Harry Keller

Image guidance for precise conformal radiotherapy

PURPOSE To review the state of the art in image-guided precision conformal radiotherapy and to describe how helical tomotherapy compares with the image-guided practices being developed for conventional radiotherapy. MATERIALS AND METHODS Image guidance is beginning to be the fundamental basis for radiotherapy planning, delivery, and verification. Radiotherapy planning requires more precision in the extension and localization of disease. When greater precision is not possible, conformal avoidance methodology may be indicated whereby the margin of disease extension is generous, except where sensitive normal tissues exist. Radiotherapy delivery requires better precision in the definition of treatment volume, on a daily basis if necessary. Helical tomotherapy has been designed to use CT imaging technology to plan, deliver, and verify that the delivery has been carried out as planned. The image-guided processes of helical tomotherapy that enable this goal are described. RESULTS Examples of the results of helical tomotherapy processes for image-guided intensity-modulated radiotherapy are presented. These processes include megavoltage CT acquisition, automated segmentation of CT images, dose reconstruction using the CT image set, deformable registration of CT images, and reoptimization. CONCLUSIONS Image-guided precision conformal radiotherapy can be used as a tool to treat the tumor yet spare critical structures. Helical tomotherapy has been designed from the ground up as an integrated image-guided intensity-modulated radiotherapy system and allows new verification processes based on megavoltage CT images to be implemented.

Application of the spirometer in respiratory gated radiotherapy

The signal from a spirometer is directly correlated with respiratory motion and is ideal for target respiratory motion tracking. However, its susceptibility to signal drift deters its application in radiotherapy. In this work, a few approaches are investigated to control spirometer signal drift for a Bernoulli-type spirometer. A method is presented for rapid daily calibration of the spirometer to obtain a flow sensitivity function. Daily calibration assures accurate airflow measurement and also reduces signal drift. Dynamic baseline adjustment further controls the signal drift. The accuracy of these techniques was studied and it was found that the spirometer is able to provide a long-term drift-free breathing signal. The tracking error is comprised of two components: calibration error and stochastic signal baseline variation error. The calibration error is very small (1% of 3 l) and therefore negligible. The stochastic baseline variation error can be as large as 20% of the normal breathing amplitude. In view of these uncertainties, the applications of spirometers in treatment techniques that rely on breathing monitoring are discussed. Spirometer-based monitoring is noted most suitable for deep inspiration breath-hold but less important for free breathing gating techniques.

Treatment plan optimization incorporating respiratory motion.

Similar to conventional conformal radiotherapy, during lung tomotherapy, a motion margin has to be set for respiratory motion. Consequently, large volume of normal tissue is irradiated by intensive radiation. To solve this problem, we have developed a new motion mitigation method by incorporating target motion into treatment optimization. In this method, the delivery-breathing correlation is determined prior to treatment plan optimization. Beamlets are calculated by using the CT images at the corresponding breathing phases from a dynamic (four-dimensional) image sequence. With the displacement vector fields at different breathing phases, a set of deformed beamlets is obtained by mapping the dose to the primary phase. Optimization incorporating motion is then performed by using the deformed beamlets obtained by dose mapping. During treatment delivery, the same breathing-delivery correlation can be reproduced by instructing the patient to breathe following a visually displayed guiding cycle. This method was tested using a computer-simulated deformable phantom and a real lung case. Results show that treatment optimization incorporating motion achieved similar high dose conformality on a mobile target compared with static delivery. The residual motion effects due to imperfect breathing tracking were also analyzed.

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.

Treatment plan modification using voxel-based weighting factors/dose prescription.

Under various clinical situations, it is desirable to modify the original treatment plan to better suit the clinical goals. In this work, a method to help physicians modify treatment plans based on their clinical preferences is proposed. The method uses a weighted quadratic dose objective function. The commonly used organ-/ROI-based weighting factors are expanded to a set of voxel-based weighting factors in order to obtain greater flexibility in treatment plan modification. Two different but equivalent modification schemes based on Rustems quadratic programming algorithms--modification of a weighting matrix and modification of prescribed doses--are presented. Case studies demonstrated the effectiveness of the two methods with regard to their capability to fine-tune treatment plans.

Design of adaptive treatment margins for non-negligible measurement uncertainty: application to ultrasound-guided prostate radiation therapy

Daily imaging during the course of a fractionated radiotherapy treatment has the potential for frequent intervention and therefore effective adaptation of the treatment to the individual patient. The treatment information gained from such images can be analysed and updated daily to obtain a set of patient individualized parameters. However, in many situations, the uncertainty with which these parameters are estimated cannot be neglected. In this work this methodology is applied to the adaptive estimation of setup errors, the derivation of a daily optimal pre-treatment correction strategy, and the daily update of the treatment margins after application of these corrections. For this purpose a dataset of 19 prostate cancer patients was analysed retrospectively. The position of the prostate was measured daily with an optically guided 3D ultrasound localization system. The measurement uncertainty of this system is approximately 2 mm. The algorithm finds the most likely position of the target maximizing an a posteriori probability given the set of measurements. These estimates are used for the optimal corrections applied to the target volume. The results show that the application of the optimal correction strategy allows a reduction in the treatment margins in a systematic way with increasing progression of the treatment. This is not the case using corrections based only on the measured values that do not take the measurement uncertainty into account.

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.

Monte Carlo methods in portal imaging

An overview of applications of Monte Carlo methods in portal imaging is presented.