The liver is a vital organ of the digestive system which performs a wide range of functions, including protein synthesis, hormone production and glycogen storage. It consists of four lobes of unequal size and shape, and is connected to two major blood vessels, the hepatic vein and the portal vein. Liver resections, also referred to as hepatectomies, are performed for the treatment of malignant neoplasms, including hepatocellular carcinoma (HCC) and/or metastasis commonly arising from colorectal cancer. Hepatectomies may also be performed to treat intrahepatic gallstones or parasitic cysts of the liver.
Traditional liver surgery planning is based on visual observation of a series of two-dimensional (2D) computed tomography (CT) images. Before a hepatectomy, the radiologist or surgeon needs to characterize the anatomic structure of the patient's liver and its components. The hepatic vein, the portal vein, functional lobes and the cancer tumors have to be identified and located on the 2D CT images. This process is known as segmentation. Following the segmentation step, a resection curve is drawn on the 2D CT images by the radiologist or surgeon. This process is manually intensive and time consuming. Furthermore, the success of traditional liver surgery planning is highly dependent on the skill of the radiologist and/or surgeon. Moreover, while most radiologists prefer surgery planning by drawing resection curves on different 2D CT images, many surgeons are naturally three dimensionally (3D) oriented, rendering it difficult for surgeons to perform liver surgery planning based on traditional 2D radiological methods.
Automated liver surgery planning systems have been developed to identify anatomical, pathological and functional parts of the liver from 2D CT scans, to visualize a 3D model of the liver, and to generate a resection proposal for the surgeon. Computer-aided liver surgery planning systems may also propose a safety margin around specific hepatic features such as the portal vein and the hepatic vein, or propose a resection plan based on a required resection volume. However, the current computer-aided liver surgery planning systems are complicated, preventing untrained surgeons from utilizing the systems effectively. In addition, the accuracy and success of the simulation is highly dependent on the initial data that is provided by the user and is still dependent upon the skill of the radiologist and/or surgeon.
Thus, what is needed is an improved computer-aided liver surgery planning system that is easy to use and produces an optimized, customizable and robust liver resection proposal for the user. Furthermore, other desirable features and characteristics will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and this background of the disclosure.