Design and development of a nonrigid phantom for the quantitative evaluation of DIR‐based mapping of simulated pulmonary ventilation

Abstract

Purpose

The validation of deformable image registration (DIR)‐based pulmonary ventilation mapping is time consuming and prone to inaccuracies and is also affected by deformation parameters. In this study, we developed a nonrigid phantom as a quality assurance (QA) tool that simulates ventilation to evaluate DIR‐based images quantitatively.

Methods

The phantom consists of an acrylic cylinder filled with polyurethane foam designed to simulate pulmonic alveoli. A polyurethane membrane is attached to the inferior end of the phantom to simulate the diaphragm. In addition, tracheobronchial‐tree‐shaped polyurethane tubes are inserted through the foam and converge outside the phantom to simulate the trachea. Solid polyurethane is also used to model arteries, which closely follow the model airways. Two three‐dimensional (3D) CT scans were performed during exhalation and inhalation phases using xenon (Xe) gas as the inhaled contrast agent. The exhalation 3D‐CT image is deformed to an inhalation 3D‐CT image using our in‐house program based on the NiftyReg open‐source package. The target registration error (TRE) between the two images was calculated for 16 landmarks located in the simulated lung volume. The DIR‐based ventilation image was generated using Jacobian determinant (JD) metrics. Subsequently, differences in the Hounsfield unit (HU) values between the two images were measured. The correlation coefficient between the JD and HU differences was calculated. In addition, three 4D‐CT scans are performed to evaluate the reproducibility of the phantom motion and Xe gas distribution.

Results

The phantom exhibited a variety of displacements for each landmark (range: 1–20 mm). The reproducibility analysis indicated that the location differences were <1 mm for all landmarks, and the HU variation in the Xe gas distribution was close to zero. The mean TRE in the evaluation of spatial accuracy according to the DIR software was 1.47 ± 0.71 mm (maximum: 2.6 mm). The relationship between the JD and HU differences had a large correlation (R = −0.71) for the DIR software.

Conclusion

The phantom implemented new features, namely, deformation and simulated ventilation. To assess the accuracy of the DIR‐based mapping of the simulated pulmonary ventilation, the phantom allows for simulation of Xe gas wash‐in and wash‐out. The phantom may be an effective QA tool, because the DIR algorithm can be quickly changed and its accuracy evaluated with a high degree of precision.