A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kV imaging

Abstract

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm/s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024 x 768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient.

Development and clinical evaluation of automatic fiducial detection for tumor tracking in cine megavoltage images during volumetric modulated arc therapy

“…Template matching was proposed by Shirato et al 17,18 to find the fiducial position. This approach was employed in the work by Mao et al [13][14][15] Here, we improve the method by developing a simple formula as a universal template that takes into account both fiducial rotation and the possibility of partial blockage of the fiducial on the cine MV image by the multileaf collimator (MLC) leaves, which can cause the apparent fiducial to be shorter than its actual length. Furthermore, to dynamically follow the movement of the fiducial, the search area in our method is updated in realtime.…”

“…The images for fiducial localization were taken with open fields during patient setup, before the treatment. In a following study, 14 they investigated the application of their algorithm to IMRT and addressed the issue of blocking of the fiducials. They presented near real-time tracking speeds for fixed gantry IMRT phantom studies.…”

Recommendation of fiducial marker implantation for better target tracking using MV imager in prostate radiotherapy

“…Real‐time prostate motion management techniques have been studied for almost a decade 2, 3, 4. Initially, the fiducial markers implanted inside the prostate served as a surrogate for precise alignment of prostate using portal imaging.…”

“…Initially, the fiducial markers implanted inside the prostate served as a surrogate for precise alignment of prostate using portal imaging. In most of the recently developed techniques, fiducial markers were used as a prostate margin tracker either by MV, kV or kV‐MV combined images 2, 3, 4, 5, 6, 7, 8, 9, 10, 11. It is important to note that the use of kV imaging techniques is not available in all clinics, and the additional dose that would be applied for every treatment fraction is of concern as well.…”

High-performance GPU-based rendering for real-time, rigid 2D/3D-image registration and motion prediction in radiation oncology

“…Methods for retrieving this additional image information range from ultrasound [6,7], magnetic resonance imaging [8] and, most important, kilovoltage and megavoltage x-ray imaging, either by means of planar radiography [9,10] or 3D modalities [11,12]. Non-rigid registration [13] techniques can be employed to simulate the deformation of the tumor [14,15] between treatment sessions.…”