Respiratory Motion Correction Research Articles

A modular motion compensation pipeline for prospective respiratory motion correction of multi-nuclear MR spectroscopy

Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner’s reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy.

Inversion recovery and saturation recovery pulmonary vein MR angiography using an image based navigator fluoro trigger and variable-density 3D cartesian sampling with spiral-like order.

Contrast enhanced pulmonary vein magnetic resonance angiography (PV CE-MRA) has value in atrial ablation pre-procedural planning. We aimed to provide high fidelity, ECG gated PV CE-MRA accelerated by variable density Cartesian sampling (VD-CASPR) with image navigator (iNAV) respiratory motion correction acquired in under 4min. We describe its use in part during the global iodinated contrast shortage. VD-CASPR/iNAV framework was applied to ECG-gated inversion and saturation recovery gradient recalled echo PV CE-MRA in 65 patients (66 exams) using .15mmol/kg Gadobutrol. Image quality was assessed by three physicians, and anatomical segmentation quality by two technologists. Left atrial SNR and left atrial/myocardial CNR were measured. 12 patients had CTA within 6months of MRA. Two readers assessed PV ostial measurements versus CTA for intermodality/interobserver agreement. Inter-rater/intermodality reliability, reproducibility of ostial measurements, SNR/CNR, image, and anatomical segmentation quality was compared. The mean acquisition time was 3.58 ± 0.60min. Of 35 PV pre-ablation datasets (34 patients), mean anatomical segmentation quality score was 3.66 ± 0.54 and 3.63 ± 0.55 as rated by technologists 1 and 2, respectively (p = 0.7113). Good/excellent anatomical segmentation quality (grade 3/4) was seen in 97% of exams. Each rated one exam as moderate quality (grade 2). 95% received a majority image quality score of good/excellent by three physicians. Ostial PV measurements correlated moderate to excellently with CTA (ICCs range 0.52-0.86). No difference in SNR was observed between IR and SR. High quality PV CE-MRA is possible in under 4min using iNAV bolus timing/motion correction and VD-CASPR.

Extended MRI-based PET motion correction for cardiac PET/MRI

PurposeA 2D image navigator (iNAV) based 3D whole-heart sequence has been used to perform MRI and PET non-rigid respiratory motion correction for hybrid PET/MRI. However, only the PET data acquired during the acquisition of the 3D whole-heart MRI is corrected for respiratory motion. This study introduces and evaluates an MRI-based respiratory motion correction method of the complete PET data.MethodsTwelve oncology patients scheduled for an additional cardiac 18F-Fluorodeoxyglucose (18F-FDG) PET/MRI and 15 patients with coronary artery disease (CAD) scheduled for cardiac 18F-Choline (18F-FCH) PET/MRI were included. A 2D iNAV recorded the respiratory motion of the myocardium during the 3D whole-heart coronary MR angiography (CMRA) acquisition (~ 10 min). A respiratory belt was used to record the respiratory motion throughout the entire PET/MRI examination (~ 30–90 min). The simultaneously acquired iNAV and respiratory belt signal were used to divide the acquired PET data into 4 bins. The binning was then extended for the complete respiratory belt signal. Data acquired at each bin was reconstructed and combined using iNAV-based motion fields to create a respiratory motion-corrected PET image. Motion-corrected (MC) and non-motion-corrected (NMC) datasets were compared. Gating was also performed to correct cardiac motion. The SUVmax and TBRmax values were calculated for the myocardial wall or a vulnerable coronary plaque for the 18F-FDG and 18F-FCH datasets, respectively.ResultsA pair-wise comparison showed that the SUVmax and TBRmax values of the motion corrected (MC) datasets were significantly higher than those for the non-motion-corrected (NMC) datasets (8.2 ± 1.0 vs 7.5 ± 1.0, p < 0.01 and 1.9 ± 0.2 vs 1.2 ± 0.2, p < 0.01, respectively). In addition, the SUVmax and TBRmax of the motion corrected and gated (MC_G) reconstructions were also higher than that of the non-motion-corrected but gated (NMC_G) datasets, although for the TBRmax this difference was not statistically significant (9.6 ± 1.3 vs 9.1 ± 1.2, p = 0.02 and 2.6 ± 0.3 vs 2.4 ± 0.3, p = 0.16, respectively). The respiratory motion-correction did not lead to a change in the signal to noise ratio.ConclusionThe proposed respiratory motion correction method for hybrid PET/MRI improved the image quality of cardiovascular PET scans by increased SUVmax and TBRmax values while maintaining the signal-to-noise ratio.Trial registration METC162043 registered 01/03/2017.

Augmented Reality Navigation System for Biliary Interventional Procedures With Dynamic Respiratory Motion Correction.

Biliary interventional procedures require physicians to track the interventional instrument tip (Tip) precisely with X-ray image. However, Tip positioning relies heavily on the physicians' experience due to the limitations of X-ray imaging and the respiratory interference, which leads to biliary damage, prolonged operation time, and increased X-ray radiation. We construct an augmented reality (AR) navigation system for biliary interventional procedures. It includes system calibration, respiratory motion correction and fusion navigation. Firstly, the magnetic and 3D computed tomography (CT) coordinates are aligned through system calibration. Secondly, a respiratory motion correction method based on manifold regularization is proposed to correct the misalignment of the two coordinates caused by respiratory motion. Thirdly, the virtual biliary, liver and Tip from CT are overlapped to the corresponding position of the patient for dynamic virtual-real fusion. Our system is respectively evaluated and achieved an average alignment error of 0.75 ± 0.17 mm and 2.79 ± 0.46 mm on phantoms and patients. The navigation experiments conducted on phantoms achieve an average Tip positioning error of 0.98 ± 0.15 mm and an average fusion error of 1.67 ± 0.34 mm after correction. Our system can automatically register the Tip to the corresponding location in CT, and dynamically overlap the 3D virtual model onto patients to provide accurate and intuitive AR navigation. This study demonstrates the clinical potential of our system by assisting physicians during biliary interventional procedures. Our system enables dynamic visualization of virtual model on patients, reducing the reliance on contrast agents and X-ray usage.

Intra-bin correction and inter-bin compensation of respiratory motion in free-running five-dimensional whole-heart magnetic resonance imaging

BackgroundFree-running cardiac and respiratory motion-resolved whole-heart five-dimensional (5D) cardiovascular magnetic resonance (CMR) can reduce scan planning and provide a means of evaluating respiratory-driven changes in clinical parameters of interest. However, respiratory-resolved imaging can be limited by user-defined parameters which create trade-offs between residual artifact and motion blur. In this work, we develop and validate strategies for both correction of intra-bin and compensation of inter-bin respiratory motion to improve the quality of 5D CMR. MethodsEach component of the reconstruction framework was systematically validated and compared to the previously established 5D approach using simulated free-running data (N = 50) and a cohort of 32 patients with congenital heart disease. The impact of intra-bin respiratory motion correction was evaluated in terms of image sharpness while inter-bin respiratory motion compensation was evaluated in terms of reconstruction error, compression of respiratory motion, and image sharpness. The full reconstruction framework (intra-acquisition correction and inter-acquisition compensation of respiratory motion [IIMC] 5D) was evaluated in terms of image sharpness and scoring of image quality by expert reviewers. ResultsIntra-bin motion correction provides significantly (p < 0.001) sharper images for both simulated and patient data. Inter-bin motion compensation results in significant (p < 0.001) lower reconstruction error, lower motion compression, and higher sharpness in both simulated (10/11) and patient (9/11) data. The combined framework resulted in significantly (p < 0.001) sharper IIMC 5D reconstructions (End-expiration (End-Exp): 0.45 ± 0.09, End-inspiration (End-Ins): 0.46 ± 0.10) relative to the previously established 5D implementation (End-Exp: 0.43 ± 0.08, End-Ins: 0.39 ± 0.09). Similarly, image scoring by three expert reviewers was significantly (p < 0.001) higher using IIMC 5D (End-Exp: 3.39 ± 0.44, End-Ins: 3.32 ± 0.45) relative to 5D images (End-Exp: 3.02 ± 0.54, End-Ins: 2.45 ± 0.52). ConclusionThe proposed IIMC reconstruction significantly improves the quality of 5D whole-heart MRI. This may be exploited for higher resolution or abbreviated scanning. Further investigation of the diagnostic impact of this framework and comparison to gold standards is needed to understand its full clinical utility, including exploration of respiratory-driven changes in physiological measurements of interest.

Highly efficient free-breathing 3D whole-heart imaging in 3-min: single center study in adults with congenital heart disease.

Three dimensional, whole-heart (3DWH) MRI is an established non-invasive imaging modality in patients with congenital heart disease (CHD) for the diagnosis of cardiovascular morphology and for clinical decision making. Current techniques utilise diaphragmatic navigation (dNAV) for respiratory motion correction and gating and are frequently limited by long acquisition times. This study proposes and evaluates the diagnostic performance of a respiratory gating-free framework, which considers respiratory image-based navigation (iNAV), and highly accelerated variable density Cartesian sampling in concert with non-rigid motion correction and low-rank patch-based denoising (iNAV-3DWH-PROST). The method is compared to the clinical dNAV-3DWH sequence in adult patients with CHD. In this prospective single center study, adult patients with CHD who underwent the clinical dNAV-3DWH MRI were also scanned with the iNAV-3DWH-PROST. Diagnostic confidence (4-point Likert scale) and diagnostic accuracy for common cardiovascular lesions was assessed by three readers. Scan times and diagnostic confidence were compared using the Wilcoxon-signed rank test. Co-axial vascular dimensions at three anatomic landmarks were measured, and agreement between the research and the corresponding clinical sequence was assessed with Bland-Altman analysis. The study included 60 participants (mean age ±[SD]: 33±14 years; 36 men). The mean acquisition time of iNAV-3DWH-PROST was significantly lower compared with the conventional clinical sequence (3.1±0.9min vs 13.9±3.9min, p<0.0001). Diagnostic confidence was higher for the iNAV-3DWH-PROST sequence compared with the clinical sequence (3.9±0.2 vs 3.4±0.8, p<0.001), however there was no significant difference in diagnostic accuracy. Narrow limits of agreement and mean bias less than 0.08cm were found between the research and the clinical vascular measurements. The iNAV-3DWH-PROST framework provides efficient, high quality and robust 3D whole-heart imaging in significantly shorter scan time compared to the standard clinical sequence.

Combined free-running four-dimensional anatomical and flow magnetic resonance imaging with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals

Four-dimensional (4D) flow magnetic resonance imaging (MRI) often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses pilot tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running three-dimensional radial acquisitions, to create co-registered anatomy and flow images. Thirteen volunteers and two Marfan syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional two-dimensional (2D) flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0-4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation. Blood-to-myocardium contrast ratio for SyNAPS 4D flow magnitude images (1.5±0.3) was significantly higher than for Native 4D flow (0.7±0.1, p<0.01) and was comparable to 2D flow (2.3±0.9, p=0.02). Image quality scores of SyNAPS 4D flow from the experts (M.P.: 1.9±0.3, E.T.: 2.5±0.5) were overall significantly higher than the scores from Native 4D flow (M.P.: 1.6±0.6, p=0.03, E.T.: 0.8±0.4, p<0.01) but still significantly lower than the scores from the reference 2D flow datasets (M.P.: 2.8±0.4, p<0.01, E.T.: 3.5±0.7, p<0.01). The Pearson correlation coefficient between the dynamic vessel area measured on SyNAPS 4D flow and that from 2D flow was 0.69±0.24 for the AAo and 0.83±0.10 for the DAo, whereas the Pearson correlation between Native 4D flow and 2D flow measurements was 0.12±0.48 for the AAo and 0.08±0.39 for the DAo. Linear correlations between SyNAPS 4D flow and 2D flow measurements of net volume (r2 =0.83) and peak flow (r2 =0.87) were larger than the correlations between Native 4D flow and 2D flow measurements of net volume (r2 =0.79) and peak flow (r2 =0.76). The feasibility and utility of SyNAPS were demonstrated for joint whole-heart anatomical and flow MRI without requiring electrocardiography gating, respiratory navigators, or contrast agents. Using SyNAPS, a high-contrast anatomical imaging sequence can be used to improve 4D flow measurements that often suffer from poor delineation of vessel boundaries in the absence of contrast agents.

Impact of respiratory motion on 18 F-FDG PET radiomics stability: Clinical evaluation with a digital PET scanner.

18 F-FDG PET quantitative features are susceptible to respiratory motion. However, studies using clinical patient data to explore the impact of respiratory motion on 18 F-FDG PET radiomic features are limited. In this study, we investigated the impact of respiratory motion on radiomics stability with clinical 18 F-FDG PET images using a data-driven gating (DDG) algorithm on the digital PET scanner. A total of 101 patients who underwent oncological 18 F-FDG PET scans were retrospectively included. A DDG algorithm combined with a motion compensation technique was used to extract the PET images with respiratory motion correction. 18 F-FDG-avid lesions from the thorax to the upper abdomen were analyzed on the non-DDG and DDG PET images. The lesions were segmented with a 40% threshold of the maximum standardized uptake. A total of 725 radiomic features were computed from the segmented lesions, including first-order, shape, texture, and wavelet features. The intraclass correlation coefficient (ICC) and coefficient of variation (COV) were calculated to evaluate feature stability. An ICC above 0.9 and a COV below 5% were considered high stability. In total, 168 lesions with and without respiratory motion correction were analyzed. Our results indicated that most 18 F-FDG PET radiomic features are sensitive to respiratory motion. Overall, only 27 out of 725 (3.72%) radiomic features were identified as highly stable, including one from the first-order features (entropy), one from the shape features (sphericity), four from the gray-level co-occurrence matrix features (normalized and unnormalized inverse difference moment, joint entropy, and sum entropy), one from the gray-level run-length matrix features (run entropy), and 20 from the wavelet filter-based features. Respiratory motion has a significant impact on 18 F-FDG PET radiomics stability. The highly stable features identified in our study may serve as potential candidates for further applications, such as machine learning modeling.

Improved [18F]FDG PET/CT Diagnostic Accuracy for Infective Endocarditis Using Conventional Cardiac Gating or Combined Cardiac and Respiratory Motion Correction (CardioFreezeTM).

Infective endocarditis (IE) is a serious and diagnostically challenging condition. [18F]FDG PET/CT is valuable for evaluating suspected IE, but it is susceptible to motion-related artefacts. This study investigated the potential benefits of cardiac motion correction for [18F]FDG PET/CT. In this prospective study, patients underwent [18F]FDG PET/CT for suspected IE, combined with a conventional cardiac gating sequence, a data-driven cardiac and respiratory gating sequence (CardioFreezeTM), or both. Scans were performed in adherence to EANM guidelines and assessors were blinded to patients' clinical contexts. Final diagnosis of IE was established based on multidisciplinary consensus after a minimum of 4 months follow-up and surgical findings, whenever performed. Seven patients participated in the study, undergoing both an ungated [18F] FDG-PET/CT and a scan with either conventional cardiac gating, CardioFreezeTM, or both. Cardiac motion correction improved the interpretability of [18F]FDG PET/CT in four out of five patients with valvular IE lesions, regardless of the method of motion correction used, which was statistically significant by Wilcoxon's signed rank test: p = 0.046. In one patient the motion-corrected sequence confirmed the diagnosis of endocarditis, which had been missed on non-gated PET. The performance of the two gating sequences was comparable. In conclusion, in this exploratory study, cardiac motion correction of [18F]FDG PET/CT improved the interpretability of [18F]FDG PET/CT. This may improve the sensitivity of PET/CT for suspected IE. Further larger comparative studies are necessary to confirm the additive value of these cardiac motion correction methods.

Improved visualization of free-running cardiac magnetic resonance by respiratory phase using principal component analysis

Rationale and objectivesTo support cardiac MR acquisitions during breathing without ECG, we developed software to mitigate the effects of respiratory displacement of the heart. The algorithm resolves respiratory motions and cardiac cycles from DICOM files. The new software automatically detects heartbeats from expiration and inspiration to decrease apparent respiratory motion. Materials and methodsOur software uses principal component analysis to resolve respiratory motions from cardiac cycles. It groups heartbeats from expiration and inspiration to decrease apparent respiratory motion. The respiratory motion correction was evaluated on short-axis views (acquired with compressed sensing) of 11 healthy subjects and 8 cardiac patients. Two expert radiologists, blinded to the processing, assessed the dynamic images in terms of blood-myocardial contrast, endocardial interface definition, and motion artifacts. ResultsThe smallest correlation coefficients between end-systolic frames of the original dynamic scans averaged 0.79. After segregation of cardiac cycles by respiratory phase, the mean correlation coefficients between cardiac cycles were 0.94±0.03 at end-expiration and 0.90±0.08 at end-inspiration. The improvements in correlation coefficients were significant in paired t-tests for healthy subjects and heart patients at end-expiration. Clinical assessment preferred cardiac cycles during end-expiration, which maintained or enhanced scores in 90% of healthy subjects and 83% of the heart patients. Performance remained high with arrhythmia and irregular breathing present. ConclusionHeartbeats collected from end-expiration mitigate respiratory motion and are accessible by applying the new software to DICOM files from real-time CMR. Inspiratory heartbeats are also accessible for examination of arrhythmias or abnormalities at end-inspiration.

Effect of different respiratory motion correction methods on PET image quality in chest PET/MRI

Objective: To investigate the effect of different respiratory motion correction methods on PET images during chest PET/MRI scans. Methods: The data of 35 patients (24 males and 11 females, aged from 29 to 84 year) of pulmonary lesions with significantly high uptake in thoracic PET/MRI scan were retrospective collected from Jingling Hospital. Four different methods were used to reconstruct the PET data. Group A was the full-time 20 min without respiratory motion correction static acquisition (Static) as a control, group B was the end-expiration static collection (Q.Static), and group C was the multi-bins respiratory gating (Gated-Respiratory). In addition, the influence of the time being considered, group D was added for reconstruction in the first 1/3 period (6 min 40 s) of group A. Then, the maximum value (L-SUVmax) and the mean value (L-SUVmean) of the SUV of the lesion, the mean value (B-SUVmean) and the standard deviation (B-SUVsd) of the SUV of the background under each reconstruction results were measured, and for each lesion the signal-to-noise ratio (L-SNR) was calculated. In order to exclude the interference of the background, the mean of the relative SUV (L-dSUVmean) of the L-SUVmean relative to the B-SUVmean was also calculated. Finally, One-Way Repeated Measures ANOVA was used, and the post-hoc pairwise comparison between groups was tested by Bonferroni's modified test. Results: There was statistically significant difference among group B or group C compared to group A and group D in L-SUVmax, L-SUVmean and L-dSUVmean [L-SUVmax:group B vs group A or group D was 8.06±3.57 vs 7.73±3.45 or 7.61±3.50, group C vs group A or group D was 8.04±3.56 vs 7.73±3.45 or 7.61±3.50 (all P<0.05); L-SUVmean: group B vs group A or group D was 4.12±1.78 vs 3.98±1.72 or 3.91±1.71, group C vs group A or group D was 4.13±1.78 vs 3.98±1.72 or 3.91±1.71 (all P<0.05); L-dSUVmean: group B vs group A or group D was 3.52±0.16 vs 3.39±0.18 or 3.31±0.18, group C vs group A or group D was 3.53±0.18 vs 3.39±0.18 or 3.31±0.18 (all P<0.05)], but there was no statistically significant difference between group B and group C (all P>0.05). There were statistically significant differences between group D and group A in B-SUVsd (0.07±0.00 vs 0.07±0.00, P=0.023) and L-SNR (69.80±44.57 vs 85.35±68.98, P=0.001). There was no statistically significant difference between group D and group A in L-SUVmax, L-SUVmean, B-SUVmean and L-dSUVmean (all P>0.05). Conclusions: There was no significant difference in PET image quality between the Q.static and Gated-Respiratory group, both of the two groups were better than the Static group which with no Gated-Respiratory motion correction. If non-respiratory gated Static is used, the PET acquisition time is recommended to be 6 min 40 s.

Respiratory signal estimation for cardiac perfusion SPECT using deep learning.

Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external tracking devices to estimate respiratory signals can add cost and operational complications in a clinical setting. We aim to develop a deep learning (DL) approach that uses only SPECT projection data for respiratory signal estimation. A modified U-Net was implemented that takes temporally finely sampled SPECT sub-projection data (100ms) as input. These sub-projections are obtained by reframing the 20-s list-mode data, resulting in 200 sub-projections, at each projection angle for each SPECT camera head. The network outputs a 200-time-point motion signal for each projection angle, which was later aggregated over all angles to give a full respiratory signal. The target signal for DL model training was from an external stereo-camera visual tracking system (VTS). In addition to comparing DL and VTS, we also included a data-driven approach based on the center-of-mass (CoM) strategy. This CoM method estimates respiratory signals by monitoring the axial changes of CoM for counts in the heart region of the sub-projections. We utilized 900 subjects with stress cardiac perfusion SPECT studies, with 302 subjects for testing and the remaining 598 subjects for training and validation. The Pearson's correlation coefficient between the DL respiratory signal and the reference VTS signal was 0.90, compared to 0.70 between the CoM signal and the reference. For respiratory motion correction on SPECT images, all VTS, DL, and CoM approaches partially de-blured the heart wall, resulting in a thinner wall thickness and increased recovered maximal image intensity within the wall, with VTS reducing blurring the most followed by the DL approach. Uptake quantification for the combined anterior and inferior segments of polar maps showed a mean absolute difference from the reference VTS of 1.7% for the DL method for patients with motion >12mm, compared to 2.6% for the CoM method and 8.5% for no correction. We demonstrate the capability of a DL approach to estimate respiratory signal from SPECT projection data for cardiac perfusion imaging. Our results show that the DL based respiratory motion correction reduces artefacts and achieves similar regional quantification to that obtained using the stereo-camera VTS signals. This may enable fully automatic data-driven respiratory motion correction without relying on external motion tracking devices.

A new compressed sensing cine cardiac MRI sequence with free-breathing real-time acquisition and fully automated motion-correction: A comprehensive evaluation

PurposeThe purpose of this study was to compare a new free-breathing compressed sensing cine (FB-CS) cardiac magnetic resonance imaging (CMR) to the standard reference multi-breath-hold segmented cine (BH-SEG) CMR in an unselected population. Materials and methodsFrom January to April 2021, 52 consecutive adult patients who underwent both conventional BH-SEG CMR and new FB-CS CMR with fully automated respiratory motion correction were retrospectively enrolled. There were 29 men and 23 women with a mean age of 57.7 ± 18.9 (standard deviation [SD]) years (age range: 19.0–90.0 years) and a mean cardiac rate of 74.6 ± 17.9 (SD) bpm. For each patient, short-axis stacks were acquired with similar parameters providing a spatial resolution of 1.8 × 1.8 × 8.0 mm3 and 25 cardiac frames. Acquisition and reconstruction times, image quality (Likert scale from 1 to 4), left and right ventricular volumes and ejection fractions, left ventricular mass, and global circumferential strain were assessed for each sequence. ResultsFB-CS CMR acquisition time was significantly shorter (123.8 ± 28.4 [SD] s vs. 267.2 ± 39.3 [SD] s for BH-SEG CMR; P < 0.0001) at the penalty of a longer reconstruction time (271.4 ± 68.7 [SD] s vs. 9.9 ± 2.1 [SD] s for BH-SEG CMR; P < 0.0001). In patients without arrhythmia or dyspnea, FB-CS CMR provided subjective image quality that was not different from that of BH-SEG CMR (P = 0.13). FB-CS CMR improved image quality in patients with arrhythmia (n = 18; P = 0.002) or dyspnea (n = 7; P = 0.02), and the edge sharpness was improved at end-systole and end-diastole (P = 0.0001). No differences were observed between the two techniques in ventricular volumes and ejection fractions, left ventricular mass or global circumferential strain in patients in sinus rhythm or with cardiac arrhythmia. ConclusionThis new FB-CS CMR addresses respiratory motion and arrhythmia-related artifacts without compromising the reliability of ventricular functional assessment.

Respiratory and cardiac motion correction in positron emission tomography using elastic motion approach for simultaneous abdomen and thorax positron emission tomography-magnetic resonance imaging.

Cardiac and respiratory motions in clinical positron emission tomography (PET) are a major contributor to inaccurate PET quantification and lesion characterisation. In this study, an elastic motion-correction (eMOCO) technique based on mass preservation optical flow is adapted and investigated for positron emission tomography-magnetic resonance imaging (PET-MRI) applications. The eMOCO technique was investigated in a motion management QA phantom and in twenty-four patients who underwent PET-MRI for dedicated liver imaging and nine patients for cardiac PET-MRI evaluation. Acquired data were reconstructed with eMOCO and gated motion correction techniques at cardiac, respiratory and dual gating modes, and compared to static images. Standardized uptake value (SUV), signal-to-noise ratio (SNR) of lesion activities from each gating mode and correction technique were measured and their means/standard deviation (SD) were compared using 2-ways ANOVA analysis and post-hoc Tukey's test. Lesions' SNR are highly recovered from phantom and patient studies. The SD of the SUV resulted from the eMOCO technique was statistically significantly less (P<0.01) than the SD resulted from conventional gated and static SUVs at the liver, lung and heart. The eMOCO technique was successfully implemented in PET-MRI in a clinical setting and produced the lowest SD compared to gated and static images, and hence provided the least noisy PET images. Therefore, the eMOCO technique can potentially be used on PET-MRI for improved respiratory and cardiac motion correction.

Dynamic cine images derived from RTCSCineMoCo of the same patients in Video 1. RTCSCineMoCo, real-time cine imaging combines compressed sensing reconstruction and retrospective fully automated respiratory motion correction.

Dynamic cine images derived from RTCSCineMoCo of the same patients in Video 1. RTCSCineMoCo, real-time cine imaging combines compressed sensing reconstruction and retrospective fully automated respiratory motion correction.

Focused navigation for respiratory-motion-corrected free-running radial 4D flow MRI.

To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI. Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets. For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04 0.32 mm and 0.31 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02 0.51 mm up to 5.85 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32 0.11 cm2 , 11.1 3.5mL, and 22.3 6.0mL/s) than for fNAV 4D flow datasets (0.10 0.03 cm2 , 2.6 0.7mL, and 5.1 .9mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92 2.95 cm2 , 5.06 2.64 cm2 , 4.87 2.57 cm2 , 4.87 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2 =0.92) and peak flow (r2 =0.94), followed by navigator-gated 4D flow (r2 =0.83 and r2 =0.86, respectively), and uncorrected 4D flow (r2 =0.69 and r2 =0.86, respectively). fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.

Ultra-wide band radar for prospective respiratory motion correction in the liver

Objective. T1 mapping of the liver is time consuming and can be challenging due to respiratory motion. Here we present a prospective slice tracking approach, which utilizes an external ultra-wide band radar signal and allows for efficient T1 mapping during free-breathing. Approach. The fast radar signal is calibrated to an MR-based motion signal to create a motion model. This motion model provides motion estimates, which are used to carry out slice tracking for any subsequent clinical scan. This approach was evaluated in simulations, phantom experiments and in vivo scans. Main results. Radar-based slice tracking was implemented on an MR system with a total latency of 77 ms. Moving phantom experiments showed accurate motion prediction with an error of 0.12 mm in anterior-posterior and 0.81 mm in head-feet direction. The model error remained stable for up to two hours. In vivo experiments showed visible image improvement with a motion model error three times smaller than with a respiratory bellow. For T1 mapping during free-breathing the proposed approach provided similar results compared to reference T1 mapping during a breathhold. Significance. The proposed radar-based approach achieves accurate slice tracking and enables efficient T1 mapping of the liver during free-breathing. This motion correction approach is independent from scanning parameters and could also be used for applications like MR guided radiotherapy or MR Elastography.

Dosimetric impact of 3D motion-compensated SPECT reconstruction for SIRT planning

BackgroundIn selective internal radiation therapy, 99mTc SPECT images are used to optimize patient treatment planning, but they are affected by respiratory motion. In this study, we evaluated on patient data the dosimetric impact of motion-compensated SPECT reconstruction on several volumes of interest (VOI), on the tumor-to-normal liver (TN) ratio and on the activity to be injected.MethodsTwenty-nine patients with liver cancer or hepatic metastases treated by radioembolization were included in this study. The biodistribution of 90Y is assumed to be the same as that of 99mTc when predictive dosimetry is implemented. A total of 31 99mTc SPECT images were acquired and reconstructed with two methods: conventional OSEM (3D) and motion-compensated OSEM (3Dcomp). Seven VOI (liver, lungs, tumors, perfused liver, hepatic reserve, healthy perfused liver and healthy liver) were delineated on the CT or obtained by thresholding SPECT images followed by Boolean operations. Absorbed doses were calculated for each reconstruction using Monte Carlo simulations. Percentages of dose difference (PDD) between 3Dcomp and 3D reconstructions were estimated as well as the relative differences for TN ratio and activities to be injected. The amplitude of movement was determined with local rigid registration of the liver between the 3Dcomp reconstructions of the extreme phases of breathing.ResultsThe mean amplitude of the liver was 9.5 ± 2.7 mm. Medians of PDD were closed to zero for all VOI except for lungs (6.4%) which means that the motion compensation overestimates the absorbed dose to the lungs compared to the 3D reconstruction. The smallest lesions had higher PDD than the largest ones. Between 3D and 3Dcomp reconstructions, means of differences in lung dose and TN ratio were not statistically significant, but in some cases these differences exceed 1 Gy (4/31) and 8% (2/31). The absolute differences in activity were on average 3.1% ± 5.1% and can reach 22.8%.ConclusionThe correction of respiratory motion mainly impacts the lung and tumor doses but only for some patients. The largest dose differences are observed for the smallest lesions.

Free-breathing cardiac cine MRI with compressed sensing real-time imaging and retrospective motion correction: clinical feasibility and validation.

To prospectively evaluate the feasibility and biventricular assessment accuracy of a free-breathing cardiac cine imaging technique (RTCSCineMoCo) combined with highly accelerated real-time (RT) acquisition, compressed sensing (CS) reconstruction, and fully automated non-rigid respiratory motion correction. We evaluated 80 patients scheduled for clinical cardiac MRI. Cardiac cine images of the same long-axis and short-axis stacks were acquired using three techniques: (1) SegBH: standard segmented cine with breath-hold; (2) RTCSCineMoCo; (3) RTCSCine: single-shot RT CS cine at 3.0 T. Image quality (IQ) was evaluated using a qualitative 5-point Likert scale and the European CMR registry standardized criteria. Quantitative parameters including left (LV) and right ventricular (RV) ejection fractions (EF), end-diastolic volumes (EDV), end-systolic volumes (ESV), stroke volumes (SV), and LV mass (LVM) were measured and compared. RTCSCineMoCo and SegBH had equivalent IQ scores (4.4 ± 0.7 vs. 4.2 ± 0.8, p = 0.066), while RTCSCine had a significantly lower IQ score than SegBH (4.0 ± 0.8 vs. 4.2 ± 0.8, p = 0.031). In a quantitative analysis, RTCSCineMoCo and SegBH yielded similar measurements for all parameters, while the majority of RTCSCine parameters were significantly different compared with SegBH, except for LVEDV. RTCSCineMoCo is a promising method for robust free-breathing cardiac cine imaging, achieving better IQ and more precise quantitative analysis results for both ventricles compared with RTCSCine. • RTCSCineMoCo is a promising method for free-breathing cardiac MR cine imaging in daily practice. • RTCSCineMoCo provided better IQ and more precise quantitative measurements compared with RTCSCine, by extending RT data acquisition to multiple heartbeats, performing non-rigid respiratory motion correction, and signal averaging. • RTCSCineMoCo may be suitable for routine clinical use for vulnerable patients who may otherwise pose a challenge to image successfully with the conventional segmented cine technique.

Free-breathing 2D radial cine MRI with respiratory auto-calibrated motion correction (RAMCO).

To develop a free-breathing (FB) 2D radial balanced steady-state free precession cine cardiac MRI method with 100% respiratory gating efficiency using respiratory auto-calibrated motion correction (RAMCO) based on a motion-sensing camera. The signal from a respiratory motion-sensing camera was recorded during a FB retrospectively electrocardiogram triggered 2D radial balanced steady-state free precession acquisition using pseudo-tiny-golden-angle ordering. With RAMCO, for each acquisition the respiratory signal was retrospectively auto-calibrated by applying different linear translations, using the resulting in-plane image sharpness as a criterium. The auto-calibration determines the optimal magnitude of the linear translations for each of the in-plane directions to minimize motion blurring caused by bulk respiratory motion. Additionally, motion-weighted density compensation was applied during radial gridding to minimize through-plane and non-bulk motion blurring. Left ventricular functional parameters and sharpness scores of FB radial cine were compared with and without RAMCO, and additionally with conventional breath-hold Cartesian cine on 9 volunteers. FB radial cine with RAMCO had similar sharpness scores as conventional breath-hold Cartesian cine and the left ventricular functional parameters agreed. For FB radial cine, RAMCO reduced respiratory motion artifacts with a statistically significant difference in sharpness scores (P < 0.05) compared to reconstructions without motion correction. 2D radial cine imaging with RAMCO allows evaluation of left ventricular functional parameters in FB with 100% respiratory efficiency. It eliminates the need for breath-holds, which is especially valuable for patients with no or impaired breath-holding capacity. Validation of the proposed method on patients is warranted.