3D surface imaging has the potential to provide submillimeter level head motion tracking. This is provided that a highly accurate camera-to-LINAC frame of reference calibration can be performed and that the reference ROI is of sufficient size and contains suitable surface features for registration.

This 6D robotic phantom has proven to be accurate under clinical standards and capable of reproducing tumor motion in 6D. Such functionality makes the robotic phantom usable for either quality assurance or research purposes.

Despite the existence of real-time kV intra-fractional tumor tracking strategies for many years, clinical adoption has been held back by concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work aims to solve this problem by investigating, for the first time, the use of convex optimization tools to optimally integrate this excess kV imaging dose into the MV therapeutic dose in order to make real-time kV tracking clinically feasible. Phase space files modeling both a 6 MV treatment beam and a kV on-board-imaging beam of a commercial LINAC were generated with BEAMnrc, and used to generate dose influence matrices in DOSXYZnrc for ten previously treated lung cancer patients. The dose optimization problem for IMRT, formulated as a quadratic problem, was modified to include additional constraints as required for real-time kV intra-fractional tracking. An interior point optimizer was used to solve the modified optimization problem. It was found that when using large kV imaging apertures during fluoroscopic tracking, combined MV + kV optimization lead to a 0.5%-5.17% reduction in the total number of monitor units assigned to the MV beam due to inclusion of the kV dose over the ten patients. This was accompanied by a reduction of up to 42% of the excess kV dose compared to standard MV IMRT with kV tracking. For all kV field sizes considered, combined MV + kV optimization provided prescription dose to the treatment volume coverage equal to the no-imaging case, yet superior to standard MV IMRT with non-optimized kV fluoroscopic tracking. With combined MV + kV optimization, it is possible to quantify in a patient specific way the dosimetric effect of real-time imaging on the patient. Such information is necessary when substantial kV imaging is performed.

Purpose Most radiation therapy optimization problems can be formulated as an unconstrained problem and solved efficiently by quasi-Newton methods such as the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. However, several next generation planning techniques such as total variation regularization based optimization and MV+kV optimization, involve constrained or mixed-norm optimization, and cannot be solved by quasi-Newton methods. Using standard optimization algorithms on such problems often leads to prohibitively long optimization times and large memory requirements. This work investigates the use of a recently developed proximal operator graph solver (POGS) in solving such radiation therapy optimization problems. Methods Radiation therapy inverse treatment planning was formulated as a graph form problem, and the proximal operators of POGS for quadratic optimization were derived. POGS was exploited for the first time to impose hard dose constraints along with soft constraints in the objective function. The solver was applied to several clinical treatment sites (TG119, liver, prostate, and head&neck), and the results were compared to the solutions obtained by other commercial and non-commercial optimizers. Results For inverse planning optimization with nonnegativity box constraints on beamlet intensity, the speed of POGS can compete with that of LBFGSB in some situations. For constrained and mixed-norm optimization, POGS is about one or two orders of magnitude faster than the other solvers while requiring less computer memory. Conclusions POGS was used for solving inverse treatment planning problems involving constrained or mixed-norm formulation on several example sites. This approach was found to improve upon standard solvers in terms of computation speed and memory usage, and is capable of solving traditionally difficult problems, such as total variation regularization based optimization and combined MV+kV optimization.

Purpose: External tracking systems used for patient positioning and motion monitoring during radiotherapy are now capable of detecting both translations and rotations. In this work, the authors develop a novel technique to evaluate the 6 degree of freedom 6(DOF) (translations and rotations) performance of external motion tracking systems. The authors apply this methodology to an infrared marker tracking system and two 3D optical surface mapping systems in a common tumor 6DOF workspace. Methods: An in-house designed and built 6DOF parallel kinematics robotic motion phantom was used to perform motions with sub-millimeter and subdegree accuracy in a 6DOF workspace. An infrared marker tracking system was first used to validate a calibration algorithm which associates the motion phantom coordinate frame to the camera frame. The 6DOF positions of the mobile robotic system in this space were then tracked and recorded independently by an optical surface tracking system after a cranial phantom was rigidly fixed to the moveable platform of the robotic stage. The calibration methodology was first employed, followed by a comprehensive 6DOF trajectory evaluation, which spanned a full range of positions and orientations in a 20 × 20 × 16 mm and 5• × 5 • × 5• workspace. The intended input motions were compared to the calibrated 6DOF measured points. Results:The technique found the accuracy of the infrared (IR) marker tracking system to have maximal root-mean square error (RMSE) values of 0.18, 0.25, 0.07 mm, 0.05• , 0.05 • , and 0.09• in left-right (LR), superior-inferior (SI), anterior-posterior (AP), pitch, roll, and yaw, respectively, comparing the intended 6DOF position and the measured position by the IR camera. Similarly, the 6DOF RSME discrepancy for the HD optical surface tracker yielded maximal values of 0.46, 0.60, 0.54 mm, 0.06• , 0.11 • , and 0.08 • in LR, SI, AP, pitch, roll, and yaw, respectively, over the same 6DOF evaluative workspace. An earlier generation 3D optical surface tracking unit was observed to have worse tracking capabilities than both the IR camera unit and the newer 3D surface tracking system with maximal RMSE of 0.69, 0.74, 0.47 mm, 0.28• , 0.19 • , and 0.18 • , in LR, SI, AP, pitch, roll, and yaw, respectively, in the same 6DOF evaluation space. Conclusions: The proposed technique was found to be effective at evaluating the performance of 6DOF patient tracking systems. All observed optical tracking systems were found to exhibit tracking capabilities at the sub-millimeter and subdegree level within a 6DOF workspace. C 2016 American Association of Physicists in Medicine. [http://dx

Purpose: To develop a control system to correct both translational and rotational head motion deviations in real-time during frameless stereotactic radiosurgery (SRS). Methods: A novel feedback control with a feed-forward algorithm was utilized to correct for the coupling of translation and rotation present in serial kinematic robotic systems. Input parameters for the algorithm include the real-time 6DOF target position, the frame pitch pivot point to target distance constant, and the translational and angular Linac beam off (gating) tolerance constants for patient safety. Testing of the algorithm was done using a 4D (XYZ + pitch) robotic stage, an infrared head position sensing unit and a control computer. The measured head position signal was processed and a resulting command was sent to the interface of a four-axis motor controller, through which four stepper motors were driven to perform motion compensation. Results: The control of the translation of a brain target was decoupled with the control of the rotation.

The automatic selection method successfully found ROIs stable over time for tracking head motion by excluding locally varying facial motions. By automating the ROI selection process, it is feasible that the time and complexity of current ROI definition can be reduced, together with user-dependent registration errors.

Purpose: With the increasing use of external 3D optical tracking cameras to guide modern radiation therapy procedures, it has become vitally important to have an accurate camera to linear accelerator (LINAC) reference frame calibration. To eliminate errors present in current calibration procedures based on the manual hand alignment of a device using the light field crosshairs and in room guidance lasers, a semiautomated quantitative calibration approach requiring only use of an electronic portal imaging device (EPID) was developed. Methods: A phantom comprised of seven highly IR reflective plastic BBs was placed on the LINAC treatment couch and imaged with both a 3D stereoscopic IR imager and the on board megavoltage (MV) EPID imager. Having knowledge of the optically determined 3D positions and projected EPID images of the BBs, simulated annealing was used to optimize the location of the BBs in the LINAC frame using four different optimization functions. Singular value decomposition was then used to calculate the transformation matrix between the camera and LINAC reference frames. Results were then compared to a traditional camera calibration method for overall accuracy. Results: Using modeled data, the simulated annealing process was able to determine the actual locations of the BBs with a RMSE of 0.23 mm. Using projection images acquired with an MV imager, the process was able to determine locations of BBs within .26 mm. The results depend on the choice of optimization function. Conclusions: Results show that the method can be used to provide highly accurate spatial registration between an external 3D imaging reference frame and the LINAC frame. The experimental MV imager results, while not as precise as the simulated results, exceed 1 mm accuracy and the current accepted AAPM TG-142 standard of 2 mm positioning accuracy.