Automated movement correction for dynamic PET/CT images: evaluation with phantom and patient data (original) (raw)
Related papers
Medical Physics, 2013
Purpose: Motion correction in PET has become more important as system resolution has improved. The purpose of this study was to evaluate the accuracy of event-by-event and frame-based MC methods in human brain PET imaging. Methods: Motion compensated image reconstructions were performed with static and dynamic simulated high resolution research tomograph data with frame-based image reconstructions, using a range of measured human head motion data. Image intensities in high-contrast regions of interest (ROI) and parameter estimates in tracer kinetic models were assessed to evaluate the accuracy of the motion correction methods. Results: Given accurate motion data, event-by-event motion correction can reliably correct for head motions. The average ROI intensities and the kinetic parameter estimates V T and BP ND were comparable to the true values. The frame-based motion correction methods with correctly aligned attenuation map using the average of externally acquired motion data or motion data derived from image registration give comparable quantitative accuracy. For large intraframe (>5 mm) motion, the framebased methods produced ∼9% bias in ROI intensities, ∼5% in V T , and ∼10% in BP ND estimates. In addition, in real studies that lack a ground truth, the normalized weighted residual sum of squared difference is a potential figure-of-merit to evaluate the accuracy of motion correction methods. Conclusions: The authors conclude that frame-based motion correction methods are accurate when the intraframe motion is less than 5 mm and when the attenuation map is accurately aligned. Given accurate motion data, event-by-event motion correction can reliably correct for head motion in human brain PET studies.
Patient motion can significantly hamper the highresolution imaging capability of PET scanners. Frame-acquired (dynamic) PET images are degraded by inter-frame and intraframe motion artifacts that can degrade the quantitative and qualitative analysis of acquired PET data. This calls for appropriate motion-correction techniques that can considerably reduce (ideally eliminate) inter-frame and intra-frame motion artifacts in dynamic PET images.
Many authors have reported the importance of motion correction (MC) for PET. Patient motion during scanning disturbs kinetic analysis and degrades resolution. In addition, using misaligned transmission for attenuation and scatter correction may produce regional quantification bias in the reconstructed emission images. The purpose of this work was the development of quality control (QC) methods for MC procedures based on external motion tracking (EMT) for human scanning using an optical motion tracking system. Methods: Two scans with minor motion and 5 with major motion (as reported by the optical motion tracking system) were selected from 18 F-FDG scans acquired on a PET scanner. The motion was measured as the maximum displacement of the markers attached to the subject's head and was considered to be major if larger than 4 mm and minor if less than 2 mm. After allowing a 40-to 60-min uptake time after tracer injection, we acquired a 6-min transmission scan, followed by a 40-min emission list-mode scan. Each emission list-mode dataset was divided into 8 frames of 5 min. The reconstructed time-framed images were aligned to a selected reference frame using either EMT or the AIR (automated image registration) software. The following 3 QC methods were used to evaluate the EMT and AIR MC: a method using the ratio between 2 regions of interest with gray matter voxels (GM) and white matter voxels (WM), called GM/WM; mutual information; and cross correlation. Results: The results of the 3 QC methods were in agreement with one another and with a visual subjective inspection of the image data. Before MC, the QC method measures varied significantly in scans with major motion and displayed limited variations on scans with minor motion. The variation was significantly reduced and measures improved after MC with AIR, whereas EMT MC performed less well. Conclusion: The 3 presented QC methods produced similar results and are useful for evaluating tracer-independent external-tracking motion-correction methods for human brain scans.
MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner
Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2011
Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MRI data can be used for motion tracking. In this work, a novel algorithm for data processing and rigid-body motion correction (MC) for the MRI-compatible BrainPET prototype scanner is described, and proof-of-principle phantom and human studies are presented. To account for motion, the PET prompt and random coincidences and sensitivity data for postnormalization were processed in the line-of-response (LOR) space according to the MRI-derived motion estimates. The processing time on the standard BrainPET workstation is approximately 16 s for each motion estimate. After rebinning in the sinogram space, the motion corrected data were summed, and the PET volume was reconstructed using the attenuation and scatter sinograms in the reference position. The accuracy...
A scale space theory based motion correction approach for dynamic PET brain imaging studies
Frontiers in Physics
Aim/Introduction: Patient head motion poses a significant challenge when performing dynamic PET brain studies. In response, we developed a fast, robust, easily implementable and tracer-independent brain motion correction technique that facilitates accurate alignment of dynamic PET images.Materials and methods: Correction of head motion was performed using motion vectors derived by the application of Gaussian scale-space theory. A multiscale pyramid consisting of three different resolution levels (1/4x: coarse, 1/2x: medium, and 1x: fine) was applied to all image frames (37 frames, framing of 12 × 10s, 15 × 30s, 10 × 300s) of the dynamic PET sequence. Frame image alignment was initially performed at the coarse scale, which was subsequently used to initialise coregistration at the next finer scale, a process repeated until the finest possible scale, that is, the original resolution was reached. In addition, as tracer distribution changes during the dynamic frame sequence, a mutual inf...
Off-line motion correction methods for multi-frame PET data
European Journal of Nuclear Medicine and Molecular Imaging, 2009
Purpose Patient motion during PET acquisition may affect measured time-activity curves, thereby reducing accuracy of tracer kinetic analyses. The aim of the present study was to evaluate different off-line frame-by-frame methods to correct patient motion, which is of particular interest when no optical motion tracking system is available or when older data sets have to be reanalysed. Methods Four different motion correction methods were evaluated. In the first method attenuation-corrected frames were realigned with the summed image of the first 3 min. The second method was identical, except that nonattenuation-corrected images were used. In the third and fourth methods non-attenuation-corrected images were realigned with standard and cupped transmission images, respectively. Two simulation studies were performed, based on [ 11 C]flumazenil and (R)-[ 11 C]PK11195 data sets, respectively. For both simulation studies different types (rotational, translational) and degrees of motion were added. Simulated PET scans were corrected for motion using all correction methods. The optimal method derived from these simulation studies was used to evaluate two (one with and one without visible movement) clinical data sets of [ 11 C]flumazenil, (R)-[ 11 C]PK11195 and [ 11 C]PIB. For these clinical data sets, the volume of distribution (V T ) was derived using Logan analysis and values were compared before and after motion correction. Results For both [ 11 C]flumazenil and (R)-[ 11 C]PK11195 simulation studies, optimal results were obtained when realignment was based on non-attenuation-corrected images. For the clinical data sets motion disappeared visually after motion correction. Regional differences of up to 433% in V T before and after motion correction were found for scans with visible movement. On the other hand, when no visual motion was present in the original data set, overall differences in V T before and after motion correction were <1.5±1.3%. Conclusion Frame-by-frame motion correction using nonattenuation-corrected images improves the accuracy of tracer kinetic analysis compared to non-motion-corrected data.
EJNMMI Physics
Background Due to comparatively long measurement times in simultaneous positron emission tomography and magnetic resonance (PET/MR) imaging, patient movement during the measurement can be challenging. This leads to artifacts which have a negative impact on the visual assessment and quantitative validity of the image data and, in the worst case, can lead to misinterpretations. Simultaneous PET/MR systems allow the MR-based registration of movements and enable correction of the PET data. To assess the effectiveness of motion correction methods, it is necessary to carry out measurements on phantoms that are moved in a reproducible way. This study explores the possibility of using such a phantom-based setup to evaluate motion correction strategies in PET/MR of the human head. Method An MR-compatible robotic system was used to generate rigid movements of a head-like phantom. Different tools, either from the manufacturer or open-source software, were used to estimate and correct for motio...
Motion correction of multi-frame PET data in neuroreceptor mapping: Simulation based validation
Neuroimage, 2009
Patient motion during positron emission tomography scanning can affect the accuracy of the data analysis in two ways: 1) movement occurring during emission data acquisition alters the time activity curves (TACs), measured at a voxel or region of interest (ROI), and hence introduces errors in the parameter estimates derived from kinetic modeling; 2) emission-transmission mismatches introduce errors during attenuation and scatter correction, and hence in the radioactivity distribution estimates for each time frame of the scan. With the aim of designing an algorithm-based frame realignment method, we first conducted investigations that aimed at optimizing the parameters of a coregistration method, such as the choice of the target volume and the similarity criterion. Based on these results we designed a novel frame realignment strategy in a multi-step algorithm using uncorrected reconstructed images, cross-correlation similarity criteria for the determination of inter-frame motion parameters and emission-transmission mismatch for each frame. Features and validation results are reported here based on a multi-subject simulated [ 11 C]raclopride dynamic PET scan database incorporating intra-frame movements of various magnitudes and with various times of occurrence. Performances of the proposed algorithm were evaluated at regional and voxel-based level for binding potential parametric images.
Correction of head movement on PET studies: comparison of methods
Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2006
Head movement presents a continuing problem in PET studies. Head restraint minimizes movement but is unreliable, resulting in the need to develop alternative strategies. These include frame-by-frame (FBF) realignment or use of motion tracking (MT) during the scan to realign PET acquisition data. Here we present a comparative analysis of these 2 methods of motion correction. Eight volunteers were examined at rest using (11)C-raclopride PET with the radioligand administered as a bolus followed by constant infusion to achieve steady state. Binding potential (BP) was estimated using the ratio method during 2 periods of the scan at steady state. Head movement was compensated by using coregistration between frames (FBF) and 3 methods using MT measurements of head position acquired with a commercially available optical tracking system. All methods of realignment improved test-retest reliability and noise characteristics of the raw data, with important consequences for the power to detect s...