Liver segmentation: indications, techniques and future directions

Abstract

ObjectivesLiver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals.MethodsUsing images from CT and MRI, this paper reviews the indications for liver segmentation, technical approaches used in segmentation software and the developing roles of liver segmentation in clinical practice.ResultsLiver segmentation for volumetric assessment is indicated prior to major hepatectomy, portal vein embolisation, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and transplant. Segmentation software can be categorised according to amount of user input involved: manual, semi-automated and fully automated. Manual segmentation is considered the “gold standard” in clinical practice and research, but is tedious and time-consuming. Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls. Emerging applications of segmentation include surgical planning and integration with MRI-based biomarkers.ConclusionsLiver segmentation has multiple clinical applications and is expanding in scope. Clinicians can employ semi-automated or fully automated segmentation options to more efficiently integrate volumetry into clinical practice.Teaching points• Liver volume is assessed via organ segmentation on CT and MRI examinations. • Liver segmentation is used for volume assessment prior to major hepatic procedures. • Segmentation approaches may be categorised according to the amount of user input involved. • Emerging applications include surgical planning and integration with MRI-based biomarkers. Electronic supplementary materialThe online version of this article (doi:10.1007/s13244-017-0558-1) contains supplementary material, which is available to authorised users.

MRI in donor candidates for living donor liver transplant: Technical and practical considerations

“…The availability of commercial software, especially with automated or semiautomated segmentation approaches, is still limited for MRI volumetry compared to CT datasets . Manual segmentation for liver volumetry is time‐consuming and laborious, and it could be even worse when thin‐section datasets are used .…”

“…Manual segmentation for liver volumetry is time‐consuming and laborious, and it could be even worse when thin‐section datasets are used . The enhanced edge magnitude of the liver using the modified flip angles and new techniques with improved temporal/spatial resolutions can be potentially helpful when automated or semiautomated methods are incorporated, as the segmentation accuracy of automated liver volumetry greatly depends on the intensity contrast between the segmented liver and nearby organs . Although these novel approaches are likely to save time and effort required for liver volumetry, they are dependent on MR field inhomogeneity, threshold values, and algorithms .…”

“…34 The availability of commercial software, especially with automated or semiautomated segmentation approaches, is still limited for MRI volumetry compared to CT datasets. 36 Manual segmentation for liver volumetry is time-consuming and laborious, and it could be even worse when thin-section datasets are used. 30 The enhanced edge magnitude of the liver using the modified flip angles and new techniques with improved temporal/spatial resolutions can be potentially helpful when automated or semiautomated methods are incorporated, as the segmentation accuracy of automated liver volumetry greatly depends on the intensity contrast between the segmented liver and nearby organs.…”

“…30,36 Although these novel approaches are likely to save time and effort required for liver volumetry, they are dependent on MR field inhomogeneity, threshold values, and algorithms. 36 Therefore, clinical validation for these approaches is warranted.…”

Needle deflection in thermal ablation procedures of liver tumors: a CT image analysis

“…Needle shape reconstruction was done using MeVisLab 2.7, a modular framework for image processing research and development, by making use of the Contour Segmentation Objects (CSO) library. Manual segmentation was chosen as it is still considered the gold standard in research and clinical practice over (semi)automatic segmentation [4]. The reconstruction method was dependent on the orientation of the needle with respect to the CT slices.…”