Improved data acquisition efficiency for respiratory motion correction in coronary MRI

A respiratory navigator with a fixed acceptance gating window is commonly used to reduce respiratory motion artifacts in cardiac MR. This approach prolongs the scan time and occasionally yields an incomplete dataset due to respiratory drifts. To address this issue, we propose an adaptive gating window approach in which the size and position of the gating window are changed adaptively during the acquisition based on the individual's breathing pattern. The adaptive gating window tracks the breathing pattern of the subject throughout the scan and adapts the size and position of the gating window such that the gating efficiency is always fixed at a constant value. To investigate the image quality and acquisition time, free breathing cardiac MRI, including both targeted coronary MRI and late gadolinium enhancement imaging, was performed in 67 subjects using the proposed navigator technique. Targeted coronary MRI was acquired from eleven healthy adult subjects using both the conventional and proposed adaptive gating window techniques. Fifty-six patients referred for cardiac MRI were also imaged using late gadolinium enhancement with the proposed adaptive gating window technique. Subjective and objective image assessments were used to evaluate the proposed method. The results demonstrate that the proposed technique allows free-breathing cardiac MRI in a relatively fixed time without compromising imaging quality due to respiratory motion artifacts.

Purpose: The aim of the project is to test the hypothesis that quasi‐breath‐hold (QBH) biofeedback improves the residual respiratory motion management within a gating window, reducing respiratory motion artifacts in gated 3D thoracic MR images. Methods: A QBH biofeedback system has been employed with gated 3D thoracic MRI acquisitions. The QBH biofeedback system utilized (1) the external marker position on the abdomen using an RPM system (Real‐time Position Management, Varian) to audio‐visually guide a human subject for 2s breath‐hold at 90% exhalation position in each respiratory cycle and (2) the gated T2 weighted SPACE MR pulse sequence of 3 T Siemens MRI for 3D thoracic imaging. The improvement in the upper liver breath‐hold motion reproducibility within the gating window using the QBH biofeedback system has been assessed for a group of volunteers. Each subject underwent two imaging sessions for the assessments of the residual respiratory motion management within the gating window and respiratory motion artifacts in 3D thoracic MRI both with/without QBH biofeedback. Results: The residual upper liver motion within the gating window during MR acquisitions (∼6 minutes) has been considerably reduced using QBH biofeedback, resulting in the reduction of respiratory motion artifacts in lungs and liver of 3D thoracic MR images. Additionally, average RMSE (root mean square error) of abdomen displacement obtained from the RPM has been reduced from 2.3mm of free breathing to 0.8mm of QBH biofeedback breathing: 65% of average displacement error reduction with QBH biofeedback. Conclusion: The study demonstrated the improvement of the upper liver breath‐hold motion reproducibility using QBH biofeedback during 3D thoracic MR imaging. This system can provide clinically applicable motion management of the internal anatomy for gated radiotherapy.

Patient-specific respiratory motion management using lung tumors vs fiducial markers for real-time tumor-tracking stereotactic body radiotherapy.

Free-breathing three-dimensional whole-heart coronary MRI is a noninvasive alternative to X-ray coronary angiography. However, the existing navigator-gated approaches do not meet the requirements of clinical practice, as they perform with suboptimal accuracy and require prolonged acquisition times. Self-navigated techniques, applied to bright-blood imaging sequences, promise to detect the position of the blood pool directly in the readouts acquired for imaging. Hence, the respiratory displacement of the heart can be calculated and used for motion correction with high accuracy and 100% scan efficiency. However, additional bright signal from the chest wall, spine, arms, and liver can render the isolation of the blood pool impossible. In this work, an innovative method based on a targeted combination of the output signals of an anterior phased-array surface coil is implemented to efficiently suppress such additional bright signal. Furthermore, an algorithm for the automatic segmentation of the blood pool is proposed. Robust self-navigation is achieved by cross-correlation. These improvements were integrated into a three-dimensional radial whole-heart coronary MRI sequence and were compared with navigator-gated imaging in vivo. Self-navigation was successful in all cases and the acquisition time was reduced up to 63%. Equivalent or slightly superior image quality, vessel length, and sharpness were achieved.

Purpose:In this work, we have tested the performance of new respiratory gating solutions for Elekta linacs. These solutions include the Response gating and the C‐RAD Catalyst surface mapping system.Verification measurements have been performed for a series of clinical cases. We also examined the beam on latency of the system and its impact on delivery efficiency.Methods:To verify the benefits of tighter gating windows, a Quasar Respiratory Motion Platform was used. Its vertical‐motion plate acted as a respiration surrogate and was tracked by the Catalyst system to generate gating signals. A MatriXX ion‐chamber array was mounted on its longitudinal‐moving platform. Clinical plans are delivered to a stationary and moving Matrix array at 100%, 50% and 30% gating windows and gamma scores were calculated comparing moving delivery results to the stationary result. It is important to note that as one moves to tighter gating windows, the delivery efficiency will be impacted by the linac's beam‐on latency. Using a specialized software package, we generated beam‐on signals of lengths of 1000ms, 600ms, 450ms, 400ms, 350ms and 300ms. As the gating windows get tighter, one can expect to reach a point where the dose rate will fall to nearly zero, indicating that the gating window is close to beam‐on latency. A clinically useful gating window needs to be significantly longer than the latency for the linac.Results:As expected, the use of tighter gating windows improved delivery accuracy. However, a lower limit of the gating window, largely defined by linac beam‐on latency, exists at around 300ms.Conclusion:The Response gating kit, combined with the C‐RAD Catalyst, provides an effective solution for respiratorygated treatment delivery. Careful patient selection, gating window design, even visual/audio coaching may be necessary to ensure both delivery quality and efficiency.This research project is funded by Elekta.

Given the ability of positron emission tomography (PET) imaging to localize malignancies in heterogeneous tumors and tumors that lack an X-ray computed tomography (CT) correlate, combined PET/CT-guided biopsy may improve the diagnostic yield of biopsies. However, PET and CT images are naturally susceptible to problems due to respiratory motion, leading to imprecise tumor localization and shape distortion. To facilitate PET/CT-guided needle biopsy, we developed and investigated the feasibility of a workflow that allows to bring PET image guidance into interventional CT suite while accounting for respiratory motion. The performance of PET/CT respiratory motion correction using registered and summed phases method was evaluated through computer simulations using the mathematical 4D extended cardiac-torso phantom, with motion simulated from real respiratory traces. The performance of PET/CT-guided biopsy procedure was evaluated through operation on a physical anthropomorphic phantom. Vials containing radiolabeled 18F-fluorodeoxyglucose were placed within the physical phantom thorax as biopsy targets. We measured the average distance between target center and the simulated biopsy location among multiple trials to evaluate the biopsy localization accuracy. The computer simulation results showed that the RASP method generated PET images with a significantly reduced noise of 0.10 ± 0.01 standardized uptake value (SUV) as compared to an end-of-expiration image noise of 0.34 ± 0.04 SUV. The respiratory motion increased the apparent liver lesion size from 5.4 ± 1.1 to 35.3 ± 3.0cc. The RASP algorithm reduced this to 15.7 ± 3.7cc. The distances between the centroids for the static image lesion and two moving lesions in the liver and lung, when reconstructed with the RASP algorithm, were 0.83 ± 0.72mm and 0.42 ± 0.72mm. For the ungated imaging, these values increased to 3.48 ± 1.45mm and 2.5 ± 0.12mm, respectively. For the ungated imaging, this increased to 1.99 ± 1.72mm. In addition, the lesion activity estimation (e.g., SUV) was accurate and constant for images reconstructed using the RASP algorithm, whereas large activity bias and variations (± 50%) were observed for lesions in the ungated images. The physical phantom studies demonstrated a biopsy needle localization error of 2.9 ± 0.9mm from CT. Combined with the localization errors due to respiration for the PET images from simulations, the overall estimated lesion localization error would be 3.08mm for PET-guided biopsies images using RASP and 3.64mm when using ungated PET images. In other words, RASP reduced the localization error by approximately 0.6mm. The combined error analysis showed that replacing the standard end-of-expiration images with the proposed RASP method in PET/CT-guided biopsy workflow yields comparable lesion localization accuracy and reduced image noise. The RASP method can produce PET images with reduced noise, attenuation artifacts and respiratory motion, resulting in more accurate lesion localization. Testing the PET/CT-guided biopsy workflow using computer simulation and physical phantoms with respiratory motion, we demonstrated that guided biopsy procedure with the RASP method can benefit from improved PET image quality due to noise reduction, without compromising the accuracy of lesion localization.

Purpose: Accuracy of delivered dose can be affected by the interplay between DMLC delivery and target motion in gated IMRTtreatment. For gated intensity‐modulated lungSBRT, this concern is even larger due to smaller target margins, fewer treatment fractions and higher dose rate (1000MU/minute). The purpose of this work is to investigate the dosimetric accuracy in the latter situation. Method and Materials: Data from 5 lung patients treated with gated SBRT were retrospectively reviewed. For each patient the gating window was individually determined to keep residual motion <5 mm through analyzing the target motion based on 4DCT. Treatment plans were generated with 50% phase CT. PTVs were generated from CTVs with a 5mm margin. Based on the respiratory cycle, MU and dose rate, the DMLC leaf sequence for each beam was segmented into multiple sections, which corresponded to different respiratory phases within the gating window. The segmented DMLC leaf sections were then used to calculate dose distributions with corresponding 4DCT image set. The 4D composite dose distribution was obtained by accumulating the contributions from all phases within gating window using a deformable registration. The 4D dose distributions and DVHs for targets and critical organs were compared with the planned. The influences of the breathing period and dose rate were investigated. Results: The results indicated, although PTV dose coverage can be significantly influenced by the interplay of the target motion and DMLC delivery, the difference in CTV dose coverage between the 4D composite and the planned results is not significant, typically less than 3%. Conclusions: Interplay between target motion and DMLC‐delivery has a clinically acceptable impact in delivered dose accuracy even for the high dose rate gated SBRTtreatment. Other factors, such as target position shift due to the irregularity of patient's breathing, may be the main reasons affecting dose accuracy.

Conventional multiple breath-hold two-dimensional (2D) balanced steady-state free precession (SSFP) presents many difficulties in cardiac cine magnetic resonance imaging (MRI). Recently, a self-gated free-breathing three-dimensional (3D) SSFP technique has been proposed as an alternative in many studies. However, the accuracy and effectiveness of self-gating signals have been barely studied before. Since self-gating signals are crucially important in image reconstruction, a systematic study of self-gating signals and comparison with external monitored signals are needed.Previously developed self-gated free-breathing 3D SSFP techniques are used on twenty-eight healthy volunteers. Both electrocardiographic (ECG) and respiratory bellow signals are also acquired during the scan as external signals. Self-gating signal and external signal are compared by trigger and gating window. Gating window is proposed to evaluate the accuracy and effectiveness of respiratory self-gating signal. Relative deviation of the trigger and root-mean-square-deviation of the cycle duration are calculated. A two-tailed paired t-test is used to identify the difference between self-gating and external signals. A Wilcoxon signed rank test is used to identify the difference between peak and valley self-gating triggers.The results demonstrate an excellent correlation (P = 0, R > 0.99) between self-gating and external triggers. Wilcoxon signed rank test shows that there is no significant difference between peak and valley self-gating triggers for both cardiac (H = 0, P > 0.10) and respiratory (H = 0, P > 0.44) motions. The difference between self-gating and externally monitored signals is not significant (two-tailed paired-sample t-test: H = 0, P > 0.90).The self-gating signals could demonstrate cardiac and respiratory motion accurately and effectively as ECG and respiratory bellow. The difference between the two methods is not significant and can be explained. Furthermore, few ECG trigger errors appear in some subjects while these errors are not found in self-gating signals.

Purpose: To determine the magnitude of error introduced into treatment delivery due to timing effects between respiratory‐gated delivery and dynamic beam delivery (enhanced dynamic wedge (EDW) and step‐and‐shoot intensity modulated radiation therapy (IMRT)). Method and Materials: EDW and IMRT fields were delivered on a linear accelerator (Trilogy, Varian Medical Systems). Gating of the beam was achieved using a commercial respiratory monitoring system (RPM, Varian Medical Systems), and respiratory motion was simulated using a commercial respiratory motion phantom (RPM phantom, Varian Medical Systems). All fields were delivered with no gating, a 1‐mm gating window, and a 2‐mm gating window.Film and ion chamber measurements were made for both EDW and IMRT fields in a water‐equivalent IMRT QA phantom, which was stationary during all measurements. Film measurements used EDR‐2 film, while ion chamber measurements were made with a 0.04 cc volume pin‐point chamber. Leakage current was subtracted from the ion chamber readings.Wedged fields of 15 and 60 degrees were delivered at a dose rate of 600 MU/min. Results were evaluated for the full IMRT plan and for one of the individual beams, at dose rates of 400 and 600 MU/min. Results: All ion chamber measurements were analyzed as percent difference between the gated (1‐mm or 2‐mm gating window) and non‐gated delivery. All differences were less than 1%. There were no significant differences between 1‐mm and 2‐mm gated delivery. Film results, as analyzed from isodose curves and the gamma metric, showed no substantial differences between gated and non‐gated beam delivery. Conclusion: The use of gated treatment delivery of EDW and step‐and‐shoot IMRT fields does not introduce clinically significant differences into the resulting dose distributions, as quantified by film and ion chamber measurements.

Beat-to-beat respiratory motion correction with near 100% efficiency: a quantitative assessment using high-resolution coronary artery imaging

Respiratory motion (RM) and cardiac motion (CM) degrade the quality and resolution in cardiac PET scans. We have developed non-rigid motion estimation methods to estimate both RM and CM based on 4D cardiac gated PET data alone, and compensate the dual respiratory and cardiac (R&C) motions after (MCAR), during (MCDR), and before (MCBR) image reconstruction. In all three R&C motion correction methods, attenuation-activity mismatch effect was modeled by using transformed attenuation maps using the estimated RM. The difference of using activity preserving and non-activity preserving models in R&C correction was also studied. Realistic Monte Carlo simulated 4D cardiac PET data using the 4D XCAT phantom and accurate models of the scanner design parameters and performance characteristics at different noise levels were employed as the known truth and for method development and evaluation. Results from the simulation study suggested that all three dual R&C motion correction methods provide substantial improvement in the quality of 4D cardiac gated PET images as compared with no motion correction. Specifically, the MCDR method yields the best performance for all different noise levels compared with the MCAR and MCBR methods. While MCBR reduces computational time dramatically but the resultant 4D cardiac gated PET images has overall inferior image quality when compared to that from the MCAR and MCDR approaches in the ‘almost’ noise free case. Also, the MCBR method has better noise handling properties when compared with MCAR and provides better quantitative results in high noise cases. When the goal is to reduce scan time or patient radiation dose, MCDR and MCBR provide a good compromise between image quality and computational times.

Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external tracking devices to estimate respiratory signals can add cost and operational complications in a clinical setting. We aim to develop a deep learning (DL) approach that uses only SPECT projection data for respiratory signal estimation. A modified U-Net was implemented that takes temporally finely sampled SPECT sub-projection data (100ms) as input. These sub-projections are obtained by reframing the 20-s list-mode data, resulting in 200 sub-projections, at each projection angle for each SPECT camera head. The network outputs a 200-time-point motion signal for each projection angle, which was later aggregated over all angles to give a full respiratory signal. The target signal for DL model training was from an external stereo-camera visual tracking system (VTS). In addition to comparing DL and VTS, we also included a data-driven approach based on the center-of-mass (CoM) strategy. This CoM method estimates respiratory signals by monitoring the axial changes of CoM for counts in the heart region of the sub-projections. We utilized 900 subjects with stress cardiac perfusion SPECT studies, with 302 subjects for testing and the remaining 598 subjects for training and validation. The Pearson's correlation coefficient between the DL respiratory signal and the reference VTS signal was 0.90, compared to 0.70 between the CoM signal and the reference. For respiratory motion correction on SPECT images, all VTS, DL, and CoM approaches partially de-blured the heart wall, resulting in a thinner wall thickness and increased recovered maximal image intensity within the wall, with VTS reducing blurring the most followed by the DL approach. Uptake quantification for the combined anterior and inferior segments of polar maps showed a mean absolute difference from the reference VTS of 1.7% for the DL method for patients with motion >12mm, compared to 2.6% for the CoM method and 8.5% for no correction. We demonstrate the capability of a DL approach to estimate respiratory signal from SPECT projection data for cardiac perfusion imaging. Our results show that the DL based respiratory motion correction reduces artefacts and achieves similar regional quantification to that obtained using the stereo-camera VTS signals. This may enable fully automatic data-driven respiratory motion correction without relying on external motion tracking devices.

Respiratory motion in emission tomography leads to reduced image quality. Proposed correction methodology has been concentrating on the use of respiratory synchronised acquisitions leading to gated frames. Such frames however are of low signal to noise ratio as a result of containing reduced statistics. Therefore a method accounting for respiratory motion effects without affecting the statistical quality of the reconstructed images is necessary. 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. 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 a Monte Carlo simulation. Transformation parameters accounting for respiratory motion were estimated according to an elastic registration of the NCAT dynamic CT images and were subsequently applied during the image reconstruction of the original emission list mode data. The One-pass list mode EM (OPL-EM) algorithm was modified to integrate the elastic transformation in the sensitivity matrix. Three different implementations have been investigated (no interpolation, trilinear interpolation, b-spline functions incorporation). The corrected images were compared with uncorrected respiratory motion average images. Results demonstrate that the use of elastic transformations in the reconstruction system matrix lead to uniform improvement across the lung field for different lesion sizes. The use of a trilinear interpolation or the incorporation of the b-spline functions lead to times of execution equivalent to standard image reconstruction. However, trilinear interpolation leads to artefacts in areas such as the diaphragm where the largest elastic deformations are occurring.

The aim of this study was to develop a method for tracking respiratory motion throughout full MR or PET/MR studies that requires only minimal additional hardware and no modifications to the sequences. Patient motion that is caused by respiration affects the quality of the signal of the individual radiofrequency receive coil elements. This effect can be detected as a modulation of a monofrequent signal that is emitted by a small portable transmitter placed inside the bore (Pilot Tone). The frequency is selected such that it is located outside of the frequency band of the actual MR readout experiment but well within the bandwidth of the radiofrequency receiver, that is, the oversampling area. Temporal variations of the detected signal indicate motion. After extraction of the signal from the raw data, principal component analysis was used to identify respiratory motion. The approach and potential applications during MR and PET/MR examinations that rely on a continuous respiratory signal were validated with an anthropomorphic, PET/MR-compatible motion phantom as well as in a volunteer study. Respiratory motion detection and correction were presented for MR and PET data in phantom and volunteer studies. The Pilot Tone successfully recovered the ground-truth respiratory signal provided by the phantom. The presented method provides reliable respiratory motion tracking during arbitrary imaging sequences throughout a full PET/MR study. All results can directly be transferred to MR-only applications as well.

Respiratory motion in the chest region during single photon emission computed tomography (SPECT) is a major degrading factor that reduces the accuracy of image quantification. This effect is more notable when the tumor is very small, or the spatial resolution of the imaging system is less than the respiratory motion amplitude. Small animals imaging systems with sub-millimeter spatial resolution need more attention to the respiratory motion for quantitative studies. We developed a motion-embedded four-dimensional (4D)-multi pinhole SPECT (MPS) reconstruction algorithm for respiratory motion correction. This algorithm makes full use of projection statistics for reconstruction of every individual frame. The ROBY phantom with small tumors in liver was generated in eight different phases during one respiratory cycle. The MPS projections were modeled using a fast ray tracing method simulating an MPS acquisition. Individual frames were reconstructed and used for motion estimation. The Demons non-rigid registration algorithm was used to calculate deformation vector fields (DVFs) for simultaneous motion correction and image reconstruction. A motion-embedded 4D-MPS method was used to reconstruct images using all the projections and corresponding DVFs, simultaneously. The 4D-MPS reconstructed images were compared to the low-count single frame (LCSF) reconstructed image, the three-dimensional (3D)-MPS images reconstructed using individual frames, and post reconstruction registration (PRR) that aligns all individual phases to a reference frame using Demons-derived DVFs. The tumor volume relative error (TVE), tumor contrast relative error (TCE), and dice index (DI) for 2, 3, and 4mm liver were calculated and compared for different reconstruction methods. For the 4D-MPS reconstruction method, TVE was reduced and DI was higher compared to PRR, 3D-MPS, and LCSF. The extent of the improvement was higher for the small tumor size (i.e. 2mm). For the biggest tumor in contrast 3 (i.e. 4mm) TVE for 4D-MPS, PRR, 3D-MPS and, LCSF were 1.33%, 8%, 8%, and 14.67%, respectively. The results suggest that motion-embedded 4D-MPS method is an effective and practical way for respiratory motion correction. It reconstructs high quality gated frames while using all projection data to reconstruct each frame.