Development of a multi-modality 4D biomechanical phantom for evaluation of simultaneous registration/segmentation algorithms

Abstract

A package for evaluating joint registration/ segmentation (“regmentation” algorithms) and motion prediction systems was developed using a pair of preserved swine lungs pneumatically controlled with a custom-built respirator. The phantom is MRI, CT and PET compatible and moves in a realistic 4D non-rigid fashion. The segmentation and registration ground truths are provided by a dual compartment mock tumor and a bifurcation tracking pipeline. The mock tumor consists of two vacuum-sealed sea sponges in separate compartments, allowing for the injection of radiotracer to approximate an active tumor and surrounding healthy tissue. Injection is possible through catheters connected to each compartment. The boundary of the inner compartment, segmented post-extraction, provides a ground truth for the boundary of the tumor region. Bifurcations of the bronchi of the lungs were used as anatomical landmarks, providing a registration ground truth between two sets of images of the lungs using in-house bifurcation detection and matching software. The accuracy of the bifurcation tracking pipeline was found to be on the order of a voxel width for human and swine lung datasets, with tracking capabilities up to deformations of 7.8 and 3.4 cm respectively. Accuracy was evaluated using a known virtual deformation. The computer-controlled respirator was found capable of mimicking human breathing traces using the swine lungs within a maximum error of ±2.2% and an average error of ±0.5%. PET/CT and MRI scans of the lungs were acquired for various levels of image noise.