Respiratory Motion Correction Research Articles

0305: A new turn in SPECT myocardial perfusion imaging: data-driven cardiac gating is now possible with the new generation CZT SPECT Discovery NM 530c

We previously developed a data-driven (DD) respiratory-motion (RM) correction method for conventional SPECT gamma-cameras (REGAT) and adapted it to the new CZT camera (Discovery NM 530c). We recently reported that RM correction with REGAT applied to CZT myocardial perfusion SPECT imaging (MPI) is clinically feasible and impacts substantially myocardial perfusion defects. In this evaluation, we study whether REGAT applied to MPI (Discovery NM 530c) is capable of generating a data-driven (DD) cardiac gating signal allowing the generation of valid global left ventricular (LV) function parameters (EDV: end diastolic volume; ESV: end systolic volume; EF: ejection fraction). Were included 7 patients addressed for stress/rest MPI. All patients had prone stress MPI (2 MBq/Kg 99mTc-Tetrofosmin) and rest MPI 3-hours later (6 MBq/Kg). All acquisitions were made on Discovery NM 530c. Each acquisition was processed with REGAT to generate a dynamic SPECT acquisition study. The latter was processed to generate a DD cardiac gating signal and generate a mean DD cardiac GSPECT study (GSPECT-DD). In parallel, a mean ECG cardiac GSPECT study was generated using the ECG trigger signal provided by traditional ECG monitor (GSPECT-M). The 2 generated cardiac GSPECT studies were reconstructed on Xeleris workstation and processed with Emory Cardiac Toolbox (ECT). LV EDV, ESV and EF were compared between cardiac GSPECT-DD and GSPECT-M. Stress LV EVD, ESV, and EF were 91±24mL, 29±13ml, and 68±10% vs 95±23ml, 29±12ml, and 70±11% with GSPECT-DD vs GSPECTM respectively (P:NS). Rest LV EDV, ESV, and EF were 97±21ml, 32±10ml, and 67±6% vs 101±21ml, 31±10ml, and 69±6% with GSPECT-DD vs GSPECT-M respectively (P:NS). Data-driven cardiac gating of MPI with Discovery NM 530c processed with REGAT is clinically feasible. It provides LV global systolic function parameters similar to those provided by the traditional clinically used ECG monitor gating.

Nonlinear myocardial perfusion imaging with motion corrected reconstruction: validation via quantitative flow mapping

Background Myocardial perfusion imaging typically uses saturation recovery to generate T1 contrast during the Gd passage. Imaging protocols lead to a tradeoff between spatial/ temporal resolution, myocardial coverage, and SNR. To improve resolution while maintaining the image quality we propose a nonlinear iterative reconstruction. This method explicitly integrates respiratory motion correction into the reconstruction to permit spatio-temporal regularization in the presence of motion. Unlike most k-t methods, the motion corrected images are directly output. In this way, complete free-breathing acquisition is achieved. Nonlinear iterative reconstruction is difficult to characterize since implicit filtering resulting from regularization is signal dependent. We propose to validate the proposed method by comparing quantitative myocardial blood flow (MBF) against linear reconstruction. Methods

Image-based 3D non-rigid respiratory motion correction for free-breathing thoracic MR angiography

Background Respiratory motion compensation is usually required in free-breathing thoracic MR imaging applications to remove the motion induced blur and ghosting artifacts. Most respiratory motion compensation techniques are based on gating in which data is acquired only at one respiratory state (RS) and therefore suffer from extended yet unpredictable scan time. Other techniques compensate for motion by correcting the phase of motion corrupted k-space data so that data acquired in multiple respiratory states can be used in reconstruction for improved scan efficiency. However, these methods are often limited to correcting rigid-body motion and thus not suitable for thoracic imaging with large field-ofview. In this work, we propose a technical strategy of correcting 3D non-rigid motion and apply it to ferumoxytol enhanced free-breathing thoracic MRA.

Quantitative Evaluation of PET Respiratory Motion Correction Using MR Derived Simulated Data

The impact of respiratory motion correction on quantitative accuracy in PET imaging is evaluated using simulations for variable patient specific characteristics such as tumor uptake and respiratory pattern. Respiratory patterns from real patients were acquired, with long quiescent motion periods (type-1) as commonly observed in most patients and with long-term amplitude variability as is expected under conditions of difficult breathing (type-2). The respiratory patterns were combined with an MR-derived motion model to simulate real-time 4-D PET-MR datasets. Lung and liver tumors were simulated with diameters of 10 and 12 mm and tumor-to-background ratio ranging from 3:1 to 6:1. Projection data for 6- and 3-mm PET resolution were generated for the Philips Gemini scanner and reconstructed without and with motion correction using OSEM (2 iterations, 23 subsets). Motion correction was incorporated into the reconstruction process based on MR-derived motion fields. Tumor peak standardized uptake values (SUVpeak) were calculated from 30 noise realizations. Respiratory motion correction improves the quantitative performance with the greatest benefit observed for patients of breathing type-2. For breathing type-1 after applying motion correction, SUVpeak of 12-mm liver tumor with 6:1 contrast was increased by 46% for a current PET resolution (i.e., 6 mm) and by 47% for a higher PET resolution (i.e., 3 mm). Furthermore, the results of this study indicate that the benefit of higher scanner resolution is small unless motion correction is applied. In particular, for large liver tumor (12 mm) with low contrast (3:1) after motion correction, the SUVpeak was increased by 34% for 6-mm resolution and by 50% for a higher PET resolution (i.e., 3-mm resolution. This investigation indicates that there is a high impact of respiratory motion correction on tumor quantitative accuracy and that motion correction is important in order to benefit from the increased resolution of future PET scanners.

Non-rigid dual respiratory and cardiac motion correction methods after, during, and before image reconstruction for 4D cardiac PET

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.

Influence of respiratory motion correction on quantification of myocardial perfusion SPECT

BackgroundRespiratory-related cardiac motion could have considerable effects on myocardial perfusion imaging, leading to misinterpretation of the images. In this study, we examined the influence of respiratory correction on ECG-gated myocardial perfusion SPECT (RC-GSPECT) concerning regional myocardial perfusion and function. Materials and MethodsUsing the NCAT phantom, a typical torso phantom was generated. SimSET, a Monte Carlo simulator, was used to image the photon emerging from the phantom. Twenty-six patients underwent a 2-day stress-rest ECG-gated myocardial perfusion SPECT (GSPECT) imaging. A separate study was also performed by simultaneous respiratory and cardiac triggering with the real-time position management (RPM) for respiratory correction (RC). ResultsIn simulation study, count density in the inferior and inferoseptal walls increased in the lower bin of the respiratory cycle. On the other hand, there was a higher correlation between RC-GSPECT and echocardiography for left ventricular ejection fraction (LVEF) (r = 0.95, P < .01 vs r = 0.88, P < .01 for GSPECT). ConclusionWe proposed a new approach for respiratory and cardiac-gated SPECT to eliminate respiratory motion artifacts. RC-GSPECT is a feasible method in MPI studies and may play an important role to improve the quality of MPI images, particularly in the inferior wall.

New approach for simultaneous respiratory and cardiac motion correction in cardiac PET (NAMC-CPET)

Respiratory and cardiac motions are inevitable during the relatively long acquisition time of cardiac positron emission tomography (PET) scan. The correction of the resultant motion blur has become a significant challenge due to recent spatial resolution improvement of the PET scanners. The majority of current motion compensation algorithms are based on gating as a primary step. A new approach based on temporal basis functions is developed to correct respiratory and cardiac motion simultaneously in cardiac PET within the normal scanning time (NAMC-CPET). Simulation and experimental studies are conducted to evaluate and validate the final outputs in comparison to the existing gating methods. A dynamic digital phantom is used to simulate realistic human thorax and abdomen with respiratory and cardiac motions. GATE simulation was run at China National Grid Center to obtain realistic PET data in a reasonable time. Moreover, Tibet minipig experiments were conducted using a preclinical small animal PET scanner developed at HUST to validate the performance of the NAMC-CPET in real data. The results reveal that NAMC-CPET outperformed the existing gating methods (respiratory, cardiac, and dual) in cardiac imaging in term of noise reduction and contrast, especially in short acquisition duration. NAMC-CPET obtained better results in the conducted experiments in terms of contrast and the visibility of the heart. In contrast, the dual gating failed to obtain valuable images in the normal scan time due to the low 18F-FDG uptake. NAMC-CPET is advantageous in the low-statistic situation. The results are promising with great potential implications in cardiac PET imaging in terms of the radioactive dose and scan time reduction.

Respiratory motion correction of PET using MR-constrained PET-PET registration.

BackgroundRespiratory motion in positron emission tomography (PET) is an unavoidable source of error in the measurement of tracer uptake, lesion position and lesion size. The introduction of PET-MR dual modality scanners opens a new avenue for addressing this issue. Motion models offer a way to estimate motion using a reduced number of parameters. This can be beneficial for estimating motion from PET, which can otherwise be difficult due to the high level of noise of the data.MethodWe propose a novel technique that makes use of a respiratory motion model, formed from initial MR scan data. The motion model is used to constrain PET-PET registrations between a reference PET gate and the gates to be corrected. For evaluation, PET with added FDG-avid lesions was simulated from real, segmented, ultrashort echo time MR data obtained from four volunteers. Respiratory motion was included in the simulations using motion fields derived from real dynamic 3D MR volumes obtained from the same volunteers.ResultsPerformance was compared to an MR-derived motion model driven method (which requires constant use of the MR scanner) and to unconstrained PET-PET registration of the PET gates. Without motion correction, a median drop in uncorrected lesion {mathrm {SUV}}_{mathrm {peak}} intensity to 78.4 pm 18.6 ,,% and an increase in median head-foot lesion width, specified by a minimum bounding box, to 179 pm 63.7,, % was observed relative to the corresponding measures in motion-free simulations. The proposed method corrected these values to 86.9 pm 13.6,, % (p<0.001) and 100 pm 29.12,, % (p<0.001) respectively, with notably improved performance close to the diaphragm and in the liver. Median lesion displacement across all lesions was observed to be 6.6 pm 5.4,mathrm {mm} without motion correction, which was reduced to 3.5 pm 1.8,mathrm {mm} (p<0.001) with motion correction.DiscussionThis paper presents a novel technique for respiratory motion correction of PET data in PET-MR imaging. After an initial 30 second MR scan, the proposed technique does not require use of the MR scanner for motion correction purposes, making it suitable for MR-intensive studies or sequential PET-MR. The accuracy of the proposed technique was similar to both comparative methods, but robustness was improved compared to the PET-PET technique, particularly in regions with higher noise such as the liver.

Local respiratory motion correction for PET/CT imaging: Application to lung cancer.

Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications. Both simulated (NURBS based 4D cardiac-torso phantom) and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions. Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the nonrigid deformation model in LRMC led to over an order of magnitude gain in computational efficiency of the correction relative to the application of the deformable model to the whole FOV. The results of this study support the use of LMRC as a flexible and efficient correction approach for respiratory motion effects for single lesions in the thoracic area.

Effect of Non-Alignment/Alignment of Attenuation Map Without/With Emission Motion Correction in Cardiac SPECT/CT.

We investigate the differences without/with respiratory motion correction in apparent imaging agent localization induced in reconstructed emission images when the attenuation maps used for attenuation correction (from CT) are misaligned with the patient anatomy during emission imaging due to differences in respiratory state. We investigated use of attenuation maps acquired at different states of a 2 cm amplitude respiratory cycle (at end-expiration, at end-inspiration, the center map, the average transmission map, and a large breath-hold beyond range of respiration during emission imaging) to correct for attenuation in MLEM reconstruction for several anatomical variants of the NCAT phantom which included both with and without non-rigid motion between heart and sub-diaphragmatic regions (such as liver, kidneys etc). We tested these cases with and without emission motion correction and attenuation map alignment/non-alignment. For the NCAT default male anatomy the false count-reduction due to breathing was largely removed upon emission motion correction for the large majority of the cases. Exceptions (for the default male) were for the cases when using the large-breathhold end-inspiration map (TI_EXT), when we used the end-expiration (TE) map, and to a smaller extent, the end-inspiration map (TI). However moving the attenuation maps rigidly to align the heart region, reduced the remaining count-reduction artifacts. For the female patient count-reduction remained post motion correction using rigid map-alignment due to the breast soft-tissue misalignment. Quantitatively, after the transmission (rigid) alignment correction, the polar-map 17-segment RMS error with respect to the reference (motion-less case) reduced by 46.5% on average for the extreme breathhold case. The reductions were 40.8% for end-expiration map and 31.9% for end-inspiration cases on the average, comparable to the semi-ideal case where each state uses its own attenuation map for correction. Two main conclusions are that even rigid emission motion correction to rigidly align the heart region to the attenuation map helps in average cases to reduce the count-reduction artifacts and secondly, within the limits of the study (ex. rigid correction) when there is lung tissue inferior to the heart as with the NCAT phantom employed in this study endexpiration maps (TE) might best be avoided as they may create more artifacts than the end-inspiration (TI) maps.

Is there an optimal respiratory reference position for self-navigated whole-heart coronary MR angiography?

To test the direct influence of the reference respiratory position on image quality for self-navigated whole-heart coronary MRI. Self-navigated whole-heart coronary MRI was performed in 11 healthy adult subjects. Respiratory motion was compensated for by using three different respiratory reference positions of the heart: end-inspiratory, end-expiratory, and the mean of the entire respiratory excursion. All datasets were reconstructed without motion compensation for comparison. Image quality was assessed in all reconstructions using signal-to-noise ratio (SNR) and contrst-to-noise ratio (CNR) measurements, as well as percentage vessel sharpness and visible length of the coronary arteries. While SNR and CNR remained close to constant in all reconstructions, a clear and significant improvement in vessel sharpness was identified in all motion corrected datasets with respect to their uncorrected counterpart (e.g., percentage sharpness of the proximal right coronary artery (RCA): 61.6 ± 8.2% for end-inspiration, 64.1 ± 10.7% for end-expiration, and 63.3 ± 7.0% for the mean respiratory position versus 55.0 ± 10.4 for the uncorrected datasets; P < 0.05). Among all motion corrected reconstructions, the use of an end-expiratory reference position most consistently provided the highest image quality. In particular, some of the improvements in vessel sharpness and length measured for end-expiration were statistically significant with respect to the reconstructions performed at end-inspiration (e.g., percentage sharpness of the proximal left anterior descending coronary: 58.2 ± 7.4% versus 55.8 ± 8.4%; P < 0.05; and visible length of the RCA: 125.7 ± 25.9 mm versus 114.4 ± 27.4 mm; P < 0.05). The use of end-expiration as a reference position for respiratory motion correction in free-breathing self-navigated whole heart coronary MRA significantly improves image quality. J

Three-dimensional heart locator and compressed sensing for whole-heart MR angiography.

We sought to develop a whole-heart magnetic resonance angiography technique with three-dimensional (3D) respiratory motion compensation and reduced scan time. A novel respiratory motion compensation method was implemented that acquires a 1D navigator (NAV) and a low-resolution 3D-image of the heart (3D-LOC) just before the angiography data. The central 10% of SSFP k-space was fully acquired using NAV-gating, and then 10% of peripheral k-space was randomly undersampled to complete the scan. Spatial registration of the 3D-LOC information was used to correct the central and peripheral k-space lines for the bulk respiratory motion in three dimensions, and then the remaining k-space data was estimated using compressed sensing (CS). Ten volunteers each underwent two angiography acquisitions with 1 mm(3) resolution: (i) conventional NAV with CS, and (ii) the new 3D-LOC with CS. Compared with conventional NAV, the new 3D-LOC with CS technique had a shorter scan time (4.8 ± 1.1 versus 6.3 ± 1.7 min; P < 0.001), better objective vessel sharpness for all three coronary arteries (P < 0.05), and no difference in subjective vessel sharpness for all three coronary arteries. Compared with conventional NAV with CS, acceleration and respiratory motion correction using 3D-LOC with CS reduces scan time and improves objective vessel sharpness.

Respiratory and cardiac motion correction in dual gated PET/MR imaging.

Respiratory and cardiac motion in PET/MR imaging leads to reduced quantitative and qualitative image accuracy. Correction methodologies involve the use of double gated acquisitions which lead to low signal-to-noise ratio (SNR) and to issues concerning the combination of cardiac and respiratory frames. The objective of this work is to use a generalized reconstruction by inversion of coupled systems (GRICS) approach, previously used for PET/MR respiratory motion correction, combined with a cardiac phase signal and a reconstruction incorporated PET motion correction approach in order to reconstruct motion free images from dual gated PET acquisitions. The GRICS method consists of formulating parallel MRI in the presence of patient motion as a coupled inverse problem. Its resolution, using a fixed-point method, allows the reconstructed image to be improved using a motion model constructed from the raw MR data and two respiratory belts. GRICS obtained respiratory displacements are interpolated using the cardiac phase derived from an ECG to model simultaneous cardiac and respiratory motion. Three different volunteer datasets (4DMR acquisitions) were used for evaluation. GATE was used to simulate 4DPET datasets corresponding to the acquired 4DMR images. Simulated data were subsequently binned using 16 cardiac phases (M1) vs diastole only (M2), in combination with 8 respiratory amplitude gates. Respiratory and cardiac motion corrected PET images using either M1 or M2 were compared to respiratory only corrected images and evaluated in terms of SNR and contrast improvement. Significant visual improvements were obtained when correcting simultaneously for respiratory and cardiac motion (using 16 cardiac phase or diastole only) compared to respiratory motion only compensation. Results were confirmed by an associated increased SNR and contrast. Results indicate that using GRICS is an efficient tool for respiratory and cardiac motion correction in dual gated PET/MR imaging.

An iterative approach to respiratory self-navigated whole-heart coronary MRA significantly improves image quality in a preliminary patient study.

In respiratory self-navigated coronary MRA, the selection of a reference position may have a direct effect on image quality. While end-expiration is commonly used as reference, it may be ill defined in cases of irregular breathing. Here, an iterative self-navigation approach that operates without a reference position was implemented and tested in healthy volunteers and patients. Data were acquired in 15 healthy volunteers and in 23 patients. Images obtained with end-expiratory self-navigation were compared with those obtained with the iterative approach that incorporates cross-correlation to iteratively minimize a global measure of respiratory displacement. Vessel sharpness, length, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were evaluated while differences in breathing patterns between the two sub-groups were assessed, too. Vessel sharpness and length were similar for both methods in healthy volunteers. In patients, a significant improvement in vessel sharpness and length was obtained using the iterative approach. SNR and CNR remained constant. While end-expiration was the most frequent respiratory phase in healthy volunteers (57.6 ± 16.2%), intermediate respiratory phases (43.4 ± 30.1%) were predominantly found in patients. An iterative approach to respiratory motion correction in self-navigation may lead to significant improvements in coronary MRA image quality in patients with a less consistent end-expiratory respiratory phase.

A dual-Kinect approach to determine torso surface motion for respiratory motion correction in PET.

Respiratory gating is commonly used to reduce blurring effects and attenuation correction artifacts in positron emission tomography (PET). Established clinically available methods that employ body-attached hardware for acquiring respiration signals rely on the assumption that external surface motion and internal organ motion are well correlated. In this paper, the authors present a markerless method comprising two Microsoft Kinects for determining the motion on the whole torso surface and aim to demonstrate its validity and usefulness-including the potential to study the external/internal correlation and to provide useful information for more advanced correction approaches. The data of two Kinects are used to calculate 3D representations of a patient's torso surface with high spatial coverage. Motion signals can be obtained for any position by tracking the mean distance to a virtual camera with a view perpendicular to the surrounding surface. The authors have conducted validation experiments including volunteers and a moving high-precision platform to verify the method's suitability for providing meaningful data. In addition, the authors employed it during clinical (18)F-FDG-PET scans and exemplarily analyzed the acquired data of ten cancer patients. External signals of abdominal and thoracic regions as well as data-driven signals were used for gating and compared with respect to detected displacement of present lesions. Additionally, the authors quantified signal similarities and time shifts by analyzing cross-correlation sequences. The authors' results suggest a Kinect depth resolution of approximately 1 mm at 75 cm distance. Accordingly, valid signals could be obtained for surface movements with small amplitudes in the range of only few millimeters. In this small sample of ten patients, the abdominal signals were better suited for gating the PET data than the thoracic signals and the correlation of data-driven signals was found to be stronger with abdominal signals than with thoracic signals (average Pearson correlation coefficients of 0.74 ± 0.17 and 0.45 ± 0.23, respectively). In all cases, except one, the abdominal respiratory motion preceded the thoracic motion-a maximum delay of approximately 600 ms was detected. The method provides motion information with sufficiently high spatial and temporal resolution. Thus, it enables meaningful analysis in the form of comparisons between amplitudes and phase shifts of signals from different regions. In combination with a large field-of-view, as given by combining the data of two Kinect cameras, it yields surface representations that might be useful in the context of motion correction and motion modeling.

Reconstruction-Incorporated Respiratory Motion Correction in Clinical Simultaneous PET/MR Imaging for Oncology Applications.

Simultaneous PET and MR imaging is a promising new technique allowing the fusion of functional (PET) and anatomic/functional (MR) information. In the thoracic-abdominal regions, respiratory motion is a major challenge leading to reduced quantitative and qualitative image accuracy. Correction methodologies include the use of gated frames that lead to low signal-to-noise ratio considering the associated low statistics. More advanced correction approaches, previously developed for PET/CT imaging, consist of either registering all the reconstructed gated frames to the reference frame or incorporating motion parameters into the iterative reconstruction process to produce a single motion-compensated PET image. The goal of this work was to compare these two—previously implemented in PET/CT—correction approaches within the context of PET/MR motion correction for oncology applications using clinical 4-dimensional PET/MR acquisitions. Two different correction approaches were evaluated comparing the incorporation of elastic transformations extracted from 4-dimensional MR imaging datasets during PET list-mode image reconstruction to a postreconstruction image-based approach. Eleven patient datasets acquired on a PET/MR system were used. T1-weighted 4D MR images were registered to the end-expiration image using a nonrigid B-spline registration algorithm to derive deformation matrices accounting for respiratory motion. The derived matrices were subsequently incorporated within a PET image reconstruction of the original emission list-mode data (reconstruction space [RS] method). The corrected images were compared with those produced by applying the deformation matrices in the image space (IS method) followed by summing the realigned gated frames, as well as with uncorrected motion-averaged images. Both correction techniques led to significant improvement in accounting for respiratory motion artifacts when compared with uncorrected motion-averaged images. These improvements included signal-to-noise ratio (mean increase of 28.0% and 24.2% for the RS and IS methods, respectively), lesion size (reduction of 60.4% and 47.9%, respectively), lesion contrast (increase of 70.1% and 57.2%, respectively), and lesion position (changes of 60.9% and 46.7%, respectively). Our results demonstrate significant respiratory motion compensation using both methods, with superior results from a 4D PET RS approach.

Recent developments in techniques for respiratory motion correction in PET-CT imaging

The advent of hybrid imaging in the form of PET CT has revolutionised the practice of respiratory medicine. Due to the high sensitivity and specificity of this technique, it is possible to detect pulmonary pathologies in early stages with high degrees of certitude thereby facilitating prompt diagnosis and treatment. However, the presence of respiratory motion artefacts depreciates the diagnostic accuracy of this technique. Multiple motion correction techniques have been developed to overcome this predicament. In this paper, these techniques have been reviewed from existing scientific literature. DOI: http://dx.doi.org/10.3329/bjnm.v17i1.22496 Bangladesh J. Nuclear Med. 17(1): 84-90, January 2014

The use of a generalized reconstruction by inversion of coupled systems (GRICS) approach for generic respiratory motion correction in PET/MR imaging

Respiratory motion is a source of artifacts in multimodality imaging such as PET/MR. Solutions include retrospective or prospective gating. They have however found limited use in clinical practice, since their increased overall acquisition duration to maintain overall image quality. More elaborate methods consist of using 4D MR datasets to extract spatial deformations in order to correct for the respiratory motion in PET. The main drawbacks of such approaches is the relatively long acquisition times associated with 4D MR imaging which is often incompatible with clinical PET/MR protocols. The objective of this work was to overcome these limitations by exploiting a generalized reconstruction by inversion of coupled systems (GRICS) approach. The methodology is based on a joint estimation of motion during the MR image reconstruction process, providing internal structure motion and associated deformation matrices for retrospective use in PET respiratory motion correction. This method was first validated on four MR volunteers and two PET/MR patient datasets by comparing GRICS generated MR images to 4D MR series obtained by retrospective gating. In a second step 4D PET datasets corresponding to acquired 4D MR images were simulated using the GATE Monte Carlo simulation platform. GRICS generated deformation matrices were subsequently used to correct respiratory motion in comparison to the 4D MR image based deformations both for the simulated and the two 4D PET/MR patient datasets. Results confirm that GRICS synchronized MR images correlate well with the acquired 4D MR series. Similarly, the use of GRICS for respiratory motion correction allows an equivalent percentage improvement on lesion contrast, position and size, considering the PET simulated tumors as well as PET real tumors. This work demonstrates the potential interest of using GRICS for PET respiratory motion correction in combined PET/MR using shorter duration acquisitions without the need for 4D MRI and associated specific MR sequences.

Motion correction for free breathing quantitative myocardial t2 mapping: impact on reproducibility and spatial variability

Background Quantitative myocardial T2 mapping is a promising technique for in-vivo assessment of inflammation and edema [1]. Free breathing T2 mapping sequences increase the flexibility in the choice of the number of T2prep echoes times (TET2P), but should be combined with respiratory motion correction technique [2]. In this study, we sought to evaluate the performance of the Adaptive Registration of varying Contrast-weighted images for improved TIssue Characterization (ARCTIC) algorithm [3] for in-plane motion correction in T2 mapping data and its impact on in-vivo reproducibility and spatial variability of myocardial T2 estimates.

Motion correction strategies for integrated PET/MR.

Integrated whole-body PET/MR facilitates the implementation of a broad variety of respiratory motion correction strategies, taking advantage of the strengths of both modalities. The goal of this study was the quantitative evaluation with clinical data of different MR- and PET-data-based motion correction strategies for integrated PET/MR. The PET and MR data of 20 patients were simultaneously acquired for 10 min on an integrated PET/MR system after administration of (18)F-FDG or (68)Ga-DOTANOC. Respiratory traces recorded with a bellows were compared against MR self-gating signals and signals extracted from PET raw data with the sensitivity method, by applying principal component analysis (PCA) or Laplacian eigenmaps and by using a novel variation combining the former and either of the latter two. Gated sinograms and MR images were generated accordingly, followed by image registration to derive MR motion models. Corrected PET images were reconstructed by incorporating this information into the reconstruction. An optical flow algorithm was applied for PET-based motion correction. Gating and motion correction were evaluated by quantitative analysis of apparent tracer uptake, lesion volume, displacement, contrast, and signal-to-noise ratio. The correlation between bellows- and MR-based signals was 0.63 ± 0.19, and that between MR and the sensitivity method was 0.52 ± 0.26. Depending on the PET raw-data compression, the average correlation between MR and PCA ranged from 0.25 ± 0.30 to 0.58 ± 0.33, and the range was 0.25 ± 0.30 to 0.42 ± 0.34 if Laplacian eigenmaps were applied. By combining the sensitivity method and PCA or Laplacian eigenmaps, the maximum average correlation to MR could be increased to 0.74 ± 0.21 and 0.70 ± 0.19, respectively. The selection of the best PET-based signal for each patient yielded an average correlation of 0.80 ± 0.13 with MR. Using the best PET-based respiratory signal for gating, mean tracer uptake increased by 17 ± 19% for gating, 13 ± 10% for MR-based motion correction, and 18 ± 15% for PET-based motion correction, compared with the static images. Lesion volumes were 76 ± 31%, 83 ± 18%, and 74 ± 22% of the sizes in the static images for gating, MR-based motion correction, and PET-based motion correction, respectively. Respiratory traces extracted from MR and PET data are comparable to those based on external sensors. The proposed PET-driven gating method improved respiratory signals and overall stability. Consistent results from MR- and PET-based correction methods enable more flexible PET/MR scan protocols while achieving higher PET image quality.