Purpose: Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc-Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors' previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart. Methods: In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior-inferior direction during free breathing using MRI navigators. A visual tracking system () synchronized with MRI acquisition tracked the anterior-posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc-Wen model by inputting the  derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson's linear correlation coefficient between the abdomen, chest, average of chest and abdomen markers, and Bouc-Wen derived signals versus the true internal motion of the heart from MRI was used to judge the signals match to the heart motion. Results: The results show that the Bouc-Wen model generated signals demonstrated strong correlation with the heart motion. This correlation was slightly larger on average than that of the external surrogate signals derived from the abdomen marker, and average of the abdomen and chest markers, but was not statistically significantly different from them. Conclusions: The results suggest that the proposed model has the potential to be a unified framework for modeling hysteresis in respiratory motion in cardiac perfusion studies and beyond. C 2014 American Association of Physicists in Medicine. [http://dx

The development of methods for correcting patient motion in emission tomography has been receiving increased attention. Often performance of these methods is evaluated through simulations using digital anthropomorphic phantoms, such as the commonly used XCAT phantom, which models both respiratory and cardiac motion based on human studies. However, non-rigid body motion, which is frequently seen in clinical studies, is not present in the standard XCAT phantom. In addition, respiratory motion in the standard phantom is limited to a single generic trend. In this work, to obtain more realistic representation of motion, we developed a series of individual-specific XCAT phantoms modeling non-rigid respiratory and non-rigid body motions derived from the MRI acquisitions of volunteers. Acquisitions were performed in the sagittal orientation using the Navigator methodology. Baseline (no motion) acquisitions at end-expiration were obtained at the beginning of each imaging session for each volunteer. For the body motion studies, MRI was again acquired only at end-expiration for five body motion poses (shoulder stretch, shoulder twist, lateral bend, side roll, and axial slide). For the respiratory motion studies, MRI was acquired during free/regular breathing. The MR slices were then retrospectively sorted into 14 amplitude-binned respiratory states, end-expiration, end-inspiration, six intermediary states during inspiration, and six during expiration using the recorded Navigator signal. XCAT phantoms were then generated based on these MRI data by interactive alignment of the organ contours of the XCAT with the MRI slices using a GUI. Thus far we have created 5 body motion and 5 respiratory motion XCAT phantoms from MRI acquisitions of 6 healthy volunteers (3 males and 3 females). Non-rigid motion exhibited by the volunteers was reflected in both respiratory and body motion phantoms with a varying extent and character for each individual. In addition to these phantoms, we recorded the position of markers placed on the chest of volunteers for the body motion studies, which could be used as external motion measurement. Using these phantoms and external motion data, investigators will be able to test their motion correction approaches for realistic motion obtained from different individuals. The NURBS data and the parameter files for these phantoms are freely available for downloading and can be used with the XCAT license.*

Respiratory motion of the heart impacts the diagnostic accuracy of myocardial-perfusion emission-imaging studies. Amplitude binning has come to be the method of choice for binning list-mode based acquisitions for correction of respiratory motion in PET and SPECT. In some subjects respiratory motion exhibits hysteretic behavior similar to damped non-linear cyclic systems. The detection and correction of hysteresis between the signals from surface movement of the patient’s body used in binning and the motion of the heart within the chest remains an open area for investigation. This study reports our investigation in nine volunteers of the combined MRI tracking of the internal respiratory motion of the heart using Navigators with stereo-tracking of markers on the volunteer’s chest and abdomen by a visual-tracking system (VTS). The respiratory motion signals from the internal organs and the external markers were evaluated for hysteretic behavior analyzing the temporal correspondence of the signals. In general, a strong, positive correlation between the external marker motion (AP direction) and the internal heart motion (SI direction) during respiration was observed. The average ± standard deviation in the Spearman’s ranked correlation coefficient (ρ) over the nine volunteer studied was 0.92 ± 0.1 between the external abdomen marker and the internal heart, and 0.87 ± 0.2 between the external chest marker and the internal heart. However despite the good correlation on average for the nine volunteers, in three studies a poor correlation was observed due to hysteretic behavior between inspiration and expiration for either the chest marker and the internal motion of the heart, or the abdominal marker and the motion of the heart. In all cases we observed a good correlation of at least either the abdomen or the chest with the heart. Based on this result, we propose the use of marker motion from both the chest and abdomen regions when estimating the internal heart motion to detect and address hysteresis when binning list-mode emission data.

Purpose Amplitude based respiratory gating is known to capture the extent of respiratory motion (RM) accurately but results in residual motion in the presence of respiratory hysteresis. In our previous study, we proposed and developed a novel approach to account for respiratory hysteresis by applying the Bouc-Wen (BW) model of hysteresis to external surrogate signals of anterior / posterior motion of the abdomen and chest with respiration. In this work using simulated and clinical SPECT myocardial perfusion imaging (MPI) studies, we investigate the effects of respiratory hysteresis and evaluate the benefit of correcting it using the proposed BW model in comparison with the abdomen signal typically employed clinically. Methods The MRI navigator data acquired in free breathing human volunteers were used in the specially modified 4-D NCAT phantoms to allow simulating three types of respiratory patterns: monotonic, mild-hysteresis, and strong-hysteresis with normal myocardial uptake, and perfusion defects in the anterior, lateral, inferior, and septal locations of the mid-ventricular wall. Clinical scans were performed using a 99mTc-Sestamibi MPI protocol while recording respiratory signals from thoracic and abdomen regions using a Visual Tracking System (VTS). The performance of the correction using the respiratory signals was assessed through polar map analysis in phantom and ten clinical studies selected on the basis of having substantial RM. Results In phantom studies, simulations illustrating normal myocardial uptake showed significant differences (p<0.001) in the uniformity of the polar maps between the RM uncorrected and corrected. No significant differences were seen in the polar map uniformity across the RM corrections. Studies simulating perfusion defects showed significantly decreased errors (p<0.001) in defect severity and extent for the RM corrected compared to the uncorrected. Only for the strong-hysteretic pattern was there a significant difference (p<0.001) among the RM corrections. The errors in defect severity and extent for the RM correction using abdomen signal were significantly higher compared to that of the BW (severity=-4.0%, p<0.001; extent=-65.4%, p<0.01) and chest (severity=-4.1%, p<0.001; extent=-52.5%, p<0.01) signals. In clinical studies, the quantitative analysis of the polar maps demonstrated qualitative and quantitative but not statistically significant differences (p=0.73) between the correction methods that used the BW signal and the abdominal signal. Conclusions This study shows that hysteresis in respiration affects the extent of residual motion left in the RM binned data, which can impact wall uniformity and the visualization of defects. Thus there appears to be the potential for improved accuracy in reconstruction in the presence of hysteretic RM with the BW model method providing a possible step in the direction of improvement.