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.

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

40 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 (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.

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.

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.

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.

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.

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%).

Quantifying Tensor Field Similarity With Global Distributions and Optimal Transport

Strain tensor fields quantify tissue deformation and are important for functional analysis of moving organs such as the heart and the tongue. Strain data can be readily obtained using medical imaging. However, quantification of similarity between different data sets is difficult. Strain patterns vary in space and time, and are inherently multidimensional. Also, the same type of mechanical deformation can be applied to different shapes; hence, automatic quantification of similarity should be unaffected by the geometry of the objects being deformed. This work introduces the application of global distributions used to classify shapes and vector fields in the pattern recognition literature, in the context of tensorial strain data. In particular, the distribution of mechanical properties of a field are approximated using a 3D histogram, and the Wasserstein distance from optimal transport theory is used to measure the similarity between histograms. To measure the method's consistency in matching deformations across different objects, the proposed approach was evaluated by sorting strain fields according to their similarity. Performance was compared to sorting via maximum shear distribution (a 1D histogram) and tensor residual magnitude (in perfectly registered objects). The technique was also applied to correlate muscle activation to muscular contraction observed via tagged MRI. The results show that the proposed approach accurately matches deformation regardless of the shape of the object being deformed. Sorting accuracy surpassed 1D shear distribution and was on par with residual magnitude, but without the need for registration between objects.

Resonance of human brain under head acceleration

Although safety standards have reduced fatal head trauma due to single severe head impacts, mild trauma from repeated head exposures may carry risks of long-term chronic changes in the brain's function and structure. To study the physical sensitivities of the brain to mild head impacts, we developed the first dynamic model of the skull-brain based on in vivo MRI data. We showed that the motion of the brain can be described by a rigid-body with constrained kinematics. We further demonstrated that skull-brain dynamics can be approximated by an under-damped system with a low-frequency resonance at around 15 Hz. Furthermore, from our previous field measurements, we found that head motions in a variety of activities, including contact sports, show a primary frequency of less than 20 Hz. This implies that typical head exposures may drive the brain dangerously close to its mechanical resonance and lead to amplified brain-skull relative motions. Our results suggest a possible cause for mild brain trauma, which could occur due to repetitive low-acceleration head oscillations in a variety of recreational and occupational activities.

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.

Distribution of normal human left ventricular myofiber stress at end diastole and end systole: a target for in silico design of heart failure treatments

Ventricular wall stress is believed to be responsible for many physical mechanisms taking place in the human heart, including ventricular remodeling, which is frequently associated with heart failure. Therefore, normalization of ventricular wall stress is the cornerstone of many existing and new treatments for heart failure. In this paper, we sought to construct reference maps of normal ventricular wall stress in humans that could be used as a target for in silico optimization studies of existing and potential new treatments for heart failure. To do so, we constructed personalized computational models of the left ventricles of five normal human subjects using magnetic resonance images and the finite-element method. These models were calibrated using left ventricular volume data extracted from magnetic resonance imaging (MRI) and validated through comparison with strain measurements from tagged MRI (950 ± 170 strain comparisons/subject). The calibrated passive material parameter values were C0 = 0.115 ± 0.008 kPa and B0 = 14.4 ± 3.18; the active material parameter value was Tmax = 143 ± 11.1 kPa. These values could serve as a reference for future construction of normal human left ventricular computational models. The differences between the predicted and the measured circumferential and longitudinal strains in each subject were 3.4 ± 6.3 and 0.5 ± 5.9%, respectively. The predicted end-diastolic and end-systolic myofiber stress fields for the five subjects were 2.21 ± 0.58 and 16.54 ± 4.73 kPa, respectively. Thus these stresses could serve as targets for in silico design of heart failure treatments.

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.

Extracting tissue deformation using Gabor filter banks

This paper presents a new approach for accurate extraction of tissue deformation imaged with tagged MR. Our method, based on banks of Gabor filters, adjusts (1) the aspect and (2) orientation of the filter's envelope and adjusts (3) the radial frequency and (4) angle of the filter's sinusoidal grating to extract information about the deformation of tissue. The method accurately extracts tag line spacing, orientation, displacement and effective contrast. Existing, non-adaptive methods often fail to recover useful displacement information in the proximity of tissue boundaries while our method works in the proximity of the boundaries. We also present an interpolation method to recover all tag information at a finer resolution than the filter bank parameters. Results are shown on simulated images of translating and contracting tissue.