A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities.
ABSTRACT: PURPOSE:To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. METHODS AND MATERIALS:A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. RESULTS:The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ?TV ranged from 10 to 248 mm3 (-26% to 61%), and the ?BP ranged from 0 to 0.2 (-71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model. CONCLUSIONS:A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.
Project description:Radiotherapy of mobile tumors requires specific imaging tools and models to reduce the impact of motion on the treatment. Online continuous nonionizing imaging has become possible with the recent development of magnetic resonance imaging devices combined with linear accelerators. This opens the way to new guided treatment methods based on the real-time tracking of anatomical motion. In such devices, 2D fast MR-images are well-suited to capture and predict the real-time motion of the tumor. To be used effectively in an adaptive radiotherapy, these MR images have to be combined with X-ray images such as CT, which are necessary to compute the irradiation dose deposition. We therefore developed a method combining both image modalities to track the motion on MR images and reproduce the tracked motion on a sequence of 3DCT images in real-time. It uses manually placed navigators to track organ interfaces in the image, making it possible to select anatomical object borders that are visible on both MRI and CT modalities and giving the operator precise control of the motion tracking quality. Precomputed deformation fields extracted from the 4DCT acquired in the planning phase are then used to deform existing 3DCT images to match the tracked object position, creating a new set of 3DCT images encompassing irregularities in the breathing pattern for the complete duration of the MRI acquisition. The final continuous reconstructed 4DCT image sequence reproduces the motion captured by the MRI sequence with high precision (difference below 2 mm).
Project description:BACKGROUND:In adults, a single pre-treatment four-dimensional CT (4D-CT) acquisition is often used to account for respiratory-induced target motion during radiotherapy. However, studies have indicated that a 4D-CT is not always representative for respiratory motion. Our aim was to investigate whether respiratory-induced diaphragm motion in children on a single pre-treatment 4DCT can accurately predict respiratory-induced diaphragm motion as observed on cone beam CTs (CBCTs). METHODS:Twelve patients (mean age 14.5 yrs.; range 8.6-17.9 yrs) were retrospectively included based on visibility of the diaphragm on abdominal or thoracic imaging data acquired during free breathing. A 4DCT for planning purposes and daily/weekly CBCTs (total 125; range 4-29 per patient) acquired prior to dose delivery were available. The amplitude, corresponding to the difference in position of the diaphragm in cranial-caudal direction in end-inspiration and end-expiration phases, was extracted from the 4DCT (A4DCT). The amplitude in CBCTs (ACBCT) was defined as displacement between averaged in- and expiration diaphragm positions on corresponding projection images, and the distribution of ACBCT was compared to A4DCT (one-sample t-test, significance level p?< 0.05). RESULTS:Over all patients, the mean A4DCT was 10.4 mm and the mean ACBCT 11.6 mm. For 9/12 patients, A4DCT differed significantly (p <?0.05) from ACBCT. Differences >?3 mm were found in 69/125 CBCTs (55%), with A4DCT mostly underestimating ACBCT. For 7/12 patients, diaphragm positions differed significantly from the baseline position. CONCLUSION:Respiratory-induced diaphragm motion determined on 4DCT does not accurately predict the daily respiratory-induced diaphragm motion observed on CBCTs, as the amplitude and baseline position differed statistically significantly in the majority of patients. Regular monitoring of respiratory motion during the treatment course using CBCTs could yield a higher accuracy when a daily adaptation to the actual breathing amplitude takes place.
Project description:As a counterpart of 4DCT in the treatment planning stage of radiotherapy treatment, 4D cone beam computed tomography (4DCBCT) method has been proposed to verify tumor motion trajectories before radiation therapy treatment delivery. Besides 4DCBCT acquisition using slower gantry rotation speed or multiple rotations, a new method using the prior image constrained compressed sensing (PICCS) image reconstruction method and the standard 1-min data acquisition were proposed. In this paper, the PICCS-4DCBCT method was combined with deformable registration to validate its capability in motion trajectory extraction using physical phantom data, simulated human subject data from 4DCT and in vivo human subject data.Two methods were used to validate PICCS-4DCBCT for the purpose of respiratory motion delineation. The standard 1-min gantry rotation Cone Beam CT acquisition was used for both methods. In the first method, 4DCBCT projection data of a physical motion phantom were acquired using an on-board CBCT acquisition system (Varian Medical Systems, Palo Alto, CA). Using a deformable registration method, the object motion trajectories were extracted from both FBP and PICCS reconstructed 4DCBCT images, and compared against the programmed motion trajectories. In the second method, using a clinical 4DCT dataset, Cone Beam CT projections were simulated by forward projection. Using a deformable registration method, the tumor motion trajectories were extracted from the reconstructed 4DCT and PICCS-4DCBCT images. The performance of PICCS-4DCBCT is assessed against the 4DCT ground truth. The breathing period was varied in the simulation to study its effect on motion extraction. For both validation methods, the root mean square error (RMSE) and the maximum of the errors (MaxE) were used to quantify the accuracy of the extracted motion trajectories. After the validation, a clinical dataset was used to demonstrate the motion delineation capability of PICCS-4DCBCT for human subjects.In both validation studies, the RMSEs of the extracted motion trajectories from PICCS-4DCBCT images are less than 0.7 mm, and their MaxEs are less than 1 mm, for all three directions. In comparison, FBP-4DCBCT shows considerably larger RMSEs in the physical phantom based validation. PICCS-4DCBCT also shows insensitivity to the breathing period in the 4DCT based validation. For the in vivo human subject study, high quality 3D motion trajectory of the tumor was obtained from PICCS-4DCBCT images and showed consistency with visual observation.These results demonstrate accurate delineation of tumor motion trajectory can be achieved using PICCS-4DCBCT and the standard 1-min data acquisition.
Project description:While four-dimensional computed tomography (4DCT) and deformable registration can be used to assess the dose delivered to regularly moving targets, there are few methods available for irregularly moving targets. 4DCT captures an idealized waveform, but human respiration during treatment is characterized by gradual baseline shifts and other deviations from a periodic signal. This paper describes a method for computing the dose delivered to irregularly moving targets based on 1D or 3D waveforms captured at the time of delivery.The procedure uses CT or 4DCT images for dose calculation, and 1D or 3D respiratory waveforms of the target position at time of delivery. Dose volumes are converted from their Cartesian geometry into a beam-specific radiological depth space, parameterized in 2D by the beam aperture, and longitudinally by the radiological depth. In this new frame of reference, the proton doses are translated according to the motion found in the 1D or 3D trajectory. These translated dose volumes are weighted and summed, then transformed back into Cartesian space, yielding an estimate of the dose that includes the effect of the measured breathing motion. The method was validated using a synthetic lung phantom and a single representative patient CT. Simulated 4DCT was generated for the phantom with 2 cm peak-to-peak motion.A passively-scattered proton treatment plan was generated using 6 mm and 5 mm smearing for the phantom and patient plans, respectively. The method was tested without motion, and with two simulated breathing signals: a 2 cm amplitude sinusoid, and a 2 cm amplitude sinusoid with 3 cm linear drift in the phantom. The tumor positions were equally weighted for the patient calculation. Motion-corrected dose was computed based on the mid-ventilation CT image in the phantom and the peak exhale position in the patient. Gamma evaluation was 97.8% without motion, 95.7% for 2 cm sinusoidal motion, 95.7% with 3 cm drift in the phantom (2 mm, 2%), and 90.8% (3 mm, 3%)for the patient data.We have demonstrated a method for accurately reproducing proton dose to an irregularly moving target from a single CT image. We believe this algorithm could prove a useful tool to study the dosimetric impact of baseline shifts either before or during treatment.
Project description:BACKGROUND:While four-dimensional computed tomography (4DCT) is extensively used in adults, reluctance remains to use 4DCT in children. Day-to-day (interfractional) variability and irregular respiration (intrafractional variability) have shown to be limiting factors of 4DCT effectiveness in adults. In order to evaluate 4DCT applicability in children, the purpose of this study is to quantify inter- and intrafractional variability of respiratory motion in children and adults. The pooled analysis enables a solid comparison to reveal if 4DCT application for planning purposes in children could be valid. METHODS/MATERIALS:We retrospectively included 90 patients (45 children and 45 adults), for whom the diaphragm was visible on abdominal/thoracic free-breathing cone beam CTs (480 pediatric, 524 adult CBCTs). For each CBCT, the cranial-caudal position of end-exhale and end-inhale positions of the right diaphragm dome were manually selected in the projection images. The difference in position between both phases defines the amplitude. Cycle time equaled inspiratory plus expiratory time. We analyzed the variability of the inter- and intrafractional respiratory-induced diaphragm motion. RESULTS:Ranges of respiratory motion characteristics were large in both children and adults (amplitude: 4-17 vs 5-24 mm, cycle time 2.1-3.9 vs 2.7-6.5 s). The mean amplitude was slightly smaller in children than in adults (10.7 vs 12.3 mm; P = 0.06). Interfractional amplitude variability was statistically significantly smaller in children than in adults (1.4 vs 2.2 mm; P = 0.00). Mean cycle time was statistically significantly shorter in children (2.9 vs 3.6 s; P = 0.00). Additionally, intrafractional cycle time variability was statistically significantly smaller in children (0.5 vs 0.7 s; P = 0.00). CONCLUSIONS:Overall variability is smaller in children than in adults, indicating that respiratory motion is more regular in children than in adults. This implies that a single pretreatment 4DCT could be a good representation of daily respiratory motion in children and will be at least equally beneficial for planning purposes as it is in adults.
Project description:BACKGROUND: Respiration-gated radiotherapy (RGRT) can decrease treatment toxicity by allowing for smaller treatment volumes for mobile tumors. RGRT is commonly performed using external surrogates of tumor motion. We describe the use of time-integrated electronic portal imaging (TI-EPI) to verify the position of internal structures during RGRT delivery METHODS: TI-EPI portals were generated by continuously collecting exit dose data (aSi500 EPID, Portal vision, Varian Medical Systems) when a respiratory motion phantom was irradiated during expiration, inspiration and free breathing phases. RGRT was delivered using the Varian RPM system, and grey value profile plots over a fixed trajectory were used to study object positions. Time-related positional information was derived by subtracting grey values from TI-EPI portals sharing the pixel matrix. TI-EPI portals were also collected in 2 patients undergoing RPM-triggered RGRT for a lung and hepatic tumor (with fiducial markers), and corresponding planning 4-dimensional CT (4DCT) scans were analyzed for motion amplitude. RESULTS: Integral grey values of phantom TI-EPI portals correlated well with mean object position in all respiratory phases. Cranio-caudal motion of internal structures ranged from 17.5-20.0 mm on planning 4DCT scans. TI-EPI of bronchial images reproduced with a mean value of 5.3 mm (1 SD 3.0 mm) located cranial to planned position. Mean hepatic fiducial markers reproduced with 3.2 mm (SD 2.2 mm) caudal to planned position. After bony alignment to exclude set-up errors, mean displacement in the two structures was 2.8 mm and 1.4 mm, respectively, and corresponding reproducibility in anatomy improved to 1.6 mm (1 SD). CONCLUSION: TI-EPI appears to be a promising method for verifying delivery of RGRT. The RPM system was a good indirect surrogate of internal anatomy, but use of TI-EPI allowed for a direct link between anatomy and breathing patterns.
Project description:To describe in detail a dataset consisting of serial four-dimensional computed tomography (4DCT) and 4D cone beam CT (4DCBCT) images acquired during chemoradiotherapy of 20 locally advanced, nonsmall cell lung cancer patients we have collected at our institution and shared publicly with the research community.As part of an NCI-sponsored research study 82 4DCT and 507 4DCBCT images were acquired in a population of 20 locally advanced nonsmall cell lung cancer patients undergoing radiation therapy. All subjects underwent concurrent radiochemotherapy to a total dose of 59.4-70.2 Gy using daily 1.8 or 2 Gy fractions. Audio-visual biofeedback was used to minimize breathing irregularity during all fractions, including acquisition of all 4DCT and 4DCBCT acquisitions in all subjects. Target, organs at risk, and implanted fiducial markers were delineated by a physician in the 4DCT images. Image coordinate system origins between 4DCT and 4DCBCT were manipulated in such a way that the images can be used to simulate initial patient setup in the treatment position. 4DCT images were acquired on a 16-slice helical CT simulator with 10 breathing phases and 3 mm slice thickness during simulation. In 13 of the 20 subjects, 4DCTs were also acquired on the same scanner weekly during therapy. Every day, 4DCBCT images were acquired on a commercial onboard CBCT scanner. An optically tracked external surrogate was synchronized with CBCT acquisition so that each CBCT projection was time stamped with the surrogate respiratory signal through in-house software and hardware tools. Approximately 2500 projections were acquired over a period of 8-10 minutes in half-fan mode with the half bow-tie filter. Using the external surrogate, the CBCT projections were sorted into 10 breathing phases and reconstructed with an in-house FDK reconstruction algorithm. Errors in respiration sorting, reconstruction, and acquisition were carefully identified and corrected.4DCT and 4DCBCT images are available in DICOM format and structures through DICOM-RT RTSTRUCT format. All data are stored in the Cancer Imaging Archive (TCIA, http://www.cancerimagingarchive.net/) as collection 4D-Lung and are publicly available.Due to high temporal frequency sampling, redundant (4DCT and 4DCBCT) data at similar timepoints, oversampled 4DCBCT, and fiducial markers, this dataset can support studies in image-guided and image-guided adaptive radiotherapy, assessment of 4D voxel trajectory variability, and development and validation of new tools for image registration and motion management.
Project description:To develop a novel four-dimensional (4D) intensity modulated radiation therapy (IMRT) treatment planning methodology based on dynamic virtual patient models.The 4D model-based planning (4DMP) is a predictive tracking method which consists of two main steps: (1) predicting the 3D deformable motion of the target and critical structures as a function of time during treatment delivery; (2) adjusting the delivery beam apertures formed by the dynamic multi-leaf collimators (DMLC) to account for the motion. The key feature of 4DMP is the application of a dynamic virtual patient model in motion prediction, treatment beam adjustment, and dose calculation. A lung case was chosen to demonstrate the feasibility of the 4DMP. For the lung case, a dynamic virtual patient model (4D model) was first developed based on the patient's 4DCT images. The 4D model was capable of simulating respiratory motion of different patterns. A model-based registration method was then applied to convert the 4D model into a set of deformation maps and 4DCT images for dosimetric purposes. Based on the 4D model, 4DMP treatment plans with different respiratory motion scenarios were developed. The quality of 4DMP plans was then compared with two other commonly used 4D planning methods: maximum intensity projection (MIP) and planning on individual phases (IP).Under regular periodic motion, 4DMP offered similar target coverage as MIP with much better normal tissue sparing. At breathing amplitude of 2 cm, the lung V20 was 23.9% for a MIP plan and 16.7% for a 4DMP plan. The plan quality was comparable between 4DMP and IP: PTV V97 was 93.8% for the IP plan and 93.6% for the 4DMP plan. Lung V20 of the 4DMP plan was 2.1% lower than that of the IP plan and Dmax to cord was 2.2 Gy higher. Under a real time irregular breathing pattern, 4DMP had the best plan quality. PTV V97 was 90.4% for a MIP plan, 88.6% for an IP plan and 94.1% for a 4DMP plan. Lung V20 was 20.1% for the MIP plan, 17.8% for the IP plan and 17.5% for the 4DMP plan. The deliverability of the real time 4DMP plan was proved by calculating the maximum leaf speed of the DMLC.The 4D model-based planning, which applies dynamic virtual patient models in IMRT treatment planning, can account for the real time deformable motion of the tumor under different breathing conditions. Under regular motion, the quality of 4DMP plans was comparable with IP and superior to MIP. Under realistic motion in which breathing amplitude and period change, 4DMP gave the best plan quality of the three 4D treatment planning techniques.
Project description:Relative motion between a tumor and a scanning proton beam results in a degradation of the dose distribution (interplay effect). This study investigates the relationship between beam scanning parameters and the interplay effect, with the goal of finding parameters that minimize interplay. 4D Monte Carlo simulations of pencil beam scanning proton therapy treatments were performed using the 4DCT geometry of five lung cancer patients of varying tumor size (50.4-167.1 cc) and motion amplitude (2.9-30.1 mm). Treatments were planned assuming delivery in 35 × 2.5 Gy(RBE) fractions. The spot size, time to change the beam energy (?es), time required for magnet settling (?ss), initial breathing phase, spot spacing, scanning direction, scanning speed, beam current and patient breathing period were varied for each of the five patients. Simulations were performed for a single fraction and an approximation of conventional fractionation. For the patients considered, the interplay effect could not be predicted using the superior-inferior motion amplitude alone. Larger spot sizes (? ~ 9-16 mm) were less susceptible to interplay, giving an equivalent uniform dose (EUD) of 99.0 ± 4.4% (1 standard deviation) in a single fraction compared to 86.1 ± 13.1% for smaller spots (? ~ 2-4 mm). The smaller spot sizes gave EUD values as low as 65.3% of the prescription dose in a single fraction. Reducing the spot spacing improved the target dose homogeneity. The initial breathing phase can have a significant effect on the interplay, particularly for shorter delivery times. No clear benefit was evident when scanning either parallel or perpendicular to the predominant axis of motion. Longer breathing periods decreased the EUD. In general, longer delivery times led to lower interplay effects. Conventional fractionation showed significant improvement in terms of interplay, giving a EUD of at least 84.7% and 100.0% of the prescription dose for the small and larger spot sizes respectively. The interplay effect is highly patient specific, depending on the motion amplitude, tumor location and the delivery parameters. Large degradations of the dose distribution in a single fraction were observed, but improved significantly using conventional fractionation.
Project description:The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intra-fraction/inter-fraction tracking, respectively. The extensive validations have demonstrated the effectiveness and reliability of the proposed model in motion tracking for both the tumor and the lung in lung cancer radiotherapy.