A more recent competing technology for implementing the DIBH technique is real-time surface photogrammetry using the AlignRT system (Vision RT Ltd., London, UK). AlignRT system use non-ionization near infrared light to track patient surface motion. The system has one projector projecting near infrared optical pattern on patient surface. The optical pattern is imaged by optical cameras (two per pod) at \~25 Hz. The user selects a region-of-interest (ROI) on the surface and the software calculates and displays the real-time position in six degrees (3 translations and 3 rotations) in real-time. Once the patient has matched the pre-determined DIBH position (within threshold accuracy), the radiation beam is enabled to be turned on for treatment.
VRT-DIBH has already applied to left breast radiotherapy to spare lung and heart. Compared to ABC-DIBH, VRT-DIBH has several potential advantages: 1. VRT monitors patient (surface) position in addition to DIBH signal, while ABC only check the tidal volume, which can remain the same even if the patient shifts slightly on the couch; 2. VRT is more cost effective, as patient tubing needs to be replaced daily for ABC; 3. VRT potentially has advantage on patient compliance, as with ABC breath is forced impeded while with VRT breath-hold is voluntary. In this study, we renovate the established DIBH motion management strategy by adopting AlignRT system. The purpose of this study is to develop, validate, and prove the feasibility of VRT-DIBH technique for lung and liver SBRT.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DEVICE_FEASIBILITY
Masking
NONE
Enrollment
10
The SOC DIBH CT scan will be transferred to Eclipse treatment planning system for treatment planning. Tidal volume measured by spirometer and DIBH surface from CT image will be used as a reference surface for patient treatment initial setup. CBCT will be acquired before each fractional treatment for the patient alignment before beam delivery.
UT Southwestern Medical Center
Dallas, Texas, United States
Correlation Between Kilovoltages X-ray Images of the Diaphragm and the Surface Guided Motion Analyzed With Matlab
VRT-DIBH (VisionRT-based deep inspiration breath-hold) feasibility will be evaluated using descriptive statistics to explore the geometry accuracy and to characterize tumor motion/surface stability and repeatability during treatment. CT images of the treatment site, as well as kV projections and VRT surface images, will be taken and analyzed for this purpose. The trajectory data and kV projection data were analyzed in Matlab. In the kV images, the diaphragm was segmented and used for tracking of the BH position. This was done using several steps including: derivatives, polynomial curve fitting and high pass filtering. The correlation was then measured using a Pearson correlation. Correlation of each breath hold was taken and averaged.
Time frame: 1 month
Target Margin Contingency Table Based on Surface and Diaphragm Motion
To assess the necessary margin for a target, the amount of surface and diaphragm motion was analyzed. For each x-ray image the diaphragm motion and corresponding surface motion were recorded. These motions were then categorized based on their size and researchers counted how often these movements fell within the specified motion ranges.
Time frame: 1 month
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