Characterization of Markerless Tumor Tracking Using the On-Board Imager of a Commercial Linear Accelerator Equipped With Fast-kV Switching Dual-Energy Imaging

Abstract

Purpose To describe and characterize fast-kV switching, dual-energy (DE) imaging implemented within the on-board imager of a commercial linear accelerator for markerless tumor tracking (MTT). Methods and Materials Fast-kV switching, DE imaging provides for rapid switching between programmed tube voltages (ie, 60 and 120 kVp) from one image frame to the next. To characterize this system, the weighting factor used for logarithmic subtraction and signal difference-to-noise ratio were analyzed as a function of time and frame rate. MTT was evaluated using a thorax motion phantom and fast kV, DE imaging was compared versus single energy (SE) imaging over 360 degrees of rotation. A template-based matching algorithm was used to track target motion on both DE and SE sequences. Receiver operating characteristics were used to compare tracking results for both modalities. Results The weighting factor was inversely related to frame rate and stable over time. After applying the frame rate–dependent weighting factor, the signal difference-to-noise ratio was consistent across all frame rates considered for simulated tumors ranging from 5 to 25 mm in diameter. An analysis of receiver operating characteristics curves showed improved tracking with DE versus SE imaging. The area under the curve for the 10-mm target ranged from 0.821 to 0.858 for SE imaging versus 0.968 to 0.974 for DE imaging. Moreover, the residual tracking errors for the same target size ranged from 2.02 to 2.18 mm versus 0.79 to 1.07 mm for SE and DE imaging, respectively. Conclusions Fast-kV switching, DE imaging was implemented on the on-board imager of a commercial linear accelerator. DE imaging resulted in improved MTT accuracy over SE imaging. Such an approach may have application for MTT of patients with lung cancer receiving stereotactic body radiation therapy, particularly for small tumors where MTT with SE imaging may fail.

Markerless 3D tumor tracking during single-fraction free-breathing 10MV flattening-filter-free stereotactic lung radiotherapy

“…The image quality is influenced by image acquisition parameters and patient related factors such as patient diameter, overlying structures and location and size of the tumor. To improve image quality, dual-energy systems are one technology being studied [19]. Tumor 1 was challenging to track mainly due to overprojection of the spine; in this case, tracking was possible for 55% of the time.…”

A novel bone suppression algorithm in intensity‐based 2D/3D image registration for real‐time tumor motion monitoring: Development and phantom‐based validation

“…The cancer detection rate, motion tracking error,and computer-aided localization of lung nodules could be improved with some commercially available softwares, such as OnGuard, SoftView, Clear-Read + Detect, [21][22][23][24] or the Samsung BS Software. 25 Block et al 20 and Roeske et al 26 tested RapidTrack software (Varian Medical Systems, Palo Alto, CA, USA) in a phantom and patient study and reported a decrease in tracking range error when BS images were used for image registration. Nodule detection visibility could also be improved with a combination of machine learning and pattern recognition algorithms.…”

“…Block et al 20 . and Roeske et al 26 . tested RapidTrack software (Varian Medical Systems, Palo Alto, CA, USA) in a phantom and patient study and reported a decrease in tracking range error when BS images were used for image registration.…”

Effect of different noise reduction techniques and template matching parameters on markerless tumor tracking using dual‐energy imaging

“…4,[6][7][8][9][10] One of these approaches is dual-energy (DE) subtraction imaging that improves the contrast of lung tumors by removing bone and has been shown to increase the accuracy of MTT. [8][9][10][11][12][13] However, this improved tumor contrast comes at the cost of increased image noise, 13 which may decrease the accuracy of MTT. To regain the benefits of bone removal, several noise reduction techniques have been investigated for DE imaging primarily in the diagnostic setting.…”

“…Although several tracking approaches are being considered for MTT, we and others have been investigating the use of template tracking algorithms. 6,[9][10][11] Template tracking uses 2-D templates of the tumor generated from the planning CT scan at the corresponding imaging angle. The template is scanned within a defined search window and the normalized cross-correlation (NCC) is calculated between template and image.…”