Biomedical subjects

T Rock Mackie

Publications and source records attributed to T Rock Mackie.

6 recordsLinked to original sources

PubMed2006

Tomotherapy and other innovative IMRT delivery systems.

Fixed-field treatments, delivered using conventional clinical linear accelerators fitted with multileaf collimators, have rapidly become the standard form of intensity-modulated radiotherapy (IMRT). Several innovative nonstandard alternatives also exist, for which delivery and treatment planning systems are now commercially available. Three of these nonstandard IMRT approaches are reviewed here: tomotherapy, robotic linear accelerators (CyberKnife, Accuray Inc., Sunnyvale, CA), and standard linear accelerators modulated by jaws alone or by their jaws acting together with a tertiary beam-masking device. Rationales for the nonstandard IMRT approaches are discussed, and elements of their delivery system designs are briefly described. Differences between fixed-field IMRT dose distributions and the distributions that can be delivered by using the nonstandard technologies are outlined. Because conventional linear accelerators are finely honed machines, innovative design enhancement of one aspect of system performance often limits another facet of machine capability. Consequently the various delivery systems may prove optimal for different types of treatment, with specific machine designs excelling for disease sites with specific target volume and normal structure topologies. However it is likely that the delivery systems will be distinguished not just by the optimality of the dose distributions they deliver, but also by factors such as the efficiency of their treatment process, the integration of their onboard imaging systems into that process, and their ability to measure and minimize or compensate for target movement, including the effects of respiratory motion.

Humans↗

PubMed2006

Automatic registration of megavoltage to kilovoltage CT images in helical tomotherapy: an evaluation of the setup verification process for the special case of a rigid head phantom.

Precise daily target localization is necessary to achieve highly conformal radiation delivery. In helical tomotherapy, setup verification may be accomplished just prior to delivering each fraction by acquiring a megavoltage CT scan of the patient in the treatment position. This daily image set may be manually or automatically registered to the image set on which the treatment plan was calculated, in order to determine any needed adjustments. The system was tested by acquiring 104 MVCT scans of an anthropomorphic head phantom to which translational displacements had been introduced with respect to the planning image set. Registration results were compared against an independent, optically guided positioning system. The total experimental uncertainty was within approximately 1 mm. Although the registration of phantom images is not fully analogous to the registration of patient images, this study confirms that the system is capable of phantom localization with sub-voxel accuracy. In seven registration problems considered, expert human observers were able to perform manual registrations with comparable or inferior accuracy to automatic registration by mutual information. The time to compute an automatic registration is considerably shorter than the time required for manual registration. However, human evaluation of automatic results is necessary in order to identify occasional outliers, and to ensure that the registration is clinically acceptable, especially in the case of deformable patient anatomy.

Algorithms↗

PubMed2005

Modelling simple helically delivered dose distributions.

In a previous paper, we described quality assurance procedures for Hi-Art helical tomotherapy machines. Here, we develop further some ideas discussed briefly in that paper. Simple helically generated dose distributions are modelled, and relationships between these dose distributions and underlying characteristics of Hi-Art treatment systems are elucidated. In particular, we describe the dependence of dose levels along the central axis of a cylinder aligned coaxially with a Hi-Art machine on fan beam width, couch velocity and helical delivery lengths. The impact on these dose levels of angular variations in gantry speed or output per linear accelerator pulse is also explored.

Body Burden↗

PubMed2005

A novel method to correct for pitch and yaw patient setup errors in helical tomotherapy.

An accurate means of determining and correcting for daily patient setup errors is important to the cancer outcome in radiotherapy. While many tools have been developed to detect setup errors, difficulty may arise in accurately adjusting the patient to account for the rotational error components. A novel, automated method to correct for rotational patient setup errors in helical tomotherapy is proposed for a treatment couch that is restricted to motion along translational axes. In tomotherapy, only a narrow superior/inferior section of the target receives a dose at any instant, thus rotations in the sagittal and coronal planes may be approximately corrected for by very slow continuous couch motion in a direction perpendicular to the scanning direction. Results from proof-of-principle tests indicate that the method improves the accuracy of treatment delivery, especially for long and narrow targets. Rotational corrections about an axis perpendicular to the transverse plane continue to be implemented easily in tomotherapy by adjustment of the initial gantry angle.

Equipment Design↗

PubMed2003

Optimal stochastic correction strategies for rigid-body target motion.

PURPOSE: To derive optimal correction strategies for setup errors, including the uncertainty in their measurement, and to analyze their impact on treatment margins. METHODS AND MATERIALS: New concepts like image-guided radiotherapy aim to provide an increasing amount of targeting information during treatment. Future treatment devices incorporating imaging capabilities will facilitate frequent correction of treatment setup errors. It is, therefore, possible to design new correction protocols that reduce not only systematic but also random setup errors. A novel, very general approach to developing optimal correction strategies in the presence of measurement uncertainties is derived from linear systems theory. In the simplest approach, the state variable of the system, which represents the patient, is the spatial displacement of the center-of-mass of the clinical target volume with respect to the planning CT. This displacement is the sum of a systematic and a random component. Uncertainties in the measured value of the state variable due to the measurement process, image processing technique, or organ deformation are naturally incorporated into a linear system. The true value of the displacement can be estimated from the noisy measurements with a stochastic filter (Kalman filter). These estimates provide an optimal control law for the system and therefore optimal values for the setup corrections. In the case of unknown systematic and random error variances, an adaptive version of the filter was implemented. The statistical properties of the filter were investigated by performing simulations of the state space model and assessed for individual patients and a large patient population subject to different action criteria. RESULTS: Over a patient population, the corrections by the Kalman filter estimates are always advantageous compared with the corrections by the measured values themselves. For a small percentage of individual patients, however, the Kalman corrections worsen the results. For large measurement error, the residual standard deviation of the random setup errors can be reduced by approximately 28% for over 90% of the patients. The uncertainty in the measured value impairs the ability to completely account for uncertainties. CONCLUSIONS: The Kalman estimates provide an effective means to perform daily setup corrections in the presence of measurement errors. The linear system approach is very versatile and can be extended to more general state variables.

Algorithms↗

PubMed2002

Monte Carlo study of a highly efficient gas ionization detector for megavoltage imaging and image-guided radiotherapy.

The imaging characteristics of an arc-shaped xenon gas ionization chamber for the purpose of megavoltage CT imaging were investigated. The detector consists of several hundred 320 microm thick gas cavities separated by thin tungsten plates of the same thickness. Dose response, efficiency and resolution parameters were calculated using Monte Carlo simulations. The calculations were compared to measurements taken in a 4 MV photon beam, assuming that the measured signal in the chambers corresponds to the therein absorbed dose. The measured response profiles for narrow and broad incident photon beams could be well reproduced with the Monte Carlo calculations. They show, that the quantum efficiency is 29.2% and the detective quantum efficiency at zero frequency DQE(0) is 20.4% for the detector arc placed in focus with the photon source. For a detector placed out of focus, these numbers even increase. The efficiency of this kind of radiation detector for megavoltage radiation therefore surpasses the reported efficiency of existing detector technologies. The resolution of the detector is quantified with calculated and measured line spread functions. The corresponding modulation transfer functions were determined for different thicknesses of the tungsten plates. They show that the resolution is only slightly dependent on the plate thickness but is predominantly determined by the cell size of the detector. The optimal plate thickness is determined by a tradeoff between quantum efficiency, total signal generation and resolution. Thicker plates are more efficient but the total signal and the resolution decrease with plate thickness. In conclusion, a gas ionization chamber of the described type is a highly efficient megavoltage radiation detector, allowing to obtain CT images with very little dose for a sufficient image quality for anatomy verification. This kind of detector might serve as a model for a future generation of highly efficient radiation detectors.

Animals↗