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The FASEB Journal



Three-dimensional (3D) models have recently been used in pre-operative planning in rare, complex surgeries in many disciplines. The goal of this study was to determine the efficacy of using 3D models in common procedures that involve increased risk of injury to hepatic arteries in the biliary region. This would allow surgeons to plan around individual variation and prevent intra-operative complications in these regions. This study focuses on the feasibility of converting computed tomography (CT) scans into 3D models to identify anatomical variation and compares the results to the published rates of anatomical variation for the structures considered.


A total of 27 (n=27) CT scans of healthy individuals were obtained from the Cancer Imaging Archive and digitally segmented with Dragonfly and the 3D Slicer software using the semi-automated grow from seeds tool. The results were then manually reviewed and edited for accuracy. The liver, gall bladder, and spleen were segmented as well as the associated hepatic arterial vasculature: celiac trunk, splenic artery, left gastric artery, common hepatic artery, gastroduodenal artery, proper hepatic artery, right and left hepatic arteries, and the superior mesenteric artery. The segmented scans were then converted to a 3D model where they were classified using the CRL classification system which has a 99.8% classification rate.


All 3D models were classified into a CRL classification type. Nineteen (n=19) models were classified as Type 1, two (n=2) models as Type 2, one (n=1) model as Type 3, one (n=1) model as Type 4, two (n=2) models as Type 5, one (n=1) model as Type 9, and one (n=1) model did not fit under the classification system and remained unclassified. Previously published data was used to calculate the statistical expected value of each CRL type. A chi-square analysis was performed to determine if the dataset fit normal patterns of variation. The results of the statistical test were statistically different χ2=0.0008 than previously published patterns of anatomical variation due to the rare unclassifiable variant.


The study showed that it is feasible to use pre-operative CT scans to reconstruct 3D models that can be used to identify variant anatomy pre-operatively to assist in the planning of complex surgeries. The 3D slicer software did not require a computer with substantial hardware requirements and is able to be used on a personal computer. This means it is not necessary to purchase special equipment to implement in the hospital and could potentially allow physicians to explain procedures to patients in clinics outside of hospitals. In order to expand on the capabilities of pre-operative 3D models, it is necessary to investigate more automated methods to accurately segment the appropriate anatomy.



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