P Keall

The management of respiratory motion in radiation oncology report of AAPM Task Group 76

This document is the report of a task group of the AAPM and has been prepared primarily to advise medical physicists involved in the external-beam radiation therapy of patients with thoracic, abdominal, and pelvic tumors affected by respiratory motion. This report describes the magnitude of respiratory motion, discusses radiotherapy specific problems caused by respiratory motion, explains techniques that explicitly manage respiratory motion during radiotherapy and gives recommendations in the application of these techniques for patient care, including quality assurance (QA) guidelines for these devices and their use with conformal and intensity modulated radiotherapy. The technologies covered by this report are motion-encompassing methods, respiratory gated techniques, breath-hold techniques, forced shallow-breathing methods, and respiration-synchronized techniques. The main outcome of this report is a clinical process guide for managing respiratory motion. Included in this guide is the recommendation that tumor motion should be measured (when possible) for each patient for whom respiratory motion is a concern. If target motion is greater than 5mm, a method of respiratory motion management is available, and if the patient can tolerate the procedure, respiratory motion management technology is appropriate. Respiratory motion management is also appropriate when the procedure will increase normal tissue sparing. Respiratory motion management involves further resources, education and the development of and adherence to QA procedures.

Stereotactic body radiation therapy: The report of AAPM Task Group 101

Task Group 101 of the AAPM has prepared this report for medical physicists, clinicians, and therapists in order to outline the best practice guidelines for the external-beam radiation therapy technique referred to as stereotactic body radiation therapy (SBRT). The task group report includes a review of the literature to identify reported clinical findings and expected outcomes for this treatment modality. Information is provided for establishing a SBRT program, including protocols, equipment, resources, and QA procedures. Additionally, suggestions for developing consistent documentation for prescribing, reporting, and recording SBRT treatment delivery is provided.

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, theability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

Four‐dimensional radiotherapy planning for DMLC‐based respiratory motion tracking

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation is respiration motion for lung tumors. The aim of this study was to develop 4D radiotherapy treatment-planning methodology for DMLC-based respiratory motion tracking. A 4D computed tomography (CT) scan consisting of a series of eight 3D CT image sets acquired at different respiratory phases was used for treatment planning. Deformable image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding to subsequent respiration phases. Deformable registration allows the contours defined on the peak-inhale CT to be automatically transferred to the other respiratory phase CT image sets. Treatment planning was simultaneously performed on each of the eight 3D image sets via automated scripts in which the MLC-defined beam aperture conforms to the PTV (which in this case equaled the GTV due to CT scan length limitations) plus a penumbral margin at each respiratory phase. The dose distribution from each respiratory phase CT image set was mapped back to the peak-inhale CT image set for analysis. The treatment intent of 4D planning is that the radiation beam defined by the DMLC tracks the respiration-induced target motion based on a feedback loop including the respiration signal to a real-time MLC controller. Deformation with respiration was observed for the lung tumor and normal tissues. This deformation was verified by examining the mapping of high contrast objects, such as the lungs and cord, between image sets. For the test case, dosimetric reductions for the cord, heart, and lungs were found for 4D planning compared with 3D planning. 4D radiotherapy planning for DMLC-based respiratory motion tracking is feasible and may offer tumor dose escalation and/or a reduction in treatment-related complications. However, 4D planning requires new planning tools, such as deformable registration and automated treatment planning on multiple CT image sets.

Quantifying the predictability of diaphragm motion during respiration with a noninvasive external marker

The aim of this work was to quantify the ability to predict intrafraction diaphragm motion from an external respiration signal during a course of radiotherapy. The data obtained included diaphragm motion traces from 63 fluoroscopic lung procedures for 5 patients, acquired simultaneously with respiratory motion signals (an infrared camera-based system was used to track abdominal wall motion). During these sessions, the patients were asked to breathe either (i) without instruction, (ii) with audio prompting, or (iii) using visual feedback. A statistical general linear model was formulated to describe the relationship between the respiration signal and diaphragm motion over all sessions and for all breathing training types. The model parameters derived from the first session for each patient were then used to predict the diaphragm motion for subsequent sessions based on the respiration signal. Quantification of the difference between the predicted and actual motion during each session determined our ability to predict diaphragm motion during a course of radiotherapy. This measure of diaphragm motion was also used to estimate clinical target volume (CTV) to planning target volume (PTV) margins for conventional, gated, and proposed four-dimensional (4D) radiotherapy. Results from statistical analysis indicated a strong linear relationship between the respiration signal and diaphragm motion (p<0.001) over all sessions, irrespective of session number (p=0.98) and breathing training type (p=0.19). Using model parameters obtained from the first session, diaphragm motion was predicted in subsequent sessions to within 0.1 cm (1 sigma) for gated and 4D radiotherapy. Assuming a 0.4 cm setup error, superior-inferior CTV-PTV margins of 1.1 cm for conventional radiotherapy could be reduced to 0.8 cm for gated and 4D radiotherapy. The diaphragm motion is strongly correlated with the respiration signal obtained from the abdominal wall. This correlation can be used to predict diaphragm motion, based on the respiration signal, to within 0.1 cm (1 sigma) over a course of radiotherapy.

Determining parameters for respiration-gated radiotherapy

Respiration-gated radiotherapy for tumor sites affected by respiratory motion will potentially improve radiotherapy outcomes by allowing reduced treatment margins leading to decreased complication rates and/or increased tumor control. Furthermore, for intensity-modulated radiotherapy (IMRT), respiratory gating will minimize the hot and cold spot artifacts in dose distributions that may occur as a result of interplay between respiratory motion and leaf motion. Most implementations of respiration gating rely on the real time knowledge of the relative position of the internal anatomy being treated with respect to that of an external marker. A method to determine the amplitude of motion and account for any difference in phase between the internal tumor motion and external marker motion has been developed. Treating patients using gating requires several clinical decisions, such as whether to gate during inhale or exhale, whether to use phase or amplitude tracking of the respiratory signal, and by how much the intrafraction tumor motion can be decreased at the cost of increased delivery time. These parameters may change from patient to patient. A method has been developed to provide the data necessary to make decisions as to the CTV to PTV margins to apply to a gated treatment plan.

Converting absorbed dose to medium to absorbed dose to water for Monte Carlo based photon beam dose calculations

Current clinical experience in radiation therapy is based upon dose computations that report the absorbed dose to water, even though the patient is not made of water but of many different types of tissue. While Monte Carlo dose calculation algorithms have the potential for higher dose accuracy, they usually transport particles in and compute the absorbed dose to the patient media such as soft tissue, lung or bone. Therefore, for dose calculation algorithm comparisons, or to report dose to water or tissue contained within a bone matrix for example, a method to convert dose to the medium to dose to water is required. This conversion has been developed here by applying Bragg-Gray cavity theory. The dose ratio for 6 and 18 MV photon beams was determined by computing the average stopping power ratio for the primary electron spectrum in the transport media. For soft tissue, the difference between dose to medium and dose to water is approximately 1.0%, while for cortical bone the dose difference exceeds 10%. The variation in the dose ratio as a function of depth and position in the field indicates that for photon beams a single correction factor can be used for each particular material throughout the field for a given photon beam energy. The only exception to this would be for the clinically non-relevant dose to air. Pre-computed energy spectra for 60Co to 24 MV are used to compute the dose ratios for these photon beams and to determine an effective energy for evaluation of the dose ratio.

Predicting respiratory motion for four-dimensional radiotherapy

Adapting radiation delivery to respiratory motion is made possible through corrective action based on real-time feedback of target position during respiration. The advantage of this approach lies with its ability to allow tighter margins around the target while simultaneously following its motion. A significant hurdle to the successful implementation of real-time target-tracking-based radiation delivery is the existence of a finite time delay between the acquisition of target position and the mechanical response of the system to the change in position. Target motion during the time delay leads to a resultant lag in the systems response to a change in tumor position. Predicting target position in advance is one approach to ensure accurate delivery. The aim of this manuscript is to estimate the predictive ability of sinusoidal and adaptive filter-based prediction algorithms on multiple sessions of patient respiratory patterns. Respiratory motion information was obtained from recordings of diaphragm motion for five patients over 60 sessions. A prediction algorithm that employed both prediction models-the sinusoidal model and the adaptive filter model-was developed to estimate prediction accuracy over all the sessions. For each session, prediction error was computed for several time instants (response time) in the future (0-1.8 seconds at 0.2-second intervals), based on position data collected over several signal-history lengths (1-7 seconds at 1-second intervals). Based on patient data included in this study, the following observations are made. Qualitative comparison of predicted and actual position indicated a progressive increase in prediction error with an increase in response time. A signal-history length of 5 seconds was found to be the optimal signal history length for prediction using the sinusoidal model for all breathing training modalities. In terms of overall error in predicting respiratory motion, the adaptive filter model performed better than the sinusoidal model. With the adaptive filter, average prediction errors of less than 0.2 cm (1sigma) are possible for response times less than 0.4 seconds. In comparing prediction error with system latency error (no prediction), the adaptive filter model exhibited lesser prediction errors as compared to the sinusoidal model, especially for longer response time values (>0.4 seconds). At smaller response time values (<0.4 seconds), improvements in prediction error reduction are required for both predictive models in order to maximize gains in position accuracy due to prediction. Respiratory motion patterns are inherently complex in nature. While linear prediction-based prediction models perform satisfactorily for shorter response times, their prediction accuracy significantly deteriorates for longer response times. Successful implementation of real-time target-tracking-based radiotherapy requires response times less than 0.4 seconds or improved prediction algorithms.

Retrospective analysis of artifacts in four-dimensional CT images of 50 abdominal and thoracic radiotherapy patients.

PURPOSE To quantify the type, frequency, and magnitude of artifacts in four-dimensional (4D) CT images acquired using a multislice cine method. METHODS AND MATERIALS Fifty consecutive patients who underwent 4D-CT scanning and radiotherapy for thoracic or abdominal cancers were included in this study. All the 4D-CT scans were performed on the GE multislice PET/CT scanner with the Varian Real-time Position Management system in cine mode. The GE Advantage 4D software was used to create 4D-CT data sets. The artifacts were then visually and quantitatively analyzed. We performed statistical analyses to evaluate the relationships between patient- or breathing-pattern-related parameters and the occurrence as well as magnitude of artifacts. RESULTS It was found that 45 of 50 patients (90%) had at least one artifact (other than blurring) with a mean magnitude of 11.6 mm (range, 4.4-56.0 mm) in the diaphragm or heart. We also observed at least one artifact in 6 of 20 lung or mediastinal tumors (30%). Statistical analysis revealed that there were significant differences between several breathing-pattern-related parameters, including abdominal displacement (p < 0.01), for the subgroups of patients with and without artifacts. The magnitude of an artifact was found to be significantly but weakly correlated with the abdominal displacement difference between two adjacent couch positions (R = 0.34, p < 0.01). CONCLUSIONS This study has identified that the frequency and magnitude of artifacts in 4D-CT is alarmingly high. Significant improvement is needed in 4D-CT imaging.

Dosimetric considerations for patients with HIP prostheses undergoing pelvic irradiation. Report of the AAPM Radiation Therapy Committee Task Group 63.

This document is the report of a task group of the Radiation Therapy Committee of the AAPM and has been prepared primarily to advise hospital physicists involved in external beam treatment of patients with pelvic malignancies who have high atomic number (Z) hip prostheses. The purpose of the report is to make the radiation oncology community aware of the problems arising from the presence of these devices in the radiation beam, to quantify the dose perturbations they cause, and, finally, to provide recommendations for treatment planning and delivery. Some of the data and recommendations are also applicable to patients having implanted high-Z prosthetic devices such as pins, humeral head replacements. The scientific understanding and methodology of clinical dosimetry for these situations is still incomplete. This report is intended to reflect the current state of scientific understanding and technical methodology in clinical dosimetry for radiation oncology patients with high-Z hip prostheses.