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448
J. Wang et al.
17.6.2.3 3D Reconstruction ofLiver andBlood
Vessels
3D visualization software was used to reconstruct the
enhanced CT data of upper abdomen, including reconstruction of liver, blood vessels, and lesion.
Viscera Reconstruction
The 3D reconstruction of liver contour was carried out by
methods such as the semiautomatic region growth method
(Dreizin etal. 2016). Firstly, the liver was automatically recognized and reconstructed by a computer, and then the
boundary of liver model was manually adjusted based on
two-dimensional image examination to establish a 3D model
of liver as realistic as possible (Fig.17.37).
Lesion Reconstruction
For calculi, according to their density characteristics in the
plain scanning phase of enhanced CT, the contour was segmented in the coronal plane, sagittal plane, and horizontal
plane to generate a preliminary three-dimensional structure;
and then the contour was ne-tuned in the two-dimensional
plane (Fig.17.38). For perihepatic hilar tumors, besides 3D
reconstruction and adjustment of contours based on the difference of venous density in enhanced CT; the range of
tumor inltration can also be judged according to the indirect
signs of bile duct expansion and “truncation.”
Vascular Reconstruction
Three-dimensional reconstruction of hepatic artery, portal
vein, hepatic vein, and dilated bile duct was performed by
the threshold segmentation method (Fig.17.39).
Synthesis andRotation
Compared with traditional imaging methods, 3D visualization can not only synthesize the planar images of the coronal
plane, sagittal plane, and horizontal plane into threedimensional structures, but also display the hepatic artery,
portal vein, hepatic vein, and lesions respectively or simultaneously. Three-dimensional visualization technology has the
functions of rotation, segmentation, reduction, amplication,
etc., which can display the spatial relationship of the hepatic
vascular vessels and the positional relationship between the
lesion and the surrounding vascular vessels stereoscopically
and intuitively, as well as simulate the operation.
Fig. 17.37 Manually modify the boundary of the liver model
17 Application of3D Visualization Technology inPerihilar Surgery
Fig. 17.38 Reconstruction and ne-tuning of the 3D structure of the lesion
449
Fig. 17.39 3D reconstruction of hepatic arteries, veins, and bile ducts
450
J. Wang et al.
Liver Segmentation andLiver Volume Calculation
The liver can be divided into eight functionally independent
segments based on Couinaud classication using; however,
this method has certain limitations. Couinaud’s liver segment classication is suitable for hepatic segments with normal portal vein course. If there are variations in the portal
vein, it is necessary to adjust the plane of a segment according
to the distribution and course of portal vein branches
(Fig.17.40).
Simulation surgery can also be performed to simulate partial hepatectomy and measure the residual liver volume
(Fig.17.41).
ab c
de f
Fig. 17.40 Steps for 3D visualization of liver segmentation. (a)
Segmentation of the left and right liver; (b) Segmentation of the right
anterior lobe and the right posterior lobe; (c) Segmentation of the seg-
Fig. 17.41 Simulation of right hepatectomy and its effects by re-specifying the cutting plane
ment V and VII, VI and VII; (d) Segmentation of the left inner lobe and
left outer lobe; (e) Segmentation of the segments II and III; (f)
Segmentation of the segments I and IV
17 Application of3D Visualization Technology inPerihilar Surgery
451
17.6.3 Distortion ofLesion Information
During 3D Visualization Processing
3D visualization technology refers to the automatic recognition/articial segmentation of the region of interest (ROI)
based on the source data of enhanced CT.Although the rendered 3D images show the lesions, hepatic vessels, and their
spatial relationships more intuitively, compared with CT
source data, the process of 3D visualization loses delity.
The evaluation results will vary according to the level and
experience of the operator in reading the original CT lm.
Because hepatocellular carcinoma has a clear envelope
and a clear boundary, the articial segmentation of the tumor
is relatively simple and accurate; while hilar cholangiocarcinoma has no envelope, so the tumor boundary is often
unclear, and the precise delineation of the lesion is difcult.
This may easily cause secondary errors and reduce the accuracy of assessment.
The segmentation of liver segments by 3D visualization
technology is based on the course of hepatic vein and portal
vein, while the selection of segmentation plane cannot be
very accurate, especially when there are variations in the
course of these veins. Thus, there are errors in the accurate
division of liver segments.
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