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Comput Methods Programs Biomed. 2018 May;158:11-19. doi: 10.1016/j.cmpb.2018.01.024. Epub 2018 Jan 31.

Dr. Liver: A preoperative planning system of liver graft volumetry for living donor liver transplantation.

Author information

1
Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea.
2
Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea.
3
Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea. Electronic address: hcyu@jbnu.ac.kr.
4
Department of Surgery, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.

Abstract

BACKGROUND AND OBJECTIVE:

Manual tracing of the right and left liver lobes from computed tomography (CT) images for graft volumetry in preoperative surgery planning of living donor liver transplantation (LDLT) is common at most medical centers. This study aims to develop an automatic system with advanced image processing algorithms and user-friendly interfaces for liver graft volumetry and evaluate its accuracy and efficiency in comparison with a manual tracing method.

METHODS:

The proposed system provides a sequential procedure consisting of (1) liver segmentation, (2) blood vessel segmentation, and (3) virtual liver resection for liver graft volumetry. Automatic segmentation algorithms using histogram analysis, hybrid level-set methods, and a customized region growing method were developed. User-friendly interfaces such as sequential and hierarchical user menus, context-sensitive on-screen hotkey menus, and real-time sound and visual feedback were implemented. Blood vessels were excluded from the liver for accurate liver graft volumetry. A large sphere-based interactive method was developed for dividing the liver into left and right lobes with a customized cutting plane. The proposed system was evaluated using 50 CT datasets in terms of graft weight estimation accuracy and task completion time through comparison to the manual tracing method. The accuracy of liver graft weight estimation was assessed by absolute difference (AD) and percentage of AD (%AD) between preoperatively estimated graft weight and intraoperatively measured graft weight. Intra- and inter-observer agreements of liver graft weight estimation were assessed by intraclass correlation coefficients (ICCs) using ten cases randomly selected.

RESULTS:

The proposed system showed significantly higher accuracy and efficiency in liver graft weight estimation (AD = 21.0 ± 18.4 g; %AD = 3.1% ± 2.8%; percentage of %AD > 10% = none; task completion time = 7.3 ± 1.4 min) than the manual tracing method (AD = 70.5 ± 52.1 g; %AD = 10.2% ± 7.5%; percentage of %AD > 10% = 46%; task completion time = 37.9 ± 7.0 min). The proposed system showed slightly higher intra- and inter-observer agreements (ICC = 0.996 to 0.998) than the manual tracing method (ICC = 0.979 to 0.999).

CONCLUSIONS:

The proposed system was proved accurate and efficient in liver graft volumetry for preoperative planning of LDLT.

KEYWORDS:

Liver graft volumetry; Liver segmentation; Living donor liver transplantation; Vessel segmentation; Virtual liver resection

PMID:
29544776
DOI:
10.1016/j.cmpb.2018.01.024
[Indexed for MEDLINE]

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