Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to ‘see what we treat, as we treat’ and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

The real-time beam-target correction method, electromagnetic transponder-guided MLC tracking, has been translated to the clinic. This achievement represents a milestone in improving geometric and dosimetric accuracy, and by inference treatment outcomes, in cancer radiotherapy.

Purpose-For intrafraction motion management, a real-time tracking system was developed by combining fiducial marker-based tracking via simultaneous kilovoltage (kV) and megavoltage (MV) imaging and a dynamic multileaf-collimator (DMLC) beam-tracking system.Methods and Materials-The integrated tracking system employed a Varian Trilogy system equipped with kV/MV imaging systems and a Millennium 120-leaf MLC. A gold marker in elliptical motion (2-cm superior-inferior, 1-cm left-right, 10 cycles/min) was simultaneously imaged by the kV and MV imagers at 6.7 Hz, and segmented in real time. With these two 2D projections, the tracking software triangulated the 3D marker position and repositioned the MLC leaves to follow the motion. Phantom studies were performed to evaluate time delay from image acquisition to MLC adjustment, tracking error, and dosimetric impact of target motion with and without tracking.Results-The time delay of the integrated tracking system was ~450 ms. The tracking error using a prediction algorithm was 0.9±0.5 mm for the elliptical motion. The dose distribution with tracking showed better target coverage and less dose to surrounding region over no tracking. The failure rate of the gamma test (3%/3-mm criteria) was 22.5% without tracking , but was reduced to 0.2% with tracking.Conclusion-For the first time, a complete tracking system combining kV/MV image-guided target tracking and DMLC beam tracking was demonstrated. The average geometric error was less than 1 mm, while the dosimetric error was negligible. This system is a promising method for intrafraction motion management.

In radiotherapy, target motion during treatment delivery can be managed either by motion inclusive margins or by gating or tracking based on intrafraction target position monitoring. If radio-opaque fiducial markers are used the required three-dimensional (3D) target position signal for gating or tracking can be obtained by simultaneous acquisition of two x-ray images from different angles. However, most treatment machines do not have such stereoscopic imaging capability. Alternatively, the 3D target position may be estimated with a single imager (monoscopic imaging) although it only provides the projected target position in the two dimensions of the imager plane. In this study, we developed a probability-based method to estimate the unresolved motion component parallel to the imager axis from the projected motion. A 3D Gaussian probability density was assumed for the target position. Projection of the target into a certain point on the imager means that it is located on the ray line that connects this point with the focus point of the x-ray source. The 1D probability density along this line was calculated from the 3D probability density and its expectation value was used as the estimate for the unresolved position. The mathematical framework of the method was developed including analytical expressions for the estimated unresolved component as a function of resolved components and for the estimation uncertainty. Use of the method was demonstrated for prostate in a simulation study of monoscopic imaging. First, the required 3D probability density was constructed as a population average from a data set consisting of 536 continuous prostate position tracks from 17 patients recorded at 10 Hz. Next, monoscopic imaging at a fixed imaging angle and imaging frequency was simulated for each prostate track. Estimated 3D prostate tracks were constructed from the simulated projection images by the proposed method and compared with the actual tracks in order to determine the root-mean-square (rms) error. The simulations were performed with imaging angles in the range from 0 degrees to 180 degrees (relative to vertical) and imaging frequencies in the range from 0.1 s (corresponding to continuous imaging) to 600 s (corresponding to no intrafraction imaging). For comparison, simulations were also performed with stereoscopic imaging, where perfect position determination in all three directions was assumed, and with monoscopic imaging without estimation of the unresolved motion, where the motion component along the imager axis was assumed to be zero. For continuous imaging, the accuracy of monoscopic imaging was limited by the uncertainty in the unresolved position estimation. The resulting vector rms error for the population corresponded closely to the theoretically derived estimation uncertainty. The estimation did not improve the accuracy of lateral monoscopic imaging, but it reduced the population rms error from 1.59 mm to 1.11 mm for vertical imaging. This improvement was most prominent for outlying tracks with large unresolv...

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Summary Most cancer radiation therapy accelerators purchased today have gantry-mounted imagers, typically used to image the patient prior to treatment. We imaged prostate cancer patients during their treatment. Combining images with marker segmentation software and a 2- to 3-dimensional reconstruction method, we were able to measure prostate motion during the treatment to within submillimeter accuracy. Because intrafraction prostate monitoring method uses widely available clinical equipment, intratreatment prostate motion monitoring could become routine. Purpose Most linear accelerators purchased today are equipped with a gantry-mounted kilovoltage X-ray imager which is typically used for patient imaging prior to therapy. A novel application of the X-ray system is kilovoltage intrafraction monitoring (KIM), in which the 3-dimensional (3D) tumor position is determined during treatment. In this paper, we report on the first use of KIM in a prospective clinical study of prostate cancer patients undergoing intensity modulated arc therapy (IMAT). Methods and Materials Ten prostate cancer patients with implanted fiducial markers undergoing conventionally fractionated IMAT (RapidArc) were enrolled in an ethics-approved study of KIM. KIM involves acquiring kV images as the gantry rotates around the patient during treatment. Post-treatment, markers in these images were segmented to obtain 2D positions. From the 2D positions, a maximum likelihood estimation of a probability density function was used to obtain 3D prostate trajectories. The trajectories were analyzed to determine the motion type and the percentage of time the prostate was displaced ≥3, 5, 7, and 10 mm. Independent verification of KIM positional accuracy was performed using kV/MV triangulation. Results KIM was performed for 268 fractions. Various prostate trajectories were observed (ie, continuous target drift, transient excursion, stable target position, persistent excursion, high-frequency excursions, and erratic behavior). For all patients, 3D displacements of ≥3, 5, 7, and 10 mm were observed 5.6%, 2.2%, 0.7% and 0.4% of the time, respectively. The average systematic accuracy of KIM was measured at 0.46 mm. Conclusions KIM for prostate IMAT was successfully implemented clinically for the first time. Key advantages of this method are (1) submillimeter accuracy, (2) widespread applicability, and (3) a low barrier to clinical implementation. A disadvantage is that KIM delivers additional imaging dose to the patient.

A method for accurate dose reconstruction for moving targets with dynamic treatments was developed and experimentally validated in a variety of delivery scenarios. The method is suitable for integration into TPSs, e.g., for reconstruction of the dose delivered to moving tumors or calculation of target doses delivered with DMLC tracking.