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Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging

Byline: Ghaneh Fananapazir (1), Mustafa R. Bashir (1), Daniele Marin (1), Daniel T. Boll (1) Keywords: MDCT; Post-processing; Liver; Volumetry Abstract: Purpose To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT d... Full description

Journal Title: Abdominal Imaging 2015, Vol.40(5), pp.1203-1212
Main Author: Fananapazir, Ghaneh
Other Authors: Bashir, Mustafa , Marin, Daniele , Boll, Daniel
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 0942-8925 ; E-ISSN: 1432-0509 ; DOI: 10.1007/s00261-014-0276-9
Link: http://dx.doi.org/10.1007/s00261-014-0276-9
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recordid: springer_jour10.1007/s00261-014-0276-9
title: Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging
format: Article
creator:
  • Fananapazir, Ghaneh
  • Bashir, Mustafa
  • Marin, Daniele
  • Boll, Daniel
subjects:
  • MDCT
  • Post-processing
  • Liver
  • Volumetry
ispartof: Abdominal Imaging, 2015, Vol.40(5), pp.1203-1212
description: Byline: Ghaneh Fananapazir (1), Mustafa R. Bashir (1), Daniele Marin (1), Daniel T. Boll (1) Keywords: MDCT; Post-processing; Liver; Volumetry Abstract: Purpose To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT datasets. Materials and methods A polymer liver phantom was used to assess accuracy of post-processing applications comparing phantom volumes determined via Archimedes' principle with MDCT segmented datasets. For the IRB-approved, HIPAA-compliant study, 25 patients were enrolled. Volumetry performance compared the manual approach with the automated prototype, assessing intraobserver variability, and interclass correlation for whole-organ and lobar segmentation using ANOVA comparison. Fidelity of segmentation was evaluated qualitatively. Results Phantom volume was 1581.0 [+ or -] 44.7 mL, manually segmented datasets estimated 1628.0 [+ or -] 47.8 mL, representing a mean overestimation of 3.0%, automatically segmented datasets estimated 1601.9 [+ or -] 0 mL, representing a mean overestimation of 1.3%. Whole-liver and segmental volumetry demonstrated no significant intraobserver variability for neither manual nor automated measurements. For whole-liver volumetry, automated measurement repetitions resulted in identical values reproducible whole-organ volumetry was also achieved with manual segmentation, p .sub.ANOVA 0.98. For lobar volumetry, automated segmentation improved reproducibility over manual approach, without significant measurement differences for either methodology, p .sub.ANOVA 0.95--0.99. Whole-organ and lobar segmentation results from manual and automated segmentation showed no significant differences, p .sub.ANOVA 0.96--1.00. Assessment of segmentation fidelity found that segments I--IV/VI showed greater segmentation inaccuracies compared to the remaining right hepatic lobe segments. Conclusion Automated whole-liver segmentation showed non-inferiority of fully-automated whole-liver segmentation compared to manual approaches with improved reproducibility and post-processing duration automated dual-seed lobar segmentation showed slight tendencies for underestimating the right hepatic lobe volume and greater variability in edge detection for the left hepatic lobe compared to manual segmentation. Author Affiliation: (1) Department of Radiology, Duke University Medical Center, DUMC 3808, Durham, NC, 27710, USA Article History: Registration Date: 13/10/2014
language: eng
source:
identifier: ISSN: 0942-8925 ; E-ISSN: 1432-0509 ; DOI: 10.1007/s00261-014-0276-9
fulltext: no_fulltext
issn:
  • 1432-0509
  • 14320509
  • 0942-8925
  • 09428925
url: Link


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titleComputer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging
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descriptionByline: Ghaneh Fananapazir (1), Mustafa R. Bashir (1), Daniele Marin (1), Daniel T. Boll (1) Keywords: MDCT; Post-processing; Liver; Volumetry Abstract: Purpose To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT datasets. Materials and methods A polymer liver phantom was used to assess accuracy of post-processing applications comparing phantom volumes determined via Archimedes' principle with MDCT segmented datasets. For the IRB-approved, HIPAA-compliant study, 25 patients were enrolled. Volumetry performance compared the manual approach with the automated prototype, assessing intraobserver variability, and interclass correlation for whole-organ and lobar segmentation using ANOVA comparison. Fidelity of segmentation was evaluated qualitatively. Results Phantom volume was 1581.0 [+ or -] 44.7 mL, manually segmented datasets estimated 1628.0 [+ or -] 47.8 mL, representing a mean overestimation of 3.0%, automatically segmented datasets estimated 1601.9 [+ or -] 0 mL, representing a mean overestimation of 1.3%. Whole-liver and segmental volumetry demonstrated no significant intraobserver variability for neither manual nor automated measurements. For whole-liver volumetry, automated measurement repetitions resulted in identical values reproducible whole-organ volumetry was also achieved with manual segmentation, p .sub.ANOVA 0.98. For lobar volumetry, automated segmentation improved reproducibility over manual approach, without significant measurement differences for either methodology, p .sub.ANOVA 0.95--0.99. Whole-organ and lobar segmentation results from manual and automated segmentation showed no significant differences, p .sub.ANOVA 0.96--1.00. Assessment of segmentation fidelity found that segments I--IV/VI showed greater segmentation inaccuracies compared to the remaining right hepatic lobe segments. Conclusion Automated whole-liver segmentation showed non-inferiority of fully-automated whole-liver segmentation compared to manual approaches with improved reproducibility and post-processing duration automated dual-seed lobar segmentation showed slight tendencies for underestimating the right hepatic lobe volume and greater variability in edge detection for the left hepatic lobe compared to manual segmentation. Author Affiliation: (1) Department of Radiology, Duke University Medical Center, DUMC 3808, Durham, NC, 27710, USA Article History: Registration Date: 13/10/2014 Online Date: 18/10/2014
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