Wavelet MRE: Imaging propagating broadband acoustic waves with wavelet-based motion-encoding gradients.

PURPOSE: To 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. METHODS: A 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. RESULTS: In 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. CONCLUSION: The 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.

MR elastography-based slip interface imaging (SII) for functional assessment of myofascial interfaces: A feasibility study.

PURPOSE: Abnormal 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. METHODS: SII 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. RESULTS: NOSS 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. CONCLUSION: The 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.

MR Elastography-Based Shear Strain Mapping for Assessment of Microvascular Invasion in Hepatocellular Carcinoma.

OBJECTIVES: To evaluate the potential of MR elastography (MRE)-based shear strain mapping to noninvasively predict the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS: Fifty-nine histopathology-proven HCC patients with conventional 60-Hz MRE examinations (+/-MVI, n = 34/25) were enrolled retrospectively between December 2016 and October 2019, with one subgroup comprising 29/59 patients (+/-MVI, n = 16/13) who also underwent 40- and 30-Hz MRE examinations. Octahedral shear strain (OSS) maps were calculated, and the percentage of peritumoral interface length with low shear strain (i.e., a low-shear-strain length, pLSL, %) was recorded. For OSS-pLSL, differences between the MVI (+) and MVI (-) groups and diagnostic performance at different MRE frequencies were analyzed using the Mann-Whitney test and area under the receiver operating characteristic curve (AUC), respectively. RESULTS: The peritumor OSS-pLSL was significantly higher in the MVI (+) group than in the MVI (-) group at the three frequencies (all p < 0.01). The AUC of peritumor OSS-pLSL for predicting MVI was good/excellent in all frequency groups (60-Hz: 0.73 (n = 59)/0.80 (n = 29); 40-Hz: 0.84; 30-Hz: 0.90). On further analysis of the 29 cases with all frequencies, the AUCs were not significantly different. As the frequency decreased from 60-Hz, the specificity of OSS increased at 40-Hz (53.8-61.5%) and further increased at 30-Hz (53.8-76.9%), and the sensitivity remained high at lower frequencies (100.0-93.8%) (all p > 0.05). CONCLUSIONS: MRE-based shear strain mapping is a promising technique for noninvasively predicting the presence of MVI in patients with HCC, and the most recommended frequency for OSS is 30-Hz. KEY POINTS: • MR elastography (MRE)-based shear strain mapping has the potential to predict the presence of microvascular invasion (MVI) in hepatocellular carcinoma preoperatively. • The low interface shear strain identified at tumor-liver boundaries was highly correlated with the presence of MVI.

Multiparametric magnetic resonance imaging/magnetic resonance elastography assesses progression and regression of steatosis, inflammation, and fibrosis in alcohol-associated liver disease.

BACKGROUND: Magnetic resonance imaging (MRI) and MRI-based elastography (MRE) are the most promising noninvasive techniques in assessing liver diseases. The purpose of this study was to evaluate an advanced multiparametric imaging method for staging disease and assessing treatment response in realistic preclinical alcohol-associated liver disease (ALD). METHODS: We utilized four different preclinical mouse models in our study: Model 1-mice were fed a fast-food diet and fructose water for 48 weeks to induce nonalcoholic fatty liver disease; Model 2-mice were fed chronic-binge ethanol (EtOH) for 10 days or 8 weeks to induce liver steatosis/inflammation. Two groups of mice were treated with interleukin-22 at different time points to induce disease regression; Model 3-mice were administered CCl4 for 2 to 4 weeks to establish liver fibrosis followed by 2 or 4 weeks of recovery; and Model 4-mice were administered EtOH plus CCl4 for 12 weeks. Mouse liver imaging biomarkers including proton density fat fraction (PDFF), liver stiffness (LS), loss modulus (LM), and damping ratio (DR) were assessed. Liver and serum samples were obtained for histologic and biochemical analyses. Ordinal logistic regression and generalized linear regression analyses were used to model the severity of steatosis, inflammation, and fibrosis, and to assess the regression of these conditions. RESULTS: Multiparametric models with combinations of biomarkers (LS, LM, DR, and PDFF) used noninvasively to predict the histologic severity and regression of steatosis, inflammation, and fibrosis were highly accurate (area under the curve > 0.84 for all). A three-parameter model that incorporates LS, DR, and ALT predicted histologic fibrosis progression (r = 0.84, p < 0.0001) and regression (r = 0.79, p < 0.0001) as measured by collagen content in livers. CONCLUSION: This preclinical study provides evidence that multiparametric MRI/MRE can be used noninvasively to assess disease severity and monitor treatment response in ALD.

A new method for quantification and 3D visualization of brain tumor adhesion using slip interface imaging in patients with meningiomas.

OBJECTIVES: To develop an objective quantitative method to characterize and visualize meningioma-brain adhesion using MR elastography (MRE)-based slip interface imaging (SII). METHODS: This retrospective study included 47 meningiomas (training dataset: n = 35; testing dataset: n = 12) with MRE/SII examinations. Normalized octahedral shear strain (NOSS) values were calculated from the acquired MRE displacement data. The change in NOSS at the tumor boundary (ΔNOSSbdy) was computed, from which a 3D ΔNOSSbdy map of the tumor surface was created and the probability distribution of ΔNOSSbdy over the entire tumor surface was calculated. Statistical features were calculated from the probability histogram. After eliminating highly correlated features, the capability of the remaining feature for tumor adhesion classification was assessed using a one-way ANOVA and ROC analysis. RESULTS: The magnitude and location of the tumor adhesion can be visualized by the reconstructed 3D ΔNOSSbdy surface map. The entropy of the ΔNOSSbdy histogram was significantly different between adherent tumors and partially/completely non-adherent tumors in both the training (AUC: 0.971) and testing datasets (AUC: 0.900). Based on the cutoff values obtained from the training set, the ΔNOSSbdy entropy in the testing dataset yielded an accuracy of 0.83 for distinguishing adherent versus partially/non-adherent tumors, and 0.67 for distinguishing non-adherent versus completely/partially adherent tumors. CONCLUSIONS: SII-derived ΔNOSSbdy values are useful for quantification and classification of meningioma-brain adhesion. The reconstructed 3D ΔNOSSbdy surface map presents the state and location of tumor adhesion in a "clinician-friendly" manner, and can identify meningiomas with a high risk of adhesion to adjacent brain parenchyma. KEY POINTS: • MR elastography (MRE)-based slip interface imaging shows promise as an objective tool to preoperatively discriminate meningiomas with a high risk of intraoperative adhesion. • Measurement of the change of shear strain at meningioma boundaries can provide quantitative metrics depicting the state of adhesion at the tumor-brain interface. • The surface map of tumor adhesion shows promise in assisting precise adhesion localization, using a comprehensible, "clinician-friendly" 3D visualization.

Prediction of nonalcoholic fatty liver disease (NAFLD) activity score (NAS) with multiparametric hepatic magnetic resonance imaging and elastography.

OBJECTIVES: To investigate the use of MR elastography (MRE)-derived mechanical properties (shear stiffness (|G*|) and loss modulus (G″)) and MRI-derived fat fraction (FF) to predict the nonalcoholic fatty liver disease (NAFLD) activity score (NAS) in a NAFLD mouse model. METHODS: Eighty-nine male mice were studied, including 64 training and 25 independent testing animals. An MRI/MRE exam and histologic evaluation were performed. Pairwise, nonparametric comparisons and multivariate analyses were used to evaluate the relationships between the three imaging parameters (FF, |G*|, and G″) and histologic features. A virtual NAS score (vNAS) was generated by combining three imaging parameters with an ordinal logistic model (OLM) and a generalized linear model (GLM). The prediction accuracy was evaluated by ROC analyses. RESULTS: The combination of FF, |G*|, and G″ predicted NAS > 1 with excellent accuracy in both training and testing sets (AUROC > 0.84). OLM and GLM predictive models misclassified 3/54 and 6/54 mice in the training, and 1/25 and 1/25 in the testing cohort respectively, in distinguishing between "not-NASH" and "definite-NASH." "Borderline-NASH" prediction was poorer in the training set, and no borderline-NASH mice were available in the testing set. CONCLUSION: This preliminary study shows that multiparametric MRI/MRE can be used to accurately predict the NAS score in a NAFLD animal model, representing a promising alternative to liver biopsy for assessing NASH severity and treatment response. KEY POINTS: • MRE-derived liver stiffness and loss modulus and MRI-assessed fat fraction can be used to predict NAFLD activity score (NAS) in our preclinical mouse model (AUROC > 0.84 for all NAS levels greater than 1). • The overall agreement between the histological-determined NASH diagnosis and the imaging-predicted NASH diagnosis is 80-92%. • The multiparametric hepatic MRI/MRE has great potential for noninvasively assessing liver disease severity and treatment efficacy.

In vivo characterization of 3D skull and brain motion during dynamic head vibration using magnetic resonance elastography.

PURPOSE: To introduce newly developed MR elastography (MRE)-based dual-saturation imaging and dual-sensitivity motion encoding schemes to directly measure in vivo skull-brain motion, and to study the skull-brain coupling in volunteers with these approaches. METHODS: Six volunteers were scanned with a high-performance compact 3T-MRI scanner. The skull-brain MRE images were obtained with a dual-saturation imaging where the skull and brain motion were acquired with fat- and water-suppression scans, respectively. A dual-sensitivity motion encoding scheme was applied to estimate the heavily wrapped phase in skull by the simultaneous acquisition of both low- and high-sensitivity phase during a single MRE exam. The low-sensitivity phase was used to guide unwrapping of the high-sensitivity phase. The amplitude and temporal phase delay of the rigid-body motion between the skull and brain was measured, and the skull-brain interface was visualized by slip interface imaging (SII). RESULTS: Both skull and brain motion can be successfully acquired and unwrapped. The skull-brain motion analysis demonstrated the motion transmission from the skull to the brain is attenuated in amplitude and delayed. However, this attenuation (%) and delay (rad) were considerably greater with rotation (59 ± 7%, 0.68 ± 0.14 rad) than with translation (92 ± 5%, 0.04 ± 0.02 rad). With SII the skull-brain slip interface was not completely evident, and the slip pattern was spatially heterogeneous. CONCLUSION: This study provides a framework for acquiring in vivo voxel-based skull and brain displacement using MRE that can be used to characterize the skull-brain coupling system for understanding of mechanical brain protection mechanisms, which has potential to facilitate risk management for future injury.

Concurrent 3D acquisition of diffusion tensor imaging and magnetic resonance elastography displacement data (DTI-MRE): Theory and in vivo application.

PURPOSE: To introduce a newly developed technique (DTI-MRE) for the simultaneous acquisition of diffusion tensor imaging (DTI) and 3D-vector field magnetic resonance elastography (MRE) data, and to demonstrate its feasibility when applied in vivo to the mouse brain. METHODS: In DTI-MRE, simultaneous encoding is achieved by using a series of diffusion/motion-sensitizing gradients (dMSGs) with specific timing and directions. By adjusting the duration of the dMSGs with the diffusion time and with the mechanical vibration frequency, the shear wave motion and diffusion are encoded into the MR phase and MR magnitude signals, respectively. The dMSGs are applied in a noncollinear and noncoplanar manner that optimizes the capture of both the DTI signal attenuation and the three-dimensional MRE displacements. In this work, the feasibility of the DTI-MRE technique was demonstrated on in vivo mouse brains (n=3) using a 9.4T animal MRI scanner. The DTI-MRE derived parameters (MD, mean diffusivity; FA, fractional anisotropy; MRE displacement fields; and shear modulus |G|) were compared with those acquired using conventional, separate MRE and diffusion methods. RESULTS: The averaged (MD, FA, and |G|) values for three mice are (0.580 ± 0.050 µm2 /ms, 0.43 ± 0.02, and 4.80 ± 0.06 kPa) and (0.583 ± 0.035 µm2 /ms, 0.46 ± 0.02, and 4.91 ± 0.19 kPa) for DTI-MRE, and conventional DTI and 3D-vector field MRE measurements, respectively. All derived parameters (MD, FA, |G|, and displacement) obtained using the combined DTI-MRE method and conventional methods were significantly correlated with P < 0.05. CONCLUSION: Simultaneous acquisition of DTI and 3D-vector field MRE is feasible in vivo and reduces the scan time by up to 50% compared with conventional, separate acquisitions, while providing an immediate co-registration of maps of diffusion properties and stiffness. Magn Reson Med 77:273-284, 2017. © 2016 Wiley Periodicals, Inc.

Slip interface imaging based on MR-elastography preoperatively predicts meningioma-brain adhesion.

PURPOSE: To investigate the ability of slip interface imaging (SII), a recently developed magnetic resonance elastography (MRE)-based technique, to predict the degree of meningioma-brain adhesion, using findings at surgery as the reference standard. MATERIALS AND METHODS: With Institutional Review Board approval and written informed consent, 25 patients with meningiomas >2.5 cm in maximal diameter underwent preoperative SII assessment. Intracranial shear motions were introduced using a soft, pillow-like head driver and the resulting displacement field was acquired with an MRE pulse sequence on 3T MR scanners. The displacement data were analyzed to determine tumor-brain adhesion by assessing intensities on shear line images and raw as well as normalized octahedral shear strain (OSS) values along the interface. The SII findings of shear line images, OSS, and normalized OSS were independently and blindly correlated with surgical findings of tumor adhesion by using the Cohen's κ coefficient and chi-squared test. RESULTS: Neurosurgeons categorized the surgical plane as extrapial (no adhesion) in 15 patients, mixed in four, and subpial (adhesion) in six. Both shear line images and OSS agreed with the surgical findings in 18 (72%) cases (fair agreement, κ = 0.37, 95% confidence interval [CI]: 0.05-0.69), while normalized OSS was concordant with the surgical findings in 23 (92%) cases (good agreement, κ = 0.86, 95% CI: 0.67-1). The correlation between SII predictions (shear line images, OSS, and normalized OSS) and the surgical findings were statistically significant (chi-squared test, P = 0.02, P = 0.02, and P < 0.0001, respectively). CONCLUSION: SII preoperatively evaluates the degree of meningioma-brain adhesion noninvasively, allowing for improved prediction of surgical risk and tumor resectability. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1007-1016.

Slip Interface Imaging Predicts Tumor-Brain Adhesion in Vestibular Schwannomas.

PURPOSE: To test the clinical feasibility and usefulness of slip interface imaging (SII) to identify and quantify the degree of tumor-brain adhesion in patients with vestibular schwannomas. MATERIALS AND METHOD: S With institutional review board approval and after obtaining written informed consent, SII examinations were performed in nine patients with vestibular schwannomas. During the SII acquisition, a low-amplitude mechanical vibration is applied to the head with a pillow-like device placed in the head coil and the resulting shear waves are imaged by using a phase-contrast pulse sequence with motion-encoding gradients synchronized with the applied vibration. Imaging was performed with a 3-T magnetic resonance (MR) system in less than 7 minutes. The acquired shear motion data were processed with two different algorithms (shear line analysis and calculation of octahedral shear strain [OSS]) to identify the degree of tumor-brain adhesion. Blinded to the SII results, neurosurgeons qualitatively assessed tumor adhesion at the time of tumor resection. Standard T2-weighted, fast imaging employing steady-state acquisition (FIESTA), and T2-weighted fluid-attenuated inversion recovery (FLAIR) imaging were reviewed to identify the presence of cerebral spinal fluid (CSF) clefts around the tumors. The performance of the use of the CSF cleft and SII to predict the degree of tumor adhesion was evaluated by using the κ coefficient and McNemar test. RESULTS: Among the nine patients, SII agreed with the intraoperative assessment of the degree of tumor adhesion in eight patients (88.9%; 95% confidence interval [CI]: 57%, 98%), with four of four, three of three, and one of two cases correctly predicted as no adhesion, partial adhesion, and complete adhesion, respectively. However, the T2-weighted, FIESTA, and T2-weighted FLAIR images that used the CSF cleft sign to predict adhesion agreed with surgical findings in only four cases (44.4% [four of nine]; 95% CI: 19%, 73%). The κ coefficients indicate good agreement (0.82 [95% CI: 0.5, 1]) for the SII prediction versus surgical findings, but only fair agreement (0.21 [95% CI: -0.21, 0.63]) between the CSF cleft prediction and surgical findings. However, the difference between the SII prediction and the CSF cleft prediction was not significant (P = .103; McNemar test), likely because of the small sample size in this study. CONCLUSION: SII can be used to predict the degree of tumor-brain adhesion of vestibular schwannomas and may provide a method to improve preoperative planning and determination of surgical risk in these patients.

Assessment of glenoid chondral healing: comparison of microfracture to autologous matrix-induced chondrogenesis in a novel rabbit shoulder model.

BACKGROUND: Management of glenohumeral arthrosis in young patients is a considerable challenge, with a growing need for non-arthroplasty alternatives. The objectives of this study were to develop an animal model to study glenoid cartilage repair and to compare surgical repair strategies to promote glenoid chondral healing. METHODS: Forty-five rabbits underwent unilateral removal of the entire glenoid articular surface and were divided into 3 groups--untreated defect (UD), microfracture (MFx), and MFx plus type I/III collagen scaffold (autologous matrix-induced chondrogenesis [AMIC])--for the evaluation of healing at 8 weeks (12 rabbits) and 32 weeks (33 rabbits) after injury. Contralateral shoulders served as unoperated controls. Tissue assessments included 11.7-T magnetic resonance imaging (long-term healing group only), equilibrium partitioning of an ionic contrast agent via micro-computed tomography (EPIC-µCT), and histologic investigation (grades on International Cartilage Repair Society II scoring system). RESULTS: At 8 weeks, x-ray attenuation, thickness, and volume did not differ by treatment group. At 32 weeks, the T2 index (ratio of T2 values of healing to intact glenoids) was significantly lower for the MFx group relative to the AMIC group (P = .01) whereas the T1ρ index was significantly lower for AMIC relative to MFx (P = .01). The micro-computed tomography-derived repair tissue volume was significantly higher for MFx than for UD. Histologic investigation generally suggested inferior healing in the AMIC and UD groups relative to the MFx group, which exhibited improvements in both integration of repair tissue with subchondral bone and tidemark formation over time. DISCUSSION: Improvements conferred by AMIC were limited to magnetic resonance imaging outcomes, whereas MFx appeared to promote increased fibrous tissue deposition via micro-computed tomography and more hyaline-like repair histologically. The findings from this novel model suggest that MFx promotes biologic resurfacing of full-thickness glenoid articular injury.

Simultaneous MR elastography and diffusion acquisitions: diffusion-MRE (dMRE).

PURPOSE: To present a new technique for concurrent MR elastography (MRE) and diffusion MRI: diffusion-MRE (dMRE). METHODS: In dMRE, shear wave motion and MR signal decay due to diffusion are encoded into the phase and magnitude components of the MR signal by using a pair of bipolar gradients for both motion-sensitization and diffusion encoding. The pulse sequence timing is adjusted so that the bipolar gradients are sensitive to both coherent and incoherent intravoxel motions. The shape, number, and duration of the gradient lobes can be adjusted to provide flexibility and encoding efficiency. In this proof-of-concept study, dMRE was validated using a tissue phantom composed of a gel bead embedded in a hydrated mixture of agarose and gelatin. The apparent diffusion coefficient (ADC) and shear stiffness measured using dMRE were compared with results obtained from separate, conventional spin-echo (SE) diffusion and SE-MRE acquisitions. RESULTS: The averaged ADC values (n = 3) for selected ROIs in the beads were (1.75 ± 0.16) µm(2) /ms and (1.74 ± 0.16) µm(2) /ms for SE-diffusion and dMRE methods, respectively. The corresponding shear stiffness values in the beads were (2.45 ± 0.23) kPa and (2.42 ± 0.20) kPa. CONCLUSION: Simultaneous MRE and diffusion acquisition is feasible and can be implemented with no observable interference between the two methods.

Magnetic resonance characterization of tissue engineered cartilage via changes in relaxation times, diffusion coefficient, and shear modulus.

The primary goal of this paper is to describe a combined MR relaxation (T(2) and T(1ρ)), diffusion (apparent diffusion coefficient [ADC]), and elastography (shear stiffness) method of fully characterizing the development of tissue-engineered cartilage in terms of the changes in its composition, structure, and mechanical properties during tissue growth. Then, we may better use MR-based methodologies to noninvasively monitor and optimize the cartilage tissue engineering process without sacrificing the constructs. This process begins by demonstrating the potential capability of T(2), T(1ρ), ADC, and shear stiffness in characterizing a scaffold-free engineered cartilage. The results show that, in addition to the conventional T(2) and ADC, T(1ρ) and MRE can be used as potential biomarkers to assess the specific changes in proteoglycan content and mechanical properties of engineered cartilage during culture. Moreover, to increase the efficiency of MR characterization, two new methodologies for simultaneous acquisition of diffusion and MRE (dMRE), and T(1ρ) and MRE (T(1ρ)-MRE) are introduced that allow the simultaneous characterization of both biochemical and mechanical properties of engineered cartilage tissue. The feasibilities of dMRE and T(1ρ)-MRE approaches are validated on tissue-mimicking phantoms. The results show good correspondence between simultaneous acquisitions and conventional separate acquisition methods.

SWENet: A Physics-Informed Deep Neural Network (PINN) for Shear Wave Elastography.

Shear wave elastography (SWE) enables the measurement of elastic properties of soft materials in a non-invasive manner and finds broad applications in various disciplines. The state-of-the-art SWE methods rely on the measurement of local shear wave speeds to infer material parameters and suffer from wave diffraction when applied to soft materials with strong heterogeneity. In the present study, we overcome this challenge by proposing a physics-informed neural network (PINN)-based SWE (SWENet) method. The spatial variation of elastic properties of inhomogeneous materials has been introduced in the governing equations, which are encoded in SWENet as loss functions. Snapshots of wave motions have been used to train neural networks, and during this course, the elastic properties within a region of interest illuminated by shear waves are inferred simultaneously. We performed finite element simulations, tissue-mimicking phantom experiments, and ex vivo experiments to validate the method. Our results show that the shear moduli of soft composites consisting of matrix and inclusions of several millimeters in cross-section dimensions with either regular or irregular geometries can be identified with excellent accuracy. The advantages of the SWENet over conventional SWE methods consist of using more features of the wave motions and enabling seamless integration of multi-source data in the inverse analysis. Given the advantages of SWENet, it may find broad applications where full wave fields get involved to infer heterogeneous mechanical properties, such as identifying small solid tumors with ultrasound SWE, and differentiating gray and white matters of the brain with magnetic resonance elastography.

Association Between Anatomic and Clinical Indicators of Injury Severity After Moderate-Severe Traumatic Brain Injury: A Pilot Study Using Multiparametric Magnetic Resonance Imaging.

This study sought to identify whether an anatomical indicator of injury severity as measured by multiparametric magnetic resonance imaging (MRI) including magnetic resonance elastography (MRE), is predictive of a clinical measure of injury severity after moderate-severe traumatic brain injury (TBI). Nine individuals who were admitted to acute inpatient rehabilitation after moderate-to-severe TBI completed a comprehensive MRI protocol prior to discharge from rehabilitation, which included conventional MRI with diffusion tensor imaging (DTI). Of those, five of nine also underwent brain MRE to measure the brain parenchyma stiffness. Clinical severity of injury was measured by the length of post-traumatic amnesia (PTA). MRI-assessed non-hemorrhage contusion score and hemorrhage score, DTI-measured white matter fractional anisotropy, and MRE-measured lesion stiffness were all assessed. A higher hemorrhagic score was significantly associated with a longer length of PTA (p = 0.026). Participants with a longer PTA tended to have a higher non-hemorrhage contusion score and softer contusion lesions than the contralateral control side, although the small sample size did not allow for assessment of a significant association. To our knowledge, this is the first report applying MRI/MRE imaging protocol to quantitate altered brain anatomy after moderate-severe TBI and its association with PTA, a known clinical predictor of post-acute outcome. Future larger studies could lead to the development of prediction models that integrate clinical data with anatomical (MRI), structural (DTI), and mechanical (MRE) changes caused by TBI, to inform prognosis and care planning.

Improved quantification of tumor adhesion in meningiomas using MR elastography-based slip interface imaging.

Meningiomas, the most prevalent primary benign intracranial tumors, often exhibit complicated levels of adhesion to adjacent normal tissues, significantly influencing resection and causing postoperative complications. Surgery remains the primary therapeutic approach, and when combined with adjuvant radiotherapy, it effectively controls residual tumors and reduces tumor recurrence when complete removal may cause a neurologic deficit. Previous studies have indicated that slip interface imaging (SII) techniques based on MR elastography (MRE) have promise as a method for sensitively determining the presence of tumor-brain adhesion. In this study, we developed and tested an improved algorithm for assessing tumor-brain adhesion, based on recognition of patterns in MRE-derived normalized octahedral shear strain (NOSS) images. The primary goal was to quantify the tumor interfaces at higher risk for adhesion, offering a precise and objective method to assess meningioma adhesions in 52 meningioma patients. We also investigated the predictive value of MRE-assessed tumor adhesion in meningioma recurrence. Our findings highlight the effectiveness of the improved SII technique in distinguishing the adhesion degrees, particularly complete adhesion. Statistical analysis revealed significant differences in adhesion percentages between complete and partial adherent tumors (p = 0.005), and complete and non-adherent tumors (p<0.001). The improved technique demonstrated superior discriminatory ability in identifying tumor adhesion patterns compared to the previously described algorithm, with an AUC of 0.86 vs. 0.72 for distinguishing complete adhesion from others (p = 0.037), and an AUC of 0.72 vs. 0.67 for non-adherent and others. Aggressive tumors exhibiting atypical features showed significantly higher adhesion percentages in recurrence group compared to non-recurrence group (p = 0.042). This study validates the efficacy of the improved SII technique in quantifying meningioma adhesions and demonstrates its potential to affect clinical decision-making. The reliability of the technique, coupled with potential to help predict meningioma recurrence, particularly in aggressive tumor subsets, highlights its promise in guiding treatment strategies.

Effects of extreme drought events on vegetation activity from the perspectives of meteorological and soil droughts in southwestern China.

Under climate warming, extreme drought events (EDEs) in southwestern China have become more frequent and severe and have had significant impacts on vegetation growth. Clarifying the influence of soil and meteorological droughts on the vegetation photosynthetic rate (PHR) and respiration rate (RER) can help policymakers to anticipate the impacts of drought on vegetation and take measures to reduce losses. In this study, the frequency and features of EDEs from 1990 to 2021 were analyzed using the standardized precipitation evapotranspiration index, and the longest-lasting and most severe EDE was chosen to assess the effects of drought on vegetation activity. Then, a land surface model was used to simulate the vegetation PHR and RER. Finally, the effects of the EDE on the vegetation PHR and RER were analyzed from the perspectives of soil and meteorological droughts. The results revealed that from 1990 to 2021, a total of 11 EDEs were observed in southwestern China, and the longest-lasting and most severe EDE occurred in 2009-2010 (EDE2009/2010). EDE2009/2010 significantly reduced the monthly mean PHR and RER by 9.82 g C m-2 month-1 and 0.80 g C m-2 month-1, respectively, causing a cumulative reduction of approximately 5.61 × 1013 g C. Soil and meteorological droughts had a driving force of 39 % on the PHR changes and an explanatory force of 42 % on the RER reduction. In particular, the soil drought had an average explanatory force of 25 % on the PHR and made a contribution of 24 % to the RER. The drought affected different types of vegetation differently, and crops were more susceptible than grassland and forests on the monthly time scale. The vegetation exhibited resilience to drought, returning to normal PHR and RER levels 2 months after the end of EDE2009/2010. This research contributes to understanding and predicting the impact of EDEs on vegetation growth in southwestern China.

Magnetic Resonance Elastography-Based Technique to Assess the Biomechanics of the Skull-Brain Interface: Repeatability and Age-Sex Characteristics.

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 (Rtr) 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 Rtr 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 Rtr 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 Rtr, 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.

The Safety and Efficacy of Low-Dose Naltrexone in Patients with Fibromyalgia: A Systematic Review.

Fibromyalgia (FM) is a chronic pain sensitivity syndrome characterized by diffuse musculoskeletal pain and many other systemic manifestations. Low-dose naltrexone (LDN) has been increasingly used as an off-label treatment option in FM. However, current evidence on the safety and efficacy of LDN in patients with FM is not well known. To systematically assess the current evidence on the safety and efficacy of LDN use in the treatment of FM. A comprehensive bibliographic search was conducted on EBM Reviews - Cochrane Central Register of Controlled Trials, EBM Reviews - Cochrane Database of Systematic, Embase, Ovid MEDLINE(R) and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations, Daily and Versions and Scopus databases in September 2022. Inclusion criteria were articles that were published in English, focusing on clinical trials involving LDN for the treatment of FM. Two reviewers independently screened and extracted the data. A qualitative analysis was used due to the high methodological heterogeneity between studies. The electronic search produced 805 articles. After applying the inclusion criteria, 9 articles (one RCT, two case reports, two case series, and four pilot trials) were selected for evaluation. LDN intervention protocols, study designs, and follow-up periods were different among the included studies. Overall, LDN was found to be effective in the symptomatic management of FM, and of the 78% of included studies that evaluated for safety, no severe adverse events were reported. Proving the efficacy and safety of low-dose naltrexone is a future possibility based on current study data, but the level of scientific evidence is limited. Future well-designed trials with large sample sizes are required.

Probing the Mechanical Properties of Large Arteries by Measuring Their Deformation In Vivo with Ultrasound.

Aging and cardiovascular diseases (CVDs) may alter the microstructures of arteries and hence their mechanical properties. Therefore, the measurement of intrinsic artery mechanical properties in vivo can provide valuable information in understanding aging and CVDs and is of clinical significance. The accuracy of advanced ultrasound imaging techniques in measuring the deformation of large arteries under blood pressure is good. However, the assessment of arterial stiffness in vivo remains a challenge. An inverse method to infer the constitutive parameters of arteries in vivo from the blood pressure-arterial radius relationship (P-r curve) is proposed here. The stability analysis reveals that a key constitutive parameter, bθ, which measures the circumferential hardening of an artery, can be reliably identified. An in vivo experiment was performed on the common carotid arteries of 41 healthy volunteers (age: 37 ± 17 y). The value of bθ varies significantly (from 0.55 ± 0.15 for the young group to 0.93 ± 0.29 for the older group, p < 0.01) and is positively correlated with age (r = 0.673, p < 0.01). Furthermore, our theoretical analysis and experimental study have revealed a strong correlation between the clinic-used stiffness index ß and bθ. This study shows that the arterial material parameter bθ can be measured in vivo, which makes it promising as a new biomarker in the diagnosis of CVDs.