,
  • Amrita Narang,
  • Ashwin M. Polnaya,
  • Sushil Patil,
  • Neeraj G. Shetty,
  • Falguni Hota,
  • Mahesh Goel

DOI
https://doi.org/10.1055/s-0040-1721534
Journal volume & issue
Vol. 4, no. 03
pp. 154 – 158

Abstract

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Purpose The purpose of this study was to validate the use of a semiautomated software for liver volumetry preoperatively by comparing it with the volume of resected specimen in patients undergoing hepatic resections. Materials and Methods This is a single-center retrospective study of patients who underwent estimation of future liver remnant (FLR) using Myrian XP-Liver which is a semiautomated software for hepatectomy. The estimated resection volume, which is the sum of volume of normal liver to be resected and tumor volume, was compared with actual specimen weight to calculate the accuracy of the software. The statistical analysis was performed with SPSS software version 24. Results Data on FLR estimation using the semiautomated software was available for 200 out of 388 patients who underwent formal hepatic resections. The median resected volume of surgical specimen was 650 mL (interquartile range [IQR] 364–950), while the median estimated volume using the Myrian software was 617 mL (IQR 362–979). There was significant correlation between estimated resection volume calculated using the semiautomated method and actual specimen weight (p-value < 0.0001) with the Spearman’s correlation value of 0.956. Conclusion The estimated volume of liver to be resected as calculated by the semiautomated software was accurate and correlated significantly with the volume of resected specimen, and hence, the estimation of FLR volume may likely correlate with the true postoperative residual liver volume. In addition, the software-based liver segmentation, FLR estimation, and color-coded three-dimensional images provide a clear road map to the surgeon to facilitate safe resection.

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