Markerless EPID image guided dynamic multi-leaf collimator tracking for lung tumors

Abstract

Compensation of target motion during the delivery of radiotherapy has the potential to improve treatment accuracy, dose conformity and sparing of healthy tissue. We implement an online image guided therapy system based on soft tissue localization (STiL) of the target from electronic portal images and treatment aperture adaptation with a dynamic multi-leaf collimator (DMLC). The treatment aperture is moved synchronously and in real-time with the tumor during the entire breathing cycle. The system is implemented and tested on a Varian TX clinical linear accelerator featuring an AS-1000 electronic portal imaging device (EPID) acquiring images at a frame rate of 12.86 Hz throughout the treatment. A position update cycle for the treatment aperture consists of 4 steps: in the first step at time t = t0 a frame is grabbed, in the second step the frame is processed with the STiL algorithm to get the tumor position at t = t0, in a third step the tumor position at t = t + δt is predicted to overcome system latencies and in the fourth step, the DMLC control software calculates the required leaf motions and applies them at time t = t + δt. The prediction model is trained before the start of the treatment with data representing the tumor motion. We analyze the system latency with a dynamic chest phantom (4D motion phantom, Washington University). We estimate the average planar position deviation between target and treatment aperture in a clinical setting by driving the phantom with several lung tumor trajectories (recorded from fiducial tracking during radiotherapy delivery to the lung). DMLC tracking for lung SBRT without fiducial markers was successfully demonstrated. The inherent system latency is found to be δt = (230 ± 11) ms for a MV portal image acquisition frame rate of 12.86 Hz. The root mean square deviation between tumor and aperture position is smaller than 1 mm. We demonstrate the feasibility of real-time markerless DMLC tracking with a standard LINAC-mounted (EPID).

A comparative study of automatic image segmentation algorithms for target tracking in MR‐IGRT

“…A recent method using 1D MRI pencil‐beam navigators to track tissue motion reported accuracy within 1.5 mm in one case of kidney motion (40) . Another real‐time markerless motion tracking method for lung tumor tracking showed a root mean square deviation less than 1 mm (41) . Here we showed that the tracking error was also within 1 mm when using FKM, KHM, and VR‐TPDS methods for segmenting bladder and kidney.…”

The first patient treatment of electromagnetic-guided real time adaptive radiotherapy using MLC tracking for lung SABR

“…The electromagnetic transponders provide an internal surrogate of the tumour and their location will affect the accuracy of their surrogate motion. Further research is directed towards markerless MLC tracking that would not require implantation of transponders, a potential source of toxicity, replaced with direct (image-based) tracking [31][32][33][34].…”

Low Z target switching to increase tumor endothelial cell dose enhancement during gold nanoparticle-aided radiation therapy

“…We anticipate that both volumetric and planar imaging with the therapy beam will be greatly improved by the target modifications presented here, resulting in improved patient setup and beam's-eye-view in-treatment imaging. 34,[43][44][45] For example, fast and periodic imaging of a lung tumor with a low Z target could be used to update predictive models of respiratory motion, without interruption of the treatment delivery. Previously published imaging work with low Z targets demonstrated a marked improvement in image contrast using a 2.35 MV beam with a carbon target.…”