Review and comparison of geometric distortion correction schemes in MR images used in stereotactic radiosurgery applications

• Published in: Journal of physics. Conference series 2017-11, Vol.931 (1), p.12031
• Main Authors: Pappas, E. P., Dellios, D., Seimenis, I., Moutsatsos, A., Georgiou, E., Karaiskos, P.
• Format: Article
• Language: English
• Subjects: Accuracy; Chemical equilibrium; Coils; Computing time; Distortion; Edge detection; Geometric accuracy; Imaging; Inhomogeneity; Physics; Radiology; Soft tissues; Surgery
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/931/1/012031

In Stereotactic Radiosurgery (SRS), MR-images are widely used for target localization and delineation in order to take advantage of the superior soft tissue contrast they exhibit. However, spatial dose delivery accuracy may be deteriorated due to geometric distortions which are partly attributed to static magnetic field inhomogeneity and patient/object-induced chemical shift and susceptibility related artifacts, known as sequence-dependent distortions. Several post-imaging sequence-dependent distortion correction schemes have been proposed which mainly employ the reversal of read gradient polarity. The scope of this work is to review, evaluate and compare the efficacy of two proposed correction approaches. A specially designed phantom which incorporates 947 control points (CPs) for distortion detection was utilized. The phantom was MR scanned at 1.5T using the head coil and the clinically employed pulse sequence for SRS treatment planning. An additional scan was performed with identical imaging parameters except for reversal of read gradient polarity. In-house MATLAB routines were developed for implementation of the signal integration and average-image distortion correction techniques. The mean CP locations of the two MR scans were regarded as the reference CP distribution. Residual distortion was assessed by comparing the corrected CP locations with corresponding reference positions. Mean absolute distortion on frequency encoding direction was reduced from 0.34mm (original images) to 0.15mm and 0.14mm following application of signal integration and average-image methods, respectively. However, a maximum residual distortion of 0.7mm was still observed for both techniques. The signal integration method relies on the accuracy of edge detection and requires 3-4 hours of post-imaging computational time. The average-image technique is a more efficient (processing time of the order of seconds) and easier to implement method to improve geometric accuracy in such applications.