Four-dimensional cone-beam computed tomography using an on-board imager

On-board cone-beam computed tomography (CBCT) has recently become available to provide volumetric information of a patient in the treatment position, and holds promises for improved target localization and irradiation dose verification. The design of currently available on-board CBCT, however, is far from optimal. Its quality is adversely influenced by many factors, such as scatter, beam hardening, and intra-scanning organ motion. In this work we quantitatively study the influence of organ motion on CBCT imaging and investigate a strategy to acquire high quality phase-resolved [four-dimensional (4D)] CBCT images based on phase binning of the CBCT projection data. An efficient and robust method for binning CBCT data according to the patient's respiratory phase derived in the projection space was developed. The phase-binned projections were reconstructed using the conventional Feldkamp algorithm to yield 4D CBCT images. Both phantom and patient studies were carried out to validate the technique and to optimize the 4D CBCT data acquisition protocol. Several factors that are important to the clinical implementation of the technique, such as the image quality, scanning time, number of projections, and radiation dose, were analyzed for various scanning schemes. The general references drawn from this study are: (i) reliable phase binning of CBCT projections is accomplishable with the aid of external or internal marker and simple analysis of its trace in the projection space, and (ii) artifact-free 4D CBCT images can be obtained without increasing the patient radiation dose as compared to the current 3D CBCT scan.     

Event-based motion correction for PET transmission measurements with a rotating point source

Accurate attenuation correction is important for quantitative positron emission tomography (PET) studies. When performing transmission measurements using an external rotating radioactive source, object motion during the transmission scan can distort the attenuation correction factors computed as the ratio of the blank to transmission counts, and cause errors and artefacts in reconstructed PET images. In this paper we report a compensation method for rigid body motion during PET transmission measurements, in which list mode transmission data are motion corrected event-by-event, based on known motion, to ensure that all events which traverse the same path through the object are recorded on a common line of response (LOR). As a result, the motion-corrected transmission LOR may record a combination of events originally detected on different LORs. To ensure that the corresponding blank LOR records events from the same combination of contributing LORs, the list mode blank data are spatially transformed event-by-event based on the same motion information. The number of counts recorded on the resulting blank LOR is then equivalent to the number of counts that would have been recorded on the corresponding motion-corrected transmission LOR in the absence of any attenuating object. The proposed method has been verified in phantom studies with both stepwise movements and continuous motion. We found that attenuation maps derived from motion-corrected transmission and blank data agree well with those of the stationary phantom and are significantly better than uncorrected attenuation data.     

List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

Respiratory motion in emission tomography leads to reduced image quality. Developed correction methodology has been concentrating on the use of respiratory synchronized acquisitions leading to gated frames. Such frames, however, are of low signal-to-noise ratio as a result of containing reduced statistics. In this work, we describe the implementation of an elastic transformation within a list-mode-based reconstruction for the correction of respiratory motion over the thorax, allowing the use of all data available throughout a respiratory motion average acquisition. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List-mode-data-based PET-simulated frames were subsequently produced by combining the NCAT datasets with Monte Carlo simulation. A non-rigid registration algorithm based on B-spline basis functions was employed to derive transformation parameters accounting for the respiratory motion using the NCAT dynamic CT images. The displacement matrices derived were subsequently applied during the image reconstruction of the original emission list mode data. Two different implementations for the incorporation of the elastic transformations within the one-pass list mode EM (OPL-EM) algorithm were developed and evaluated. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lung fields, the elastic-transformation-based correction leads to a more uniform improvement across the lungs for different lesion sizes and locations.     

CT image registration in sinogram space

Object displacement in a CT scan is generally reflected in CT projection data or sinogram. In this work, the direct relationship between object motion and the change of CT projection data (sinogram) is investigated and this knowledge is applied to create a novel algorithm for sinogram registration. Calculated and experimental results demonstrate that the registration technique works well for registering rigid 2D or 3D motion in parallel and fan beam samplings. Problem and solution for 3D sinogram-based registration of metallic fiducials are also addressed. Since the motion is registered before image reconstruction, the presented algorithm is particularly useful when registering images with metal or truncation artifacts. In addition, this algorithm is valuable for dealing with situations where only limited projection data are available, making it appealing for various applications in image guided radiation therapy.     

DMLC IMRT delivery to targets moving in 2D in Beam's eye view

The goal of this article is to present the algorithm for DMLC leaf control capable of delivering IMRT to tumors that experience motion in two dimensions in the beams eye view (BEV) plane. The generic, two-dimensional (2D) motion of the projection of the rigid target on BEV plane can be divided into two components. The first component describes the motion of the projection of the target along the x axis (parallel to the MLC leaf motions) and the other describes the motion of the target projection on the y axis (perpendicular to the leaf motion direction). First, time optimal leaf trajectories are calculated independently for each leaf pair of the MLC assembly to compensate the x-axis component of the 2D motion of the target on the BEV. These leaf trajectories are then synchronized following the mid time (MT) synchronization procedure. To compensate for the y-axis component of the motion of the target projection on the BEV plane, the procedure of "switching" leaf pair trajectories in the upward (or downward) direction is executed when the target's BEV projection moves upward (or downward) from its equilibrium position along the y axis. When the intensity function is a 2D histogram, the error between the intended and delivered intensity in 2D DMLC IMRT delivery will depend on the shape of the intensity map and on the MLC physical constraint (leaf width and maximum admissible leaf speed). The MT synchronization of leaf trajectories decreases the impact of above constraints on the error in 2D DMLC IMRT intensity map delivery. The proof is provided, that if hardware constraints in the 2D DMLC IMRT delivery strategy are removed, the errors between planned and delivered 2D intensity maps are entirely eliminated. Examples of 2D DMLC IMRT delivery to rigid targets moving along elliptical orbits on BEV planes are calculated and analyzed for 20 clinical fluence maps. The comparisons between the intensity delivered without motion correction, with motion correction along x axis only, and with motion correction for full 2D motion of the target are calculated and quantitatively evaluated. The fluence maps were normalized to 100 MU and the rms difference between the desired and delivered fluence was 12 MU for no motion compensation, 11.18 MU for 1D compensation, and 4.73 MU for 2D motion compensations. The advantage of correcting for full 2D motion of target projected on the BEV plane is demonstrated.     

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.     

The effect on IMRT conformality of elastic tissue movement and a practical suggestion for movement compensation via the modified dynamic multileaf collimator (dMLC) technique

A major remaining problem in delivering radiotherapy, specifically intensity-modulated radiation therapy (IMRT), is the need to accommodate and correct for intrafraction movement. The developing availability of 4D computed tomographic images can potentially form the basis of the new field of image-guided IMRT. It is important to understand the effects on delivered dose of the patient breathing during IMRT and this paper models the effect which applies whether there is or is not a time component to the IMRT delivery method. It then goes on to suggest a practical correction strategy. The 'stretch-and-shift-the-planned-modulations' strategy is proposed and a practical method to deliver this is explained. This practical strategy is based on a modification of the dynamic multileaf collimator IMRT method whereby the leaves are arranged to 'breath' in tandem with the breathing of the patient. Some examples are also given from a study of mismatching the patient and leaf-correction motions.     

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.     

Mitigation of motion artifacts in CBCT of lung tumors based on tracked tumor motion during CBCT acquisition

An algorithm capable of mitigating respiratory motion blurring artifacts in cone-beam computed tomography (CBCT) lung tumor images based on the motion of the tumor during the CBCT scan is developed. The tumor motion trajectory and probability density function (PDF) are reconstructed from the acquired CBCT projection images using a recently developed algorithm Lewis et al (2010 Phys. Med. Biol. 55 2505-22). Assuming that the effects of motion blurring can be represented by convolution of the static lung (or tumor) anatomy with the motion PDF, a cost function is defined, consisting of a data fidelity term and a total variation regularization term. Deconvolution is performed through iterative minimization of this cost function. The algorithm was tested on digital respiratory phantom, physical respiratory phantom and patient data. A clear qualitative improvement is evident in the deblurred images as compared to the motion-blurred images for all cases. Line profiles show that the tumor boundaries are more accurately and clearly represented in the deblurred images. The normalized root-mean-squared error between the images used as ground truth and the motion-blurred images are 0.29, 0.12 and 0.30 in the digital phantom, physical phantom and patient data, respectively. Deblurring reduces the corresponding values to 0.13, 0.07 and 0.19. Application of a -700 HU threshold to the digital phantom results in tumor dimension measurements along the superior-inferior axis of 2.8, 1.8 and 1.9 cm in the motion-blurred, ground truth and deblurred images, respectively. Corresponding values for the physical phantom are 3.4, 2.7 and 2.7 cm. A threshold of -500 HU applied to the patient case gives measurements of 3.1, 1.6 and 1.7 cm along the SI axis in the CBCT, 4DCT and deblurred images, respectively. This technique could provide more accurate information about a lung tumor's size and shape on the day of treatment.     

Respiratory motion correction for PET oncology applications using affine transformation of list mode data

Respiratory motion is a source of artefacts and reduced image quality in PET. Proposed methodology for correction of respiratory effects involves the use of gated frames, which are however of low signal-to-noise ratio. Therefore a method accounting for respiratory motion effects without affecting the statistical quality of the reconstructed images is necessary. We have implemented an affine transformation of list mode data for the correction of respiratory motion over the thorax. The study was performed using datasets of the NCAT phantom at different points throughout the respiratory cycle. List mode data based PET simulated frames were produced by combining the NCAT datasets with a Monte Carlo simulation. Transformation parameters accounting for respiratory motion were estimated according to an affine registration and were subsequently applied on the original list mode data. The corrected and uncorrected list mode datasets were subsequently reconstructed using the one-pass list mode EM (OPL-EM) algorithm. Comparison of corrected and uncorrected respiratory motion average frames suggests that an affine transformation in the list mode data prior to reconstruction can produce significant improvements in accounting for respiratory motion artefacts in the lungs and heart. However, the application of a common set of transformation parameters across the imaging field of view does not significantly correct the respiratory effects on organs such as the stomach, liver or spleen.     

Removal of ring artifacts in CT imaging through detection and correction of stripes in the sinogram

Due to malfunctioning and mis-calibration of cells in digital x-ray detectors as well as impurities on the scintillator screens, stripe artifacts arise in the sinogram which in turn generate ring artifacts in the reconstructed x-ray computed tomography images. In this paper, a novel technique is proposed for the detection and removal of stripe artifacts in a sinogram with a view to suppress the ring artifacts from the tomographic images. To accurately detect the stripe creating pixels using a derivative-based algorithm, at first the sinogram is windowed to create a sub-sinogram by keeping the pixel of examination at the center position in the sub-sinogram. The other pixels in the sub-sinogram are selected from a polyphase component of the sinogram. A new mathematical index is proposed here to isolate the strong and weak ring-generating stripes from the good ones. For the correction of strong ring artifacts resulting from the defective detector elements and dusty scintillator crystals, 2D variable window moving average and weighted moving average filters are proposed in this work. On the other hand, a conventionally trusted constant bias correction scheme is adopted to correct the responses of the mis-calibrated detector elements. To evaluate and compare the performance of the proposed algorithm, real micro-CT images acquired from two flat panel detectors under different operating conditions are used. Experimental results show that the proposed method can remove ring artifacts more effectively without imparting noticeable distortion in the image as compared to a recently reported technique in the literature.     

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.     

Integrating respiratory gating into a megavoltage cone-beam CT system

We have previously described a low-dose megavoltage cone beam computed tomography (MV CBCT) system capable of producing projection image using one beam pulse. In this study, we report on its integration with respiratory gating for gated radiotherapy. The respiratory gating system tracks a reflective marker on the patient's abdomen midway between the xiphoid and umbilicus, and disables radiation delivery when the marker position is outside predefined thresholds. We investigate two strategies for acquiring gated scans. In the continuous rotation-gated acquisition, the linear accelerator (LINAC) is set to the fixed x-ray mode and the gantry makes a 5 min, 360 degree continuous rotation, during which the gating system turns the radiation beam on and off, resulting in projection images with an uneven distribution of projection angles (e.g., in 70 arcs each covering 2 degrees). In the gated rotation-continuous acquisition, the LINAC is set to the dynamic arc mode, which suspends the gantry rotation when the gating system inhibits the beam, leading to a slightly longer (6-7 min) scan time, but yielding projection images with more evenly distributed projection angles (e.g., approximately 0.8 degrees between two consecutive projection angles). We have tested both data acquisition schemes on stationary (a contrast detail and a thoracic) phantoms and protocol lung patients. For stationary phantoms, a separate motion phantom not visible in the images is used to trigger the RPM system. Frame rate is adjusted so that approximately 450 images (13 MU) are acquired for each scan and three-dimensional tomographic images reconstructed using a Feldkamp filtered backprojection algorithm. The gated rotation-continuous acquisition yield reconstructions free of breathing artifacts. The tumor in parenchymal lung and normal tissues are easily discernible and the boundary between the diaphragm and the lung sharply defined. Contrast-to-noise ratio (CNR) is not degraded relative to nongated scans of stationary phantoms. The continuous rotation-gated acquisition scan also yields tomographic images with discernible anatomic features; however, streak artifacts are observed and CNR is reduced by approximately a factor of 4. In conclusion, we have successfully developed a gated MV CBCT system to verify the patient positioning for gated radiotherapy.     

Motion correction for improved target localization with on-board cone-beam computed tomography

On-board imager (OBI) based cone-beam computed tomography (CBCT) has become available in radiotherapy clinics to accurately identify the target in the treatment position. However, due to the relatively slow gantry rotation (typically about 60 s for a full 360 degrees scan) in acquiring the CBCT projection data, the patient's respiratory motion causes serious problems such as blurring, doubling, streaking and distortion in the reconstructed images, which heavily degrade the image quality and the target localization. In this work, we present a motion compensation method for slow-rotating CBCT scans by incorporating into image reconstruction a patient-specific motion model, which is derived from previously obtained four-dimensional (4D) treatment planning CT images of the same patient via deformable registration. The registration of the 4D CT phases results in transformations representing a temporal sequence of three-dimensional (3D) deformation fields, or in other words, a 4D model of organ motion. The algorithm was developed heuristically in two-dimensional (2D) parallel-beam geometry and extended to 3D cone-beam geometry. By simulations with digital phantoms capable of translational motion and other complex motion, we demonstrated that the algorithm can reduce the motion artefacts locally, and restore the tumour size and shape, which may thereby improve the accuracy of target localization and patient positioning when CBCT is used as the treatment guidance.     

Rigid-body transformation of list-mode projection data for respiratory motion correction in cardiac PET

High-resolution cardiac PET imaging with emphasis on quantification would benefit from eliminating the problem of respiratory movement during data acquisition. Respiratory gating on the basis of list-mode data has been employed previously as one approach to reduce motion effects. However, it results in poor count statistics with degradation of image quality. This work reports on the implementation of a technique to correct for respiratory motion in the area of the heart at no extra cost for count statistics and with the potential to maintain ECG gating, based on rigid-body transformations on list-mode data event-by-event. A motion-corrected data set is obtained by assigning, after pre-correction for detector efficiency and photon attenuation, individual lines-of-response to new detector pairs with consideration of respiratory motion. Parameters of respiratory motion are obtained from a series of gated image sets by means of image registration. Respiration is recorded simultaneously with the list-mode data using an inductive respiration monitor with an elasticized belt at chest level. The accuracy of the technique was assessed with point-source data showing a good correlation between measured and true transformations. The technique was applied on phantom data with simulated respiratory motion, showing successful recovery of tracer distribution and contrast on the motion-corrected images, and on patient data with C15O and 18FDG. Quantitative assessment of preliminary C15O patient data showed improvement in the recovery coefficient at the centre of the left ventricle.     

Performance studies of four-dimensional cone beam computed tomography

Four-dimensional cone beam computed tomography (4DCBCT) has been proposed to characterize the breathing motion of tumors before radiotherapy treatment. However, when the acquired cone beam projection data are retrospectively gated into several respiratory phases, the available data to reconstruct each phase is under-sampled and thus causes streaking artifacts in the reconstructed images. To solve the under-sampling problem and improve image quality in 4DCBCT, various methods have been developed. This paper presents performance studies of three different 4DCBCT methods based on different reconstruction algorithms. The aims of this paper are to study (1) the relationship between the accuracy of the extracted motion trajectories and the data acquisition time of a 4DCBCT scan and (2) the relationship between the accuracy of the extracted motion trajectories and the number of phase bins used to sort projection data. These aims will be applied to three different 4DCBCT methods: conventional filtered backprojection reconstruction (FBP), FBP with McKinnon-Bates correction (MB) and prior image constrained compressed sensing (PICCS) reconstruction. A hybrid phantom consisting of realistic chest anatomy and a moving elliptical object with known 3D motion trajectories was constructed by superimposing the analytical projection data of the moving object to the simulated projection data from a chest CT volume dataset. CBCT scans with gantry rotation times from 1 to 4 min were simulated, and the generated projection data were sorted into 5, 10 and 20 phase bins before different methods were used to reconstruct 4D images. The motion trajectories of the moving object were extracted using a fast free-form deformable registration algorithm. The root mean square errors (RMSE) of the extracted motion trajectories were evaluated for all simulated cases to quantitatively study the performance. The results demonstrate (1) longer acquisition times result in more accurate motion delineation for each method; (2) ten or more phase bins are necessary in 4DCBCT to ensure sufficient temporal resolution in tumor motion and (3) to achieve the same performance as FBP-4DCBCT with a 4 min data acquisition time, MB-4DCBCT and PICCS-4DCBCT need about 2- and 1 min data acquisition times, respectively.     

Model-based respiratory motion compensation for emission tomography image reconstruction

In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.     

Study of the IMRT interplay effect using a 4DCT Monte Carlo dose calculation

Respiratory motion may lead to dose errors when treating thoracic and abdominal tumours with radiotherapy. The interplay between complex multileaf collimator patterns and patient respiratory motion could result in unintuitive dose changes. We have developed a treatment reconstruction simulation computer code that accounts for interplay effects by combining multileaf collimator controller log files, respiratory trace log files, 4DCT images and a Monte Carlo dose calculator. Two three-dimensional (3D) IMRT step-and-shoot plans, a concave target and integrated boost were delivered to a 1D rigid motion phantom. Three sets of experiments were performed with 100%, 50% and 25% duty cycle gating. The log files were collected, and five simulation types were performed on each data set: continuous isocentre shift, discrete isocentre shift, 4DCT, 4DCT delivery average and 4DCT plan average. Analysis was performed using 3D gamma analysis with passing criteria of 2%, 2 mm. The simulation framework was able to demonstrate that a single fraction of the integrated boost plan was more sensitive to interplay effects than the concave target. Gating was shown to reduce the interplay effects. We have developed a 4DCT Monte Carlo simulation method that accounts for IMRT interplay effects with respiratory motion by utilizing delivery log files.     

Monte Carlo dose calculation of segmental IMRT delivery to a moving phantom using dynamic MLC and gating log files

Respiratory gating is emerging as a tool to limit the effect of motion for liver and lung tumors. In order to study the impact of target motion and gated intensity modulated radiation therapy (IMRT) delivery, a computer program was developed to simulate segmental IMRT delivery to a moving phantom. Two distinct plans were delivered to a rigid-motion phantom with a film insert in place under four conditions: static, sinusoidal motion, gated sinusoidal motion with a duty cycle of 25% and gated sinusoidal motion with duty cycle of 50% under motion conditions of a typical patient (A = 1 cm, T = 4 s). The MLC controller log files and gating log files were retained to perform a retrospective Monte Carlo dose calculation of the plans. Comparison of the 2D planar dose distributions between simulation and measurement demonstrated that our technique had at least 94% of the points passing gamma criteria of 3% for dose difference and 3 mm as the distance to agreement. This note demonstrates that the use of dynamic multi-leaf collimator and respiratory monitoring system log files together with a fast Monte Carlo dose calculation algorithm is an accurate and efficient way to study the dosimetric effect of motion for gated or non-gated IMRT delivery on a rigidly-moving body.