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Motion Tracking Using Implanted Fiducials and Template Matching and Triangulation in Fluoroscopic Images for Pancreatic Cancer Stereotactic Body Radiation Therapy

O Oderinde1*, H Mostafavi2 , D Simpson1 , J Murphy1 , L Cervino1 , (1) University of California San Diego, San Diego, CA, (2) ,Palo Alto, CA,

Presentations

(Sunday, 7/14/2019) 4:30 PM - 5:00 PM

Room: Exhibit Hall | Forum 5

Purpose: Pancreatic cancer stereotactic body radiotherapy (SBRT) treatments are affected by respiratory motion, which can lead to an overdose of organs at risk (OARs) or suboptimal treatment. It is increasingly important to track the tumor motion to provide accurate and precise treatments. This study reports our first experience with RapidTrack (Varian Medical Systems, Palo Alto, CA), an offline research tool, designed to track target motion from radiographic projections using template matching and sequential stereo triangulation algorithms, by investigating the correlation between breathing amplitude sensed by an external surrogate and tumor motion from fluoroscopic images before and after SBRT (treatment time was 6-9 minutes).

Methods: Anterior-posterior (AP) and lateral fluoroscopic images of four pancreatic cancer patients treated on a Varian TrueBeam linac were used in this study. Tumor implanted fiducial markers’ position was correlated with the external surrogate signal (RPM, Varian) using RapidTrack.

Results: For the 10 treatment fractions considered, there is a significant correlation between the superior-inferior displacement of the fiducial markers and the RPM signal with average (±Standard Deviation) regression coefficients (r2) of 0.51±0.33, 0.95±0.08, and 0.74±0.20 for LR, SI and AP respectively. The average absolute baseline drift of the fiducials between the pre-treatment and post-treatment were 0.63±0.17, 0.54±0.08 and 0.90±0.24 mm for LR, SI and AP directions respectively.

Conclusion: The template matching and triangulation algorithm provides useful fiducials’ motion information for pre-treatment and post-treatment fluoroscopic projections. This algorithm is capable of locating fiducial markers in fluoroscopic images, hence proving useful for patient setup optimization.

Funding Support, Disclosures, and Conflict of Interest: This study was funded by Varian Medical Systems, Palo Alto, California, USA

Keywords

Fluoroscopy, Image-guided Therapy, Internal Dosimetry

Taxonomy

TH- RT Interfraction motion management : Registration and localization

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