Automated Liver Volumetry in Orthotopic Liver Transplantation Using Multiphase Acquisitions on MDCT

Abstract

Both manual and automated multiphase MDCT-based volume measurements were strongly correlated to liver volume (Pearson correlation coefficient, r = 0.87 [p < 0.0001] and 0.90 [p < 0.0001], respectively). Automated multiphase segmentation was significantly more rapid than manual segmentation (mean time, 16 ± 5 [SD] and 86 ± 3 seconds, respectively; p = 0.01). Overall, automated liver volumetry based on multiphase CT acquisitions is feasible and more rapid than manual segmentation.

Fast and accurate liver volumetry prior to hepatectomy

“…The present study showed that after a short training liver volumetry could be performed adequately, even in inexperienced hands. Others already showed that CT based auto-segmentation of the TLV was also possible with Windows 4.4 framework ® , 8 Philips Intellispace Portal ® , 9 Voxar ® , 12 and CAD technologies ® . 13 Only two studies actually compared manual with automated volumetry with generally good correlations.…”

“…13 Only two studies actually compared manual with automated volumetry with generally good correlations. 8,13 These studies were done on liver transplant patients, and only total liver volumetry was performed. To our knowledge the present study is the first to not only test total liver volumetry but also future remnant liver volumetry and determination of the remnant liver volume percentage.…”

“…4,6 With specialised software, auto-segmentation of organs is possible. [8][9][10][11][12][13][14] However, CT-based automated segmentation of the liver is challenging because organs with comparable density surround the liver. Automated future remnant liver volumetric analysis has not yet been validated by comparing it with manual slice-by-slice drawing of contours.…”

Liver volumetry: Is imaging reliable? Personal experience and review of the literature

“…If a maximum error of 5% in the calculated graft volume will not have a significant clinical impact, 5-mm-thick images are acceptable for CT volumetry, but if the impact is significant, 3D images could be essential. Luciani et al [65] reported that both manual and automated multiphase CT-based volume measurements were strongly correlated to liver volume (r = 0.87 and 0.90, respectively), but automated segmentation was significantly more rapid than manual segmentation (mean time: 16 ± 5 and 86 ± 3 s, respectively). Suzuki et al [66] developed a general framework for liver segmentation in both CT and MRI, using an anisotropic diffusion filter to reduce noise, a scale-specific gradient magnitude filter to enhance liver boundaries, a fast-marching algorithm to roughly determine liver boundaries, and a geodesic-active-contour model coupled with a level-set algorithm to refine the initial boundaries.…”

Automated segmentation methods for liver analysis in oncology applications

“…This means a relatively short time (175/44·0.5 = 1.95 minutes) is enough, when only the liver volume is required by the physician. This estimation was confirmed by another study [10] where 86 second was reported as average contouring time for manual liver volume estimation. Similar to , is very (and is even more) sensitive to the distance between interpolated slices.…”