Calculating tumor trajectory and dose‐of‐the‐day using cone‐beam CT projections

Abstract

Purpose: Cone-beam CT (CBCT) projection images provide anatomical data in real-time over several respiratory cycles, forming a comprehensive picture of tumor movement. We developed and validated a method which uses these projections to determine the trajectory of and dose to highly mobile tumors during each fraction of treatment.Methods: CBCT images of a respiration phantom were acquired, the trajectory of which mimicked a lung tumor with high amplitude (up to 2.5 cm) and hysteresis. A template-matching algorithm was used to identify the location of a steel BB in each CBCT projection, and a Gaussian probability density function for the absolute BB position was calculated which best fit the observed trajectory of the BB in the imager geometry. Two modifications of the trajectory reconstruction were investigated: first, using respiratory phase information to refine the trajectory estimation (Phase), and second, using the Monte Carlo (MC) method to sample the estimated Gaussian tumor position distribution. The accuracies of the proposed methods were evaluated by comparing the known and calculated BB trajectories in phantom-simulated clinical scenarios using abdominal tumor volumes.Results: With all methods, the mean position of the BB was determined with accuracy better than 0.1 mm, and root-mean-square (RMS) trajectory errors averaged 3.8±1.1% of the marker amplitude. Dosimetric calculations using Phase methods were more accurate, with mean absolute error less than 0.5%, and with error less than 1% in the highest-noise trajectory. MC-based trajectories prevent the over-estimation of dose, but when viewed in an absolute sense, add a small amount of dosimetric error (<0.1%).Conclusions: Marker trajectory and target dose-of-the-day were accurately calculated using CBCT projections. This technique provides a method to evaluate highly-mobile tumors using ordinary CBCT data, and could facilitate better strategies to mitigate or compensate for motion during SBRT.This manuscript was submitted to Medical Physics

An evaluation of motion mitigation techniques for pancreatic SBRT

“…Due to such discrepancies, more comprehensive techniques for motion evaluation are required [19]. We have developed and implemented an in-house motion reconstruction technique to accurately determine daily tumor motion (described below) [20]. As such, motion measurements for this work were obtained by cone-beam CT (CBCT) imaging just prior to treatment.…”

“…A two-part, in-house routine developed and implemented in MATLAB (Mathworks, Natick, MA) was used to track fiducial markers in CBCT projection images and then reconstruct the 3D trajectory that occurred during each CBCT scan, both of which have been described elsewhere [20,21]. In brief, the fiducial marker tracking component of the routine automatically tracks markers with an iterative routine that reconstructs the cluster of markers, creates template images based on this reconstruction, then uses template-matching to track and stabilize markers in projection images.…”

Adaptive motion mapping in pancreatic SBRT patients using Fourier transforms

“…The daily trajectory of the tumor throughout the CBCT acquisition was calculated using a previously developed and validated method 19 . This technique was based on the work of Poulsen et al 20,21 and proceeded as follows.…”

Model-Supported Radiotherapy Personalization: In silico Test of Hyper- and Hypo-Fractionation Effects

“…Regarding dose delivery, irradiation is usually carefully planned by optimizing the beam entry and activation strategies to administer the tumor with the prescribed amount of dose while sparing the organ at risks (OAR). The dose profile can be adjusted according to slow morphological changes (inter-fraction) using a plan-of-the-day approach ( Heijkoop et al, 2014 ; Jones et al, 2015 ; Sharfo et al, 2016 ) while faster dynamics (e.g., respiration) can be addressed by means of time resolved images ( Keall et al, 2006 ; Schaerer et al, 2012 ; Paganelli et al, 2015 ). In other words, the level of treatment personalization in dose delivery management can be quite impressive.…”