Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias.

Early identification of atrial fibrillation (AF) can reduce the risk of stroke, heart failure, and other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even after a two-week continuous monitoring period. We developed a model to quantify the risk of near-term AF in a two-week period, based on AF-free ECG intervals of up to 24 h from 459,889 patch-based ambulatory single-lead ECG (modified lead II) recordings of up to 14 days. A deep learning model was used to integrate ECG morphology data with demographic and heart rhythm features toward AF prediction. Observing a 1-day AF-free ECG recording, the model with deep learning features produced the most accurate prediction of near-term AF with an area under the curve AUC = 0.80 (95% confidence interval, CI = 0.79-0.81), significantly improving discrimination compared to demographic metrics alone (AUC 0.67; CI = 0.66-0.68). Our model was able to predict incident AF over a two-week time frame with high discrimination, based on AF-free single-lead ECG recordings of various lengths. Application of the model may enable a digital strategy for improving diagnostic capture of AF by risk stratifying individuals with AF-negative ambulatory monitoring for prolonged or recurrent monitoring, potentially leading to more rapid initiation of treatment.

Magnetic resonance elastography (MRE) shows significant reduction of thigh muscle stiffness in healthy older adults.

Determining the effect of ageing on thigh muscle stiffness using magnetic resonance elastography (MRE) and investigate whether fat fraction and muscle cross-sectional area (CSA) are related to stiffness. Six healthy older adults in their eighth and ninth decade and eight healthy young men were recruited and underwent a 3 T MRI protocol including MRE and Dixon fat fraction imaging. Muscle stiffness, fat fraction and muscle CSA were calculated in ROIs corresponding to the four quadriceps muscles (i.e. vastus lateralis (VL), vastus medialis (VM), vastus intermedius (VI), rectus femoris (RF)), combined quadriceps, combined hamstrings and adductors and whole thigh. Muscle stiffness was significantly reduced (p < 0.05) in the older group in all measured ROIs except the VI (p = 0.573) and RF (p = 0.081). Similarly, mean fat fraction was significantly increased (p < 0.05) in the older group over all ROIs with the exception of the VI (p = 0.059) and VL muscle groups (p = 0.142). Muscle CSA was significantly reduced in older participants in the VM (p = 0.003) and the combined quadriceps (p = 0.001), hamstrings and adductors (p = 0.008) and whole thigh (p = 0.003). Over the whole thigh, stiffness was significantly negatively correlated with fat fraction (r = - 0.560, p = 0.037) and positively correlated with CSA (r = 0.749, p = 0.002). Stepwise regression analysis revealed that age was the most significant predictor of muscle stiffness (p = 0.001). These results suggest that muscle stiffness is significantly decreased in healthy older adults. Muscle fat fraction and muscle CSA are also significantly changed in older adults; however, age is the most significant predictor of muscle stiffness.

Fast Robust Dejitter and Interslice Discontinuity Removal in MRI Phase Acquisitions: Application to Magnetic Resonance Elastography.

MRI phase contrast imaging methods that assemble slice-wise acquisitions into volumes can contain interslice phase discontinuities (IPDs) over the course of the scan from sources, including unavoidable physiological activity. In magnetic resonance elastography (MRE), this can alter wavelength and tissue stiffness estimates, invalidating the analysis. We first model this behavior as jitter along the z-axis of the phase of 3D complex-valued wave volumes. A two-step image processing pipeline is then proposed that removes IPDs. First, constant slicewise phase shift is removed with a novel, non-convex dejittering algorithm. Then, regional physiological noise artifacts are removed with novel filtering of 3D wavelet coefficients. Calibration of two pipeline coefficients, the dejitter parameter α and the wavelet band high-pass coefficient ωc , was first performed on a finite-element method brain phantom. A comparative investigation was then performed, on a cohort of 48 brain acquisitions, of four approaches to IPDs: 1) the proposed method; 2) a "control" condition of neglect of IPDs; 3) an anisotropic wavelet-based method; and 4) a method of in-plane (2D) processing. The present method showed medians of [Formula: see text] Pa for a multifrequency wave inversion centered at 40 Hz which was within 6% of methods 3) and 4), while neglect produced [Formula: see text] estimates a mean of 17% lower. The proposed method reduced the value range of the cohort against methods 3) and 4) by 29% and 31%, respectively. Such reduction in variance enhances the ability of brain MRE to predict subtler physiological changes. Our theoretical approach further enables more powerful applications of fundamental findings in noise and denoising to MRE.

Fast tomoelastography of the mouse brain by multifrequency single-shot MR elastography.

PURPOSE: To introduce in vivo multifrequency single-shot magnetic resonance elastography for full-FOV stiffness mapping of the mouse brain and to compare in vivo stiffness of neural tissues with different white-to-gray matter ratios. METHODS: Viscous phantoms and 10 C57BL-6 mice were investigated by 7T small-animal MRI using a single-shot spin-echo planar imaging magnetic resonance elastography sequence with motion-encoding gradients positioned before the refocusing pulse. Wave images were acquired over 10 minutes for 6 mechanical vibration frequencies between 900 and 1400 Hz. Stiffness maps of shear wave speed (SWS) were computed using tomoelastography data processing and compared with algebraic Helmholtz inversion (AHI) for signal-to-noise ratio (SNR) analysis. Different brain regions were analyzed including cerebral cortex, corpus callosum, hippocampus, and diencephalon. RESULTS: In phantoms, algebraic Helmholtz inversion-based SWS was systematically biased by noise and discretization, whereas tomoelastography-derived SWS was consistent over the full SNR range analyzed. Mean in vivo SWS of the whole brain was 3.76 ± 0.33 m/s with significant regional variation (hippocampus = 4.91 ± 0.49 m/s, diencephalon = 4.78 ± 0.78 m/s, cerebral cortex = 3.53 ± 0.29 m/s, and corpus callosum = 2.89 ± 0.17 m/s). CONCLUSION: Tomoelastography retrieves mouse brain stiffness within shorter scan times and with greater detail resolution than classical algebraic Helmholtz inversion-based magnetic resonance elastography. The range of SWS values obtained here indicates that mouse white matter is softer than gray matter at the frequencies investigated.

Heterogeneous Multifrequency Direct Inversion (HMDI) for magnetic resonance elastography with application to a clinical brain exam.

A new viscoelastic wave inversion method for MRE, called Heterogeneous Multifrequency Direct Inversion (HMDI), was developed which accommodates heterogeneous elasticity within a direct inversion (DI) by incorporating first-order gradients and combining results from a narrow band of multiple frequencies. The method is compared with a Helmholtz-type DI, Multifrequency Dual Elasto-Visco inversion (MDEV), both on ground-truth Finite Element Method simulations at varied noise levels and a prospective in vivo brain cohort of 48 subjects ages 18-65. In simulated data, MDEV recovered background material within 5% and HMDI within 1% of prescribed up to SNR of 20 dB. In vivo HMDI and MDEV were then combined with segmentation from SPM to create a fully automated "brain palpation" exam for both whole brain (WB), and brain white matter (WM), measuring two parameters, the complex modulus magnitude |G*| , which measures tissue "stiffness", and the slope of |G*| values across frequencies, a measure of viscous dispersion. |G*| values for MDEV and HMDI were comparable to the literature (for a 3-frequency set centered at 50 Hz, WB means were 2.17 and 2.15 kPa respectively, and WM means were 2.47 and 2.49 kPa respectively). Both methods showed moderate correlation to age in both WB and WM, for both |G*| and |G*| slope, with Pearson's r ≥ 0.4 in the most sensitive frequency sets. In comparison to MDEV, HMDI showed better preservation of recovered target shapes, more noise-robustness, and stabler recovery values in regions with rapid property change, however summary statistics for both methods were quite similar. By eliminating homogeneity assumptions within a fast, fully automatic, regularization-free direct inversion, HMDI appears to be a worthwhile addition to the MRE image reconstruction repertoire. In addition to supporting the literature showing decrease in brain viscoelasticity with age, our work supports a wide range of inter-individual variation in brain MRE results.

Perfusion alters stiffness of deep gray matter.

Viscoelastic properties of the brain reflect tissue architecture at multiple length scales. However, little is known about the relation between vital tissue functions, such as perfusion, and the macroscopic mechanical properties of cerebral tissue. In this study, arterial spin labelling is paired with magnetic resonance elastography to investigate the relationship between tissue stiffness and cerebral blood flow (CBF) in the in vivo human brain. The viscoelastic modulus, | G*|, and CBF were studied in deep gray matter (DGM) of 14 healthy male volunteers in the following sub-regions: putamen, nucleus accumbens, hippocampus, thalamus, globus pallidus, and amygdala. CBF was further normalized by vessel area data to obtain the flux rate q which is proportional to the perfusion pressure gradient. The striatum (represented by putamen and nucleus accumbens) was distinct from the other DGM regions by displaying markedly higher stiffness and perfusion values. q was a predictive marker for DGM stiffness as analyzed by linear regression | G*| = q·(4.2 ± 0.6)kPa·s + (0.80 ± 0.06)kPa ( R2 = 0.92, P = 0.006). These results suggest a high sensitivity of MRE in DGM to perfusion pressure. The distinct mechano-vascular properties of striatum tissue, as compared to the rest of DGM, may reflect elevated perfusion pressure, which could explain the well-known susceptibility of the putamen to hemorrhages.

MR elastography measurement of the effect of passive warmup prior to eccentric exercise on thigh muscle mechanical properties.

PURPOSE: To investigate the effect of warmup by application of the thermal agent Deep Heat (DH) on muscle mechanical properties using magnetic resonance elastography (MRE) at 3T before and after exercise-induced muscle damage (EIMD). MATERIALS AND METHODS: Twenty male participants performed an individualized protocol designed to induce EIMD in the quadriceps. DH was applied to the thigh in 50% of the participants before exercise. MRE, T2 -weighted MRI, maximal voluntary contraction (MVC), creatine kinase (CK) concentration, and muscle soreness were measured before and after the protocol to assess EIMD effects. Five participants were excluded: four having not experienced EIMD and one due to incidental findings. RESULTS: Total workload performed during the EIMD protocol was greater in the DH group than the control group (P < 0.03), despite no significant differences in baseline MVC (P = 0.23). Shear stiffness |G*| increased in the rectus femoris (RF) muscle in both groups (P < 0.03); however, DH was not a significant between-group factor (P = 0.15). MVC values returned to baseline faster in the DH group (5 days) than the control group (7 days). Participants who displayed hyperintensity on T2 -weighted images had a greater stiffness increase following damage than those without: RF; 0.61 kPa vs. 0.15 kPa, P < 0.006, vastus intermedius; 0.34 kPa vs. 0.03 kPa, P = 0.06. CONCLUSION: EIMD produces increased muscle stiffness as measured by MRE, with the change in |G*| significantly increased when T2 hyperintensity was present. DH did not affect CK concentration or soreness; however, DH participants produced greater workload during the EIMD protocol and exhibited accelerated MVC recovery. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1115-1127.

Nonlinear multiscale regularisation in MR elastography: Towards fine feature mapping.

Fine-featured elastograms may provide additional information of radiological interest in the context of in vivo elastography. Here a new image processing pipeline called ESP (Elastography Software Pipeline) is developed to create Magnetic Resonance Elastography (MRE) maps of viscoelastic parameters (complex modulus magnitude |G*| and loss angle ϕ) that preserve fine-scale information through nonlinear, multi-scale extensions of typical MRE post-processing techniques. METHODS: A new MRE image processing pipeline was developed that incorporates wavelet-domain denoising, image-driven noise estimation, and feature detection. ESP was first validated using simulated data, including viscoelastic Finite Element Method (FEM) simulations, at multiple noise levels. ESP images were compared with MDEV pipeline images, both in the FEM models and in three ten-subject cohorts of brain, thigh, and liver acquisitions. ESP and MDEV mean values were compared to 2D local frequency estimation (LFE) mean values for the same cohorts as a benchmark. Finally, the proportion of spectral energy at fine frequencies was quantified using the Reduced Energy Ratio (RER) for both ESP and MDEV. RESULTS: Blind estimates of added noise (σ) were within 5.3% ± 2.6% of prescribed, and the same technique estimated σ in the in vivo cohorts at 1.7 ± 0.8%. A 5 × 5 × 5 truncated Gabor filter bank effectively detects local spatial frequencies at wavelengths λ ≤ 10px. For FEM inversions, mean |G*| of hard target, soft target, and background remained within 8% of prescribed up to σ=20%, and mean ϕ results were within 10%, excepting hard target ϕ, which required redrawing around a ring artefact to achieve similar accuracy. Inspection of FEM |G*| images showed some spatial distortion around hard target boundaries and inspection of ϕ images showed ring artefacts around the same target. For the in vivo cohorts, ESP results showed mean correlation of R=0.83 with MDEV and liver stiffness estimates within 7% of 2D-LFE results. Finally, ESP showed statistically significant increase in fine feature spectral energy as measured with RER for both |G*| (p<1×10-9) and ϕ (p<1×10-3). CONCLUSION: Information at finer frequencies can be recovered in ESP elastograms in typical experimental conditions, however scatter- and boundary-related artefacts may cause the fine features to have inaccurate values. In in vivo cohorts, ESP delivers an increase in fine feature spectral energy, and better performance with longer wavelengths, than MDEV while showing similar stability and robustness.

Tomoelastography of the abdomen: Tissue mechanical properties of the liver, spleen, kidney, and pancreas from single MR elastography scans at different hydration states.

PURPOSE: To develop a compact magnetic resonance elastography (MRE) protocol for abdomen and to investigate the effect of water uptake on tissue stiffness in the liver, spleen, kidney, and pancreas. METHODS: Nine asymptomatic volunteers were investigated by MRE before and after 1 liter water uptake. Shear-wave excitation at four frequencies was transferred to the abdomen from anterior and posterior directions using pressurized air drivers. Tomographic representations of shear-wave speed were produced by analysis of multifrequency wave numbers in axial and coronal images acquired within four breath-holds or under free breathing, respectively. RESULTS: Pre and post water, stiffness of the spleen (pre/post: 2.20 ± 0.10/2.06 ± 0.18 m/s) and kidney (pre/post: 1.93 ± 0.22/1.97 ± 0.23 m/s) was higher than in the liver (pre/post: 1.36 ± 0.10/1.38 ± 0.13 m/s) and pancreas (pre/post: 1.20 ± 0.12/1.20 ± 0.08 m/s), all P < 0.01. Accounting for four drive frequencies, water drinking only changed the splenic stiffness (-6%, P = 0.03), whereas in the frequency range from 50 to 60 Hz the effect became significant also in the pancreas (-6%, P = 0.04) and liver (+3%, P = 0.03). Elastograms of the kidney in coronal view clearly depicted higher stiffness in cortex than in medulla. CONCLUSION: Tomoelastography reveals sensitivity of tissue mechanical properties to the hydration state of multiple abdominal organs within one scan and in unprecedented resolution of anatomical details. Magn Reson Med 78:976-983, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Increasing the spatial resolution and sensitivity of magnetic resonance elastography by correcting for subject motion and susceptibility-induced image distortions.

PURPOSE: To improve the resolution of elasticity maps by adapting motion and distortion correction methods for phase-based magnetic resonance imaging (MRI) contrasts such as magnetic resonance elastography (MRE), a technique for measuring mechanical tissue properties in vivo. MATERIALS AND METHODS: MRE data of the brain were acquired with echo-planar imaging (EPI) at 3T (n = 14) and 7T (n = 18). Motion and distortion correction parameters were estimated using the magnitude images. The real and imaginary part of the complex MRE data were corrected separately and recombined. The width of the point-spread function (PSF) and the position variability were calculated. The images were normalized to the Montreal Neurological Institute (MNI) anatomical template. The gray-to-white matter separability of the elasticity maps was tested. RESULTS: Motion correction sharpened the |G*| maps as demonstrated by a narrowing of the PSF by 0.78 ± 0.51 mm at 7T and 0.52 ± 0.63 mm at 3T. The amount of individual head motion during MRE acquisition correlated with the decrease in the width of the PSF at 7T (r = 0.53, P = 0.025) and at 3T (r = 0.69, P = 0.006) and with the increase of gray-to-white matter separability after motion correction at 7T (r = 0.64, P = 0.0039) and at 3T (r = 0.57, P = 0.0319). Improved spatial accuracy after distortion correction results in a significant increase in separability of gray and white matter stiffness (P = 0.0067), especially in inferior parts of the brain suffering from strong B0 inhomogeneities. CONCLUSION: We demonstrate that our method leads to sharper images and higher spatial accuracy, raising the prospect of the investigation of smaller brain areas with increased sensitivity in studies using MRE. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:134-141.

Magnetic resonance elastography (MRE) of the human brain: technique, findings and clinical applications.

Neurological disorders are one of the most important public health concerns in developed countries. Established brain imaging techniques such as magnetic resonance imaging (MRI) and x-ray computerised tomography (CT) have been essential in the identification and diagnosis of a wide range of disorders, although usually are insufficient in sensitivity for detecting subtle pathological alterations to the brain prior to the onset of clinical symptoms-at a time when prognosis for treatment is more favourable. The mechanical properties of biological tissue provide information related to the strength and integrity of the cellular microstructure. In recent years, mechanical properties of the brain have been visualised and measured non-invasively with magnetic resonance elastography (MRE), a particularly sensitive medical imaging technique that may increase the potential for early diagnosis. This review begins with an introduction to the various methods used for the acquisition and analysis of MRE data. A systematic literature search is then conducted to identify studies that have specifically utilised MRE to investigate the human brain. Through the conversion of MRE-derived measurements to shear stiffness (kPa) and, where possible, the loss tangent (rad), a summary of results for global brain tissue and grey and white matter across studies is provided for healthy participants, as potential baseline values to be used in future clinical investigations. In addition, the extent to which MRE has revealed significant alterations to the brain in patients with neurological disorders is assessed and discussed in terms of known pathophysiology. The review concludes by predicting the trends for future MRE research and applications in neuroscience.

Tomoelastography by multifrequency wave number recovery from time-harmonic propagating shear waves.

Palpation is one of the most sensitive, effective diagnostic practices, motivating the quantitative and spatially resolved determination of soft tissue elasticity parameters by medical ultrasound or MRI. However, this so-called elastography often suffers from limited anatomical resolution due to noise and insufficient elastic deformation, currently precluding its use as a tomographic modality on its own. We here introduce an efficient way of processing wave images acquired by multifrequency magnetic resonance elastography (MMRE), which relies on wave number reconstruction at different harmonic frequencies followed by their amplitude-weighted averaging prior to inversion. This results in compound maps of wave speed, which reveal variations in tissue elasticity in a tomographic fashion, i.e. an unmasked, slice-wise display of anatomical details at pixel-wise resolution. The method is demonstrated using MMRE data from the literature including abdominal and pelvic organs such as the liver, spleen, uterus body and uterus cervix. Even in small regions with low wave amplitudes, such as nucleus pulposus and spinal cord, elastic parameters consistent with literature values were obtained. Overall, the proposed method provides a simple and noise-robust strategy of in-plane wave analysis of MMRE data, with a pixel-wise resolution producing superior detail to MRE direct inversion methods.

Real-time 4D phase unwrapping applied to magnetic resonance elastography.

PURPOSE: Phase amplitude is a source of signal in magnetic resonance elastography (MRE) experiments but its exploitation in experimental design has been limited due to the challenges of phase wrap. This study addressed this aspect of MRE through new developments in algorithms, heuristic strategy, and user interface. METHODS: A test dataset with systematic variation of three parameters-nested wrap, gradient, and noise level-was developed to choose phase-unwrapping algorithms and to analyze their performance. A new application, PhaseTools, was developed that implemented three phase-unwrapping algorithms that adhere to a "real-time" criterion of less than 3 min for a four-dimensional MRE acquisition. Two of the algorithms extend previously published algorithms and one was newly developed. The algorithms were then applied to five datasets from MRE, two typical cases and three edge cases that were particularly challenging in one of the three parameters. RESULTS: The performance of the PhaseTools algorithms on the test dataset was comparable to two widely cited algorithms that take hours or days to complete. Guidelines for the optimal use of each algorithm are established. CONCLUSION: PhaseTools enables the substantial increase of signal-to-noise in MRE experiments at negligible additional computational cost. PhaseTools is freely released with this study, making robust real-time phase unwrapping available to any group using phase-based imaging.

Statistical mapping of the effect of knee extension on thigh muscle viscoelastic properties using magnetic resonance elastography.

Skeletal muscle viscoelastic properties reflect muscle microstructure and neuromuscular activation. Elastographic methods, including magnetic resonance elastography, have been used to characterize muscle viscoelastic properties in terms of region of interest (ROI) measurements. The present study extended this approach to create thresholded pixel-by-pixel maps of viscoelastic properties of skeletal muscle during rest and knee extension in eleven subjects. ROI measurements were taken for individual quadricep muscles and the quadriceps region as a whole, and the viscoelastic parameter map pixels were statistically tested at positive false discovery rate q ≤ 0.25. ROI measurements showed significant (p ≤ 0.05) increase in storage modulus (G') and loss modulus (G″), with G″ increasing more than G', in agreement with previous findings. The q-value maps further identified the vastus intermedius as the primary driver of this change, with greater G″/G' increase than surrounding regions. Additionally, a cluster of significant decrease in G″/G' was found in the region of vastus lateralis below the fulcrum point of the lift. Viscoelastic parameter mapping of contracted muscle allows new insight into the relationship between physiology, neuromuscular activation, and human performance.