Respiratory regularity gated 4D CT acquisition: concepts and proof of principle.

Four-dimensional CT images are generally sorted through a post-acquisition procedure correlating images with a time-synchronized external respiration signal. The patient's ability to maintain reproducible respiration is the limiting factor during 4D CT, where artifacts occur in approximately 85% of scans with current technology. To reduce these artifacts and their subsequent effects during radiotherapy planning, a method for improved 4D CT image acquisition that relies on gating 4D CT acquisition based on the real time monitoring of the respiration signal has been proposed. The respiration signal and CT data acquisition are linked, such that data from irregular breathing cycles, which cause artifacts, are not acquired by gating CT acquisition by the respiratory signal. A proof-of-principle application of the respiratory regularity gated 4D CT method using patient respiratory signals demonstrates the potential of this method to reduce artifacts currently found in 4D CT scans. Numerical simulations indicate a potential reduction in motion within a respiratory phase bin by 20-40% depending on tolerances chosen. Additional advantages of the proposed method are dose reduction by eliminating unnecessary oversampling and obviating the need for post-processing to create the 4D CT data set.

The application of the sinusoidal model to lung cancer patient respiratory motion.

Accurate modeling of the respiratory cycle is important to account for the effect of organ motion on dose calculation for lung cancer patients. The aim of this study is to evaluate the accuracy of a respiratory model for lung cancer patients. Lujan et al. [Med. Phys. 26(5), 715-720 (1999)] proposed a model, which became widely used, to describe organ motion due to respiration. This model assumes that the parameters do not vary between and within breathing cycles. In this study, first, the correlation of respiratory motion traces with the model f(t) as a function of the parameter n (n = 1, 2, 3) was undertaken for each breathing cycle from 331 four-minute respiratory traces acquired from 24 lung cancer patients using three breathing types: free breathing, audio instruction, and audio-visual biofeedback. Because cos2 and cos4 had similar correlation coefficients, and cos2 and cos1 have a trigonometric relationship, for simplicity, the cos1 value was consequently used for further analysis in which the variations in mean position (z0), amplitude of motion (b) and period (tau) with and without biofeedback or instructions were investigated. For all breathing types, the parameter values, mean position (z0), amplitude of motion (b), and period (tau) exhibited significant cycle-to-cycle variations. Audio-visual biofeedback showed the least variations for all three parameters (z0, b, and tau). It was found that mean position (z0) could be approximated with a normal distribution, and the amplitude of motion (b) and period (tau) could be approximated with log normal distributions. The overall probability density function (pdf) of f(t) for each of the three breathing types was fitted with three models: normal, bimodal, and the pdf of a simple harmonic oscillator. It was found that the normal and the bimodal models represented the overall respiratory motion pdfs with correlation values from 0.95 to 0.99, whereas the range of the simple harmonic oscillator pdf correlation values was 0.71 to 0.81. This study demonstrates that the pdfs of mean position (z0), amplitude of motion (b), and period (tau) can be used for sampling to obtain more realistic respiratory traces. The overall standard deviations of respiratory motion were 0.48, 0.57, and 0.55 cm for free breathing, audio instruction, and audio-visual biofeedback, respectively.

Determination of maximum leaf velocity and acceleration of a dynamic multileaf collimator: implications for 4D radiotherapy.

The dynamic multileaf collimator (MLC) can be used for four-dimensional (4D), or tumor tracking radiotherapy. However, the leaf velocity and acceleration limitations become a crucial factor as the MLC leaves need to respond in near real time to the incoming respiration signal. The aims of this paper are to measure maximum leaf velocity, acceleration, and deceleration to obtain the mechanical response times for the MLC, and determine whether the MLC is suitable for 4D radiotherapy. MLC leaf sequence files, requiring the leaves to reach maximum acceleration and velocity during motion, were written. The leaf positions were recorded every 50 ms, from which the maximum leaf velocity, acceleration, and deceleration were derived. The dependence on the velocity and acceleration of the following variables were studied: leaf banks, inner and outer leaves, MLC-MLC variations, gravity, friction, and the stability of measurements over time. Measurement results show that the two leaf banks of a MLC behave similarly, while the inner and outer leaves have significantly different maximum leaf velocities. The MLC-MLC variations and the dependence of gravity on maximum leaf velocity are statistically significant. The average maximum leaf velocity at the isocenter plane of the MLC ranged from 3.3 to 3.9 cm/s. The acceleration and deceleration at the isocenter plane of the MLC ranged from 50 to 69 cm/s2 and 46 to 52 cm/s2, respectively. Interleaf friction had a negligible effect on the results, and the MLC parameters remained stable with time. Equations of motion were derived to determine the ability of the MLC response to fluoroscopymeasured diaphragm motion. Given the present MLC mechanical characteristics, 4D radiotherapy is feasible for up to 97% of respiratory motion. For the largest respiratory motion velocities observed, beam delivery should be temporarily stopped (beam hold).

Is the diaphragm motion probability density function normally distributed?

During radiotherapy treatment planning, the margins given to the clinical target volume to form the planning target volume accounts for internal motion and set-up error. Most margin formulas assume that the underlying distributions are independent and normal. Clinical data suggests that the set-up error probability density function (pdf) can be considered to have an approximately normal distribution. However, there is evidence that internal motion does not have a normal distribution. Thus, in general, a convolution of the two pdfs should be performed to determine the total geometric error. The goals of this article were to (1) determine if the internal motion pdf due to respiration can be characterized using a normal distribution, and (2) if not, determine if the total geometric uncertainty for combining internal motion and set-up error can be characterized by a normal distribution. Sixty fluoroscopy diaphragm motion data sets were obtained using three breathing training types: free breathing, audio instruction, and visual feedback. Diaphragm motion was used as a surrogate for liver and lung cancer motion. The data were analyzed with normality tests in the following groups: (1) single motion measurements, (2) combined motion measurements for each patient, and (3) combined motion measurements for all patients. Following this analysis, the diaphragm motion pdfs were convolved with a set-up error pdf, and the standard deviation of the set-up error pdf at which the total geometric error pdf became normal was determined. At set-up error standard deviation values of at least 0.27 and 0.1 cm for free breathing, 0.57 and 0.42 cm for audio instruction, and 0.55 and 0 cm for visual feedback, for single motion measurements and combined motion measurements for each patient, respectively, total geometric error pdfs became approximately normal. When the motion measurements for all the patients were combined, diaphragm motion pdfs were approximately normal for all feedback types. Therefore, for treatment planning purposes in the absence of individual patient measurements, the diaphragm motion pdf can be considered an approximately normal distribution. However, care should be taken when determining a margin based on individual patients measurements as the total geometric error will, in general, not be normally distributed.

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 system's 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.

Acquiring 4D thoracic CT scans using a multislice helical method.

Respiratory motion degrades anatomic position reproducibility during imaging, necessitates larger margins during radiotherapy planning and causes errors during radiation delivery. Computed tomography (CT) scans acquired synchronously with the respiratory signal can be used to reconstruct 4D CT scans, which can be employed for 4D treatment planning to explicitly account for respiratory motion. The aim of this research was to develop, test and clinically implement a method to acquire 4D thoracic CT scans using a multislice helical method. A commercial position-monitoring system used for respiratory-gated radiotherapy was interfaced with a third generation multislice scanner. 4D cardiac reconstruction methods were modified to allow 4D thoracic CT acquisition. The technique was tested on a phantom under different conditions: stationary, periodic motion and non-periodic motion. 4D CT was also implemented for a lung cancer patient with audio-visual breathing coaching. For all cases, 4D CT images were successfully acquired from eight discrete breathing phases, however, some limitations of the system in terms of respiration reproducibility and breathing period relative to scanner settings were evident. Lung mass for the 4D CT patient scan was reproducible to within 2.1% over the eight phases, though the lung volume changed by 20% between end inspiration and end expiration (870 cm3). 4D CT can be used for 4D radiotherapy, respiration-gated radiotherapy, 'slow' CT acquisition and tumour motion studies.

On the use of EPID-based implanted marker tracking for 4D radiotherapy.

Four-dimensional (4D) radiotherapy delivery to dynamically moving tumors requires a real-time signal of the tumor position as a function of time so that the radiation beam can continuously track the tumor during the respiration cycle. The aim of this study was to develop and evaluate an electronic portal imaging device (EPID)-based marker-tracking system that can be used for real-time tumor targeting, or 4D radiotherapy. Three gold cylinders, 3 mm in length and 1 mm in diameter, were implanted in a dynamic lung phantom. The phantom range of motion was 4 cm with a 3-s "breathing" period. EPID image acquisition parameters were modified, allowing image acquisition in 0.1 s. Images of the stationary and moving phantom were acquired. Software was developed to segment automatically the marker positions from the EPID images. Images acquired in 0.1 s displayed higher noise and a lower signal-noise ratio than those obtained using regular (> 1 s) acquisition settings. However, the markers were still clearly visible on the 0.1-s images. The motion of the phantom blurred the images of the markers and further reduced the signal-noise ratio, though they could still be successfully segmented from the images in 10-30 ms of computation time. The positions of gold markers placed in the lung phantom were detected successfully, even for phantom velocities substantially higher than those observed for typical lung tumors. This study shows that using EPID-based marker tracking for 4D radiotherapy is feasible, however, changes in linear accelerator technology and EPID-based image acquisition as well as patient studies are required before this method can be implemented clinically.

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.

Quantifying the effect of intrafraction motion during breast IMRT planning and dose delivery.

Respiratory motion during intensity modulated radiation therapy (IMRT) causes two types of problems. First, the clinical target volume (CTV) to planning target volume (PTV) margin needed to account for respiratory motion means that the lung and heart dose is higher than would occur in the absence of such motion. Second, because respiratory motion is not synchronized with multileaf collimator (MLC) motion, the delivered dose is not the same as the planned dose. The aims of this work were to evaluate these problems to determine (a) the effects of respiratory motion and setup error during breast IMRT treatment planning, (b) the effects of the interplay between respiratory motion and multileaf collimator (MLC) motion during breast IMRT delivery, and (c) the potential benefits of breast IMRT using breath-hold, respiratory gated, and 4D techniques. Seven early stage breast cancer patient data sets were planned for IMRT delivered with a dynamic MLC (DMLC). For each patient case, eight IMRT plans with varying respiratory motion magnitudes and setup errors (and hence CTV to PTV margins) were created. The effects of respiratory motion and setup error on the treatment plan were determined by comparing the eight dose distributions. For each fraction of these plans, the effect of the interplay between respiratory motion and MLC motion during IMRT delivery was simulated by superimposing the respiratory trace on the planned DMLC leaf motion, facilitating comparisons between the planned and expected dose distributions. When considering respiratory motion in the CTV-PTV expansion during breast IMRT planning, our results show that PTV dose heterogeneity increases with respiratory motion. Lung and heart doses also increase with respiratory motion. Due to the interplay between respiratory motion and MLC motion during IMRT delivery, the planned and expected dose distributions differ. This difference increases with respiratory motion. The expected dose varies from fraction to fraction. However, for the seven patients studied and respiratory trace used, for no breathing, shallow breathing, and normal breathing, there were no statistically significant differences between the planned and expected dose distributions. Thus, for breast IMRT, intrafraction motion degrades treatment plans predominantly by the necessary addition of a larger CTV to PTV margin than would be required in the absence of such motion. This motion can be limited by breath-hold, respiratory gated, or 4D techniques.

Acquiring a four-dimensional computed tomography dataset using an external respiratory signal.

Four-dimensional (4D) methods strive to achieve highly conformal radiotherapy, particularly for lung and breast tumours, in the presence of respiratory-induced motion of tumours and normal tissues. Four-dimensional radiotherapy accounts for respiratory motion during imaging, planning and radiation delivery, and requires a 4D CT image in which the internal anatomy motion as a function of the respiratory cycle can be quantified. The aims of our research were (a) to develop a method to acquire 4D CT images from a spiral CT scan using an external respiratory signal and (b) to examine the potential utility of 4D CT imaging. A commercially available respiratory motion monitoring system provided an 'external' tracking signal of the patient's breathing. Simultaneous recording of a TTL 'X-Ray ON' signal from the CT scanner indicated the start time of CT image acquisition, thus facilitating time stamping of all subsequent images. An over-sampled spiral CT scan was acquired using a pitch of 0.5 and scanner rotation time of 1.5 s. Each image from such a scan was sorted into an image bin that corresponded with the phase of the respiratory cycle in which the image was acquired. The complete set of such image bins accumulated over a respiratory cycle constitutes a 4D CT dataset. Four-dimensional CT datasets of a mechanical oscillator phantom and a patient undergoing lung radiotherapy were acquired. Motion artefacts were significantly reduced in the images in the 4D CT dataset compared to the three-dimensional (3D) images, for which respiratory motion was not accounted. Accounting for respiratory motion using 4D CT imaging is feasible and yields images with less distortion than 3D images. 4D images also contain respiratory motion information not available in a 3D CT image.

Potential radiotherapy improvements with respiratory gating.

Gating is a relatively new and potentially useful therapeutic addition to external beam radiotherapy applied to regions affected by intra-fraction motion. The impact was of gating on treatment margins, image artifacts, and volume and positional accuracy was investigated by CT imaging of sinusoidally moving spheres. The motion of the spheres simulates target motion. During the CT imaging of dynamically moving spheres, gating reproduced the static volume to within 1%, whereas errors of over 20% were observed where gating was not used. Using a theoretical analysis of margins, gating alone or in combination with an electronic portal imaging device may allow a 2-11 mm reduction in the CTV to PTV margin, and thus less healthy tissue need be irradiated. Gating may allow a reduction of treatment margins, an improvement in image quality, and an improvement in positional and volumetric accuracy of the gross tumor volume.

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.

Motion adaptive x-ray therapy: a feasibility study.

Intrafraction motion caused by breathing requires increased treatment margins for chest and abdominal radiotherapy and may lead to 'motion artefacts' in dose distributions during intensity modulated radiotherapy (IMRT). Technologies such as gated radiotherapy may significantly increase the treatment time, while breath-hold techniques may be poorly tolerated by pulmonarily compromised patients. A solution that allows reduced margins and dose distribution artefacts, without compromising delivery time, is to synchronously follow the target motion by adapting the x-ray beam using a dynamic multileaf collimator (MLC), i.e. motion adaptive x-ray therapy, or MAX-T for short. Though the target is moving with time, in the MAX-T beam view the target is static. The MAX-T method superimposes the target motion due to respiration onto the beam originally planned for delivery. Thus during beam delivery the beam is dynamically changing position with respect to the isocentre using a dynamic MLC, the leaf positions of which are dependent upon the target position. Synchronization of the MLC motion and target motion occurs using respiration gated radiotherapy equipment. The concept and feasibility of MAX-T and the capability of the treatment machine to deliver such a treatment were investigated by performing measurements for uniform and IMRT fields using a mechanical sinusoidal oscillator to simulate target motion. Target dose measurements obtained using MAX-T for a moving target were found to be equivalent to those delivered to a static target by a static beam.