Patient motion is inevitable in SPECT and PET due to the lengthy period of time patients are imaged. The authors hypothesized that the use of external-tracking devices which provide additional information on patient motion independent of SPECT data could be employed to provide a more robust correction than obtainable from data-driven methods. Therefore, the authors investigated the Vicon MX visual-tracking system ͑VTS͒ which utilizes near-infrared ͑NIR͒ cameras to stereo-image small retroreflective markers on stretchy bands wrapped about the chest and abdomen of patients during cardiac SPECT. The chest markers are used to provide an estimate of the rigid-body ͑RB͒ motion of the heart. The abdomen markers are used to provide a signal used to bin list-mode acquisitions as part of correction of respiratory motion of the heart. The system is flexible in that the layout of the cameras can be designed to facilitate marker viewing. The system also automatically adapts marker tracking to employ all of the cameras visualizing a marker at any instant, with visualization by any two being sufficient for stereo-tracking. Herein the ability of this VTS to track motion with submillimeter and subdegree accuracy is established through studies comparing the motion of Tc-99m containing markers as assessed via stereo-tracking and from SPECT reconstructions. The temporal synchronization between motion-tracking data and timing marks embedded in list-mode SPECT acquisitions is shown to agree within 100 ms. In addition, motion artifacts were considerably reduced in reconstructed SPECT slices of an anthropomorphic phantom by employing within iterative reconstruction the motion-tracking information from markers attached to the phantom. The authors assessed the number and placement of NIR cameras required for robust motion tracking of markers during clinical imaging in 77 SPECT patients. They determined that they were able to track without loss during the entire period of SPECT and transmission imaging at least three of the four markers on the chest and one on the abdomen bands 94% and 92% of the time, respectively. The ability of the VTS to correct motion clinically is illustrated for ten patients who volunteered to undergo repeat-rest imaging with the original-rest SPECT study serving as the standard against which to compare the success of correction. Comparison of short-axis slices shows that VTS-based motion correction provides better agreement with the original-rest-imaging slices than either no correction or the vendor-supplied software for motion correction on our SPECT system. Comparison of polar maps shows that VTS-based motioncorrection results in less numerical difference on average in the segments of the polar maps between the original-rest study and the second-rest study than the other two strategies. The difference was statistically significant for the comparison between VTS-based and clinical vendor-supplied software correction. Taken together, these findings suggest that VTS-based motion correction is superior to either no...

Motion of patients undergoing cardiac SPECT perfusion imaging causes artifacts in the acquired images which may lead to difficulty in interpretation. Our work investigates a technique of obtaining patient motion estimates from retro-reflective markers on stretchy bands wrapped around the chest and abdomen of patients being imaged clinically. Motion signals obtained from the markers consist of at least two components, body motion (BM) and periodic motion (PM) due to respiration. We present a method for separating these components from the motion-tracking data of each marker, and then report a method for combining the BM estimated from chest markers to estimate the 6-degree-of-freedom (6-DOF) rigid-body motion (RBM) of the heart. Motion studies of volunteers and patients are used to evaluate the methods. Illustrative examples of the motion of the heart due to patient body movement and respiration (upward creep) are presented and compared to estimates of the motion of the heart obtained directly from SPECT data. Our motion-tracking method is seen to give reasonable agreement with the motion-estimates from the SPECT data while being considerably less noisy.

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

We report patient motion in 110 Tl-201 cardiac perfusion SPECT studies in 66 patients. The imaging consisted of emission followed by sequential transmission imaging during which motion tracking with a visual tracking system (VTS) was performed. We investigated the extent, time, and frequency of respiratory and rigid-body motion in these patients. We also determined whether the motion occurred gradually or in sudden jumps, whether it was sustained, and if it occurred along one or more axes predominantly. We then studied the differences in respiratory and body motion (BM), if any, between stress versus rest imaging groups, male versus female subjects, and exercise versus pharmacological stress groups. We found that 23% of the studies had sustained motion (> 4min.) of between 3–6 mm, and 5% had sustained motion larger than 6 mm during emission imaging. In terms of respiratory motion, 13% showed a downward trend of the respiratory baseline of more than 6 mm during emission imaging. Also, in 9% of the studies, the average position of patients was displaced by more than 3 mm between emission and transmission imaging phases. Both of these motions may lead to misalignment of the attenuation map. In hypothesis testing of grouped studies, it was determined that stress and rest imaging did not show any significant differences in body motion but did in respiratory motion associated with a change in respiration following stress. Exercise-stress studies showed a larger extent of respiratory motion than the pharmacologically induced stress studies. Significant differences in body and respiratory motion of male and female groups were also observed. A visual assessment of the reconstructed slices in the studies with measured motion was made to investigate the impact of the motion. Illustrative example studies are included.

Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is not susceptible to motion introduced between CT and PET acquisitions. Conclusions: The authors have shown that they can estimate motion for frames with time intervals as short as 5 s using nonattenuation corrected reconstructed FDG PET brain images. Intraframe motion in 60-s frames causes degradation of accuracy to about 2 mm based on the motion type. C 2016 American Association of Physicists in Medicine. [http://dx