Abstract
ObjectivesTo evaluate the accuracy of fully automated liver volume quantification vs. manual quantification using unenhanced as well as enhanced CT-image data as well as two different radiation dose levels and also two image reconstruction kernels.Material and methodsThe local ethics board gave its approval for retrospective data analysis. Automated liver volume quantification in 300 consecutive livers in 164 male and 103 female oncologic patients (64±12y) performed at our institution (between January 2020 and May 2020) using two different dual-energy helicals: portal-venous phase enhanced, ref. tube current 300mAs (CARE Dose4D) for tube A (100 kV) and ref. 232mAs tube current for tube B (Sn140kV), slice collimation 0.6mm, reconstruction kernel I30f/1, recon. thickness of 0.6mm and 5mm, 80–100 mL iodine contrast agent 350 mg/mL, (flow 2mL/s) and unenhanced ref. tube current 100mAs (CARE Dose4D) for tube A (100 kV) and ref. 77mAs tube current for tube B (Sn140kV), slice collimation 0.6mm (kernel Q40f) were analyzed. The post-processing tool (syngo.CT Liver Analysis) is already FDA-approved. Two resident radiologists with no and 1-year CT-experience performed both the automated measurements independently from each other. Results were compared with those of manual liver volume quantification using the same software which was supervised by a senior radiologist with 30-year CT-experience (ground truth).ResultsIn total, a correlation of 98% was obtained for liver volumetry based on enhanced and unenhanced data sets compared to the manual liver quantification. Radiologist #1 and #2 achieved an inter-reader agreement of 99.8% for manual liver segmentation (p<0.0001). Automated liver volumetry resulted in an overestimation (>5% deviation) of 3.7% for unenhanced CT-image data and 4.0% for contrast-enhanced CT-images. Underestimation (<5%) of liver volume was 2.0% for unenhanced CT-image data and 1.3% for enhanced images after automated liver volumetry. Number and distribution of erroneous volume measurements using either thin or thick slice reconstructions was exactly the same, both for the enhanced as well for the unenhanced image data sets (p> 0.05).ConclusionResults of fully automated liver volume quantification are accurate and comparable with those of manual liver volume quantification and the technique seems to be confident even if unenhanced lower-dose CT image data is used.
Highlights
Precise assessment of liver volume is required in many clinical settings
A correlation of 98% was obtained for liver volumetry based on enhanced and unenhanced data sets compared to the manual liver quantification
Automated liver volumetry resulted in an overestimation (>5% deviation) of 3.7% for unenhanced CT-image data and 4.0% for contrast-enhanced CT-images
Summary
Precise assessment of liver volume is required in many clinical settings. In particular, in patients admitted for liver surgery (liver lobe resection or liver transplantation), estimation of the future liver volume remnant as well as of the donor organ size is essential for good patient management and for reducing the risk of postoperative hepatic insufficiency [1, 2]. Volumetry of the liver is performed using different techniques which generally rely on different segmentation techniques, contour recognition, etc. Manual contour tracing for organ volumetry is knowingly limited as it is cumbersome, time-consuming and underlies inter- and intra-observer variability [10]. For this reason, semi-automated and automated liver volume calculation software tools have been further developed and are in use worldwide [8,9,10,11]. Differences exist between post-processing tools, many of them showing expectedly strengths, and limitations by comparison with the manual quantification [2, 9, 12, 13]. The dependency of these measurements from CT-examinational protocol (i.e. unenhanced vs. contrast-enhanced CT; contrast volume and enhancement phase as well as slice thickness) are still an issue of debate in searching for optimal solution [14, 15]
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