Segmentation of focal liver lesions and virtual resection based on computed tomography data

Abstract

 The aim of the study was to test the work of plugins for segmentation and virtual resection of focal liver lesions based on CT data.

Materials and methods. Analysis of CT data of the abdominal organs with bolus contrast enhancement in 80 patients with focal liver lesions was carried out. Segmentation and 3D-modeling of the CT data was carried out by radiologists and the surgeon in the ‘Autoplan’ system.

Results. The liver nosological structure in patients was determined (the most common were hemangiomas in 21.25% of 80 patients, cysts in 20%, parasitic cysts in 20%, etc.), according to the computed tomography results. The segmentation of the liver, its focal lesions, arteries and veins was carried out using the ‘Autoplan’ system. The surgeon determined the volume of the parenchyma and focal liver formations using the standard function ‘volume of segmentation’, chose the optimal treatment tactics and performed a  virtual liver resection. In some cases, the use of segmentation and preoperative planning made it possible to avoid an inefficient surgery. The effectiveness of modeling changed the treatment tactics of 42 patients.

Conclusion. The obtained results indicate that the use of the ‘Autoplan’ system plugins for planning an abdominal surgery allows doctors: 1) to carry out the segmentation of liver, focal lesions and blood vessels; 2) to determine the location of a focal formation in a particular segment, their combination; 3) to perform a virtual resection, evaluate the structures passing through it; 4) to choose the optimal tactics of intervention or  abandon it due to objective anatomical reasons.