Yin, Ziying

Brain MR elastography (MRE) is becoming a powerful tool in the investigation of neurophysiological and neuropathological states. In brain MRE, quantitative measures of brain mechanical properties can be assessed noninvasively by analyzing the induced brain motion in response to extrinsic or intrinsic excitation, providing unique clues to the mechanical rigidity, viscosity, friction, and connectivity of brain tissues. Changes in brain elasticity and viscosity are associated with inflammation, demyelination, and neurodegeneration during the onset and progression of many brain diseases. Beyond shear stiffness and modulus, MRE contains rich information that can be derived to enhance the characterization of disease-related structural changes, especially in intracranial tumors and traumatic brain injury, which will be the focus here. MRE-based slip interface imaging (SII) utilizes shear strain mapping to qualitatively assess the degree of adhesiveness of intracranial tumors. Together with tumor consistency, MRE offers a unique opportunity for improving preoperative planning before tumor resection as well as predicting patient outcomes. Analysis of head dynamics induced by non-impact dynamic loading from MRE measures the mechanical dampening and isolation capability of the skull-brain interface and changes in those features in sub-concussive repetitive head impacts, which could provide imaging biomarkers to facilitate risk management for future brain injury.

OBJECTIVE Pituitary adenoma is one of the most common primary intracranial neoplasms. Most of these tumors are soft, but up to 17% may have a firmer consistency. Therefore, knowing the tumor consistency in the preoperative setting could be helpful. Multiple imaging methods have been proposed to predict tumor consistency, but the results are controversial. This study aimed to evaluate the efficacy of MR elastography (MRE) in predicting tumor consistency and its potential use in a series of patients with pituitary adenomas. METHODS Thirty-eight patients with pituitary adenomas (≥ 2.5 cm) were prospectively evaluated with MRI and MRE before surgery. Absolute MRE stiffness values and relative MRE stiffness ratios, as well as the relative ratio of T1 signal, T2 signal, and diffusion-weighted imaging apparent diffusion coefficient (ADC) values were determined prospectively by calculating the ratio of those values in the tumor to adjacent left temporal white matter. Tumors were classified into three groups according to surgical consistency (soft, intermediate, and firm). Statistical analysis was used to identify the predictive value of the different radiological parameters in determining pituitary adenoma consistency. RESULTS The authors included 32 (84.21%) nonfunctional and 6 (15.79%) functional adenomas. The mean maximum tumor diameter was 3.7 cm, and the mean preoperative tumor volume was 16.4 cm 3 . Cavernous sinus invasion was present in 20 patients (52.63%). A gross-total resection was possible in 9 (23.68%) patients. The entire cohort’s mean absolute tumor stiffness value was 1.8 kPa (range 1.1–3.7 kPa), whereas the mean tumor stiffness ratio was 0.66 (range 0.37–1.6). Intraoperative tumor consistency was significantly correlated with absolute and relative tumor stiffness (p = 0.0087 and 0.007, respectively). Tumor consistency alone was not a significant factor for predicting gross-total resection. Patients with intermediate and firm tumors had more complications compared to patients with soft tumors (50.00% vs 12.50%, p = 0.02) and also had longer operative times (p = 0.0002). CONCLUSIONS Whereas other MRI sequences have proven to be unreliable in determining tumor consistency, MRE has been shown to be a reliable tool for predicting adenoma consistency. Preoperative knowledge of tumor consistency could be potentially useful for surgical planning, counseling about potential surgical risks, and estimating the length of operative time.

Abstract 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 CCl 4 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 CCl 4 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.

Circulating extracellular vesicles (EVs) are a novel and emerging biomarker for nonalcoholic steatohepatitis (NASH). It has been demonstrated that total circulating EVs and hepatocyte‐derived EVs are elevated in male mice with diet‐induced NASH. How hepatocyte‐derived EVs change over time and other cellular sources of EVs in NASH have not been determined. Our objective was to define the quantitative evolution of hepatocyte‐derived, macrophage‐derived, neutrophil‐derived, and platelet‐derived EVs in male and female mice with dietary NASH. Fluorescently labeled antibodies and a nanoscale flow cytometer were used to detect plasma levels of EVs. Asialoglycoprotein receptor 1 (ASGR1) and cytochrome P450 family 2 subfamily E member 1 (CYP2E1) are markers of hepatocyte‐derived EVs; galectin 3 is a marker of macrophage‐derived EVs; common epitope on lymphocyte antigen 6 complex, locus G/C1 (Ly‐6G and Ly‐6C) is a marker of neutrophil‐derived EVs; and clusters of differentiation 61 (CD61) is a marker of platelet‐derived EVs. Nonalcoholic fatty liver disease activity score (NAS) was calculated using hematoxylin and eosin‐stained liver sections, and magnetic resonance imaging (MRI) was used for measurement of the fat fraction and elastography. Hepatocyte‐derived EVs increased in both male and female mice at 12 and 10 weeks of feeding, respectively, and remained elevated at 24 weeks in both male and female mice and at 48 weeks in male mice and 36 weeks in female mice. Macrophage‐ and neutrophil‐derived EVs were significantly elevated at 24 weeks of dietary feeding concomitant with the histologic presence of inflammatory foci in the liver. In fat‐, fructose‐, and cholesterol‐ (FFC) fed male mice, platelet‐derived EVs were elevated at 12, 24, and 48 weeks, whereas in female mice, platelet derived EVs were significantly elevated at 24 weeks. Hepatocyte‐, macrophage‐ and neutrophil‐derived EVs correlated well with the histologic NAS. Conclusion: Circulating cell‐type‐specific EVs may be a novel biomarker for NASH diagnosis and longitudinal follow up.

PurposeTo 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.MethodsSix 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).ResultsBoth 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.ConclusionThis 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.

PurposeTo 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 MethodsWith 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.ResultsNeurosurgeons 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).ConclusionSII preoperatively evaluates the degree of meningioma–brain adhesion noninvasively, allowing for improved prediction of surgical risk and tumor resectability.Level of Evidence: 1Technical Efficacy: Stage 1J. Magn. Reson. Imaging 2017;46:1007–1016.