A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images

Real-time magnetic resonance imaging (RT-MRI) of human speech production is enabling significant advances in speech science, linguistics, bio-inspired speech technology development, and clinical applications. Easy access to RT-MRI is however limited, and comprehensive datasets with broad access are needed to catalyze research across numerous domains. The imaging of the rapidly moving articulators and dynamic airway shaping during speech demands high spatio-temporal resolution and robust reconstruction methods. Further, while reconstructed images have been published, to-date there is no open dataset providing raw multi-coil RT-MRI data from an optimized speech production experimental setup. Such datasets could enable new and improved methods for dynamic image reconstruction, artifact correction, feature extraction, and direct extraction of linguistically-relevant biomarkers. The present dataset offers a unique corpus of 2D sagittal-view RT-MRI videos along with synchronized audio for 75 subjects performing linguistically motivated speech tasks, alongside the corresponding first-ever public domain raw RT-MRI data. The dataset also includes 3D volumetric vocal tract MRI during sustained speech sounds and high-resolution static anatomical T2-weighted upper airway MRI for each subject.Comment: 27 pages, 6 figures, 5 tables, submitted to Nature Scientific Dat

Real-Time Magnetic Resonance Imaging

Real‐time magnetic resonance imaging (RT‐MRI) allows for imaging dynamic processes as they occur, without relying on any repetition or synchronization. This is made possible by modern MRI technology such as fast‐switching gradients and parallel imaging. It is compatible with many (but not all) MRI sequences, including spoiled gradient echo, balanced steady‐state free precession, and single‐shot rapid acquisition with relaxation enhancement. RT‐MRI has earned an important role in both diagnostic imaging and image guidance of invasive procedures. Its unique diagnostic value is prominent in areas of the body that undergo substantial and often irregular motion, such as the heart, gastrointestinal system, upper airway vocal tract, and joints. Its value in interventional procedure guidance is prominent for procedures that require multiple forms of soft‐tissue contrast, as well as flow information. In this review, we discuss the history of RT‐MRI, fundamental tradeoffs, enabling technology, established applications, and current trends

Cardiac magnetic resonance assessment of central and peripheral vascular function in patients undergoing renal sympathetic denervation as predictor for blood pressure response

Background: Most trials regarding catheter-based renal sympathetic denervation (RDN) describe a proportion of patients without blood pressure response. Recently, we were able to show arterial stiffness, measured by invasive pulse wave velocity (IPWV), seems to be an excellent predictor for blood pressure response. However, given the invasiveness, IPWV is less suitable as a selection criterion for patients undergoing RDN. Consequently, we aimed to investigate the value of cardiac magnetic resonance (CMR) based measures of arterial stiffness in predicting the outcome of RDN compared to IPWV as reference. Methods: Patients underwent CMR prior to RDN to assess ascending aortic distensibility (AAD), total arterial compliance (TAC), and systemic vascular resistance (SVR). In a second step, central aortic blood pressure was estimated from ascending aortic area change and flow sequences and used to re-calculate total arterial compliance (cTAC). Additionally, IPWV was acquired. Results: Thirty-two patients (24 responders and 8 non-responders) were available for analysis. AAD, TAC and cTAC were higher in responders, IPWV was higher in non-responders. SVR was not different between the groups. Patients with AAD, cTAC or TAC above median and IPWV below median had significantly better BP response. Receiver operating characteristic (ROC) curves predicting blood pressure response for IPWV, AAD, cTAC and TAC revealed areas under the curve of 0.849, 0.828, 0.776 and 0.753 (p = 0.004, 0.006, 0.021 and 0.035). Conclusions: Beyond IPWV, AAD, cTAC and TAC appear as useful outcome predictors for RDN in patients with hypertension. CMR-derived markers of arterial stiffness might serve as non-invasive selection criteria for RDN

Rapid dynamic speech imaging at 3 Tesla using combination of a custom vocal tract coil, variable density spirals and manifold regularization

Purpose: To improve dynamic speech imaging at 3 Tesla. Methods: A novel scheme combining a 16-channel vocal tract coil, variable density spirals (VDS), and manifold regularization was developed. Short readout duration spirals (1.3 ms long) were used to minimize sensitivity to off-resonance. The manifold model leveraged similarities between frames sharing similar vocal tract postures without explicit motion binning. Reconstruction was posed as a SENSE-based non-local soft weighted temporal regularization scheme. The self-navigating capability of VDS was leveraged to learn the structure of the manifold. Our approach was compared against low-rank and finite difference reconstruction constraints on two volunteers performing repetitive and arbitrary speaking tasks. Blinded image quality evaluation in the categories of alias artifacts, spatial blurring, and temporal blurring were performed by three experts in voice research. Results: We achieved a spatial resolution of 2.4mm2/pixel and a temporal resolution of 17.4 ms/frame for single slice imaging, and 52.2 ms/frame for concurrent 3-slice imaging. Implicit motion binning of the manifold scheme for both repetitive and fluent speaking tasks was demonstrated. The manifold scheme provided superior fidelity in modeling articulatory motion compared to low rank and temporal finite difference schemes. This was reflected by higher image quality scores in spatial and temporal blurring categories. Our technique exhibited faint alias artifacts, but offered a reduced interquartile range of scores compared to other methods in alias artifact category. Conclusion: Synergistic combination of a custom vocal-tract coil, variable density spirals and manifold regularization enables robust dynamic speech imaging at 3 Tesla.Comment: 30 pages, 10 figure

Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI

Objective. Imaging dynamic object with high temporal resolution is challenging in magnetic resonance imaging (MRI). Partial separable (PS) model was proposed to improve the imaging quality by reducing the degrees of freedom of the inverse problem. However, PS model still suffers from long acquisition time and even longer reconstruction time. The main objective of this study is to accelerate the PS model, shorten the time required for acquisition and reconstruction, and maintain good image quality simultaneously. Approach. We proposed to fully exploit the dimension reduction property of the PS model, which means implementing the optimization algorithm in subspace. We optimized the data consistency term, and used a Tikhonov regularization term based on the Frobenius norm of temporal difference. The proposed dimension-reduced optimization technique was validated in free-running cardiac MRI. We have performed both retrospective experiments on public dataset and prospective experiments on in-vivo data. The proposed method was compared with four competing algorithms based on PS model, and two non-PS model methods. Main results. The proposed method has robust performance against shortened acquisition time or suboptimal hyper-parameter settings, and achieves superior image quality over all other competing algorithms. The proposed method is 20-fold faster than the widely accepted PS+Sparse method, enabling image reconstruction to be finished in just a few seconds. Significance. Accelerated PS model has the potential to save much time for clinical dynamic MRI examination, and is promising for real-time MRI applications.Comment: 23 pages, 11 figures. Accepted as manuscript on Physics in Medicine & Biolog

Fast upper airway magnetic resonance imaging for assessment of speech production and sleep apnea

The human upper airway is involved in various functions, including speech, swallowing, and respiration. Magnetic resonance imaging (MRI) can visualize the motion of the upper airway and has been used in scientific studies to understand the dynamics of vocal tract shaping during speech and for assessment of upper airway abnormalities related to obstructive sleep apnea and swallowing disorders. Acceleration technologies in MRI are crucial in improving spatiotemporal resolution or spatial coverage. Recent trends in technical aspects of upper airway MRI are to develop state-of-the-art image acquisition methods for improved dynamic imaging of the upper airway and develop automatic image analysis methods for efficient and accurate quantification of upper airway parameters of interest. This review covers the fast upper airway magnetic resonance (MR) acquisition and reconstruction, MR experimental issues, image analysis techniques, and applications, mainly with respect to studies of speech production and sleep apnea

High-resolution full-vocal-tract dynamic speech magnetic resonance imaging

Dynamic magnetic resonance imaging (MRI) holds great promise for speech-related studies because of its potential to investigate velopharyngeal motion and physiological properties jointly in real time. However, many applications of dynamic speech MRI are limited by the technical trade-offs in imaging speed, spatial coverage, spatial resolution and clinical interpretation. In particular, high-resolution dynamic speech MRI with full-vocal-tract coverage and phonetically meaningful interpretation remains a challenging goal for many speech researchers. This dissertation develops novel model-based dynamic speech MRI approaches to enable high-resolution, full-vocal-tract 3D dynamic speech MRI with quantitative characterization of the articulatory motion. Our approaches include technical developments in imaging models, data acquisition strategies and image reconstruction methods: (a) high-spatiotemporal-resolution speech MRI from sparsely sampled data is achieved by employing a low-rank imaging model that leverages the spatiotemporal correlations in dynamic speech motion; (b) a self-navigated sampling strategy is developed and employed to acquire spatiotemporal data at high imaging speed, which collects high-nominal-frame-rate cone navigators and randomized Cartesian imaging data within a single TR; (c) quantitative interpretation of speech motion is enabled by introducing a deformation-based sparsity constraint that not only improves image reconstruction quality but also analyzes articulatory motion by a high-resolution deformation field; and (d) accurate assessment of subject-specific motion as opposed to generic motion pattern is realized by using a low-rank plus sparse imaging model jointly with a technique to construct high-quality spatiotemporal atlas. Regional sparse modeling is further introduced to assist effective motion analysis in the regions of interest. Our approaches are evaluated through both simulations on numerical phantoms and in vivo validation experiments across multiple subject groups. Both simulation and experimental results allow visualization of articulatory dynamics with a frame rate of 166 frames per second, a spatial resolution of 2.2 mm x 2.2 mm x 5.0 mm, and a spatial coverage of 280 mm x 280 mm x 40 mm covering the entire upper vocal tract across 8 mid-sagittal slices. Deformation fields yielded from our approaches share an identical spatiotemporal resolution that characterizes accurate soft-tissue motion. With a high-quality atlas, the low-rank and the sparse components are reconstructed to reveal both subject-specific motion and generic speech motion across a specific subject group. The effectiveness of our approaches is demonstrated through practical phonetics investigations that include (a) integrative imaging and acoustics analysis of velopharyngeal closure; (b) understanding the formation and variation in a variety of languages, American English, North Metropolitan French, Brazilian Portuguese and Levantine Arabic; and (c) analyzing motion variability of a particular subject with respect to a specific subject group. The capabilities of our method have the potential for precise assessment of the oropharyngeal dynamics and comprehensive evaluation of speech motion