Effect of different noise reduction techniques and template matching parameters on markerless tumor tracking using dual‐energy imaging

• Published in: Journal of applied clinical medical physics 2022-12, Vol.23 (12), p.e13821-n/a
• Main Authors: Kaur, Mandeep, Wagstaff, Peter, Mostafavi, Hassan, Lehmann, Mathias, Morf, Daniel, Zhu, Liangjia, Kang, Hyejoo, Walczak, Michal, Harkenrider, Matthew M., Roeske, John C.
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Bayes Theorem; dual‐energy imaging; Energy; Humans; image‐guided radiation therapy; Lung; Lung cancer; Lung Neoplasms - diagnostic imaging; lung tumor tracking; Medical imaging; Patients; Phantoms, Imaging; Planning; Tumors
• ISSN: 1526-9914; 1526-9914
• DOI: 10.1002/acm2.13821

Purpose To evaluate the impact of various noise reduction algorithms and template matching parameters on the accuracy of markerless tumor tracking (MTT) using dual‐energy (DE) imaging. Methods A Varian TrueBeam linear accelerator was used to acquire a series of alternating 60 and 120 kVp images (over a 180° arc) using fast kV switching, on five early‐stage lung cancer patients. Subsequently, DE logarithmic weighted subtraction was performed offline on sequential images to remove bone. Various noise reduction techniques—simple smoothing, anticorrelated noise reduction (ACNR), noise clipping (NC), and NC‐ACNR—were applied to the resultant DE images. Separately, tumor templates were generated from the individual planning CT scans, and band‐pass parameter settings for template matching were varied. Template tracking was performed for each combination of noise reduction techniques and templates (based on band‐pass filter settings). The tracking success rate (TSR), root mean square error (RMSE), and missing frames (percent unable to track) were evaluated against the estimated ground truth, which was obtained using Bayesian inference. Results DE‐ACNR, combined with template band‐pass filter settings of σlow = 0.4 mm and σhigh = 1.6 mm resulted in the highest TSR (87.5%), RMSE (1.40 mm), and a reasonable amount of missing frames (3.1%). In comparison to unprocessed DE images, with optimized band‐pass filter settings of σlow = 0.6 mm and σhigh = 1.2 mm, the TSR, RMSE, and missing frames were 85.3%, 1.62 mm, and 2.7%, respectively. Optimized band‐pass filter settings resulted in improved TSR values and a lower missing frame rate for both unprocessed DE and DE‐ACNR as compared to the use previously published band‐pass parameters based on single energy kV images. Conclusion Noise reduction strategies combined with the optimal selection of band‐pass filter parameters can improve the accuracy and TSR of MTT for lung tumors when using DE imaging.