Purpose: Real-time tracking of implanted fiducials in cine megavoltage (MV) imaging during volumetric modulated arc therapy (VMAT) delivery is complicated due to the inherent low contrast of MV images and potential blockage of dynamic leaves configurations. The purpose of this work is to develop a clinically practical autodetection algorithm for motion management during VMAT. Methods: The expected field-specific segments and the planned fiducial position from the Eclipse (Varian Medical Systems, Palo Alto, CA) treatment planning system were projected onto the MV images. The fiducials were enhanced by applying a Laplacian of Gaussian filter in the spatial domain for each image, with a blob-shaped object as the impulse response. The search of implanted fiducials was then performed on a region of interest centered on the projection of the fiducial when it was within an open field including the case when it was close to the field edge or partially occluded by the leaves. A universal template formula was proposed for template matching and normalized cross correlation was employed for its simplicity and computational efficiency. The search region for every image was adaptively updated through a prediction model that employed the 3D position of the fiducial estimated from the localized positions in previous images. This prediction model allowed the actual fiducial position to be tracked dynamically and was used to initialize the search region. The artifacts caused by electronic interference during the acquisition were effectively removed. A score map was computed by combining both morphological information and image intensity. The pixel location with the highest score was selected as the detected fiducial position. The sets of cine MV images taken during treatment were analyzed with in-house developed software written in MATLAB (The Mathworks, Inc., Natick, MA). Five prostate patients were analyzed to assess the algorithm performance by measuring their positioning accuracy during treatment. Results: The algorithm was able to accurately localize the fiducial position on MV images with success rates of more than 90% per case. The percentage of images in which each fiducial was localized in the studied cases varied between 23% and 65%, with at least one fiducial having been localized between 40% and 95% of the images. This depended mainly on the modulation of the plan and fiducial blockage. The prostate movement in the presented cases varied between 0.8 and 3.5 mm (mean values). The maximum displacement detected among all patients was of 5.7 mm. Conclusions: An algorithm for automatic detection of fiducial markers in cine MV images has been developed and tested with five clinical cases. Despite the challenges posed by complex beam aperture shapes, fiducial localization close to the field edge, partial occlusion of fiducials, fast leaf and gantry movement, and inherently low MV image quality, good localization results were achieved in patient images. This work provides a technique for enabling real-time accurate fiducial d...

Purpose To develop a method for dose reconstruction by incorporating the interplay effect between aperture modulation and target motion, and to assess the dosimetric impact of real-time prostate motion during volumetric modulated arc therapy (VMAT). Methods and Materials Clinical VMAT plans were delivered with the TrueBeam linac for 8 patients with prostate cancer. The real-time target motion during dose delivery was determined based on the 2-dimensional fiducial localization using an onboard electronic portal imaging device. The target shift in each image was correlated with the control point with the same gantry angle in the VMAT plan. An in-house–developed Monte Carlo simulation tool was used to calculate the 3-dimensional dose distribution for each control point individually, taking into account the corresponding real-time target motion (assuming a nondeform-able target with no rotation). The delivered target dose was then estimated by accumulating the dose from all control points in the plan. On the basis of this information, dose-volume histograms and 3-dimensional dose distributions were calculated to assess their degradation from the planned dose caused by target motion. Thirty-two prostate motion trajectories were analyzed. Results The minimum dose to 0.03 cm3 of the gross tumor volume (D0.03cc) was only slightly degraded after taking motion into account, with a minimum value of 94.1% of the planned dose among all patients and fractions. However, the gross tumor volume receiving prescription dose (V100%) could be largely affected by motion, dropping below 60% in 1 trajectory. We did not observe a correlation between motion magnitude and dose degradation. Conclusions Prostate motion degrades the delivered dose to the target in an unpredictable way, although its effect is reduced over multiple fractions, and for most patients the degradation is small. Patients with greater prostate motion or those treated with stereotactic body radiation therapy would benefit from real-time prostate tracking to reduce the margin.

Purpose To use four‐dimensional (4D) dose accumulation based on deformable image registration (DIR) to assess dosimetric uncertainty in lung stereotactic body radiation therapy (SBRT) treatment planning. A novel concept, the Evaluation Target Volume (ETV), was introduced to achieve this goal. Methods The internal target volume (ITV) approach was used for treatment planning for 11 patients receiving lung SBRT. Retrospectively, 4D dose calculation was done in Pinnacle v9.10. Total dose was accumulated in the reference phase using DIR with MIM. DIR was validated using landmarks introduced by an expert radiation oncologist. The 4D and three‐dimensional (3D) dose distributions were compared within the gross tumor volume (GTV) and the planning target volume (PTV) using the D95 and Dmin (calculated as Dmin,0.035cc) metrics. For lung involvement, the mean dose and V20, V10, and V5 were used in the 3D to 4D dose comparison, and Dmax (D0.1cc) was used for all other organs at risk (OAR). The new evaluation target volume (ETV) was calculated by expanding the GTV in the reference phase in order to include geometrical uncertainties of the DIR, interobserver variability in the definition of the tumor, and uncertainties of imaging and delivery systems. D95 and Dmin,0.035cc metrics were then calculated on the basis of the ETV for 4D accumulated dose distributions, and these metrics were compared with those calculated from the PTV for 3D planned dose distributions. Results The target registration error (TRE) per spatial component was below 0.5 ± 2.1mm for all our patients. For five patients, dose degradation above 2% (>4% in 2 patients) was found in the PTV after 4D accumulation and attributed to anatomical variations due to breathing. Comparison of D95 and Dmin,0.035cc metrics showed that the ETV (4D accumulated dose) estimated substantially lower coverage than the PTV (3D planning dose): in six out of the 11 cases, and for at least for one of the two metrics, coverage estimated by ETV was at least 5% lower than that estimated by PTV. Furthermore, the ETV approach revealed hot and cold spots within its boundaries. Conclusions A workflow for 4D dose accumulation based on DIR has been devised. Dose degradation was attributed to respiratory motion. To overcome limitations in the PTV for the purposes of evaluating DIR‐based 4D accumulated dose distributions, a new concept, the ETV, was proposed. This concept appears to facilitate more reliable dose evaluation and a better understanding of dosimetric uncertainties due to motion and deformation.

The number of intensity modulated radiation therapy ͑IMRT͒ procedures is continuously growing worldwide and it is necessary to develop tools for patient specific quality assurance ͑QA͒ that avoid using machine time that could be employed in treating additional patients. One way of achieving this goal is to perform a multileaf collimator quality assurance periodically in the linear accelerator and check the treatment planning system ͑TPS͒ calculation by employing an independent calculation system. Within the work frame of the pencil beam kernel approach, a new system was developed for obtaining an experimental kernel. This new technique is based on a deconvolution procedure using the Hankel transform. The resulting kernel is obtained in a way completely independent of those employed in commercial treatment planning systems, usually calculated by Monte Carlo simulations. Also provided are comparisons between calculated and measured doses with radiographic film, linear array of diodes, and ionization chamber. Measurements taken in polystyrene and water for clinical IMRT plans demonstrate that this method can calculate IMRT dose distributions, as well as treatment times, with great accuracy. Apart from other applications, it can be used as a double-check algorithm for IMRT QA.

Purpose To assess the prostate intrafraction motion in volumetric modulated arc therapy treatments using cine megavoltage (MV) images acquired with the electronic portal imaging device (EPID). Materials and methods Ten prostate cancer patients were treated with volumetric modulated radiation therapy (VMAT), using a Varian TrueBeam (Varian Medical Systems, Palo Alto, CA) linear accelerator (linac) equipped with EPID for acquiring cine MV images during treatment. Cine MV images acquisition was scheduled for single or multiple treatment fractions (between 1 and 8). A novel automatic fiducial detection algorithm that can handle irregular multileaf collimator (MLC) apertures, field edges, fast leaf and gantry movement, and MV image noise and artifacts in patient anatomy was used. All sets of images (~25,000 images in total) were analyzed to measure the positioning accuracy of implanted fiducial markers and assess the prostate movement. Results Prostate motion can vary greatly in magnitude among different patients. Different motion patterns were identified showing its unpredictability. The mean displacement and standard deviation of the intrafraction motion was generally less than 2.0 ± 2.0 mm in each of the spatial directions. In certain patients, however, the percentage of the treatment time in which the prostate is displaced more than 5 mm from its planned position in at least one spatial direction was 10% or more. The maximum prostate displacement observed was 13.3 mm. Conclusion Prostate tracking and motion assessment was performed with MV imaging and an EPID. The amount of prostate motion observed suggests that patients will benefit from its real-time monitoring. MV imaging can provide the basis for real-time prostate tracking using conventional linacs.