Improved real-time tagged MRI using REALTAG.

OBJECTIVES: To evaluate a novel method for real-time tagged MRI with increased tag persistence using phase sensitive tagging (REALTAG), demonstrated for speech imaging. METHODS: Tagging is applied as a brief interruption to a continuous real-time spiral acquisition. REALTAG is implemented using a total tagging flip angle of 180° and a novel frame-by-frame phase sensitive reconstruction to remove smooth background phase while preserving the sign of the tag lines. Tag contrast-to-noise ratio of REALTAG and conventional tagging (total flip angle of 90°) is simulated and evaluated in vivo. The ability to extend tag persistence is tested during the production of vowel-to-vowel transitions by American English speakers. RESULTS: REALTAG resulted in a doubling of contrast-to-noise ratio at each time point and increased tag persistence by more than 1.9-fold. The tag persistence was 1150 ms with contrast-to-noise ratio >6 at 1.5T, providing 2 mm in-plane resolution, 179 frames/s, with 72.6 ms temporal window width, and phase sensitive reconstruction. The new imaging window is able to capture internal tongue deformation over word-to-word transitions in natural speech production. CONCLUSION: Tag persistence is substantially increased in intermittently tagged real-time MRI by using the improved REALTAG method. This makes it possible to capture longer motion patterns in the tongue, such as cross-word vowel-to-vowel transitions, and provides a powerful new window to study tongue biomechanics.

Detecting liver fibrosis using a machine learning-based approach to the quantification of the heart-induced deformation in tagged MR images.

Liver disease causes millions of deaths per year worldwide, and approximately half of these cases are due to cirrhosis, which is an advanced stage of liver fibrosis that can be accompanied by liver failure and portal hypertension. Early detection of liver fibrosis helps in improving its treatment and prevents its progression to cirrhosis. In this work, we present a novel noninvasive method to detect liver fibrosis from tagged MRI images using a machine learning-based approach. Specifically, coronal and sagittal tagged MRI imaging are analyzed separately to capture cardiac-induced deformation of the liver. The liver is manually delineated and a novel image feature, namely, the histogram of the peak strain (HPS) value, is computed from the segmented liver region and is used to classify the liver as being either normal or fibrotic. Classification is achieved using a support vector machine algorithm. The in vivo study included 15 healthy volunteers (10 males; age range 30-45 years) and 22 patients (15 males; age range 25-50 years) with liver fibrosis verified and graded by transient elastography, and 10 patients only had a liver biopsy and were diagnosed with a score of F3-F4. The proposed method demonstrates the usefulness and efficiency of extracting the HPS features from the sagittal slices for patients with moderate fibrosis. Cross-validation of the method showed an accuracy of 83.7% (specificity = 86.6%, sensitivity = 81.8%).

Analysis of three-chamber view conventional and tagged cine MRI in patients with suspected hypertrophic cardiomyopathy.

OBJECTIVES: To investigate the potential value of adding a tagged three-chamber (3Ch) cine to clinical hypertrophic cardiomyopathy (HCM) magnetic resonance imaging (MRI) protocols, including to help distinguish HCM patients with regionally impaired cardiac function. METHODS: Forty-eight HCM patients, five patients with "septal knuckle" (SK), and 20 healthy volunteers underwent MRI at 1.5T; a tagged 3Ch cine was added to the protocol. Regional strain, myocardial wall thickness, and mitral valve leaflet lengths were measured in the 3Ch view. RESULTS: In HCM, we found a reduced tangential strain with decreased diastolic relaxation in both hypertrophied (p = 0.003) and remote segments (p = 0.035). Strain in the basal septum correlated with the length of the coaptation zone + residual leaflet (r = 0.48, p < 0.001). In the basal free wall, patients with SK had faster relaxation compared to HCM patients with septal hypertrophy. DISCUSSION: The 3Ch tagged MRI sequence provides useful information for the examination of suspected HCM patients, with minimal additional time cost. Local wall function is closely associated with morphological changes of the mitral apparatus measured in the same plane and may provide insights into mechanisms of obstruction. The additional strain information may be helpful when analyzing local myocardial wall motion patterns in the presence of SK.

Assessment of infarct-specific cardiac motion dysfunction using modeling and multimodal magnetic resonance merging.

PURPOSE: To propose a cardiac motion tracking model that evaluates wall motion abnormality in postmyocardial infarction patients. Correlation between the motion parameter of the model and left ventricle (LV) function was also determined. MATERIALS AND METHODS: Twelve male patients with post-ST elevation myocardial infarction (post-STEMI) and 10 healthy controls of the same gender were recruited to undergo cardiac magnetic resonance imaging (MRI) using a 1.5T scanner. Using an infarct-specific LV division approach, the late gadolinium enhancement (LGE) MRI images were used to divide the LV on the tagged MRI images into infarct, adjacent, and remote sectors. Motion tracking was performed using the infarct-specific two-parameter empirical deformable model (TPEDM). The match quality was defined as the position error computed using root-mean-square (RMS) distance between the estimated and expert-verified tag intersections. The position errors were compared with the ones from our previously published fixed-sector TPEDM. Cine MRI images were used to calculate regional ejection fraction (REF). Correlation between the end-systolic contraction parameter (αES ) with REF was determined. RESULTS: The position errors in the proposed model were significantly lower than the fixed-sector model (P < 0.01). The median position errors were 0.82 mm versus 1.23 mm. The αES correlates significantly with REF (r = 0.91, P < 0.01). CONCLUSION: The infarct-specific TPEDM combines the morphological and functional information from LGE and tagged MRI images. It was shown to outperform the fixed-sector model in assessing regional LV dysfunction. The significant correlation between αES and REF added prognostic value because it indicated an impairment of cardiac function with the increase of infarct transmurality. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017;45:525-534.

Regional myocardial functional patterns: Quantitative tagged magnetic resonance imaging in an adult population free of cardiovascular risk factors: The multi-ethnic study of atherosclerosis (MESA).

PURPOSE: To characterize the left ventricular (LV) regional deformation patterns and identify normal values of left ventricular strains from tagged magnetic resonance imaging (MRI) in a population with low-risk-factor (LRF) exposure. MATERIALS AND METHODS: Tagged CMR on three LV short axis slices was performed in participants of the MESA study who were free of cardiovascular disease at baseline. Images were analyzed by the harmonic phase imaging method to obtain: peak torsion, circumferential (Ecc) and radial (Err) strains, and systolic (SRs) and early-diastolic (SRe) strain rates. An LRF group was created from the overall population based on strict exclusion criteria (n = 129) based on risk factors and events observed over a 10-year follow-up. RESULTS: The normative prediction intervals for the averaged peak Ecc (%) and torsion (deg/cm) measures were: in 45-59-year-old women: (-20.8, -13.2) and (2.1, 6.3); 60-84-year-old women: (-20.6, -12.8) and (2.2, 6.9); 45-59-year-old men: (-21.3, -13.5) and (1.9, 5.7); 60-84-year-old men: (-20.5, -12.5) and (1.5, 5.2). In general, African-Americans (Ecc = -15.9, torsion = 3.3) had lower strains as compared to Chinese (Ecc = -17.1, torsion = 3.9), while Caucasians and Hispanics were intermediate and not significantly different. Circumferential shortening increased spatially from the epicardium to the endocardium (-16.9 to -18.2 at the mid-ventricle) and from the base to the apex (-15.1 to -17.5 at the midwall). CONCLUSION: The present study provides reference ranges and deformation patterns of deformation values from a large healthy population free of cardiovascular disease at baseline.

Three-dimensional regional strain computation method with displacement encoding with stimulated echoes (DENSE) in non-ischemic, non-valvular dilated cardiomyopathy patients and healthy subjects validated by tagged MRI.

PURPOSE: Fast cine displacement encoding with stimulated echoes (DENSE) MR has higher spatial resolution and enables rapid postprocessing. Thus we compared the accuracy of regional strains computation by DENSE with tagged MR in healthy and non-ischemic, non-valvular dilated cardiomyopathy (DCM) subjects. MATERIALS AND METHODS: Validation of three-dimensional regional strains computed with DENSE was conducted in reference to standard tagged MRI (TMRI) in healthy subjects and patients with DCM. Additional repeatability studies in healthy subjects were conducted to increase confidence in DENSE. A meshfree multiquadrics radial point interpolation method (RPIM) was used for computing Lagrange strains in sixteen left ventricular segments. Bland-Altman analysis and Student's t-tests were conducted to observe similarities in regional strains between sequences and in DENSE repeatability studies. RESULTS: Regional circumferential strains ranged from -0.21 ± 0.07 (Lateral-Apex) to -0.11 ± 0.05 (Posterorseptal-Base) in healthy subjects and -0.15 ± 0.04 (Anterior-Apex) to -0.02 ± 0.08 (Posterorseptal-Base) in DCM patients. Computed mean differences in regional circumferential strain from the DENSE-TMRI comparison study was 0.01 ± 0.03 (95% limits of agreement) in normal subjects, -0.01 ± 0.06 in DCM patients and 0.0 ± 0.02 in repeatability studies, with similar agreements in longitudinal and radial strains. CONCLUSION: We found agreement between DENSE and tagged MR in patients and volunteers in terms of evaluation of regional strains.

Liver stiffness assessment with tagged MRI of cardiac-induced liver motion in cirrhosis patients.

PURPOSE: To assess liver stiffness using magnetization-tagged magnetic resonance imaging (MRI) to measure the cardiac-induced motion in the liver of cirrhosis patients with known Child-Pugh scores. MATERIALS AND METHODS: Tagged MRI was performed using a 3T MR scanner on 52 cirrhosis patients classified into two groups: liver cirrhosis with Child-Pugh A (LCA; n = 39) and liver cirrhosis with Child-Pugh B or C (LCBC; n = 13). We also included 19 healthy controls. Tagged images were acquired encompassing both the liver and the heart. The corresponding displacement and strains were calculated using a Gabor filter bank. The maximum displacement (MaxDisp) was found over the cardiac cycle, as well as the local maximum P1 (MaxP1) and minimum P2 strains (MinP2). Group comparisons were made without and with adjustment for age and gender. RESULTS: In control, LCA, and LCBC groups, the MaxDisp was 3.98 ± 0.88 mm, 2.52 ± 0.73 mm, and 1.86 ± 0.77 mm; the MaxP1 was 0.10 ± 0.02, 0.04 ± 0.01, and 0.02 ± 0.01; and the MinP2 was -0.08 ± 0.01, -0.05 ± 0.02, and -0.03 ± 0.01, respectively. Statistically significant differences were found between groups (P < 0.05 for all). CONCLUSION: This method measures cardiac-induced liver motion and deformation to assess liver stiffness. Significant differences were found in our stiffness measures between control, LCA, and LCBC groups, with more severe disease being associated with greater stiffness.

Speech Motion Anomaly Detection via Cross-Modal Translation of 4D Motion Fields from Tagged MRI.

Understanding the relationship between tongue motion patterns during speech and their resulting speech acoustic outcomes-i.e., articulatory-acoustic relation-is of great importance in assessing speech quality and developing innovative treatment and rehabilitative strategies. This is especially important when evaluating and detecting abnormal articulatory features in patients with speech-related disorders. In this work, we aim to develop a framework for detecting speech motion anomalies in conjunction with their corresponding speech acoustics. This is achieved through the use of a deep cross-modal translator trained on data from healthy individuals only, which bridges the gap between 4D motion fields obtained from tagged MRI and 2D spectrograms derived from speech acoustic data. The trained translator is used as an anomaly detector, by measuring the spectrogram reconstruction quality on healthy individuals or patients. In particular, the cross-modal translator is likely to yield limited generalization capabilities on patient data, which includes unseen out-of-distribution patterns and demonstrates subpar performance, when compared with healthy individuals. A one-class SVM is then used to distinguish the spectrograms of healthy individuals from those of patients. To validate our framework, we collected a total of 39 paired tagged MRI and speech waveforms, consisting of data from 36 healthy individuals and 3 tongue cancer patients. We used both 3D convolutional and transformer-based deep translation models, training them on the healthy training set and then applying them to both the healthy and patient testing sets. Our framework demonstrates a capability to detect abnormal patient data, thereby illustrating its potential in enhancing the understanding of the articulatory-acoustic relation for both healthy individuals and patients.

Tetraplegic obstructive sleep apnoea patients dilate the airway similarly to able-bodied obstructive sleep apnoea patients.

Context/objective: Obstructive sleep apnoea (OSA) develops soon after cervical spinal cord injury (SCI) at rates higher than the general population, but the mechanisms are not understood. This study aimed to determine whether OSA in SCI is associated with altered pharyngeal muscle dilatory mechanics during quiet breathing, as has been observed in the non-SCI injured with obstructive sleep apnoea.Design: Cross sectional imaging study.Setting: Medical research institute.Participants: Eight cervical SCI patients with OSA were recruited and compared to 13 able-bodied OSA patients and 12 able-bodied healthy controls of similar age and BMI.Interventions and outcome measures: 3T MRI scans of upper airway anatomy and tagged-MRI to characterize airway muscle motion during quiet breathing were collected for analysis.Results: Considerable variation in the patterns of inspiratory airway muscle motion was observed in the SCI group, with some participants exhibiting large inspiratory airway dilatory motions, and others exhibiting counterproductive narrowing during inspiration. These patterns were not dissimilar to those observed in the able-bodied OSA participants. The increase in airway cross-sectional area of able-bodied control participants was proportional to increase in BMI, and a similar, but not significant, relationship was present in all groups.Conclusion: Despite the limited sample size, these data suggest that SCI OSA patients have heterogeneous pharyngeal dilator muscle responses to the negative pressures occurring during inspiration but, as a group, appear to be more similar to able-bodied OSA patients than healthy controls of similar age and BMI. This may reflect altered pharyngeal pressure reflex responses in at least some people with SCI.

Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglement.

Cycle reconstruction regularized adversarial training-e.g., CycleGAN, DiscoGAN, and DualGAN-has been widely used for image style transfer with unpaired training data. Several recent works, however, have shown that local distortions are frequent, and structural consistency cannot be guaranteed. Targeting this issue, prior works usually relied on additional segmentation or consistent feature extraction steps that are task-specific. To counter this, this work aims to learn a general add-on structural feature extractor, by explicitly enforcing the structural alignment between an input and its synthesized image. Specifically, we propose a novel input-output image patches self-training scheme to achieve a disentanglement of underlying anatomical structures and imaging modalities. The translator and structure encoder are updated, following an alternating training protocol. In addition, the information w.r.t. imaging modality can be eliminated with an asymmetric adversarial game. We train, validate, and test our network on 1,768, 416, and 1,560 unpaired subject-independent slices of tagged and cine magnetic resonance imaging from a total of twenty healthy subjects, respectively, demonstrating superior performance over competing methods.

Measuring Strain in Diffusion-Weighted Data Using Tagged Magnetic Resonance Imaging.

Accurate strain measurement in a deforming organ has been essential in motion analysis using medical images. In recent years, internal tissue's in vivo motion and strain computation has been mostly achieved through dynamic magnetic resonance (MR) imaging. However, such data lack information on tissue's intrinsic fiber directions, preventing computed strain tensors from being projected onto a direction of interest. Although diffusion-weighted MR imaging excels at providing fiber tractography, it yields static images unmatched with dynamic MR data. This work reports an algorithm workflow that estimates strain values in the diffusion MR space by matching corresponding tagged dynamic MR images. We focus on processing a dataset of various human tongue deformations in speech. The geometry of tongue muscle fibers is provided by diffusion tractography, while spatiotemporal motion fields are provided by tagged MR analysis. The tongue's deforming shapes are determined by segmenting a synthetic cine dynamic MR sequence generated from tagged data using a deep neural network. Estimated motion fields are transformed into the diffusion MR space using diffeomorphic registration, eventually leading to strain values computed in the direction of muscle fibers. The method was tested on 78 time volumes acquired during three sets of specific tongue deformations including both speech and protrusion motion. Strain in the line of action of seven internal tongue muscles was extracted and compared both intra- and inter-subject. Resulting compression and stretching patterns of individual muscles revealed the unique behavior of individual muscles and their potential activation pattern.

The relationship between mandibular advancement, tongue movement, and treatment outcome in obstructive sleep apnea.

STUDY OBJECTIVES: To characterize how mandibular advancement enlarges the upper airway via posterior tongue advancement in people with obstructive sleep apnea (OSA) and whether this is associated with mandibular advancement splint (MAS) treatment outcome. METHODS: One-hundred and one untreated people with OSA underwent a 3T magnetic resonance (MRI) scan. Dynamic mid-sagittal posterior tongue and mandible movements during passive jaw advancement were measured with tagged MRI. Upper airway cross-sectional areas were measured with the mandible in a neutral position and advanced to 70% of maximum advancement. Treatment outcome was determined after a minimum of 9 weeks of therapy. RESULTS: Seventy-one participants completed the study: 33 were responders (AHI<5 or AHI≤10 events/hr with >50% AHI reduction), 11 were partial responders (>50% AHI reduction but AHI>10 events/hr), and 27 nonresponders (AHI reduction<50% and AHI≥10 events/hr). Responders had the greatest naso- and oropharyngeal tongue anterior movement (0.40 ± 0.08 and 0.47 ± 0.13 mm, respectively) and oropharyngeal cross-sectional area enlargement (6.41 ± 2.12%) per millimeter of mandibular advancement. A multivariate model that included tongue movement and percentage of airway enlargement per millimeter of mandibular advancement along with baseline AHI correctly classified 69.2% (5-fold cross-validated 62.5%, n = 39) of participants in response categories when the jaw was advanced in the range that would usually be regarded as sufficient for clinical efficacy (> 4 mm). In comparison, a model using only baseline AHI correctly classified 50.0% of patients (5-fold cross-validated 52.5%, n = 40). CONCLUSIONS: Tongue advancement and upper airway enlargement with mandibular advancement in conjunction with baseline AHI improve treatment response categorization to a satisfactory level (69.2%, 5-fold cross-validated 62.5%).

A deep joint sparse non-negative matrix factorization framework for identifying the common and subject-specific functional units of tongue motion during speech.

Intelligible speech is produced by creating varying internal local muscle groupings-i.e., functional units-that are generated in a systematic and coordinated manner. There are two major challenges in characterizing and analyzing functional units. First, due to the complex and convoluted nature of tongue structure and function, it is of great importance to develop a method that can accurately decode complex muscle coordination patterns during speech. Second, it is challenging to keep identified functional units across subjects comparable due to their substantial variability. In this work, to address these challenges, we develop a new deep learning framework to identify common and subject-specific functional units of tongue motion during speech. Our framework hinges on joint deep graph-regularized sparse non-negative matrix factorization (NMF) using motion quantities derived from displacements by tagged Magnetic Resonance Imaging. More specifically, we transform NMF with sparse and graph regularizations into modular architectures akin to deep neural networks by means of unfolding the Iterative Shrinkage-Thresholding Algorithm to learn interpretable building blocks and associated weighting map. We then apply spectral clustering to common and subject-specific weighting maps from which we jointly determine the common and subject-specific functional units. Experiments carried out with simulated datasets show that the proposed method achieved on par or better clustering performance over the comparison methods.Experiments carried out with in vivo tongue motion data show that the proposed method can determine the common and subject-specific functional units with increased interpretability and decreased size variability.

DUAL-CYCLE CONSTRAINED BIJECTIVE VAE-GAN FOR TAGGED-TO-CINE MAGNETIC RESONANCE IMAGE SYNTHESIS.

Tagged magnetic resonance imaging (MRI) is a widely used imaging technique for measuring tissue deformation in moving organs. Due to tagged MRI's intrinsic low anatomical resolution, another matching set of cine MRI with higher resolution is sometimes acquired in the same scanning session to facilitate tissue segmentation, thus adding extra time and cost. To mitigate this, in this work, we propose a novel dual-cycle constrained bijective VAE-GAN approach to carry out tagged-to-cine MR image synthesis. Our method is based on a variational autoencoder backbone with cycle reconstruction constrained adversarial training to yield accurate and realistic cine MR images given tagged MR images. Our framework has been trained, validated, and tested using 1,768, 416, and 1,560 subject-independent paired slices of tagged and cine MRI from twenty healthy subjects, respectively, demonstrating superior performance over the comparison methods. Our method can potentially be used to reduce the extra acquisition time and cost, while maintaining the same workflow for further motion analyses.

Natural oscillatory modes of 3D deformation of the human brain in vivo.

Natural modes and frequencies of three-dimensional (3D) deformation of the human brain were identified from in vivo tagged magnetic resonance images (MRI) acquired dynamically during transient mild acceleration of the head. Twenty 3D strain fields, estimated from tagged MRI image volumes in 19 adult subjects, were analyzed using dynamic mode decomposition (DMD). These strain fields represented dynamic, 3D brain deformations during constrained head accelerations, either involving rotation about the vertical axis of the neck or neck extension. DMD results reveal fundamental oscillatory modes of deformation at damped frequencies near 7 Hz (in neck rotation) and 11 Hz (in neck extension). Modes at these frequencies were found consistently among all subjects. These characteristic features of 3D human brain deformation are important for understanding the response of the brain in head impacts and provide valuable quantitative criteria for the evaluation and use of computer models of brain mechanics.

Influence of mandibular advancement on tongue dilatory movement during wakefulness and how this is related to oral appliance therapy outcome for obstructive sleep apnea.

STUDY OBJECTIVES: To characterize how mandibular advancement splint (MAS) alters inspiratory tongue movement in people with obstructive sleep apnea (OSA) during wakefulness and whether this is associated with MAS treatment outcome. METHODS: A total of 87 untreated OSA participants (20 women, apnea-hypopnea index (AHI) 7-102 events/h, aged 19-76 years) underwent a 3T MRI with a MAS in situ. Mid-sagittal tagged images quantified inspiratory tongue movement with the mandible in a neutral position and advanced to 70% of the maximum. Movement was quantified with harmonic phase methods. Treatment outcome was determined after at least 9 weeks of therapy. RESULTS: A total of 72 participants completed the study: 34 were responders (AHI < 5 or AHI ≤ 10events/h with >50% reduction in AHI), 9 were partial responders (>50% reduction in AHI but AHI > 10 events/h), and 29 nonresponders (change in AHI <50% and AHI ≥ 10 events/h). About 62% (45/72) of participants had minimal inspiratory tongue movement (<1 mm) in the neutral position, and this increased to 72% (52/72) after advancing the mandible. Mandibular advancement altered inspiratory tongue movement pattern for 40% (29/72) of participants. When tongue dilatory patterns altered with advancement, 80% (4/5) of those who changed to a counterproductive movement pattern (posterior movement >1 mm) were nonresponders and 71% (5/7) of those who changed to beneficial (anterior movement >1 mm) were partial or complete responders. CONCLUSIONS: The mandibular advancement action on upper airway dilator muscles differs between individuals. When mandibular advancement alters inspiratory tongue movement, therapeutic response to MAS therapy was more common among those who convert to a beneficial movement pattern.

Effect of upper airway fat on tongue dilation during inspiration in awake people with obstructive sleep apnea.

STUDY OBJECTIVES: To investigate the effect of upper airway fat composition on tongue inspiratory movement and obstructive sleep apnea (OSA). METHODS: Participants without or with untreated OSA underwent a 3T magnetic resonance imaging (MRI) scan. Anatomical measurements were obtained from T2-weighted images. Mid-sagittal inspiratory tongue movements were imaged using tagged MRI during wakefulness. Tissue volumes and percentages of fat were quantified using an mDIXON scan. RESULTS: Forty predominantly overweight participants with OSA were compared to 10 predominantly normal weight controls. After adjusting for age, BMI, and gender, the percentage of fat in the tongue was not different between groups (analysis of covariance [ANCOVA], p = 0.45), but apnoeic patients had a greater tongue volume (ANCOVA, p = 0.025). After adjusting for age, BMI, and gender, higher OSA severity was associated with larger whole tongue volume (r = 0.51, p < 0.001), and greater dilatory motion of the anterior horizontal tongue compartment (r = -0.33, p = 0.023), but not with upper airway fat percentage. Higher tongue fat percentage was associated with higher BMI and older age (Spearman r = 0.43, p = 0.002, and r =0.44, p = 0.001, respectively), but not with inspiratory tongue movements. Greater inspiratory tongue movement was associated with larger tongue volume (e.g. horizontal posterior compartment, r = -0.44, p = 0.002) and smaller nasopharyngeal airway (e.g. oblique compartment, r = 0.29, p = 0.040). CONCLUSIONS: Larger tongue volume and a smaller nasopharynx are associated with increased inspiratory tongue dilation during wakefulness in people with and without OSA. This compensatory response was not influenced by higher tongue fat content. Whether this is also true in more obese patient populations requires further investigation.

Assessment of fasted and fed gastrointestinal contraction frequencies in healthy subjects using continuously tagged MRI.

BACKGROUND: Continuously tagged MRI during free breathing can assess bowel motility at frequencies as low as the slow wave, motility pattern range. This study aimed to evaluate noninvasive gastrointestinal-tagged MRI for small bowel motility assessment and to observe the physiological response to a 300-kcal meal challenge in healthy, overnight-fasted volunteers. METHODS: After overnight fasting, 16 healthy subjects (7 women, mean age 25.5, range 19-37 years) underwent a free breathing, tagged MRI scan to capture small bowel motility. Each subject underwent a (a) baseline motility scan, (b) food challenge, (c) postchallenge scan, and (d) second postchallenge scan (after 20 minutes). Motility was quantified using a frequency analysis technique for measuring the spectral power of the strain, referred to as motility score. Motility score was assessed in 20 frequency intervals between 1 and 20 contractions per minute (cpm), and the data were analyzed with linear mixed-effect models. KEY RESULT: The stimulation protocol demonstrated an immediate, food-induced, motility response in the low-frequency range (2-10 cpm), which is consistent with the stomach and small bowel frequency range (3-12 cpm). CONCLUSIONS AND INFERENCES: This study shows that this MRI tagging technique is able to quantify the fasted-to-fed response to a 300-kcal meal challenge within the specific small bowel motility frequency range in healthy subjects. The food provocation MRI protocol provides a tool to explore the gut's response to a stimulus in specific motility frequency ranges in patients with gastrointestinal dysmotility and functional disorders.

In vivo estimates of axonal stretch and 3D brain deformation during mild head impact.

The rapid deformation of brain tissue in response to head impact can lead to traumatic brain injury. In vivo measurements of brain deformation during non-injurious head impacts are necessary to understand the underlying mechanisms of traumatic brain injury and compare to computational models of brain biomechanics. Using tagged magnetic resonance imaging (MRI), we obtained measurements of three-dimensional strain tensors that resulted from a mild head impact after neck rotation or neck extension. Measurements of maximum principal strain (MPS) peaked shortly after impact, with maximal values of 0.019-0.053 that correlated strongly with peak angular velocity. Subject-specific patterns of MPS were spatially heterogeneous and consistent across subjects for the same motion, though regions of high deformation differed between motions. The largest MPS values were seen in the cortical gray matter and cerebral white matter for neck rotation and the brainstem and cerebellum for neck extension. Axonal fiber strain (Ef) was estimated by combining the strain tensor with diffusion tensor imaging data. As with MPS, patterns of Ef varied spatially within subjects, were similar across subjects within each motion, and showed group differences between motions. Values were highest and most strongly correlated with peak angular velocity in the corpus callosum for neck rotation and in the brainstem for neck extension. The different patterns of brain deformation between head motions highlight potential areas of greater risk of injury between motions at higher loading conditions. Additionally, these experimental measurements can be directly compared to predictions of generic or subject-specific computational models of traumatic brain injury.

Analysis of fiber strain in the human tongue during speech.

This study investigates mechanical cooperation among tongue muscles. Five volunteers were imaged using tagged magnetic resonance imaging to quantify spatiotemporal kinematics while speaking. Waveforms of strain in the line of action of fibers (SLAF) were estimated by projecting strain tensors onto a model of fiber directionality. SLAF waveforms were temporally aligned to determine consistency across subjects and correlation across muscles. The cohort exhibited consistent patterns of SLAF, and muscular extension-contraction was correlated. Volume-preserving tongue movement in speech generation can be achieved through multiple paths, but the study reveals similarities in motion patterns and muscular action-despite anatomical (and other) dissimilarities.