Virtual planning of liver resections: image processing, visualization and volumetric evaluation
Introduction
Selection of the patients to be surgically treated out of the continuum of metastatic tumor progression is the crucial step in liver resection planning. The surgical strategy is dependent on the localization of the liver tumor in relation to the three liver vascular trees. In detail three cornerstones have to be considered in liver surgery:
- 1.
The liver tumor has to be resected completely within sound liver parenchyma.
- 2.
Segments or even subsegments of the liver which might get devascularized by liver resection have to be removed as well.
- 3.
Liver function is dependent on sufficient functionally active liver volume.
In patients with multiple liver lesions operation planning is getting difficult as resection planes may cut in a complicated way through the vascular trees leading to devascularized (sub-)segments which have to be removed as well. Distorted anatomy after preceding liver resection and consecutive hypertrophy of the remaining liver parenchyma demands high skills in imagination and operation planning is not quantifiable.
A prediction of absolute or relative rest liver volume has been very difficult and has widely been substituted by simple imagination and rough estimation. Up to now a computer based calculation was not practicable due to missing analysis systems dedicated to tumor resections. A variety of efforts has been undertaken in the past to establish a computer based 3D presentation system for the liver anatomy of individual patients [1], [2]. To our knowledge none of these is available in clinical routine.
The knowledge of the exact three-dimensional relation of the tumor and the vascular trees within the liver decides on the preoperative selection of patients for hepatic resection. Despite low perioperative mortality there is still a high complication rate. Therefore objective and quantifiable selection criteria should be mandatory.
The aim of the developments was to establish a computer based, quantitative, three-dimensional operation planning system in liver surgery. An individualized operation strategy is facilitated which takes into account the anatomic variability of liver architecture in the individual patient. The classical approximation of the liver anatomy is given by the Couinaud model which divides the liver into eight segments [3]. These segments shown in Fig. 1 represent areas that are vascularly independent.
A precise operation planning system has to be based on the exact knowledge of the individual liver anatomy. Patients with multiple liver metastases may benefit by minimizing resection volume without devascularizing sound parenchyma.
The three major goals have been:
- •
To recognize and visualize parenchyma, vessels and tumor.
- •
To calculate the absolute and relative volumes and thus obtain quantified measurements.
- •
To calculate a resection proposal, which may be modified by the user interactively.
These developments might optimize patient selection as operation planning is getting quantifiable and objective. Complication rates might decrease due to an improved patient selection and by a highly individualized operation planning and resection. Besides the advantages for the patient there might be a reduction of the expenditure for intensive care and hospital stay (Fig. 2).
Section snippets
Imaging
CT scans taken from routine diagnostics are used as the input for image processing. According to the actual problem two different methods of contrast agent based techniques may be used:
- 1.
Bolus tracking: contrast agent injection using a high pressure pump is triggered by a computer so that the contrast medium reaches the liver just in time when the spiral-CT-scan starts sampling the data from the liver. The cross-section pictures are reconstructed in 2 mm slices.
- 2.
CTAP (arterial portal CT): An
Discussion
Despite the fact that 3D rendering of CT-scans of the liver are carried out for several years no virtual liver resection planning system has been available for use in clinical practice. Quality of patient selection is dependent on a precise quantifiable tumor resection planning. Security margins around the tumor, recognition of vascularly dependent liver segments and sufficient functionally active remaining liver volume are the cornerstones of resection planning.
We have developed a computer
Acknowledgements
This work is supported by the Tumorzentrum Heidelberg/Mannheim and the University of Heidelberg.
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2010, European Journal of RadiologyCitation Excerpt :In fact, the diagnostic quality of these MDCT was shown in studies, some of them performed in a randomized fashion [8–10]. We and others were dealing with three dimensional (3D) visualization of the liver anatomy based on CT data for many years [11–15]. The main goal of this research was to increase anatomical and surgical understanding for challenging surgical procedures such as liver transplantations [11,16–19].
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