Breathing-synchronized delivery: a potential four-dimensional tomotherapy treatment technique.

PURPOSE: To introduce a four-dimensional (4D) tomotherapy treatment technique with improved motion control and patient tolerance. METHODS AND MATERIALS: Computed tomographic images at 10 breathing phases were acquired for treatment planning. The full exhalation phase was chosen as the planning phase, and the CT images at this phase were used as treatment-planning images. Region of interest delineation was the same as in traditional treatment planning, except that no breathing motion margin was used in clinical target volume-planning target volume expansion. The correlation between delivery and breathing phases was set assuming a constant gantry speed and a fixed breathing period. Deformable image registration yielded the deformation fields at each phase relative to the planning phase. With the delivery/breathing phase correlation and voxel displacements at each breathing phase, a 4D tomotherapy plan was obtained by incorporating the motion into inverse treatment plan optimization. A combined laser/spirometer breathing tracking system has been developed to monitor patient breathing. This system is able to produce stable and reproducible breathing signals representing tidal volume. RESULTS: We compared the 4D tomotherapy treatment planning method with conventional tomotherapy on a static target. The results showed that 4D tomotherapy can achieve dose distributions on a moving target similar to those obtained with conventional delivery on a stationary target. Regular breathing motion is fully compensated by motion-incorporated breathing-synchronized delivery planning. Four-dimensional tomotherapy also has close to 100% duty cycle and does not prolong treatment time. CONCLUSION: Breathing-synchronized delivery is a feasible 4D tomotherapy treatment technique with improved motion control and patient tolerance.

Efficient on-line setup correction strategies using plan-intent functions.

With the introduction of image-guided radiation therapy (IGRT) delivery systems on-line set-up correction strategies have gained in popularity. Usually, the correction workload of these strategies is high compared to off-line strategies as daily setup corrections have to be performed based on a predefined action level. In this work, it is proposed that on-line strategies must not only be judged in terms of workload but also in terms of efficacy. While workload can be easily predicted for such strategies, the efficacy must ultimately reflect the efficiency with which the original treatment plan intent is met. The purpose of this work is to investigate the tradeoff between workload and efficacy of three different on-line set-up correction strategies: The common fixed action level strategy and two novel on-line setup correction strategies, i.e., a dose-volume histogram (DVH) constraint and an equivalent uniform dose (EUD) score strategy that aim directly for better compliance with original treatment plan intent. All strategies were reformulated in terms of a score function that reflected treatment plan intent. A retrospective study was conducted on 5 prostate patients (7-field conformal, 79.8 Gy, 42 fractions). PTV margins were 10 mm except in the posterior direction (7 mm). The original treatment plan intent for these patients was defined using a set of DVH constraints. The results show that the on-line setup correction strategy based on a fixed action level of 3 mm resulted in a considerable correction workload. For larger action levels, a dose benefit (in terms of EUD) in the rectum and bladder was observed for all patients which is clinically "fortuitous" but difficult to take advantage of. In contrast, the application of the two novel strategies generally resulted in a controlled decrease of the dose to the rectum and the bladder with a smaller workload. It is concluded that using information about target anatomy and the planned dose distribution allows the design of specific correction strategies that are better tailored to the individual patient and that comply effectively with initial treatment plan intent.

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.

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.

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 Rustem's 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.

Pulmonary tumor measurements from x-ray computed tomography in one, two, and three dimensions.

RATIONALE AND OBJECTIVES: We evaluated the accuracy and reproducibility of three-dimensional (3D) measurements of lung phantoms and patient tumors from x-ray computed tomography (CT) and compared these to one-dimensional (1D) and two-dimensional (2D) measurements. MATERIALS AND METHODS: CT images of three spherical and three irregularly shaped tumor phantoms were evaluated by three observers who performed five repeated measurements. Additionally, three observers manually segmented 29 patient lung tumors five times each. Follow-up imaging was performed for 23 tumors and response criteria were compared. For a single subject, imaging was performed on nine occasions over 2 years to evaluate multidimensional tumor response. To evaluate measurement accuracy, we compared imaging measurements to ground truth using analysis of variance. For estimates of precision, intraobserver and interobserver coefficients of variation and intraclass correlations (ICC) were used. Linear regression and Pearson correlations were used to evaluate agreement and tumor response was descriptively compared. RESULTS: For spherical shaped phantoms, all measurements were highly accurate, but for irregularly shaped phantoms, only 3D measurements were in high agreement with ground truth measurements. All phantom and patient measurements showed high intra- and interobserver reproducibility (ICC >0.900). Over a 2-year period for a single patient, there was disagreement between tumor response classifications based on 3D measurements and those generated using 1D and 2D measurements. CONCLUSION: Tumor volume measurements were highly reproducible and accurate for irregular, spherical phantoms and patient tumors with nonuniform dimensions. Response classifications obtained from multidimensional measurements suggest that 3D measurements provide higher sensitivity to tumor response.