Real-time speech MRI datasets with corresponding articulator ground-truth segmentations.

The use of real-time magnetic resonance imaging (rt-MRI) of speech is increasing in clinical practice and speech science research. Analysis of such images often requires segmentation of articulators and the vocal tract, and the community is turning to deep-learning-based methods to perform this segmentation. While there are publicly available rt-MRI datasets of speech, these do not include ground-truth (GT) segmentations, a key requirement for the development of deep-learning-based segmentation methods. To begin to address this barrier, this work presents rt-MRI speech datasets of five healthy adult volunteers with corresponding GT segmentations and velopharyngeal closure patterns. The images were acquired using standard clinical MRI scanners, coils and sequences to facilitate acquisition of similar images in other centres. The datasets include manually created GT segmentations of six anatomical features including the tongue, soft palate and vocal tract. In addition, this work makes code and instructions to implement a current state-of-the-art deep-learning-based method to segment rt-MRI speech datasets publicly available, thus providing the community and others with a starting point for developing such methods.

A segmentation-informed deep learning framework to register dynamic two-dimensional magnetic resonance images of the vocal tract during speech.

Objective: Dynamic magnetic resonance (MR) imaging enables visualisation of articulators during speech. There is growing interest in quantifying articulator motion in two-dimensional MR images of the vocal tract, to better understand speech production and potentially inform patient management decisions. Image registration is an established way to achieve this quantification. Recently, segmentation-informed deformable registration frameworks have been developed and have achieved state-of-the-art accuracy. This work aims to adapt such a framework and optimise it for estimating displacement fields between dynamic two-dimensional MR images of the vocal tract during speech. Methods: A deep-learning-based registration framework was developed and compared with current state-of-the-art registration methods and frameworks (two traditional methods and three deep-learning-based frameworks, two of which are segmentation informed). The accuracy of the methods and frameworks was evaluated using the Dice coefficient (DSC), average surface distance (ASD) and a metric based on velopharyngeal closure. The metric evaluated if the fields captured a clinically relevant and quantifiable aspect of articulator motion. Results: The segmentation-informed frameworks achieved higher DSCs and lower ASDs and captured more velopharyngeal closures than the traditional methods and the framework that was not segmentation informed. All segmentation-informed frameworks achieved similar DSCs and ASDs. However, the proposed framework captured the most velopharyngeal closures. Conclusions: A framework was successfully developed and found to more accurately estimate articulator motion than five current state-of-the-art methods and frameworks. Significance: The first deep-learning-based framework specifically for registering dynamic two-dimensional MR images of the vocal tract during speech has been developed and evaluated.

Effects of spatial and temporal resolution on cardiovascular magnetic resonance feature tracking measurements using a simple realistic numerical phantom.

OBJECTIVES: To develop a single-slice numerical phantom with known myocardial motion, at several temporal and in-plane spatial resolutions, for testing and comparison of Cardiovascular Magnetic Resonance (CMR) feature tracking (FT) software. METHODS: The phantom was developed based on CMR acquisitions of one volunteer (acquired cine, tagging cine, T1 map, T2 map, proton density weighted image). The numerical MRI simulator JEMRIS was used, and the phantom was generated at several in-plane spatial resolutions (1.4 × 1.4 mm2 to 3.0 × 3.0 mm2) and temporal resolutions (20 to 40 cardiac phases). Two feature tracking software packages were tested: Medical Image Tracking Toolbox (MITT) and two versions of cvi42 (v5.3.8 and v5.13.7). The effect of resolution on strain results was investigated with reference to ground-truth radial and circumferential strain. RESULTS: Peak radial strain was consistently undermeasured more for cvi42 v5.13.7 than for v5.3.8. Increased pixel size produced a trend of increased difference from ground-truth peak strain, with the largest changes for cvi42 obtained using v5.13.7 between 1.4 × 1.4 mm2 and 3.0 × 3.0 mm2, at 9.17 percentage points (radial) and 8.42 percentage points (circumferential). CONCLUSIONS: The results corroborate the presence of intervendor differences in feature tracking results and show the magnitude of strain differences between software versions. ADVANCES IN KNOWLEDGE: This study shows how temporal and in-plane spatial resolution can affect feature tracking with reference to the ground-truth strain of a numerical phantom. Results reaffirm the need for numerical phantom development for the validation and testing of FT software.

Individual differences in vocal size exaggeration.

The human voice carries socially relevant information such as how authoritative, dominant, and attractive the speaker sounds. However, some speakers may be able to manipulate listeners by modulating the shape and size of their vocal tract to exaggerate certain characteristics of their voice. We analysed the veridical size of speakers' vocal tracts using real-time magnetic resonance imaging as they volitionally modulated their voice to sound larger or smaller, corresponding changes to the size implied by the acoustics of their voice, and their influence over the perceptions of listeners. Individual differences in this ability were marked, spanning from nearly incapable to nearly perfect vocal modulation, and was consistent across modalities of measurement. Further research is needed to determine whether speakers who are effective at vocal size exaggeration are better able to manipulate their social environment, and whether this variation is an inherited quality of the individual, or the result of life experiences such as vocal training.

High-resolution quantitative MRI of multiple sclerosis spinal cord lesions.

PURPOSE: Validation of quantitative MR measures for myelin imaging in the postmortem multiple sclerosis spinal cord. METHODS: Four fixed spinal cord samples were imaged first with a 3T clinical MR scanner to identify areas of interest for scanning, and then with a 7T small bore scanner using a multicomponent-driven equilibrium single-pulse observation of T1 and T2 protocol to produce apparent proton density, T1 , T2 , myelin water, intracellular water, and free-water fraction maps. After imaging, the cords were sectioned and stained with histological markers (hematoxylin and eosin, myelin basic protein, and neurofilament protein), which were quantitatively compared with the MR maps. RESULTS: Excellent correspondence was found between high-resolution MR parameter maps and histology, particularly for apparent proton density MRI and myelin basic protein staining. CONCLUSION: High-resolution quantitative MRI of the spinal cord provides biologically meaningful measures, and could be beneficial to diagnose and track multiple sclerosis lesions in the spinal cord.

Singers show enhanced performance and neural representation of vocal imitation.

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of the right somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song. This article is part of the theme issue 'Voice modulation: from origin and mechanism to social impact (Part I)'.

Diagnostic Accuracy of FEC-PET/CT, FDG-PET/CT, and Diffusion-Weighted MRI in Detection of Nodal Metastases in Surgically Treated Endometrial and Cervical Carcinoma.

PURPOSE: Preoperative nodal staging is important for planning treatment in cervical cancer and endometrial cancer, but remains challenging. We compare nodal staging accuracy of 18F-ethyl-choline-(FEC)-PET/CT, 18F-fluoro-deoxy-glucose-(FDG)-PET/CT, and diffusion-weighted-MRI (DW-MRI) with conventional morphologic MRI. EXPERIMENTAL DESIGN: A prospective, multicenter observational study of diagnostic accuracy for nodal metastases was undertaken in 5 gyne-oncology centers. FEC-PET/CT, FDG-PET/CT, and DW-MRI were compared with nodal size and morphology on MRI. Reference standard was strictly correlated nodal histology. Eligibility included operable cervical cancer stage ≥ 1B1 or endometrial cancer (grade 3 any stage with myometrial invasion or grade 1-2 stage ≥ II). RESULTS: Among 162 consenting participants, 136 underwent study DW-MRI and FDG-PET/CT and 60 underwent FEC-PET/CT. In 118 patients, 267 nodal regions were strictly correlated at histology (nodal positivity rate, 25%). Sensitivity per patient (n = 118) for nodal size, morphology, DW-MRI, FDG- and FEC-PET/CT was 40%*, 53%, 53%, 63%*, and 67% for all cases (*, P = 0.016); 10%, 10%, 20%, 30%, and 25% in cervical cancer (n = 40); 65%, 75%, 70%, 80% and 88% in endometrial cancer (n = 78). FDG-PET/CT outperformed nodal size (P = 0.006) and size ratio (P = 0.04) for per-region sensitivity. False positive rates were all <10%. CONCLUSIONS: All imaging techniques had low sensitivity for detection of nodal metastases and cannot replace surgical nodal staging. The performance of FEC-PET/CT was not statistically different from other techniques that are more widely available. FDG-PET/CT had higher sensitivity than size in detecting nodal metastases. False positive rates were low across all methods. The low false positive rate demonstrated by FDG-PET/CT may be helpful in arbitration of challenging surgical planning decisions.

Assessment of Apparent Diffusion Coefficients and SUVs as Predicators of Histological Differentiation in Anal Squamous Cell Carcinoma.

AIM: The study aims to assess minimal apparent diffusion coefficient (ADCmin) and SUVmax as predictors of histological differentiation in patients with anal squamous cell carcinoma (ASCC) and to determine cutoff values for each histopathological tumor grade. PATIENTS AND METHODS: A retrospective study of 41 ASCC patients (14 males, 27 females; mean age, 65 ± 13 years) staged with FDG PET/CT and MRI (mean scan time interval, 21 ± 11 days). SUVmax and ADCmin values were measured and compared with histopathological tumor grading obtained from biopsy. RESULTS: The mean size and tumor volume were 3 ± 2 cm and 16.5 ± 27.3 cm3, respectively. The mean ADCmin values for well-, moderately, and poorly differentiated ASCC were 935 ± 179, 896 ± 123, and 637 ± 114, respectively. The mean SUVmax for well-, moderately, and poorly differentiated ASCC were 6.9 ± 1.8, 11.5 ± 4.1, and 13.4 ± 2.6, respectively. The difference in mean ADCmin values between poorly and moderately/well-differentiated tumors was statistically significant, whereas this was not significant between moderately and well-differentiated tumors. Differences in SUVmax values were statistically significant between poorly/moderately and well-differentiated tumors, whereas there was no statistical significance between poorly and moderately differentiated tumors. By combining the 2 modalities using cutoff values of 675 × 10-6 mm2·s-1 for ADCmin and 8.5 for SUVmax, it was possible to differentiate the tumor categories with a sensitivity, specificity, positive predictive value, and negative predictive value, respectively, of 84.6%, 96.4%, 91.7%, and 93.1% for well-differentiated ASCC, 76.5%, 87.5%, 81.3%, and 84% for moderately, and 90.9%, 89.3%, 76.9%, and 96.2% for poorly differentiated ASCC, respectively. CONCLUSIONS: ADCmin and SUVmax values correlated with the degree of differentiation in ASCC and can be used as predictors of tumor grading and aggressiveness. Combined ADCmin and SUVmax cutoff values can therefore be used for early patient risk stratification and treatment decision making.

Deep-learning-based segmentation of the vocal tract and articulators in real-time magnetic resonance images of speech.

BACKGROUND AND OBJECTIVE: Magnetic resonance (MR) imaging is increasingly used in studies of speech as it enables non-invasive visualisation of the vocal tract and articulators, thus providing information about their shape, size, motion and position. Extraction of this information for quantitative analysis is achieved using segmentation. Methods have been developed to segment the vocal tract, however, none of these also fully segment any articulators. The objective of this work was to develop a method to fully segment multiple groups of articulators as well as the vocal tract in two-dimensional MR images of speech, thus overcoming the limitations of existing methods. METHODS: Five speech MR image sets (392 MR images in total), each of a different healthy adult volunteer, were used in this work. A fully convolutional network with an architecture similar to the original U-Net was developed to segment the following six regions in the image sets: the head, soft palate, jaw, tongue, vocal tract and tooth space. A five-fold cross-validation was performed to investigate the segmentation accuracy and generalisability of the network. The segmentation accuracy was assessed using standard overlap-based metrics (Dice coefficient and general Hausdorff distance) and a novel clinically relevant metric based on velopharyngeal closure. RESULTS: The segmentations created by the method had a median Dice coefficient of 0.92 and a median general Hausdorff distance of 5mm. The method segmented the head most accurately (median Dice coefficient of 0.99), and the soft palate and tooth space least accurately (median Dice coefficients of 0.92 and 0.93 respectively). The segmentations created by the method correctly showed 90% (27 out of 30) of the velopharyngeal closures in the MR image sets. CONCLUSIONS: An automatic method to fully segment multiple groups of articulators as well as the vocal tract in two-dimensional MR images of speech was successfully developed. The method is intended for use in clinical and non-clinical speech studies which involve quantitative analysis of the shape, size, motion and position of the vocal tract and articulators. In addition, a novel clinically relevant metric for assessing the accuracy of vocal tract and articulator segmentation methods was developed.

Realistic Dynamic Numerical Phantom for MRI of the Upper Vocal Tract.

Dynamic and real-time MRI (rtMRI) of human speech is an active field of research, with interest from both the linguistics and clinical communities. At present, different research groups are investigating a range of rtMRI acquisition and reconstruction approaches to visualise the speech organs. Similar to other moving organs, it is difficult to create a physical phantom of the speech organs to optimise these approaches; therefore, the optimisation requires extensive scanner access and imaging of volunteers. As previously demonstrated in cardiac imaging, realistic numerical phantoms can be useful tools for optimising rtMRI approaches and reduce reliance on scanner access and imaging volunteers. However, currently, no such speech rtMRI phantom exists. In this work, a numerical phantom for optimising speech rtMRI approaches was developed and tested on different reconstruction schemes. The novel phantom comprised a dynamic image series and corresponding k-space data of a single mid-sagittal slice with a temporal resolution of 30 frames per second (fps). The phantom was developed based on images of a volunteer acquired at a frame rate of 10 fps. The creation of the numerical phantom involved the following steps: image acquisition, image enhancement, segmentation, mask optimisation, through-time and spatial interpolation and finally the derived k-space phantom. The phantom was used to: (1) test different k-space sampling schemes (Cartesian, radial and spiral); (2) create lower frame rate acquisitions by simulating segmented k-space acquisitions; (3) simulate parallel imaging reconstructions (SENSE and GRAPPA). This demonstrated how such a numerical phantom could be used to optimise images and test multiple sampling strategies without extensive scanner access.

Application of radial GRAPPA techniques to single- and multislice dynamic speech MRI using a 16-channel neurovascular coil.

PURPOSE: To investigate: (1) the feasibility of using through-time radial GeneRalized Autocalibrating Partially Parallel Acquisitions (rGRAPPA) and hybrid radial GRAPPA (h-rGRAPPA) in single- and multislice dynamic speech MRI; (2) whether single-slice dynamic speech MRI at a rate of 15 frames per second (fps) or higher and with adequate image quality can be achieved using these radial GRAPPA techniques. METHODS: Seven healthy adult volunteers were imaged at 3T using a 16-channel neurovascular coil and 2 spoiled gradient echo sequences (radial trajectory, field of view = 192 × 192 mm2 , acquired pixel size = 2.4 × 2.4 mm2 ). One sequence imaged a single slice at 16.8 fps, the other imaged 2 interleaved slices at 7.8 fps per slice. Image sets were reconstructed using rGRAPPA and h-rGRAPPA, and their image quality was compared using the root mean square error, structural similarity index, and visual assessments. RESULTS: Image quality deteriorated when fewer than 170 calibration frames were used in the rGRAPPA reconstruction. rGRAPPA image sets demonstrated: (1) in 97% of cases, a similar image quality to h-rGRAPPA image sets reconstructed using a k-space segment size of 4, (2) in 98% of cases, a better image quality than h-rGRAPPA image sets reconstructed using a k-space segment size of 32. CONCLUSION: This study confirmed: (1) the feasibility of using rGRAPPA and h-rGRAPPA in single- and multislice dynamic speech MRI, (2) that single-slice speech imaging at a frame rate higher than 15 fps and with adequate image quality can be achieved using these radial GRAPPA techniques.

Improving liver lesion characterisation using retrospective fusion of FDG PET/CT and MRI.

AIM: To compare retrospectively fused FDG PET/CT and MRI (PET/MRI) to FDG PET/CT and MRI for characterisation of indeterminate focal liver lesions as malignant or benign in patients with a known primary malignancy. MATERIALS AND METHOD: A retrospective review of 70 patients (30 females, 40 males; mean age 56 ±â€¯14 years) with 150 indeterminate lesions after FDG PET/CT and MRI (mean scan time interval 21 ±â€¯11 days). HERMES® software was used to fuse PET/CT and MRI scans which were reviewed by 2 readers using the Likert score (scale 1-5) to characterise lesions as benign (1-3) or malignant (4-5). Final diagnosis was determined by histopathology or follow up imaging. Results for fused PET/MRI were compared to PET/CT and MRI alone. RESULTS: For detection, MRI and fused PET/MRI detected all the lesions while PET/CT detected 89.4%. Characterisation of liver lesions as malignant on PET/CT alone yielded sensitivity, specificity, accuracy, PPV and NPV of 55.6%, 83.3%, 66.7%, 83.3%, 55.6% respectively and 67.6%, 92.1%, 80%, 89.3%, 74.5% for MRI, respectively. The sensitivity, specificity, accuracy, PPV and NPV for characterising lesions as malignant increased to 91.9%, 97.4%, 94.7%, 97.1%, 92.5% with PET/MRI fusion. The sensitivity, specificity, accuracy, PPV and NPV of fused PET/MRI for characterising lesions as malignant remained superior to PET/CT and MRI. CONCLUSION: Retrospective fusion of PET with MRI has improved characterisation of indeterminate focal liver lesions compared to MRI or FDG PET/CT alone.

Magnetic resonance imaging correlates of neuro-axonal pathology in the MS spinal cord.

In people with multiple sclerosis (MS), the spinal cord is the structure most commonly affected by clinically detectable pathology at presentation, and a key part of the central nervous system involved in chronic disease deterioration. Indices, such as the spinal cord cross-sectional area at the level C2 have been developed as tools to predict future disability, and-by inference-axonal loss. However, this and other histo-pathological correlates of spinal cord magnetic resonance imaging (MRI) changes in MS remain incompletely understood. In recent years, there has been a surge of interest in developing quantitative MRI tools to measure specific tissue features, including axonal density, myelin content, neurite density, and orientation, among others, with an emphasis on the spinal cord. Quantitative MRI techniques including T1 and T2 , magnetization transfer and a number of diffusion-derived indices have all been applied to MS spinal cord. Particularly diffusion-based MRI techniques combined with microscopic resolution achievable using high magnetic field scanners enable a new level of anatomical detail and quantification of indices that are clinically meaningful.

Real-time speech MRI: Commercial Cartesian and non-Cartesian sequences at 3T and feasibility of offline TGV reconstruction to visualise velopharyngeal motion.

PURPOSE: This study aims to improve clinical reliability of real-time Magnetic Resonance Imaging (rt-MRI) in the visualisation of velopharyngeal motion during speech. METHODS: Seven subjects were imaged at 3T during natural phonation. Speech rt-MRI methodologies were investigated with (i) a comparison of commercial Cartesian and non-Cartesian (radial and spiral) rt-MRI sequences and (ii) investigation of further improvement with accelerated radial acquisition and offline reconstruction methodology. RESULTS: Cartesian and non-Cartesian protocols were implemented with temporal resolutions between 10 frames per second (fps) and 27 fps and voxel sizes between 1.5 × 1.5 × 10 mm3 and 2.7 × 2.7 × 10 mm3. Commercial spiral acquisitions provided superior contrast-to-noise ratio (CNR) than otherwise equivalent Cartesian and radial. Spirals at 22 fps allowed for improved spatial resolution (1.9 × 1.9 mm2) when compared to similar Cartesian protocols (20 fps), limited to a lower spatial resolution (2.7 × 2.7 mm2). Cartesian protocols were on average scored higher than spiral protocols in visual quality. However, some variability was found on choice of recommended imaging protocol between subjects. Accelerated radial data reconstructed offline with a Total Generalized Variation (TGV) scheme showed improved visual sharpness of velum motion. DISCUSSION/CONCLUSION: Adequate visualisation of velopharyngeal motion with commercial rt-MRI at 3T was possible. Both Cartesian and spiral protocols demonstrated adequate temporal depiction and overall image quality. However, choice of optimal imaging protocol at 3T was more subject-dependent than in previously published 1.5T data and additional care should be taken when selecting an adequate protocol. Offline TGV reconstruction of radial data has shown potential to improve temporal sharpness.

UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer.

OBJECTIVE: Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology. METHODS: A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control. RESULTS: The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T. CONCLUSION: This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.

Myocardial deformation assessment using cardiovascular magnetic resonance-feature tracking technique.

BACKGROUND: Cardiovascular magnetic resonance (CMR) imaging is an important modality that allows the assessment of regional myocardial function by measuring myocardial deformation parameters, such as strain and strain rate throughout the cardiac cycle. Feature tracking is a promising quantitative post-processing technique that is increasingly used. It is commonly applied to cine images, in particular steady-state free precession, acquired during routine CMR examinations. OBJECTIVE: To review the studies that have used feature tracking techniques in healthy subjects or patients with cardiovascular diseases. The article emphasizes the advantages and limitations of feature tracking when applied to regional deformation parameters. The challenges of applying the techniques in clinics and potential solutions are also reviewed. RESULTS: Research studies in healthy volunteers and/or patients either applied CMR-feature tracking alone to assess myocardial motion or compared it with either established CMR-tagging techniques or to speckle tracking echocardiography. These studies assessed the feasibility and reliability of calculating or determining global and regional myocardial deformation strain parameters. Regional deformation parameters are reviewed and compared. Better reproducibility for global deformation was observed compared with segmental parameters. Overall, studies demonstrated that circumferential was the most reproducible deformation parameter, usually followed by longitudinal strain; in contrast, radial strain showed high variability. CONCLUSION: Although feature tracking is a promising tool, there are still discrepancies in the results obtained using different software packages. This highlights a clear need for standardization of MRI acquisition parameters and feature tracking analysis methodologies. Validation, including physical and numerical phantoms, is still required to facilitate the use of feature tracking in routine clinical practice.

Functional brain outcomes of L2 speech learning emerge during sensorimotor transformation.

Sensorimotor transformation (ST) may be a critical process in mapping perceived speech input onto non-native (L2) phonemes, in support of subsequent speech production. Yet, little is known concerning the role of ST with respect to L2 speech, particularly where learned L2 phones (e.g., vowels) must be produced in more complex lexical contexts (e.g., multi-syllabic words). Here, we charted the behavioral and neural outcomes of producing trained L2 vowels at word level, using a speech imitation paradigm and functional MRI. We asked whether participants would be able to faithfully imitate trained L2 vowels when they occurred in non-words of varying complexity (one or three syllables). Moreover, we related individual differences in imitation success during training to BOLD activation during ST (i.e., pre-imitation listening), and during later imitation. We predicted that superior temporal and peri-Sylvian speech regions would show increased activation as a function of item complexity and non-nativeness of vowels, during ST. We further anticipated that pre-scan acoustic learning performance would predict BOLD activation for non-native (vs. native) speech during ST and imitation. We found individual differences in imitation success for training on the non-native vowel tokens in isolation; these were preserved in a subsequent task, during imitation of mono- and trisyllabic words containing those vowels. fMRI data revealed a widespread network involved in ST, modulated by both vowel nativeness and utterance complexity: superior temporal activation increased monotonically with complexity, showing greater activation for non-native than native vowels when presented in isolation and in trisyllables, but not in monosyllables. Individual differences analyses showed that learning versus lack of improvement on the non-native vowel during pre-scan training predicted increased ST activation for non-native compared with native items, at insular cortex, pre-SMA/SMA, and cerebellum. Our results hold implications for the importance of ST as a process underlying successful imitation of non-native speech.

Vocal Tract Images Reveal Neural Representations of Sensorimotor Transformation During Speech Imitation.

Imitating speech necessitates the transformation from sensory targets to vocal tract motor output, yet little is known about the representational basis of this process in the human brain. Here, we address this question by using real-time MR imaging (rtMRI) of the vocal tract and functional MRI (fMRI) of the brain in a speech imitation paradigm. Participants trained on imitating a native vowel and a similar nonnative vowel that required lip rounding. Later, participants imitated these vowels and an untrained vowel pair during separate fMRI and rtMRI runs. Univariate fMRI analyses revealed that regions including left inferior frontal gyrus were more active during sensorimotor transformation (ST) and production of nonnative vowels, compared with native vowels; further, ST for nonnative vowels activated somatomotor cortex bilaterally, compared with ST of native vowels. Using test representational similarity analysis (RSA) models constructed from participants' vocal tract images and from stimulus formant distances, we found that RSA searchlight analyses of fMRI data showed either type of model could be represented in somatomotor, temporal, cerebellar, and hippocampal neural activation patterns during ST. We thus provide the first evidence of widespread and robust cortical and subcortical neural representation of vocal tract and/or formant parameters, during prearticulatory ST.

Comparison of Cartesian and Non-Cartesian Real-Time MRI Sequences at 1.5T to Assess Velar Motion and Velopharyngeal Closure during Speech.

Dynamic imaging of the vocal tract using real-time MRI has been an active and growing area of research, having demonstrated great potential to become routinely performed in the clinical evaluation of speech and swallowing disorders. Although many technical advances have been made in regards to acquisition and reconstruction methodologies, there is still no consensus in best practice protocols. This study aims to compare Cartesian and non-Cartesian real-time MRI sequences, regarding image quality and temporal resolution trade-off, for dynamic speech imaging. Five subjects were imaged at 1.5T, while performing normal phonation, in order to assess velar motion and velopharyngeal closure. Data was acquired using both Cartesian and non-Cartesian (spiral and radial) real-time sequences at five different spatial-temporal resolution sets, between 10 fps (1.7×1.7×10 mm3) and 25 fps (1.5×1.5×10 mm3). Only standard scanning resources provided by the MRI scanner manufacturer were used to ensure easy applicability to clinical evaluation and reproducibility. Data sets were evaluated by comparing measurements of the velar structure, dynamic contrast-to-noise ratio and image quality visual scoring. Results showed that for all proposed sequences, FLASH spiral acquisitions provided higher contrast-to-noise ratio, up to a 170.34% increase at 20 fps, than equivalent bSSFP Cartesian acquisitions for the same spatial-temporal resolution. At higher frame rates (22 and 25 fps), spiral protocols were optimal and provided higher CNR and visual scoring than equivalent radial protocols. Comparison of dynamic imaging at 10 and 22 fps for radial and spiral acquisitions revealed no significant difference in CNR performance, thus indicating that temporal resolution can be doubled without compromising spatial resolution (1.9×1.9 mm2) or CNR. In summary, this study suggests that the use of FLASH spiral protocols should be preferred over bSSFP Cartesian for the dynamic imaging of velopharyngeal closure, as it allows for an improvement in CNR and overall image quality without compromising spatial-temporal resolution.

Assessment of a carbon fibre MRI flatbed insert for radiotherapy treatment planning.

OBJECTIVE: The purpose of this work was to assess heating and radiofrequency (RF) deposition and image quality effects of a prototype three-section carbon fibre flatbed insert for use in MRI. METHODS: RF deposition was assessed using two different thermometry techniques, infrared thermometry and Bragg-grating thermometry. Image quality effects were assessed with and without the flatbed insert in place by using mineral oil phantoms and a human subject. RESULTS: Neither technique detected heating of the insert in typical MRI examinations. We found that the insert was less suitable for MRI applications owing to severe RF shielding artefact. For spin-echo (SE), turbo spin-echo (TSE) and gradient-echo sequences, the reduction in signal-to-noise ratio (SNR) was as much as 89% when the insert was in place compared with the standard couch, making it less suitable as a patient-support material. Turning on the MultiTransmit switch together with using the scanner's quadrature body coil improved the reduction in SNR from 89% to 39% for the SE sequence and from 82% to 12% for the TSE sequence. CONCLUSION: No evidence was found to support reports in the literature that carbon fibre is an unsuitable material for use in MRI because of heating. ADVANCES IN KNOWLEDGE: This study suggests that carbon fibre is less suitable for large-scale MRI applications owing to it causing severe RF shading. Further research is needed to establish the suitability of the flatbed for treatment planning using alternative sequences or whether an alternative carbon fibre composite for large-scale MRI applications or a design that can minimize shielding can be found.