Literature DB >> 27680014

Comparison of MRI- and CT-based semiautomated liver segmentation: a validation study.

Akshat Gotra1,2, Gabriel Chartrand3, Kim-Nhien Vu1, Franck Vandenbroucke-Menu4, Karine Massicotte-Tisluck1, Jacques A de Guise3, An Tang5,6.   

Abstract

PURPOSE: To compare the repeatability, agreement, and efficiency of MRI- and CT-based semiautomated liver segmentation for the assessment of total and subsegmental liver volume.
METHODS: This retrospective study was conducted in 31 subjects who underwent contemporaneous liver MRI and CT. Total and subsegmental liver volumes were segmented from contrast-enhanced 3D gradient-recalled echo MRI sequences and CT images. Semiautomated segmentation was based on variational interpolation and Laplacian mesh optimization. All segmentations were repeated after 2 weeks. Manual segmentation of CT images using an active contour tool was used as the reference standard. Repeatability and agreement of the methods were evaluated with intra-class correlation coefficients (ICC) and Bland-Altman analysis. Total interaction time was recorded.
RESULTS: Intra-reader ICC were ≥0.987 for MRI and ≥0.995 for CT. Intra-reader repeatability was 30 ± 217 ml (bias ± 1.96 SD) (95% limits of agreement: -187 to 247 ml) for MRI and -10 ± 143 ml (-153 to 133 ml) for CT. Inter-method ICC between semiautomated and manual volumetry were ≥0.995 for MRI and ≥0.986 for CT. Inter-method segmental ICC varied between 0.584 and 0.865 for MRI and between 0.596 and 0.890 for CT. Inter-method agreement was -14 ± 136 ml (-150 to 122 ml) for MRI and 50 ± 226 ml (-176 to 276 ml) for CT. Inter-method segmental agreement ranged from 10 ± 47 ml (-37 to 57 ml) to 2 ± 214 ml (-212 to 216 ml) for MRI and 9 ± 45 ml (-36 to 54 ml) to -46 ± 183 ml (-229 to 137 ml) for CT. Interaction time (mean ± SD) was significantly shorter for MRI-based semiautomated segmentation (7.2 ± 0.1 min, p < 0.001) and for CT-based semiautomated segmentation (6.5 ± 0.2 min, p < 0.001) than for CT-based manual segmentation (14.5 ± 0.4 min).
CONCLUSION: MRI-based semiautomated segmentation provides similar repeatability and agreement to CT-based segmentation for total liver volume.

Entities:  

Keywords:  Agreement; CT; Liver volume; MRI; Repeatability; Semiautomated segmentation

Mesh:

Substances:

Year:  2017        PMID: 27680014     DOI: 10.1007/s00261-016-0912-7

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  5 in total

1.  Assessment of treatment response in non-alcoholic steatohepatitis using advanced magnetic resonance imaging.

Authors:  S C Lin; E Heba; R Bettencourt; G Y Lin; M A Valasek; O Lunde; G Hamilton; C B Sirlin; R Loomba
Journal:  Aliment Pharmacol Ther       Date:  2017-01-24       Impact factor: 8.171

Review 2.  Portal vein embolization in extended liver resection.

Authors:  Nisha Narula; Thomas A Aloia
Journal:  Langenbecks Arch Surg       Date:  2017-05-31       Impact factor: 3.445

3.  Portal vein embolization with ethylene-vinyl alcohol copolymer for contralateral lobe hypertrophy before liver resection: safety, feasibility and initial experience.

Authors:  Sébastien Gautier; Olivier Chevallier; Charles Mastier; Philippe d'Athis; Nicolas Falvo; Frank Pilleul; Marco Midulla; Patrick Rat; Olivier Facy; Romaric Loffroy
Journal:  Quant Imaging Med Surg       Date:  2021-02

Review 4.  Liver segmentation: indications, techniques and future directions.

Authors:  Akshat Gotra; Lojan Sivakumaran; Gabriel Chartrand; Kim-Nhien Vu; Franck Vandenbroucke-Menu; Claude Kauffmann; Samuel Kadoury; Benoît Gallix; Jacques A de Guise; An Tang
Journal:  Insights Imaging       Date:  2017-06-14

5.  Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections.

Authors:  Grzegorz Chlebus; Hans Meine; Smita Thoduka; Nasreddin Abolmaali; Bram van Ginneken; Horst Karl Hahn; Andrea Schenk
Journal:  PLoS One       Date:  2019-05-20       Impact factor: 3.240

  5 in total

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