Nonrigid active shape model-based registration framework for motion correction of cardiac T1 mapping.
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ABSTRACT:
SUBMITTER: El-Rewaidy H
PROVIDER: S-EPMC5941305 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
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Project description:ObjectiveOur aim was to investigate the technical feasibility of a novel motion compensation method for cardiac magntic resonance (MR) T1 and extracellular volume fraction (ECV) mapping.Materials and methodsNative and post-contrast T1 maps were obtained using modified look-locker inversion recovery (MOLLI) pulse sequences with acquisition scheme defined in seconds. A nonrigid, nonparametric, fast elastic registration method was applied to generate motion-corrected T1 maps and subsequently ECV maps. Qualitative rating was performed based on T1 fitting-error maps and overlay images. Local deformation vector fields were produced for quantitative assessment. Intra- and inter-observer reproducibility were compared with and without motion compensation.ResultsEighty-two T1 and 39 ECV maps were obtained in 21 patients with diverse myocardial diseases. Approximately 60% demonstrated clear quality improvement after motion correction for T1 mapping, particularly for the poor-rating cases (23% before vs 2% after). Approximately 67% showed further improvement with co-registration in ECV mapping. Although T1 and ECV values were not clinically significantly different before and after motion compensation, there was improved intra- and inter-observer reproducibility after motion compensation.ConclusionsAutomated motion correction and co-registration improved the qualitative assessment and reproducibility of cardiac MR T1 and ECV measurements, allowing for more reliable ECV mapping.
| S-EPMC5813095 | biostudies-literature
Project description:PURPOSE:To present and assess an automatic nonrigid image registration framework that compensates motion in cardiac magnetic resonance imaging (MRI) perfusion series and auxiliary images acquired under a wide range of conditions to facilitate myocardial perfusion quantification. MATERIALS AND METHODS:Our framework combines discrete feature matching for large displacement estimation with a dense variational optical flow formulation in a multithreaded architecture. This framework was evaluated on 291 clinical subjects to register 1.5T and 3.0T steady-state free-precession (FISP) and fast low-angle shot (FLASH) dynamic contrast myocardial perfusion images, arterial input function (AIF) images, and proton density (PD)-weighted images acquired under breath-hold (BH) and free-breath (FB) settings. RESULTS:Our method significantly improved frame-to-frame appearance consistency compared to raw series, expressed in correlation coefficient (R2 ?=?0.996?±?3.735E-3 vs. 0.978?±?2.024E-2, P < 0.0001) and mutual information (3.823?±?4.098E-1 vs. 2.967?±?4.697E-1, P < 0.0001). It is applicable to both BH (R2 ?=?0.998?±?3.217E-3 vs. 0.990?±?7.527E-3) and FB (R2 ?=?0.995?±?3.410E-3 vs. 0.968?±?2.257E-3) paradigms as well as FISP and FLASH sequences. The method registers PD images to perfusion T1 series (9.70% max increase in R2 vs. no registration, P < 0.001) and also corrects motion in low-resolution AIF series (R2 ?=?0.987?±?1.180E-2 vs. 0.964?±?3.860E-2, P < 0.001). Finally, we showed the myocardial perfusion contrast dynamic was preserved in the motion-corrected images compared to the raw series (R2 ?=?0.995?±?6.420E-3). CONCLUSION:The critical step of motion correction prior to pixel-wise cardiac MR perfusion quantification can be performed with the proposed universal system. It is applicable to a wide range of perfusion series and auxiliary images with different acquisition settings. LEVEL OF EVIDENCE:3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1060-1072.
| S-EPMC5557713 | biostudies-literature
Project description:Quantification of myocardial T1 relaxation has potential value in the diagnosis of both ischemic and nonischemic cardiomyopathies. Image acquisition using the modified Look-Locker inversion recovery technique is clinically feasible for T1 mapping. However, respiratory motion limits its applicability and degrades the accuracy of T1 estimation. The robust registration of acquired inversion recovery images is particularly challenging due to the large changes in image contrast, especially for those images acquired near the signal null point of the inversion recovery and other inversion times for which there is little tissue contrast. In this article, we propose a novel motion correction algorithm. This approach is based on estimating synthetic images presenting contrast changes similar to the acquired images. The estimation of synthetic images is formulated as a variational energy minimization problem. Validation on a consecutive patient data cohort shows that this strategy can perform robust nonrigid registration to align inversion recovery images experiencing significant motion and lead to suppression of motion induced artifacts in the T1 map.
| S-EPMC4158317 | biostudies-literature
Project description:Digital image analysis is a fundamental component of quantitative microscopy. However, intravital microscopy presents many challenges for digital image analysis. In general, microscopy volumes are inherently anisotropic, suffer from decreasing contrast with tissue depth, lack object edge detail and characteristically have low signal levels. Intravital microscopy introduces the additional problem of motion artefacts, resulting from respiratory motion and heartbeat from specimens imaged in vivo. This paper describes an image registration technique for use with sequences of intravital microscopy images collected in time-series or in 3D volumes. Our registration method involves both rigid and nonrigid components. The rigid registration component corrects global image translations, whereas the nonrigid component manipulates a uniform grid of control points defined by B-splines. Each control point is optimized by minimizing a cost function consisting of two parts: a term to define image similarity, and a term to ensure deformation grid smoothness. Experimental results indicate that this approach is promising based on the analysis of several image volumes collected from the kidney, lung and salivary gland of living rodents.
| S-EPMC3856233 | biostudies-literature
Project description:Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the attenuation measurements often lead to significant artifacts in the reconstructed images. Gating can remove motion artifacts at the cost of increased noise. This paper presents an approach to respiratory motion correction using simultaneous PET/MRI to demonstrate initial results in phantoms, rabbits, and nonhuman primates and discusses the prospects for clinical application.Studies with a deformable phantom, a free-breathing primate, and rabbits implanted with radioactive beads were performed with simultaneous PET/MRI. Motion fields were estimated from concurrently acquired tagged MR images using 2 B-spline nonrigid image registration methods and incorporated into a PET list-mode ordered-subsets expectation maximization algorithm. Using the measured motion fields to transform both the emission data and the attenuation data, we could use all the coincidence data to reconstruct any phase of the respiratory cycle. We compared the resulting SNR and the channelized Hotelling observer (CHO) detection signal-to-noise ratio (SNR) in the motion-corrected reconstruction with the results obtained from standard gating and uncorrected studies.Motion correction virtually eliminated motion blur without reducing SNR, yielding images with SNR comparable to those obtained by gating with 5-8 times longer acquisitions in all studies. The CHO study in dynamic phantoms demonstrated a significant improvement (166%-276%) in lesion detection SNR with MRI-based motion correction as compared with gating (P < 0.001). This improvement was 43%-92% for large motion compared with lesion detection without motion correction (P < 0.001). CHO SNR in the rabbit studies confirmed these results.Tagged MRI motion correction in simultaneous PET/MRI significantly improves lesion detection compared with respiratory gating and no motion correction while reducing radiation dose. In vivo primate and rabbit studies confirmed the improvement in PET image quality and provide the rationale for evaluation in simultaneous whole-body PET/MRI clinical studies.
| S-EPMC4077320 | biostudies-literature
Project description:To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence.Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs.To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results, demonstrating good feasibility and applicability of the proposed method.The authors have developed a novel method to estimate the nonrigid motion of GOIs in the presence of spatial intensity and contrast variations, taking advantage of robust shape features. Quantitative analysis and qualitative evaluation demonstrated good promise of the proposed method. Further clinical assessment and validation is being performed.
| S-EPMC3855165 | biostudies-other
Project description:Accurate cardiac motion estimation from medical images such as ultrasound is important for clinical evaluation. We present a novel regularisation layer for cardiac motion estimation that will be applied after image registration and demonstrate its effectiveness. The regularisation utilises a spatio-temporal model of motion, b-splines of Fourier, to fit to displacement fields from pairwise image registration. In the process, it enforces spatial and temporal smoothness and consistency, cyclic nature of cardiac motion, and better adherence to the stroke volume of the heart. Flexibility is further given for inclusion of any set of registration displacement fields. The approach gave high accuracy. When applied to human adult Ultrasound data from a Cardiac Motion Analysis Challenge (CMAC), the proposed method is found to have 10% lower tracking error over CMAC participants. Satisfactory cardiac motion estimation is also demonstrated on other data sets, including human fetal echocardiography, chick embryonic heart ultrasound images, and zebrafish embryonic microscope images, with the average Dice coefficient between estimation motion and manual segmentation at 0.82-0.87. The approach of performing regularisation as an add-on layer after the completion of image registration is thus a viable option for cardiac motion estimation that can still have good accuracy. Since motion estimation algorithms are complex, dividing up regularisation and registration can simplify the process and provide flexibility. Further, owing to a large variety of existing registration algorithms, such an approach that is usable on any algorithm may be useful.
| S-EPMC7595231 | biostudies-literature
Project description:A test-retest study of FreeSurfer derived cortical thickness, cortical surface area, and cortical volume, as well as quantitative R1 relaxometry assessed on the midpoint of the cortex, was performed on a cohort of pediatric subjects (6-12 years old) scanned without sedation using SNARE-MPnRAGE (self navigated retrospective motion corrected magnetization prepared with n rapid gradient echoes) imaging. Reliability was assessed with coefficients of variation (CoVs) and intraclass correlation coefficients (ICCs) and statistical tests were used to determine differences with and without SNARE motion correction. Comparison of the test-retest measures of SNARE-MPnRAGE with prospectively motion corrected PROMO MPRAGE were also performed. When SNARE motion correction was used all parameters had statistically significant improvements and demonstrated high reliability. Reliability varied depending on parameter, region, and measurement type (vertex or region of interest). For mean thickness/surface area/volume/mean R1 across the regions of FreeSurfer's DK Atlas, the mean CoVs (% x100) were (1.2/1.6/1.9/0.9) and the mean ICCs were (0.88/0.96/0.94/0.83). When assessed on a per-vertex basis, the CoVs and ICCs for thickness/R1 had mean values of (2.9/1.9) and (0.82/0.68) across the regions of the DK Atlas. Retrospectively motion corrected MPnRAGE had significantly lower CoVs and higher ICCs for the morphological measures than PROMO MPRAGE. Motion correction effectively removed motion related biases in nearly all regions for R1 and morphometric measures.
| S-EPMC8525331 | biostudies-literature
Project description:PurposeEstablishing a framework to evaluate performances of prospective motion correction (PMC) MRI considering motion variability between MRI scans.MethodsA framework was developed to obtain quantitative comparisons between different motion correction setups, considering that varying intrinsic motion patterns between acquisitions can induce bias. Intrinsic motion was considered by replaying in a phantom experiment the recorded motion trajectories from subjects. T1-weighted MRI on five volunteers and two different marker fixations (mouth guard and nose bridge fixations) were used to test the framework. Two metrics were investigated to quantify the improvement of the image quality with PMC.ResultsMotion patterns vary between subjects as well as between repeated scans within a subject. This variability can be approximated by replaying the motion in a distinct phantom experiment and used as a covariate in models comparing motion corrections. We show that considering the intrinsic motion alters the statistical significance in comparing marker fixations. As an example, two marker fixations, a mouth guard and a nose bridge, were evaluated in terms of their effectiveness for PMC. A mouth guard achieved better PMC performance.ConclusionIntrinsic motion patterns can bias comparisons between PMC configurations and must be considered for robust evaluations. A framework for evaluating intrinsic motion patterns in PMC is presented.
| S-EPMC4567538 | biostudies-literature
Project description:PURPOSE:To provide nonrigid respiratory motion-corrected DCE-MRI images with isotropic resolution of 1.5 mm, full coverage of abdomen, and covering the entire uptake curve with a temporal resolution of 6 seconds, for the quantitative assessment of hepatic lesions. METHODS:3D DCE-MRI data were acquired at 3 T during free breathing for 5 minutes using a 3D T1 -weighted golden-angle radial phase-encoding sequence. Nonrigid respiratory motion information was extracted and used in motion-corrected image reconstruction to obtain high-quality DCE-MRI images with temporal resolution of 6 seconds and isotropic resolution of 1.5 mm. An extended Tofts model was fitted to the dynamic data sets, yielding quantitative parametric maps of endothelial permeability using the hepatic artery as input function. The proposed approach was evaluated in 11 patients (52 ± 17 years, 5 men) with and without known hepatic lesions, undergoing DCE-MRI. RESULTS:Respiratory motion produced artifacts and misalignment between dynamic volumes (lesion average motion amplitude of 3.82 ± 1.11 mm). Motion correction minimized artifacts and improved average contrast-to-noise ratio of hepatic lesions in late phase by 47% (p < .01). Quantitative endothelial permeability maps of motion-corrected data demonstrated enhanced visibility of different pathologies (e.g., metastases, hemangiomas, cysts, necrotic tumor substructure) and showed improved contrast-to-noise ratio by 62% (p < .01) compared with uncorrected data. CONCLUSION:3D nonrigid motion correction in DCE-MRI improves both visual and quantitative assessment of hepatic lesions by ensuring accurate alignment between 3D DCE images and reducing motion blurring. This approach does not require breath-holds and minimizes scan planning by using a large FOV with isotropic resolution.
| S-EPMC6771884 | biostudies-other