Background: Myocardial strain is an important measure of cardiac function and can be assessed on cardiac magnetic resonance (MR) through the current gold standard of breath-held segmented steady-state free precession (SSFP) cine imaging. Novel free-breathing techniques have been validated for volumetry and systolic function, allowing for evaluation of sicker and younger children who cannot reliably hold their breath. It is unclear whether strain measurements can be reliably performed on free-breathing, motion-corrected, re-binning cine images.
Objective: To compare strain analysis from motion-corrected retrospective re-binning images to the breath-held SSFP cine images to explore their validity.
Materials And Methods: Twenty-five children and young adults, ages (2.1-18.6 years) underwent breath-held and motion-corrected retrospective re-binning cine techniques during the same MR examination on a 1.5-tesla magnet. We measured endocardial end-systolic global circumferential strain and endocardial averaged segmental strain using commercial software (MEDIS QStrain 2.1). We used Pearson correlation coefficients to test agreement across techniques.
Results: Analysis was possible in all 25 breath-held and motion-corrected retrospective re-binning studies. Global circumferential strain and endocardial averaged segmental strain obtained by motion-corrected retrospective re-binning compared favorably to breath-held studies. Global circumferential strain linear regression models demonstrated acceptable agreement, with coefficients of determination of 0.75 for breath-held compared to motion-corrected retrospective re-binning (P<0.001) and for endocardial averaged segmental strain comparisons yielded 0.77 for breath-held vs. motion-corrected retrospective re-binning (P<0.001). Bland-Altman assessment demonstrated minimal bias for breath-held compared to motion-corrected retrospective re-binning (mean 2.4 and 1.9, respectively, for global circumferential strain and endocardial averaged segmental strain).
Conclusion: Free-breathing imaging by motion-corrected retrospective re-binning cine imaging provides adequate spatial and temporal resolution to measure myocardial deformation when compared to the gold-standard breath-held SSFP cine imaging in children with normal or borderline systolic function.
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http://dx.doi.org/10.1007/s00247-018-4251-4 | DOI Listing |
Magn Reson Med
March 2025
Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS, University Bordeaux, Bordeaux, France.
Purpose: Several barriers prevent the use of whole-brain T mapping in routine use despite increasing interest in this parameter. One of the main barriers is the long scan time resulting in patient discomfort and motion corrupted data. To address this challenge, a method for accurate whole-brain T mapping with a limited acquisition time and motion correction capabilities is investigated.
View Article and Find Full Text PDFNeuroimage
October 2024
Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
Background: Three-dimensional (3D) T1-weighted MRI sequences such as the magnetization prepared rapid gradient echo (MPRAGE) sequence are important for assessing regional cortical atrophy in the clinical evaluation of dementia but have long acquisition times and are prone to motion artifact. The recently developed Scout Accelerated Motion Estimation and Reduction (SAMER) retrospective motion correction method addresses motion artifact within clinically-acceptable computation times and has been validated through qualitative evaluation in inpatient and emergency settings.
Methods: We evaluated the quantitative accuracy of morphometric analysis of SAMER motion-corrected compared to non-motion-corrected MPRAGE images by estimating cortical volume and thickness across neuroanatomical regions in two subject groups: (1) healthy volunteers and (2) patients undergoing evaluation for dementia.
Front Psychiatry
June 2024
Centre of Precision Rehabilitation for Spinal Pain, School of Sports Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom.
Background And Purpose: There are distinct challenges in the preprocessing of spinal cord fMRI data, particularly concerning the mitigation of voluntary or involuntary movement artifacts during image acquisition. Despite the notable progress in data processing techniques for movement detection and correction, applying motion correction algorithms developed for the brain cortex to the brainstem and spinal cord remains a challenging endeavor.
Methods: In this study, we employed a deep learning-based convolutional neural network (CNN) named DeepRetroMoCo, trained using an unsupervised learning algorithm.
EJNMMI Phys
June 2024
Division of Nuclear Medicine, Department of Radiology, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 10, 63-ro, Yeongdeungpo-gu, Seoul, 07345, Republic of Korea.
Background: Head motion during brain positron emission tomography (PET)/computed tomography (CT) imaging degrades image quality, resulting in reduced reading accuracy. We evaluated the performance of a head motion correction algorithm using F-flutemetamol (FMM) brain PET/CT images.
Methods: FMM brain PET/CT images were retrospectively included, and PET images were reconstructed using a motion correction algorithm: (1) motion estimation through 3D time-domain signal analysis, signal smoothing, and calculation of motion-free intervals using a Merging Adjacent Clustering method; (2) estimation of 3D motion transformations using the Summing Tree Structural algorithm; and (3) calculation of the final motion-corrected images using the 3D motion transformations during the iterative reconstruction process.
Magn Reson Med
November 2024
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Purpose: This study leverages externally generated Pilot Tone (PT) signals to perform motion-corrected brain MRI for sequences with arbitrary k-space sampling and image contrast.
Theory And Methods: PT signals are promising external motion sensors due to their cost-effectiveness, easy workflow, and consistent performance across contrasts and sampling patterns. However, they lack robust calibration pipelines.
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