Joseph E. McNamara

A flexible multicamera visual‐tracking system for detecting and correcting motion‐induced artifacts in cardiac SPECT slices

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 (VTS) which utilizes near-infrared (NIR) 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 (RB) 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 motion-correction 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 correction or the vendor-supplied software the authors investigated in clinical practice.

Estimation of Rigid-Body and Respiratory Motion of the Heart From Marker-Tracking Data for SPECT Motion Correction

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.

An Assessment of a Low-Cost Visual Tracking System (VTS) to Detect and Compensate for Patient Motion During SPECT

Patient motion is inevitable in SPECT and PET due to the lengthy period of time patients are imaged and patient motion can degrade diagnostic accuracy. The goal of our studies is to perfect a methodology for tracking and correcting patient motion when it occurs. In this paper we report on enhancements to the calibration, camera stability, accuracy of motion tracking, and temporal synchronization of a low-cost visual tracking system (VTS) we are developing. The purpose of the VTS is to track the motion of retro-reflective markers on stretchy bands wrapped about the chest and abdomen of patients. We have improved the accuracy of 3D spatial calibration by using a MATLAB optical camera calibration package with a planar calibration pattern. This allowed us to determine the intrinsic and extrinsic parameters for stereo-imaging with our CCD cameras. Locations in the VTS coordinate system are transformed to the SPECT coordinate system by a VTS/SPECT mapping using a phantom of 7 retro-reflective spheres each filled with a drop of Tc99m. We switched from pan, tilt and zoom (PTZ) network cameras to fixed network cameras to reduce the amount of camera drift. The improved stability was verified by tracking the positions of fixed retro-reflective markers on a wall. The ability of our VTS to track movement, on average, with sub-millimeter and sub-degree accuracy was established with the 7-sphere phantom for 1 cm vertical and axial steps as well as for an arbitrary rotation and translation. The difference in the time of optical image acquisition as decoded from the image headers relative to synchronization signals sent to the SPECT system was used to establish temporal synchrony between optical and list-mode SPECT acquisition. Two experiments showed better than 100 ms agreement between VTS and SPECT observed motion for three axial translations. We were able to track 3 reflective markers on an anthropomorphic phantom with a precision that allowed us to correct motion such that no loss in visual quality was noted in motion corrected slices relative to motion free slices.

Estimation of rigid-body and respiratory motion of the heart for SPECT motion correction

Motion of patients undergoing cardiac SPECT perfusion imaging causes artifacts in the acquired images which may lead to difficulty in interpretation. Our work investigates the technique of obtaining patient motion estimates from retro-reflective markers on stretchy bands wrapped around the chest and abdomen of subjects when they are imaged. Motion signals obtained from the markers consist of at least two components, rigid body motion (RBM) and respiratory motion (RM). In this paper an improved method of separation of the marker motion signals into the two components, RBM and RM is reported. Motion studies of rigid-tool, volunteers and patients are used to evaluate the method and preliminary estimates of the motion of the heart due to patient movement and respiration are obtained.

Quantitative Study of Rigid-Body and Respiratory Motion of Patients Undergoing Stress and Rest Cardiac SPECT Imaging

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 (> 4 min.) 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.

Impact of respiratory motion on the detection of small pulmonary nodules in SPECT imaging

The objective of this investigation is to determine the impact of respiratory motion on the detection of small solitary pulmonary nodules (SPN) in single photon emission computed tomographic (SPECT) imaging. We have previously modeled the respiratory motion of SPN based on the change of location of anatomic structures within the lungs identified on breath-held CT images of volunteers acquired at two different stages of respiration. This information on respiratory motion within the lungs was combined with the end-expiration and time-averaged NCAT phantoms to allow the creation of source and attenuation maps for the normal background distribution of Tc-99m NeoTect. With the source and attenuation distribution thus defined, the SIMIND Monte Carlo program was used to produce SPECT projection data for the normal background and separately for each of 150 end-expiration and time-averaged simulated 1.0 cm tumors. Normal and tumor SPECT projection sets each containing one lesion were combined with a clinically realistic noise level and counts. These were reconstructed with RBI-EM using 1) no correction (NC), 2) attenuation correction (AC), 3) detector response correction (RC), and 4) attenuation correction, detector response correction, and scatter correction (ACRCSC). The post-reconstruction parameters of number of iterations and 3-D Gaussian filtering were optimized by human- observer studies. Comparison of lesion detection by human- observer LROC studies reveals that respiratory motion degrades tumor detection for all four reconstruction strategies, and that the magnitude of this effect is greatest for NC and RC, and least for AC RC SC. Additionally, the AC RC SC strategy results in the best detection of lesions.

Motion capture of chest and abdominal markers using a flexible multi-camera motion-tracking system for correcting motion-induced artifacts in cardiac SPECT

Patient motion is inevitable in SPECT and PET due to the lengthy period of time patients are imaged. Motion of only 2 pixels (~13 mm) is enough to create minor to moderate defects in SPECT studies. The use of external tracking devices provides additional information independent of SPECT data that should result in a more robust correction. We have been investigating the use of stereo-imaging of retro-reflective markers on stretchy bands wrapped about the chest and abdomen of patients to provide 6-DOF tracking of the patient during cardiac SPECT. Herein we summarize the performance of a motion-capture system (Vicon MX) which utilizes 5 near-infrared (NIR) cameras to track markers via stereo-imaging. Tracking with the 5 cameras is integrated such that only 2 of the 5 camera views are required, at any instant, to track a given marker in 3D. The ability of the Vicon system to track 6 DOF motion with sub- millimeter and sub-degree accuracy was established with a Tc99m labeled 7-sphere phantom. We also established temporal synchronization between motion-tracking data and list-mode SPECT acquisitions. In addition, we were able to track 3 retro-reflective markers on an anthropomorphic phantom with a precision that allowed us to correct motion such that no loss in visual quality was noted in motion-corrected images relative to motion-free images. Finally with months of clinical usage of the system tracking chest and abdomen markers, we have looked at various combinations of cameras to determine optimal placement and number required for robust tracking in our clinic.

MRI based assessment of the extent to which stereo-tracking of markers on the chest can predict motion of the heart

We have developed a visual-tracking-system (VTS) which uses stereo-imaging to track the motion of markers on patients during cardiac SPECT imaging with the goal of using the tracked motion to correct for patient motion. The aim of this study is to determine using MRI in volunteers if the rigid-body-motion (RBM) model can be used to predict the motion of the heart within the chest from the motion of markers on the surface of the chest. Our methodology for investigating body-motion separate from the influence of respiration is to have the volunteer hold their breath during the acquisition of a sequence of 2 sets of EKG-triggered MRI sagittal slices covering the heart, the first set pre-motion and the second post-motion. We link the acquisition of these studies such that this process takes ∼ 45 seconds from the initiation of the first acquisition till the volunteer is given the instruction to resume breathing. An analysis of the combined motion of the individual markers on the chest is used to obtain an estimate of the six-degree-of-freedom (6DOF) RBM motion of the volunteer. The motion of the heart within the slices is estimated by semi-automatic 3D segmentation of the heart region in the second set of slices and subsequent registration of this region to the first set of slices. Studies in which the volunteer did not intentionally move between the 2 acquisitions were used to establish a baseline for agreement between the 2 methods of motion estimation for small motions. The agreement between the VTS and MRI estimates of motion was good in this “no-motion” case with a maximum difference of ≪ 5 mm between the 2 for any translation component, and ≪2 deg for any rotational component. With body translations such as an axial-slide which might be expected to approximate RBM, the maximum difference in any translation estimate was also good being ≪ 6 mm, and the maximum rotational difference was ≪ 2.5 deg. Application of the VTS to correct non-RBM such as a counter-clock-wise (CCW) twist at the shoulders with the hips fixed, decreased the magnitude of the misalignment caused by motion but not to the same extent as for the previous classes of motion. The maximum differences for this class of motions was ≪11 mm for translation and ≪ 4.5 deg for angular. Thus use of the RBM model with VTS predictions of heart motion for use in motion correction during reconstruction should decrease the extent of artifacts for the types of patient motion studied, but less so for those which are better modeled as non-RBM.

Pattern independent deformation estimation illustrated by MRI

Patient motion during SPECT imaging has been shown to produce artifacts. Our previous work has corrected for patient motion using an optical imaging system to detect retro-reflective markers on the patient’s surface. This paper makes two contributions to this work: 1) We introduce an algorithm that allows an arbitrary marker pattern and gives technicians freedom on where to place the markers, and 2) We use MRI data to validate the estimation of patient motion with our improved algorithm. The goal is to show that estimation of volume motion inside patients is consistent with interior motion observed by MRI.

Quantitative study of rigid-body and respiratory motion of patients undergoing stress and rest cardiac SPECT imaging

In our previous work we investigated the technique of obtaining patient motion estimates from retro-reflective markers on stretchy bands wrapped around the chest and abdomen of patients undergoing cardiac SPECT perfusion imaging [1]. Motion signals obtained from the markers were separated into two components, body motion (BM) and respiratory motion (RM). In this paper we studied the frequency of occurrence, the time and the extent of estimated body motion of patients, and the extent of respiratory motion. Additionally, studies were grouped by Stress or Rest imaging to determine statistically significant differences in respiratory and body motion. Based on 80 studies, with 40 pairs of Stress and Rest motion data, we found 39% of studies containing 3-6 mm and 10% containing more than 6 mm of body motion during emission imaging. About 26% of the studies contained body motion more than 3 mm during transmission imaging. In 21% of the studies, large respiratory baseline drift of more than 6 mm was observed. Stress and Rest studies showed significant differences in body motion and respiratory motion, all of which were associated with change in respiration due to stress.