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Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation: Robustness and Accuracy Assessment. Int J Radiat Oncol Biol Phys 2018 Feb 01;100(2):325-334

Date

11/22/2017

Pubmed ID

29157746

DOI

10.1016/j.ijrobp.2017.10.004

Scopus ID

2-s2.0-85034114144   15 Citations

Abstract

PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments.

METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized cross-correlation function as the likelihood calculation. With a total of 5 healthy volunteers and 8 patients, the robustness of the algorithm was tested on 24 dynamic magnetic resonance imaging (MRI) time series with varying resolution, contrast, and signal-to-noise ratio. The complete data set included data acquired with different scan parameters on a number of MRI scanners with varying field strengths, including the 1.5T MR linear accelerator. Tracking errors were computed by comparing the results obtained by the particle filter algorithm with experts' delineations.

RESULTS: The ameliorated tracking algorithm was able to accurately track abdominal as well as thoracic tumors, whereas the previous Bhattacharyya distance-based implementation failed in more than 50% of the cases. The tracking error, combined over all MRI acquisitions, is 1.1 ± 0.4 mm, which demonstrated high robustness against variations in contrast, noise, and image resolution. Finally, the effect of the input/control parameters of the model was very similar across all cases, suggesting a class-based optimization is possible.

CONCLUSIONS: The modified particle filter tracking algorithm is highly accurate and robust against varying image quality. This makes the algorithm a promising candidate for automated tracking on the MR linear accelerator.

Author List

Bourque AE, Bedwani S, Carrier JF, Ménard C, Borman P, Bos C, Raaymakers BW, Mickevicius N, Paulson E, Tijssen RHN

Authors

Nikolai J. Mickevicius PhD Assistant Professor in the Radiology department at Medical College of Wisconsin
Eric Paulson PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Algorithms
Filtration
Humans
Magnetic Resonance Imaging
Neoplasms
Radiotherapy, Image-Guided
Respiration