Manduca, Armando

BackgroundMR elastography (MRE) at 60 Hz is widely used for staging liver fibrosis. MRE with lower frequencies may provide inflammation biomarkers.PurposeTo establish a practical simultaneous dual‐frequency liver MRE protocol at both 30 Hz and 60 Hz during a single examination and validate the occurrence of second harmonic waves at 30 Hz.Study TypeRetrospective.SubjectsOne hundred six patients (48 females, age: 50.0 ± 13.4 years) were divided as follows: Cohort One (15 patients with chronic liver disease [CLD] and 25 healthy volunteers) with simultaneous dual‐frequency MRE. Cohort Two (66 patients with CLD) with second harmonic MRE.Field Strength/Sequence3‐T, single‐ or dual‐frequency MRE at 30 Hz and 60 Hz.AssessmentLiver stiffness (LS) in both cohorts was evaluated with manually placed volumetric ROIs by two independent analyzers. Image quality was assessed by three independent readers on a 4‐point scale (0–3: none/failed, fair, moderate, excellent) based on the depth of wave propagation with 1/3 incremental penetration. The success rate was derived from the percentage of nonzero quality scores.Statistical TestsMeasurement agreement, bias, and repeatability of LS were assessed using intraclass correlation coefficients (ICCs), Bland–Altman plots, and repeatability coefficient (RC). Mann–Whitney U tests were used to evaluate the differences in image quality between different methods. A P‐value <0.05 was considered statistically significant.ResultsSuccess rate was 97.5% in Cohort One and 91% success rate for the second harmonic MRE in Cohort Two. The second harmonic and conventional MRE showed excellent agreement in LS (all ICCs >0.90). The quality scores for the second harmonic wave images were lower than those from the conventional MRE (Z = −4.523).Data ConclusionCompared with conventional and second harmonic methods, simultaneous dual‐frequency had better image quality, high success rate and the advantage of intrinsic co‐registration, while the second harmonic method can be an alternative if custom waveform is not available.Evidence Level3Technical EfficacyStage 1

Abstract Functional MRI (fMRI) is widely used to spatially localize neural activity in the brain associated with functional stimuli. Functional MR Elastography (fMRE) has recently been introduced as a complementary approach that measures the mechanical response to functional stimulus. The hypothesis of the current study is that the stiffness change in fMRE is proportional to the underlying neural activity. This hypothesis is tested by measuring the median stiffness change in the visual cortex as a function of luminance-matched contrast intensity of a checkerboard visual stimulus in 16 healthy subjects. The fMRE signal in the visual cortex was observed to be proportional to the contrast intensity of the visual stimulus. In regions of activation, fMRE signal increased in the range of 2 ± 1% to 5.8 ± 1% and fMRI signal increased by the expected 0.4 ± 0.2% to 0.9 ± 0.2%, for contrast levels of 5% to 100%, respectively. In conclusion, this study shows that the fMRE signal in the visual cortex can be directly modulated by the contrast intensity of a visual stimulus. The presence of some overlap between fMRI and fMRE regions of activation may suggest two distinct mechanisms governing the fMRI and fMRE signals, which will be investigated in future studies.

AbstractPurposeAbnormal adherence at functional myofascial interfaces is hypothesized as an important phenomenon in myofascial pain syndrome. This study aimed to investigate the feasibility of MR elastography (MRE)–based slip interface imaging (SII) to visualize and assess myofascial mobility in healthy volunteers.MethodsSII was used to assess local shear strain at functional myofascial interfaces in the flexor digitorum profundus (FDP) and thighs. In the FDP, MRE was performed at 90 Hz vibration to each index, middle, ring, and little finger. Two thigh MRE scans were performed at 40 Hz with knees flexed and extended. The normalized octahedral shear strain (NOSS) maps were calculated to visualize myofascial slip interfaces. The entropy of the probability distribution of the gradient NOSS was computed for the two knee positions at the intermuscular interface between vastus lateralis and vastus intermedius, around rectus femoris, and between vastus intermedius and vastus medialis.ResultsNOSS map depicted distinct functional slip interfaces in the FDP for each finger. Compared to knee flexion, clearer slip interfaces and larger gradient NOSS entropy at the vastus lateralis–vastus intermedius interface were observed during knee extension, where the quadriceps are not passively stretched. This suggests the optimal position for using SII to visualize myofascial slip interface in skeletal muscles is when muscles are not subjected to any additional force.ConclusionThe study demonstrated that MRE‐based SII can visualize and assess myofascial interface mobility in extremities. The results provide a foundation for investigating the hypothesis that myofascial pain syndrome is characterized by changes in the mobility of myofascial interfaces.

Abstract Vascular brain injury results in loss of structural and functional connectivity and leads to cognitive impairment. Its various manifestations, including microinfarcts, microhaemorrhages and white matter hyperintensities, result in microstructural tissue integrity loss and secondary neurodegeneration. Among these, tissue microstructural alteration is a relatively early event compared with atrophy along the aging and neurodegeneration continuum. Understanding its association with cognition may provide the opportunity to further elucidate the relationship between vascular health and clinical outcomes. Magnetic resonance elastography offers a non-invasive approach to evaluate tissue mechanical properties, providing a window into the microstructural integrity of the brain. This retrospective study evaluated brain stiffness as a potential biomarker for vascular brain injury and its role in mediating the impact of vascular dysfunction on cognitive impairment. Seventy-five participants from the Mayo Clinic Study of Aging underwent brain imaging using a 3T MR imager with a spin-echo echo-planar imaging sequence for magnetic resonance elastography and T1- and T2-weighted pulse sequences. This study evaluated the effects of vascular biomarkers (white matter hyperintensities and cardiometabolic condition score) on brain stiffness using voxelwise analysis. Partial correlation analysis explored associations between brain stiffness, white matter hyperintensities, cardiometabolic condition and global cognition. Mediation analysis determined the role of stiffness in mediating the relationship between vascular biomarkers and cognitive performance. Statistical significance was set at P-values &lt; 0.05. Diagnostic accuracy of magnetic resonance elastography stiffness for white matter hyperintensities and cardiometabolic condition was evaluated using receiver operator characteristic curves. Voxelwise linear regression analysis indicated white matter hyperintensities negatively correlate with brain stiffness, specifically in periventricular regions with high white matter hyperintensity levels. A negative association between cardiovascular risk factors and stiffness was also observed across the brain. No significant patterns of stiffness changes were associated with amyloid load. Global stiffness (µ) negatively correlated with both white matter hyperintensities and cardiometabolic condition when all other covariables including amyloid load were controlled. The positive correlation between white matter hyperintensities and cardiometabolic condition weakened and became statistically insignificant when controlling for other covariables. Brain stiffness and global cognition were positively correlated, maintaining statistical significance after adjusting for all covariables. These findings suggest mechanical alterations are associated with cognitive dysfunction and vascular brain injury. Brain stiffness significantly mediated the indirect effects of white matter hyperintensities and cardiometabolic condition on global cognition. Local cerebrovascular diseases (assessed by white matter hyperintensities) and systemic vascular risk factors (assessed by cardiometabolic condition) impact brain stiffness with spatially and statistically distinct effects. Global brain stiffness is a significant mediator between vascular disease measures and cognitive function, highlighting the value of magnetic resonance elastography-based mechanical assessments in understanding this relationship.

AbstractBackgroundCognitive decline with aging and neurodegeneration is caused by various neurobiological processes at molecular, cellular, and organ levels. Advanced imaging techniques that detect tissue microstructural alterations may predict cognitive decline earlier than atrophy measures. Tissue‐level mechanical properties are thought to primarily reflect the rigidity and tension of extracellular matrix‐cytoskeleton matrix (https://doi.org/10.1038/s41586‐019‐1516‐5) and can be measured noninvasively by Magnetic Resonance Elastography (MRE) (https://doi.org/10.1126/science.7569924). These properties are sensitive to pathophysiological processes that characterize neurological disease including dementias. This study examines the role of medial temporal lobe stiffness in predicting global cognitive decline in participants along the Alzheimer’s disease spectrum.MethodSeventy‐five participants underwent MRE, MRI, amyloid PET imaging, and cognitive assessments with informed consent, and the study was approved by the Mayo Clinic IRB. MRE stiffness maps were calculated by neural network inversion, and medial temporal (MT) stiffness extracted (https://doi.org/10.1002/mrm.29226https://doi.org/10.1016/j.nicl.2023.103328). White matter hyperintensity (WMH) load, average cortical thickness of AD signature regions, PiB‐PET standardized uptake ratio (PiB‐SUVr), and global cognition z‐scores were each computed (https://doi.org/10.1016/j.neurobiolaging.2020.09.005). Linear mixed effect models were used to assess the effects of MT‐stiffness and its interaction with follow‐up time on global cognition. The additional effects of cortical thickness, WMH, and PiB‐SUVr, and their interactions with cognition follow‐up time were evaluated.ResultTable 1 summarizes results from three mixed effect models. MT‐stiffness and its interaction with time were significant predictors in models 1 (MT‐stiffness only) and 2 (MT‐stiffness+cortical thickness). In model 3 (MT‐stiffness+cortical thickness+PiB‐ratio+WMH), MT‐stiffness alone did not reach significance (P= 0.058), but its interaction with time was a significant predictor. Fig.1 shows global cognition z‐scores with age. Figs. 2A,2B, and 2C show global cognition prediction trajectories. These results suggest that softer MT‐stiffness predicts faster cognitive decline. MT‐stiffness was a significant predictor of cognitive score even when controlling for other biomarkers such as cortical thickness, PiB‐SUVr, and WMH. These results indicate that stiffness measurements can add predictive value regarding cognitive decline in addition to atrophy and amyloidosis.ConclusionBrain mechanical alterations capture microstructural changes that may aid in understanding disease progression and provide information about future cognitive decline in elderly participants along the Alzheimer’s disease continuum.

AbstractPurposeTo demonstrate a novel MR elastography (MRE) technique, termed here wavelet MRE. With this technique, broadband motion sensitivity is achievable. Moreover, the true tissue displacement can be reconstructed with a simple inverse transform.MethodsA wavelet MRE sequence was developed with motion‐encoding gradients based on Haar wavelets. From the phase images' displacement was estimated using an inverse transform. Simulations were performed using a frequency sweep and a transient as ground‐truth motions. A PVC phantom was scanned using wavelet MRE and standard MRE with both transient (one and 10 cycles of 90‐Hz motion) and steady‐state dual‐frequency motion (30 and 60 Hz) for comparison. The technique was tested in a human brain, and motion trajectories were estimated for each voxel.ResultsIn simulation, the displacement information estimated from wavelet MRE closely matched the true motion. In the phantom test, the MRE phase data generated from the displacement information derived from wavelet MRE agreed well with standard MRE data. Testing of wavelet MRE to assess transient motion waveforms in the brain was successful, and the tissue motion observed was consistent with a previous study.ConclusionThe uniform and broadband frequency response of wavelet MRE makes it a promising method for imaging transient, multifrequency motion, or motion with unknown frequency content. One potential application is measuring the response of brain tissue undergoing low‐amplitude, transient vibrations as a model for the study of traumatic brain injury.

Increasing concerns have been raised about the long-term negative effects of subconcussive repeated head impact (RHI). To elucidate RHI injury mechanisms, many efforts have studied how head impacts affect the skull-brain biomechanics and have found that mechanical interactions at the skull-brain interface dampen and isolate brain motions by decoupling the brain from the skull. Despite intense interest, in vivo quantification of the functional state of the skull-brain interface remains difficult. This study developed a magnetic resonance elastography (MRE) based technique to non-invasively assess skull-brain mechanical interactions (i.e., motion transmission and isolation function) under dynamic loading. The full MRE displacement data were separated into rigid body motion and wave motion. The rigid body motion was used to calculate the brain-to-skull rotational motion transmission ratio ( R tr ) to quantify skull-brain motion transmissibility, and the wave motion was used to calculate the cortical normalized octahedral shear strain ( NOSS ) (calculated based on a partial derivative computing neural network) to evaluate the isolation capability of the skull-brain interface. Forty-seven healthy volunteers were recruited to investigate the effects of age/sex on R tr and cortical NOSS , and 17 of 47 volunteers received multiple scans to test the repeatability of the proposed techniques under different strain conditions. The results showed that both R tr and NOSS were robust to MRE driver variations and had good repeatability, with intraclass correlation coefficient (ICC) values between 0.68 and 0.97 (fair to excellent). No age or sex dependence were observed with R tr , whereas a significant positive correlation between age and NOSS was found in the cerebrum, frontal, temporal, and parietal lobes (all p < 0.05), but not in the occipital lobe ( p = 0.99). The greatest change in NOSS with age was found in the frontal lobe, one of the most frequent locations of traumatic brain injury (TBI). Except for the temporal lobe ( p = 0.0087), there was no significant difference in NOSS between men and women. This work provides motivation for utilizing MRE as a non-invasive tool for quantifying the biomechanics of the skull-brain interface. It evaluated the age and sex dependence and may lead to a better understanding of the protective role and mechanisms of the skull-brain interface in RHI and TBI, as well as improve the accuracy of computational models in simulating the skull-brain interface.

Background and Aims: The presence of at-risk NASH is associated with an increased risk of cirrhosis and complications. Therefore, noninvasive identification of at-risk NASH with an accurate biomarker is a critical need for pharmacologic therapy. We aim to explore the performance of several magnetic resonance (MR)-based imaging parameters in diagnosing at-risk NASH. Approach and Results: This prospective clinical trial (NCT02565446) includes 104 paired MR examinations and liver biopsies performed in patients with suspected or diagnosed NAFLD. Magnetic resonance elastography-assessed liver stiffness (LS), 6-point Dixon-derived proton density fat fraction (PDFF), and single-point saturation-recovery acquisition-calculated T1 relaxation time were explored. Among all predictors, LS showed the significantly highest accuracy in diagnosing at-risk NASH [AUCLS: 0.89 (0.82, 0.95), AUCPDFF: 0.70 (0.58, 0.81), AUCT1: 0.72 (0.61, 0.82), z-score test z >1.96 for LS vs any of others]. The optimal cutoff value of LS to identify at-risk NASH patients was 3.3 kPa (sensitivity: 79%, specificity: 82%, negative predictive value: 91%), whereas the optimal cutoff value of T1 was 850 ms (sensitivity: 75%, specificity: 63%, and negative predictive value: 87%). PDFF had the highest performance in diagnosing NASH with any fibrosis stage [AUCPDFF: 0.82 (0.72, 0.91), AUCLS: 0.73 (0.63, 0.84), AUCT1: 0.72 (0.61, 0.83), |z| <1.96 for all]. Conclusion: Magnetic resonance elastography-assessed LS alone outperformed PDFF, and T1 in identifying patients with at-risk NASH for therapeutic trials.

PurposeInversion algorithms used to convert acquired MR elastography wave data into material property estimates often assume that the underlying materials are locally homogeneous. Here we evaluate the impact of that assumption on stiffness estimates in gray‐matter regions of interest in brain MR elastography.MethodsWe describe an updated neural network inversion framework using finite‐difference model–derived data to train convolutional neural network inversion algorithms. Neural network inversions trained on homogeneous simulations (homogeneous learned inversions [HLIs]) or inhomogeneous simulations (inhomogeneous learned inversions [ILIs]) are generated with a variety of kernel sizes. These inversions are evaluated in a brain MR elastography simulation experiment and in vivo in a test–retest repeatability experiment including 10 healthy volunteers.ResultsIn simulation and in vivo, HLI and ILI with small kernels produce similar results. As kernel size increases, the assumption of homogeneity has a larger effect, and HLI and ILI stiffness estimates show larger differences. At each inversion's optimal kernel size in simulation (7 × 7 × 7 for HLI, 11 × 11 × 11 for ILI), ILI is more sensitive to true changes in stiffness in gray‐matter regions of interest in simulation. In vivo, there is no difference in the region‐level repeatability of stiffness estimates between the inversions, although ILI appears to better maintain the stiffness map structure as kernel size increases, while decreasing the spatial variance in stiffness estimates.ConclusionsThis study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.