Sex Differences in Aging-related Myocardial Stiffening Quantitatively Measured with MR Elastography

Purpose To investigate the feasibility of using quantitative MR elastography (MRE) to characterize the influence of aging and sex on left ventricular (LV) shear stiffness. Materials and Methods In this prospective study, LV myocardial shear stiffness was measured in 109 healthy volunteers (age range: 18-84 years; mean age, 40 years ± 18 [SD]; 57 women, 52 men) enrolled between November 2018 and September 2019, using a 5-minute MRE acquisition added to a clinical MRI protocol. Linear regression models were used to estimate the association of cardiac MRI and MRE characteristics with age and sex; models were also fit to assess potential age-sex interaction. Results Myocardial shear stiffness significantly increased with age in female (age slope = 0.03 kPa/year ± 0.01, P = .009) but not male (age slope = 0.008 kPa/year ± 0.009, P = .38) volunteers. LV ejection fraction (LVEF) increased significantly with age in female volunteers (0.23% ± 0.08 per year, P = .005). LV end-systolic volume (LVESV) decreased with age in female volunteers (-0.20 mL/m2 ± 0.07, P = .003). MRI parameters, including T1, strain, and LV mass, did not demonstrate this interaction (P > .05). Myocardial shear stiffness was not significantly correlated with LVEF, LV stroke volume, body mass index, or any MRI strain metrics (P > .05) but showed significant correlations with LV end-diastolic volume/body surface area (BSA) (slope = -3 kPa/mL/m2 ± 1, P = .004, r2 = 0.08) and LVESV/BSA (-1.6 kPa/mL/m2 ± 0.5, P = .003, r2 = 0.08). Conclusion This study demonstrates that female, but not male, individuals experience disproportionate LV stiffening with natural aging, and these changes can be noninvasively measured with MRE. Keywords: Cardiac, Elastography, Biological Effects, Experimental Investigations, Sexual Dimorphisms, MR Elastography, Myocardial Shear Stiffness, Quantitative Stiffness Imaging, Aging Heart, Myocardial Biomechanics, Cardiac MRE Supplemental material is available for this article. Published under a CC BY 4.0 license.

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.

Associations between vascular health, brain stiffness and global cognitive function

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 < 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.

Head-to-head comparison of magnetic resonance elastography-based liver stiffness, fat fraction, and T1 relaxation time in identifying at-risk NASH

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 [AUC LS : 0.89 (0.82, 0.95), AUC PDFF : 0.70 (0.58, 0.81), AUC T1 : 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 [AUC PDFF : 0.82 (0.72, 0.91), AUC LS : 0.73 (0.63, 0.84), AUC T1 : 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.

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.

Differential effect of dementia etiology on cortical stiffness as assessed by MR elastography

BACKGROUND

Aging and dementia involve the disruption of brain molecular pathways leading to the alterations in tissue composition and gross morphology of the brain. Phenotypic and biomarker overlap between various etiologies of dementia supports a need for new modes of information to more accurately distinguish these disorders. Brain mechanical properties, which can be measured noninvasively by MR elastography, represent one understudied feature that are sensitive to neurodegenerative processes. In this study, we used two stiffness estimation schemes to test the hypothesis that different etiologies of dementia are associated with unique patterns of mechanical alterations across the cerebral cortex.

METHODS

MR elastography data were acquired for six clinical groups including amyloid-negative cognitively unimpaired (CU), amyloid-positive cognitively unimpaired (A + CU), amyloid-positive participants with mild cognitive impairment (A + MCI), amyloid-positive participants with Alzheimer's clinical syndrome (A + ACS), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). Stiffness maps were computed using two neural network inversions with the objective to at least partially separate the parenchyma-specific and morphological effects of neurodegeneration on mechanical property estimates. A tissue-confined inversion algorithm was designed to obtain the best estimate of stiffness in the brain parenchyma itself, while a regionally-aware inversion algorithm was used to measure the tissue stiffness along with the surroundings. Mean stiffness of 15 bilateral gray matter cortical regions were considered for statistical analysis. First, we tested the hypothesis that cortical stiffness changes in the aging brain. Next, we tested the overall study hypothesis by first comparing stiffness in each clinical group to the CU group, and then comparing the clinical groups against one another. Finally, we assessed the spatial and statistical overlap between atrophy and stiffness changes for both inversions.

RESULTS

Cortical brain regions become softer with age for both inversions with larger effects observed using regionally-aware stiffness. Stiffness decreases in the range 0.010-0.027 kPa per year were observed. Pairwise comparisons of each clinical group with cognitively unimpaired participants demonstrated 5 statistically significant differences in stiffness for tissue-confined measurements and 19 statistically different stiffness changes for the regionally-aware stiffness measurements. Pairwise comparisons between clinical groups further demonstrated unique patterns of stiffness differences. Analysis of the atrophy-versus-stiffness relationship showed that regionally-aware stiffness measurements exhibit higher sensitivity to neurodegeneration with findings that are not fully explained by partial volume effects or atrophy.

CONCLUSIONS

Both tissue-confined and regionally-aware stiffness estimates exhibited unique and complementary stiffness differences in various etiologies of dementia. Our results suggest that mechanical alterations measured by MRE reflect both tissue-specific differences as well as environmental effects. Multi-inversion schemes in MRE may provide new insights into the relationships between neuropathology and brain biomechanics.

Longitudinal Changes in MR Elastography-based Biomarkers in Obese Patients Treated with Bariatric Surgery

Obesity-related chronic inflammation contributes to nonalcoholic fatty liver disease (NAFLD) progression in obese patients (body mass index [BMI] >30 kg/m2).1 The early detection of inflammation with noninvasive imaging technology may help identify individuals with a high risk of developing NAFLD.

Impact of material homogeneity assumption on cortical stiffness estimates by MR elastography

PURPOSE

Inversion 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.

METHODS

We 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.

RESULTS

In 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.

CONCLUSIONS

This study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.

An under-recognized phenomenon: Myocardial volume change during the cardiac cycle

BACKGROUND

Myocardial volume is assumed to be constant over the cardiac cycle in the echocardiographic models used by professional guidelines, despite evidence that suggests otherwise. The aim of this paper is to use literature-derived myocardial strain values from healthy patients to determine if myocardial volume changes during the cardiac cycle.

METHODS

A systematic review for studies with longitudinal, radial, and circumferential strain from echocardiography in healthy volunteers ultimately yielded 16 studies, corresponding to 2917 patients. Myocardial volume in systole (MVs) and diastole (MVd) was used to calculate MVs/MVd for each study by applying this published strain data to three models: the standard ellipsoid geometric model, a thin-apex geometric model, and a strain-volume ratio.

RESULTS

MVs/MVd<1 in 14 of the 16 studies, when computed using these three models. A sensitivity analysis of the two geometric models was performed by varying the dimensions of the ellipsoid and calculating MVs/MVd. This demonstrated little variability in MVs/MVd, suggesting that strain values were the primary determinant of MVs/MVd rather than the geometric model used. Another sensitivity analysis using the 97.5th percentile of each orthogonal strain demonstrated that even with extreme values, in the largest two studies of healthy populations, the calculated MVs/MVd was <1.

CONCLUSIONS

Healthy human myocardium appears to decrease in volume during systole. This is seen in MRI studies and is clinically relevant, but this study demonstrates that this characteristic was also present but unrecognized in the existing echocardiography literature.

Simultaneous Noise Suppression and Incoherent Artifact Reduction in Ultrafast Ultrasound Vascular Imaging

Ultrasound vascular imaging based on ultrafast plane wave imaging and singular value decomposition (SVD) clutter filtering has demonstrated superior sensitivity in blood flow detection. However, ultrafast ultrasound vascular imaging is susceptible to electronic noise due to the weak penetration of unfocused waves, leading to a lower signal-to-noise ratio (SNR) at larger depths. In addition, incoherent clutter artifacts originating from strong and moving tissue scatterers that cannot be completely removed create a strong mask on top of the blood signal that obscures the vessels. Herein, a method that can simultaneously suppress the background noise and incoherent artifacts is proposed. The method divides the tilted plane or diverging waves into two subgroups. Coherent spatial compounding is performed within each subgroup, resulting in two compounded data sets. An SVD-based clutter filter is applied to each data set, followed by a correlation between the two data sets to produce a vascular image. Uncorrelated noise and incoherent artifacts can be effectively suppressed with the correlation process, while the coherent blood signal can be preserved. The method was evaluated in wire-target simulations and phantom, in which around 7-10-dB SNR improvement was shown. Consistent results were found in a flow channel phantom with improved SNR by the proposed method (39.9 ± 0.2 dB) against conventional power Doppler (29.1 ± 0.6 dB). Last, we demonstrated the effectiveness of the method combined with block-wise SVD clutter filtering in a human liver, breast tumor, and inflammatory bowel disease data sets. The improved blood flow visualization may facilitate more reliable small vessel imaging for a wide range of clinical applications, such as cancer and inflammatory diseases.

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 (ΔNOSS_bdy) was computed, from which a 3D ΔNOSS_bdy map of the tumor surface was created and the probability distribution of ΔNOSS_bdy 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 ΔNOSS_bdy surface map. The entropy of the ΔNOSS_bdy 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 ΔNOSS_bdy 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 ΔNOSS_bdy values are useful for quantification and classification of meningioma-brain adhesion. The reconstructed 3D ΔNOSS_bdy 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.

Harnessing brain waves: a review of brain magnetic resonance elastography for clinicians and scientists entering the field

Brain magnetic resonance elastography (MRE) is an imaging technique capable of accurately and non-invasively measuring the mechanical properties of the living human brain. Recent studies have shown that MRE has potential to provide clinically useful information in patients with intracranial tumors, demyelinating disease, neurodegenerative disease, elevated intracranial pressure, and altered functional states. The objectives of this review are: (1) to give a general overview of the types of measurements that have been obtained with brain MRE in patient populations, (2) to survey the tools currently being used to make these measurements possible, and (3) to highlight brain MRE-based quantitative biomarkers that have the highest potential of being adopted into clinical use within the next 5 to 10 years. The specifics of MRE methodology strategies are described, from wave generation to material parameter estimations. The potential clinical role of MRE for characterizing and planning surgical resection of intracranial tumors and assessing diffuse changes in brain stiffness resulting from diffuse neurological diseases and altered intracranial pressure are described. In addition, the emerging technique of functional MRE, the role of artificial intelligence in MRE, and promising applications of MRE in general neuroscience research are presented.

A new method for assessing anal distensibility with a barostat and magnetic resonance imaging in healthy and constipated women

OBJECTIVES

Defecation requires relaxation of the internal and external anal sphincters. High anal resting pressure is associated with painful constipation, defecatory disorders, and increased healthcare utilization in constipated patients; the mechanisms are unclear. Perhaps patients with a high anal resting pressure have a less distensible canal, which impedes defecation.

METHODS

In 50 of 64 participants (33 healthy and 17 constipated women), anal pressures and distensibility were measured, respectively, with manometry and balloon distention combined with magnetic resonance imaging; rectal balloon expulsion time (BET) was also studied.

RESULTS

The BET (P = .006) was longer, and the mean (SD) rectoanal pressure gradient (-58[40] vs -34[26] mm Hg, P = .03) was more negative in constipated than healthy women; anal resting pressure was not different. During anal distention, the balloon expanded rapidly at an opening pressure of 49 (18) mm Hg, which was lower (P < .0001) than resting pressure (90 [25] mm Hg). The resting pressure was correlated with the opening pressure (r = 0.57, P < .0001) and inversely (r = -0.38, P = .007) with maximum volume but not with anal distensibility (volume-pressure slope). In healthy women, the difference (opening-resting pressure) was correlated with anal relaxation during evacuation (r = 0.35, P = .04). Anal distensibility and sensory thresholds were not different between constipated and healthy women.

CONCLUSIONS

Among healthy and constipated women, a greater anal resting pressure is correlated with greater opening pressure and lower maximum volume during distention, and, hence, provides a surrogate marker of anal distensibility. The difference (opening-resting pressure), which reflects anal relaxation during distention, is correlated with anal relaxation during evacuation. Anal resting pressure and distensibility were comparable in healthy and constipated women.

Deploying MMEJ using MENdel in precision gene editing applications for gene therapy and functional genomics

Gene-editing experiments commonly elicit the error-prone non-homologous end joining for DNA double-strand break (DSB) repair. Microhomology-mediated end joining (MMEJ) can generate more predictable outcomes for functional genomic and somatic therapeutic applications. We compared three DSB repair prediction algorithms – MENTHU, inDelphi, and Lindel – in identifying MMEJ-repaired, homogeneous genotypes (PreMAs) in an independent dataset of 5,885 distinct Cas9-mediated mouse embryonic stem cell DSB repair events. MENTHU correctly identified 46% of all PreMAs available, a ∼2- and ∼60-fold sensitivity increase compared to inDelphi and Lindel, respectively. In contrast, only Lindel correctly predicted predominant single-base insertions. We report the new algorithm MENdel, a combination of MENTHU and Lindel, that achieves the most predictive coverage of homogeneous out-of-frame mutations in this large dataset. We then estimated the frequency of Cas9-targetable homogeneous frameshift-inducing DSBs in vertebrate coding regions for gene discovery using MENdel. 47 out of 54 genes (87%) contained at least one early frameshift-inducing DSB and 49 out of 54 (91%) did so when also considering Cas12a-mediated deletions. We suggest that the use of MENdel helps researchers use MMEJ at scale for reverse genetics screenings and with sufficient intra-gene density rates to be viable for nearly all loss-of-function based gene editing therapeutic applications.

MR elastography: Principles, guidelines, and terminology

Magnetic resonance elastography (MRE) is a phase contrast-based MRI technique that can measure displacement due to propagating mechanical waves, from which material properties such as shear modulus can be calculated. Magnetic resonance elastography can be thought of as quantitative, noninvasive palpation. It is increasing in clinical importance, has become widespread in the diagnosis and staging of liver fibrosis, and additional clinical applications are being explored. However, publications have reported MRE results using many different parameters, acquisition techniques, processing methods, and varied nomenclature. The diversity of terminology can lead to confusion (particularly among clinicians) about the meaning of and interpretation of MRE results. This paper was written by the MRE Guidelines Committee, a group formalized at the first meeting of the ISMRM MRE Study Group, to clarify and move toward standardization of MRE nomenclature. The purpose of this paper is to (1) explain MRE terminology and concepts to those not familiar with them, (2) define "good practices" for practitioners of MRE, and (3) identify opportunities to standardize terminology, to avoid confusion.

Three-dimensional shear wave elastography on conventional ultrasound scanners with external vibration

Two-dimensional (2D) ultrasound shear wave elastography (SWE) has been widely used for soft tissue properties assessment. Given that shear waves propagate in three dimensions (3D), extending SWE from 2D to 3D is important for comprehensive and accurate stiffness measurement. However, implementation of 3D SWE on a conventional ultrasound scanner is challenging due to the low volume rate (tens of Hertz) associated with limited parallel receive capability of the scanner's hardware beamformer. Therefore, we developed an external mechanical vibration-based 3D SWE technique allowing robust 3D shear wave tracking and speed reconstruction for conventional scanners. The aliased shear wave signal detected with a sub-Nyquist sampling frequency was corrected by leveraging the cyclic nature of the sinusoidal shear wave generated by the external vibrator. Shear wave signals from different sub-volumes were aligned in temporal direction to correct time delays from sequential pulse-echo events, followed by 3D speed reconstruction using a 3D local frequency estimation algorithm. The technique was validated on liver fibrosis phantoms with different stiffness, showing good correlation (r = 0.99, p < 0.001) with values measured from a state-of-the-art SWE system (GE LOGIQ E9). The phantoms with different stiffnesses can be well-differentiated regardless of the external vibrator position, indicating the feasibility of the 3D SWE with regard to different shear wave propagation scenarios. Finally, shear wave speed calculated by the 3D method correlated well with magnetic resonance elastography performed on human liver (r = 0.93, p = 0.02), demonstrating the in vivo feasibility. The proposed technique relies on low volume rate imaging and can be implemented on the widely available clinical ultrasound scanners, facilitating its clinical translation to improve liver fibrosis evaluation.

Quantitative assessment of portal hypertension with bi-parametric dual-frequency hepatic MR elastography in mouse models

OBJECTIVES

To determine the potential of bi-parametric dual-frequency hepatic MR elastography (MRE) for predicting portal pressure (PP) in mouse models of portal hypertension (PHTN) with the presence of varying hepatic fibrosis.

METHODS

We studied 73 wild-type male mice, including 22 mice with hepatic congestion, 20 mice with cholestatic liver injury, and 31 age-matched sham mice. Hepatic shear stiffness (SS) and volumetric strain (VS) were calculated by 3D MRE acquired at 80 and 200 Hz. We measured PP immediately after MRE. Liver fibrosis was verified by hydroxyproline assay. We predicted PP by fitting generalized linear models with single- and dual-frequency SS and VS, respectively. The relationship between predicted and actual PP was evaluated by Spearman's correlation. We compared the prediction accuracy of portal hypertension for all models with DeLong tests at a significance level of 0.05.

RESULTS

Animals with congestive or cholestatic liver disease developed significant PHTN and hepatic fibrosis to varying degrees. In both models, SS increased, while VS decreased significantly compared with shams. All bi-parametric models had high diagnostic accuracy for PHTN. The dual-frequency models (AUCs: 0.90 [81-95%], 0.91 [81-95%]) had substantially or significantly higher accuracy than single-frequency ones (AUCs: 0.83 [71-91%], and 0.78 [66-87%]). The predicted PP of dual-frequency models also showed stronger correlations with actual PP than single-frequency predictions.

CONCLUSIONS

The bi-parametric dual-frequency model improved the diagnostic accuracy of liver MRE in diagnosing PHTN in preclinical models. This technical advance has the potential to monitor PHTN progression and treatment efficacy in the presence of varying fibrosis.

KEY POINTS

• Bi-parametric hepatic MR elastography can predict portal pressure. • The prediction models of shear stiffness and volumetric strain with dual-frequency measurements demonstrate high diagnostic accuracy (AUCs > 0.9) in two different portal hypertension mouse models with varying fibrosis.

Kalman Filter-Based Microbubble Tracking for Robust Super-Resolution Ultrasound Microvessel Imaging

Contrast microbubble (MB)-based super-resolution ultrasound microvessel imaging (SR-UMI) overcomes the compromise in conventional ultrasound imaging between spatial resolution and penetration depth and has been successfully applied to a wide range of clinical applications. However, clinical translation of SR-UMI remains challenging due to the limited number of MBs detected within a given accumulation time. Here, we propose a Kalman filter-based method for robust MB tracking and improved blood flow speed measurement with reduced numbers of MBs. An acceleration constraint and a direction constraint for MB movement were developed to control the quality of the estimated MB trajectory. An adaptive interpolation approach was developed to inpaint the missing microvessel signal based on the estimated local blood flow speed, facilitating more robust depiction of microvasculature with a limited amount of MBs. The proposed method was validated on an ex ovo chorioallantoic membrane and an in vivo rabbit kidney. Results demonstrated improved imaging performance on both microvessel density maps and blood flow speed maps. With the proposed method, the percentage of microvessel filling in a selected blood vessel at a given accumulation period was increased from 28.17% to 74.45%. A similar SR-UMI performance was achieved with MB numbers reduced by 85.96%, compared to that with the original MB number. The results indicate that the proposed method substantially improves the robustness of SR-UMI under a clinically relevant imaging scenario where SR-UMI is challenged by a limited MB accumulation time, reduced number of MBs, lowered imaging frame rate, and degraded signal-to-noise ratio.

Cardiac MRI demonstrates compressibility in healthy myocardium but not in myocardium with reduced ejection fraction

BACKGROUND

The professional guidelines assume that the myocardial volume in systole (MVs) is equal to that in diastole (MVd), despite some limited evidence that points to the contrary. The aim of this manuscript is to determine whether this is true in healthy myocardium using gold standard cardiac MRI, as well as transthoracic echocardiography (TTE). The secondary aim is to determine whether there are similar MV changes in patients with heart failure with reduced ejection fraction (HFrEF).

METHOD

A prospectively derived cohort at Mayo Clinic of 115 adult subjects (mean age 42.8 years, 58% female) with no cardiac risk factors was identified. Cardiac MRI was obtained on all 115 patients, 51 of whom also consented to a TTE. MRI from a retrospectively derived cohort of 50 HFrEF patients was also collected. MVs and MVd was calculated using standard approaches with inclusion of the papillary muscles.

RESULTS

In the healthy population, MRI demonstrated MVs/MVd = 0.87 (SD 0.04) and TTE demonstrated MVs/MVd = 0.79 (SD 0.07), suggesting compressibility (p < 0.0001). In the 51 healthy patients who received both imaging modalities, MVs/MVd was 8.0% higher in MRI than TTE (p < 0.0001), but both modalities had MVs/MVd < 1 (p < 0.0001). A Bland-Altman plot demonstrated that as the mean MVs/MVd increases, the difference in MVs/MVd MRI-TTE declines (r = -0.53, p < 0.0001). However, in HFrEF populations, MVs/MVd = 1.01 (0.03), suggesting myocardial incompressibility.

CONCLUSION

Contrary to currently accepted standards, healthy myocardium is compressible but HFrEF myocardium is incompressible. The ratio MVs/MVd merits further study in an expanded normal cohort and in disease states.

Systolic-to-diastolic myocardial volume ratio as a novel imaging marker of cardiomyopathy

BACKGROUND

In patients with normal left ventricular ejection fraction, it may be difficult to distinguish between the normal and diseased heart. Novel assessments of ventricular function, such as extracellular volume imaging, myocardial perfusion imaging and myocardial contraction fraction are emerging to better assess disease burden in these cases. This study endeavored to determine whether the ratio of myocardial volume in systole to myocardial volume in diastole (MVs/MVd), differs between normal hearts and those with disease states characterized by normal ejection fraction.

METHOD

Consecutive patients from 2008 to 2018 with hypertrophic cardiomyopathy (HCM), cardiac amyloidosis, and heart failure with preserved ejection fraction (HFpEF) who underwent cardiac magnetic resonance imaging (MRI) were selected for inclusion, along with a sex- and age-matched cohort of normal volunteers who also underwent cardiac MRI. Manual tracings were performed on each MRI to calculate MVs/MVd, which was then compared across subgroups.

RESULTS

Included were 50 patients with HCM, 50 patients with cardiac amyloidosis, 26 patients with HFpEF, and 30 normal subjects. Age was 54.1 years (SD 16.7); mean MVs/MVd was 0.88 (SD 0.04) in the normal subgroup, 1.03 (SD 0.06) in HCM patients, 1.03 (SD 0.06) in cardiac amyloidosis patients, and 0.97 (SD 0.02) in HFpEF patients, with all pathology subgroups different from the normal subgroup (p < .0001 for each). The ratio of MVs/MVd discriminated diseased from normal with c statistic 0.989 (p < .001).

CONCLUSIONS

This study suggests that a novel and easily-captured metric of ventricular function, MVs/MVd, can differentiate normal ventricular function from multiple cardiomyopathies with normal ejection fractions.

TURBINE-MRE: A 3D hybrid radial-Cartesian EPI acquisition for MR elastography

PURPOSE

To develop a novel magnetic resonance elastography (MRE) acquisition using a hybrid radial EPI readout scheme (TURBINE), and to demonstrate its feasibility to obtain wave images and stiffness maps in a phantom and in vivo brain.

METHOD

The proposed 3D TURBINE-MRE is based on a spoiled gradient-echo MRE sequence with the EPI readout radially rotating about the phase-encoding axis to sample a full 3D k-space. A polyvinyl chloride phantom and 6 volunteers were scanned on a compact 3T GE scanner with a 32-channel head coil at 80 Hz and 60 Hz external vibration, respectively. For comparison, a standard 2D, multislice, spin-echo (SE) EPI-MRE acquisition was also performed with the same motion encoding and resolution. The TURBINE-MRE images were off-line reconstructed with iterative SENSE algorithm. The regional ROI analysis was performed on the 6 volunteers, and the median stiffness values were compared between SE-EPI-MRE and TURBINE-MRE.

RESULTS

The 3D wave-field images and the generated stiffness maps were comparable between TURBINE-MRE and standard SE-EPI-MRE for the phantom and the volunteers. The Bland-Altman plot showed no significant difference in the median regional stiffness values between the two methods. The stiffness measured with the 2 methods had a strong linear relationship with a Pearson correlation coefficient of 0.943.

CONCLUSION

We demonstrated the feasibility of the new TURBINE-MRE sequence for acquiring the desired 3D wave-field data and stiffness maps in a phantom and in-vivo brains. This pilot study encourages further exploration of TURBINE-MRE for functional MRE, free-breathing abdominal MRE, and cardiac MRE applications.

Artificial neural networks for magnetic resonance elastography stiffness estimation in inhomogeneous materials

PURPOSE

To test the hypothesis that removing the assumption of material homogeneity will improve the spatial accuracy of stiffness estimates made by Magnetic Resonance Elastography (MRE).

METHODS

An artificial neural network was trained using synthetic wave data computed using a coupled harmonic oscillator model. Material properties were allowed to vary in a piecewise smooth pattern. This neural network inversion (Inhomogeneous Learned Inversion (ILI)) was compared against a previous homogeneous neural network inversion (Homogeneous Learned Inversion (HLI)) and conventional direct inversion (DI) in simulation, phantom, and in-vivo experiments.

RESULTS

In simulation experiments, ILI was more accurate than HLI and DI in predicting the stiffness of an inclusion in noise-free, low-noise, and high-noise data. In the phantom experiment, ILI delineated inclusions ≤ 2.25 cm in diameter more clearly than HLI and DI, and provided a higher contrast-to-noise ratio for all inclusions. In a series of stiff brain tumors, ILI shows sharper stiffness transitions at the edges of tumors than the other inversions evaluated.

CONCLUSION

ILI is an artificial neural network based framework for MRE inversion that does not assume homogeneity in material stiffness. Preliminary results suggest that it provides more accurate stiffness estimates and better contrast in small inclusions and at large stiffness gradients than existing algorithms that assume local homogeneity. These results support the need for continued exploration of learning-based approaches to MRE inversion, particularly for applications where high resolution is required.

Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation

Super-resolution ultrasound localization microscopy (ULM), based on localization and tracking of individual microbubbles (MBs), offers unprecedented microvascular imaging resolution at clinically relevant penetration depths. However, ULM is currently limited by the requirement of dilute MB concentrations to ensure spatially sparse MB events for accurate localization and tracking. The corresponding long imaging acquisition times (tens of seconds or several minutes) to accumulate sufficient isolated MB events for full reconstruction of microvasculature preclude the clinical translation of the technique. To break this fundamental tradeoff between acquisition time and MB concentration, in this paper we propose to separate spatially overlapping MB events into sub-populations, each with sparser MB concentration, based on spatiotemporal differences in the flow dynamics (flow speeds and directions). MB localization and tracking are performed for each sub-population separately, permitting more robust ULM imaging of high-concentration MB injections. The superiority of the proposed MB separation technique over conventional ULM processing is demonstrated in flow channel phantom data, and in the chorioallantoic membrane of chicken embryos with optical imaging as an in vivo reference standard. Substantial improvement of ULM is further demonstrated on a chicken embryo tumor xenograft model and a chicken brain, showing both morphological and functional microvasculature details at super-resolution within a short acquisition time (several seconds). The proposed technique allows more robust MB localization and tracking at relatively high MB concentrations, alleviating the need for dilute MB injections, and thereby shortening the acquisition time of ULM imaging and showing great potential for clinical translation.

Debiasing-Based Noise Suppression for Ultrafast Ultrasound Microvessel Imaging

Ultrasound microvessel imaging (UMI) based on the combination of singular value decomposition (SVD) clutter filtering and ultrafast plane wave imaging has recently demonstrated significantly improved Doppler sensitivity, especially to small vessels that are invisible to conventional Doppler imaging. Practical implementation of UMI is hindered by the high computational cost associated with SVD and low blood signal-to-noise ratio (SNR) in deep regions of the tissue due to the lack of transmit focusing of plane waves. Concerning the high computational cost, an accelerated SVD clutter filtering method based on randomized SVD (rSVD) and randomized spatial downsampling (rSD) was recently proposed by our group, which showed the feasibility of real-time implementation of UMI. Concerning the low blood flow SNR in deep imaging regions, here we propose a noise suppression method based on noise debiasing that can be easily applied to the accelerated SVD method to bridge the gap between real-time implementation and high imaging quality. The proposed method experimentally measures the noise-induced bias by collecting the noise signal using the identical imaging sequence as regular UMI, but with the ultrasound transmission turned off. The estimated bias can then be subtracted from the original power Doppler (PD) image to obtain effective noise suppression. The feasibility of the proposed method was validated under different ultrasound imaging parameters [including transmitting voltages and time-gain compensation (TGC) settings] with a phantom experiment. The noise-debiased images showed an increase of up to 15.3 and 13.4 dB in SNR as compared to original PD images on the blood flow phantom and an in vivo human kidney data set, respectively. The proposed noise suppression method has negligible computational cost and can be conveniently combined with the previously proposed accelerated SVD clutter filtering technique to achieve high quality, real-time UMI imaging.

Functional Ultrasound Imaging of Spinal Cord Hemodynamic Responses to Epidural Electrical Stimulation: A Feasibility Study

This study presents the first implementation of functional ultrasound (fUS) imaging of the spinal cord to monitor local hemodynamic response to epidural electrical spinal cord stimulation (SCS) on two small and large animal models. SCS has been successfully applied to control chronic refractory pain and recently was evolved to alleviate motor impairment in Parkinson's disease and after spinal cord injury. At present, however, the mechanisms underlying SCS remain unclear, and current methods for monitoring SCS are limited in their capacity to provide the required sensitivity and spatiotemporal resolutions to evaluate functional changes in response to SCS. fUS is an emerging technology that has recently shown promising results in monitoring a variety of neural activities associated with the brain. Here we demonstrated the feasibility of performing fUS on two animal models during SCS. We showed in vivo spinal cord hemodynamic responses measured by fUS evoked by different SCS parameters. We also demonstrated that fUS has a higher sensitivity in monitoring spinal cord response than electromyography. The high spatial and temporal resolutions of fUS were demonstrated by localized measurements of hemodynamic responses at different spinal cord segments, and by reliable tracking of spinal cord responses to patterned electrical stimulations, respectively. Finally, we proposed optimized fUS imaging and post-processing methods for spinal cord. These results support feasibility of fUS imaging of the spinal cord and could pave the way for future systematic studies to investigate spinal cord functional organization and the mechanisms of spinal cord neuromodulation in vivo.

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.

On the Effects of Spatial Sampling Quantization in Super-Resolution Ultrasound Microvessel Imaging

Ultrasound super-resolution (SR) microvessel imaging technologies are rapidly emerging and evolving. The unprecedented combination of imaging resolution and penetration promises a wide range of preclinical and clinical applications. This paper concerns spatial quantization error in SR imaging, a common issue that involves a majority of current SR imaging methods. While quantization error can be alleviated by the microbubble localization process (e.g., via upsampling or parametric fitting), it is unclear to what extent the localization process can suppress the spatial quantization error induced by discrete sampling. It is also unclear when low spatial sampling frequency will result in irreversible quantization errors that cannot be suppressed by the localization process. This paper had two goals: 1) to systematically investigate the effect of quantization in SR imaging and establish principles of adequate SR imaging spatial sampling that yield minimal quantization error with proper localization methods and 2) to compare the performance of various localization methods and study the level of tolerance of each method to quantization. We conducted experiments on a small wire target and on a microbubble flow phantom. We found that the Fourier analysis of an oversampled spatial profile of the microbubble signal could provide reliable guidance for selecting beamforming spatial sampling frequency. Among various localization methods, parametric Gaussian fitting and centroid-based localization on upsampled data had better microbubble localization performance and were less susceptible to quantization error than peak intensity-based localization methods. When spatial sampling resolution was low, parametric Gaussian fitting-based localization had the best performance in suppressing quantization error, and could produce acceptable SR microvessel imaging with no significant quantization artifacts. The findings from this paper can be used in practice to help intelligently determine the minimum requirement of spatial sampling for robust microbubble localization to avoid adding or even reduce the burden of computational cost and data storage that are commonly associated with SR imaging.

Stiffness and Beyond: What MR Elastography Can Tell Us About Brain Structure and Function Under Physiologic and Pathologic Conditions

Brain magnetic resonance elastography (MRE) was developed on the basis of a desire to "palpate by imaging" and is becoming a powerful tool in the investigation of neurophysiological and neuropathological states. Measurements are acquired with a specialized MR phase-contrast pulse sequence that can detect tissue motion in response to an applied external or internal excitation. The tissue viscoelasticity is then reconstructed from the measured displacement. Quantitative characterization of brain viscoelastic behaviors provides us an insight into the brain structure and function by assessing the mechanical rigidity, viscosity, friction, and connectivity of brain tissues. Changes in these features are associated with inflammation, demyelination, and neurodegeneration that contribute to brain disease onset and progression. Here, we review the basic principles and limitations of brain MRE and summarize its current neuroanatomical studies and clinical applications to the most common neurosurgical and neurodegenerative disorders, including intracranial tumors, dementia, multiple sclerosis, amyotrophic lateral sclerosis, and traumatic brain injury. Going forward, further improvement in acquisition techniques, stable inverse reconstruction algorithms, and advanced numerical, physical, and preclinical validation models is needed to increase the utility of brain MRE in both research and clinical applications.

Waveguide effects and implications for cardiac magnetic resonance elastography: A finite element study

Magnetic resonance elastography (MRE) is increasingly being applied to thin or small structures in which wave propagation is dominated by waveguide effects, which can substantially bias stiffness results with common processing approaches. The purpose of this work was to investigate the importance of such biases and artifacts on MRE inversion results in: (i) various idealized 2D and 3D geometries with one or more dimensions that are small relative to the shear wavelength; and (ii) a realistic cardiac geometry. Finite element models were created using simple 2D geometries as well as a simplified and a realistic 3D cardiac geometry, and simulated displacements acquired by MRE from harmonic excitations from 60 to 220 Hz across a range of frequencies. The displacement wave fields were inverted with direct inversion of the Helmholtz equation with and without the application of bandpass filtering and/or the curl operator to the displacement field. In all geometries considered, and at all frequencies considered, strong biases and artifacts were present in inversion results when the curl operator was not applied. Bandpass filtering without the curl was not sufficient to yield accurate recovery. In the 3D geometries, strong biases and artifacts were present in 2D inversions even when the curl was applied, while only 3D inversions with application of the curl yielded accurate recovery of the complex shear modulus. These results establish that taking the curl of the wave field and performing a full 3D inversion are both necessary steps for accurate estimation of the shear modulus both in simple thin-walled or small structures and in a realistic cardiac geometry when using simple inversions that neglect the hydrostatic pressure term. In practice, sufficient wave amplitude, signal-to-noise ratio, and resolution will be required to achieve accurate results.

Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study

BACKGROUND

Background parenchymal uptake (BPU), which refers to the level of Tc-99m sestamibi uptake within normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor, independent of mammographic density. Prior analyses have used subjective categories to describe BPU. We evaluate a new quantitative method for assessing BPU by testing its reproducibility, comparing quantitative results with previously established subjective BPU categories, and determining the association of quantitative BPU with breast cancer risk.

METHODS

Two nonradiologist operators independently performed region-of-interest analysis on MBI images viewed in conjunction with corresponding digital mammograms. Quantitative BPU was defined as a unitless ratio of the average pixel intensity (counts/pixel) within the fibroglandular tissue versus the average pixel intensity in fat. Operator agreement and the correlation of quantitative BPU measures with subjective BPU categories assessed by expert radiologists were determined. Percent density on mammograms was estimated using Cumulus. The association of quantitative BPU with breast cancer (per one unit BPU) was examined within an established case-control study of 62 incident breast cancer cases and 177 matched controls.

RESULTS

Quantitative BPU ranged from 0.4 to 3.2 across all subjects and was on average higher in cases compared to controls (1.4 versus 1.2, p < 0.007 for both operators). Quantitative BPU was strongly correlated with subjective BPU categories (Spearman's r = 0.59 to 0.69, p < 0.0001, for each paired combination of two operators and two radiologists). Interoperator and intraoperator agreement in the quantitative BPU measure, assessed by intraclass correlation, was 0.92 and 0.98, respectively. Quantitative BPU measures showed either no correlation or weak negative correlation with mammographic percent density. In a model adjusted for body mass index and percent density, higher quantitative BPU was associated with increased risk of breast cancer for both operators (OR = 4.0, 95% confidence interval (CI) 1.6-10.1, and 2.4, 95% CI 1.2-4.7).

CONCLUSION

Quantitative measurement of BPU, defined as the ratio of average counts in fibroglandular tissue relative to that in fat, can be reliably performed by nonradiologist operators with a simple region-of-interest analysis tool. Similar to results obtained with subjective BPU categories, quantitative BPU is a functional imaging biomarker of breast cancer risk, independent of mammographic density and hormonal factors.

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.

Probe Oscillation Shear Wave Elastography: Initial In Vivo Results in Liver

Shear wave elastography methods are able to accurately measure tissue stiffness, allowing these techniques to monitor the progression of hepatic fibrosis. While many methods rely on acoustic radiation force to generate shear waves for 2-D imaging, probe oscillation shear wave elastography (PROSE) provides an alternative approach by generating shear waves through continuous vibration of the ultrasound probe while simultaneously detecting the resulting motion. The generated shear wave field in in vivo liver is complicated, and the amplitude and quality of these shear waves can be influenced by the placement of the vibrating probe. To address these challenges, a real-time shear wave visualization tool was implemented to provide instantaneous visual feedback to optimize probe placement. Even with the real-time display, it was not possible to fully suppress residual motion with established filtering methods. To solve this problem, the shear wave signal in each frame was decoupled from motion and other sources through the use of a parameter-free empirical mode decomposition before calculating shear wave speeds. This method was evaluated in a phantom as well as in in vivo livers from five volunteers. PROSE results in the phantom as well as in vivo liver correlated well with independent measurements using the commercial General Electric Logiq E9 scanner.

Improved Super-Resolution Ultrasound Microvessel Imaging With Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking

Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This paper aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane-wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high-frame-rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this paper, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation, and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-sectional profile with full-width at half-maximum of could be imaged at approximately 2-cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ). Cortical microvessels that are apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

Cardiac MR elastography using reduced-FOV, single-shot, spin-echo EPI

Purpose

To implement a reduced field of view (rFOV) technique for cardiac MR elastography (MRE) and to demonstrate the improvement in image quality of both magnitude images and post‐processed MRE stiffness maps compared to the conventional full field of view (full‐FOV) acquisition.

Methods

With Institutional Review Board approval, 17 healthy volunteers underwent both full‐FOV and rFOV cardiac MRE scans using 140‐Hz vibrations. Two cardiac radiologists blindly compared the magnitude images and stiffness maps and graded the images based on several image quality attributes using a 5‐point ordinal scale. Fisher's combined probability test was performed to assess the overall evaluation. The octahedral shear strain‐based signal‐to‐noise ratio (OSS‐SNR) and median stiffness over the left ventricular myocardium were also compared.

Results

One volunteer was excluded because of an inconsistent imaging resolution during the exam. In the remaining 16 volunteers (9 males, 7 females), the rFOV scans outperformed the full‐FOV scans in terms of subjective image quality and ghosting artifacts in the magnitude images and stiffness maps, as well as the overall preference. The quantitative measurements showed that rFOV had significantly higher OSS‐SNR (median: 1.4 [95% confidence interval (CI): 1.2–1.5] vs. 2.1 [95% CI: 1.8–2.4]), P < 0.05) compared to full‐FOV. Although no significant change was found in the median myocardial stiffness between the 2 scans, we observed a decrease in the stiffness variation within the myocardium from 2.1 kPa (95% CI: [1.9, 2.3]) to 1.9 kPa (95% CI: [1.7, 2.0]) for full‐FOV and rFOV, respectively (P < 0.05) in a subgroup of 7 subjects with ghosting present in the myocardium.

Conclusion

This pilot volunteer study demonstrated that rFOV cardiac MRE has the capability to reduce ghosting and to improve image quality in both MRE magnitude images and stiffness maps. Magn Reson Med 80:231–238, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Artificial neural networks for stiffness estimation in magnetic resonance elastography

PURPOSE

To investigate the feasibility of using artificial neural networks to estimate stiffness from MR elastography (MRE) data.

METHODS

Artificial neural networks were fit using model-based training patterns to estimate stiffness from images of displacement using a patch size of ∼1 cm in each dimension. These neural network inversions (NNIs) were then evaluated in a set of simulation experiments designed to investigate the effects of wave interference and noise on NNI accuracy. NNI was also tested in vivo, comparing NNI results against currently used methods.

RESULTS

In 4 simulation experiments, NNI performed as well or better than direct inversion (DI) for predicting the known stiffness of the data. Summary NNI results were also shown to be significantly correlated with DI results in the liver (R²  = 0.974) and in the brain (R²  = 0.915), and also correlated with established biological effects including fibrosis stage in the liver and age in the brain. Finally, repeatability error was lower in the brain using NNI compared to DI, and voxel-wise modeling using NNI stiffness maps detected larger effects than using DI maps with similar levels of smoothing.

CONCLUSION

Artificial neural networks represent a new approach to inversion of MRE data. Summary results from NNI and DI are highly correlated and both are capable of detecting biologically relevant signals. Preliminary evidence suggests that NNI stiffness estimates may be more resistant to noise than an algebraic DI approach. Taken together, these results merit future investigation into NNIs to improve the estimation of stiffness in small regions. Magn Reson Med 80:351-360, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Noise Equalization for Ultrafast Plane Wave Microvessel Imaging

Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity by increasing the number of Doppler ensembles that can be collected within a short period of time. The rich spatiotemporal plane wave data also enable more robust clutter filtering based on singular value decomposition. However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. This paper was designed to: 1) study the relationship between ultrasound system noise (primarily time gain compensation induced) and microvessel blood flow signal and 2) propose an adaptive and computationally cost-effective noise equalization method that is independent of hardware or software imaging settings to improve microvessel image quality.

MR Elastography Analysis of Glioma Stiffness and IDH1-Mutation Status

BACKGROUND AND PURPOSE

Our aim was to noninvasively evaluate gliomas with MR elastography to characterize the relationship of tumor stiffness with tumor grade and mutations in the isocitrate dehydrogenase 1 (IDH1) gene.

MATERIALS AND METHODS

Tumor stiffness properties were prospectively quantified in 18 patients (mean age, 42 years; 6 women) with histologically proved gliomas using MR elastography from 2014 to 2016. Images were acquired on a 3T MR imaging unit with a vibration frequency of 60 Hz. Tumor stiffness was compared with unaffected contralateral white matter, across tumor grade, and by IDH1-mutation status. The performance of the use of tumor stiffness to predict tumor grade and IDH1 mutation was evaluated with the Wilcoxon rank sum, 1-way ANOVA, and Tukey-Kramer tests.

RESULTS

Gliomas were softer than healthy brain parenchyma, 2.2 kPa compared with 3.3 kPa (P < .001), with grade IV tumors softer than grade II. Tumors with an IDH1 mutation were significantly stiffer than those with wild type IDH1, 2.5 kPa versus 1.6 kPa, respectively (P = .007).

CONCLUSIONS

MR elastography demonstrated that not only were gliomas softer than normal brain but the degree of softening was directly correlated with tumor grade and IDH1-mutation status. Noninvasive determination of tumor grade and IDH1 mutation may result in improved stratification of patients for different treatment options and the evaluation of novel therapeutics. This work reports on the emerging field of "mechanogenomics": the identification of genetic features such as IDH1 mutation using intrinsic biomechanical information.

Acute pressure changes in the brain are correlated with MR elastography stiffness measurements: initial feasibility in an in vivo large animal model

PURPOSE

The homeostasis of intracranial pressure (ICP) is of paramount importance for maintaining normal brain function. A noninvasive technique capable of making direct measurements of ICP currently does not exist. MR elastography (MRE) is capable of noninvasively measuring brain tissue stiffness in vivo, and may act as a surrogate to measure ICP. The objective of this study was to investigate the impact of changing ICP on brain stiffness using MRE in a swine model.

METHODS

Baseline MRE measurements were obtained, and then catheters were surgically placed into the left and right lateral ventricles of three animals. ICP was systematically increased over the range of 0 to 55 millimeters mercury (mmHg), and stiffness measurements were made using brain MRE at vibration frequencies of 60 hertz (Hz), 90 Hz, 120 Hz, and 150 Hz.

RESULTS

A significant linear correlation between stiffness and ICP in the cross-subject comparison was observed for all tested vibrational frequencies (P ≤ 0.01). The 120 Hz (0.030 ± 0.004 kilopascal (kPa)/mmHg, P < 0.0001) and 150 Hz (0.031 ± 0.008 kPa/mmHg, P = 0.01) vibrational frequencies had nearly identical slopes, which were approximately two- to three-fold higher than the 90 Hz (0.017 ± 0.002 kPa/mmHg, P < 0.0001) and 60 Hz (0.009 ± 0.002 kPa/mmHg, P = 0.001) slopes, respectively.

CONCLUSION

In this study, MRE demonstrated the potential for noninvasive measurement of changes in ICP. Magn Reson Med 79:1043-1051, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

An effective noise reduction method for multi-energy CT images that exploit spatio-spectral features

PURPOSE

To develop and evaluate an image-domain noise reduction method for multi-energy CT (MECT) data.

METHODS

Multi-Energy Non-Local Means (MENLM) is a technique that uses the redundant information in MECT images to achieve noise reduction. In this method, spatio-spectral features are used to determine the similarity between pixels, making the similarity evaluation more robust to image noise. The performance of this MENLM filter was tested on images acquired on a whole-body research photon counting CT system. The impact of filtering on image quality was quantitatively evaluated in phantom studies in terms of image noise level (standard deviation of pixel values), noise power spectrum (NPS), in-plane and cross-plane spatial resolution, CT number accuracy, material decomposition performance, and subjective low-contrast spatial resolution using the American College of Radiology (ACR) CT accreditation phantom. Clinical feasibility was assessed by performing MENLM on contrast-enhanced swine images and unenhanced cadaver head images using clinically relevant doses and dose rates.

RESULTS

The phantom studies demonstrated that the MENLM filter reduced noise substantially and still preserved the shape and peak frequency of the NPS. With 80% noise reduction, MENLM filtering caused no degradation of high-contrast spatial resolution, as illustrated by the modulation transfer function (MTF) and slice sensitivity profile (SSP). CT number accuracy was also maintained for all energy channels, demonstrating that energy resolution was not affected by filtering. Material decomposition performance was improved with MENLM filtering. The subjective evaluation using the ACR phantom demonstrated an improvement in low-contrast performance. MENLM achieved effective noise reduction in both contrast-enhanced swine images and unenhanced cadaver head images, resulting in improved detection of subtle vascular structures and the differentiation of white/gray matter.

CONCLUSION

In MECT, MENLM achieved around 80% noise reduction and greatly improved material decomposition performance and the detection of subtle anatomical/low-contrast features while maintaining spatial and energy resolution. MENLM filtering may improve diagnostic or functional analysis accuracy and facilitate radiation dose and contrast media reduction for MECT.

Regional assessment of in vivo myocardial stiffness using 3D magnetic resonance elastography in a porcine model of myocardial infarction

PURPOSE

The stiffness of a myocardial infarct affects the left ventricular pump function and remodeling. Magnetic resonance elastography (MRE) is a noninvasive imaging technique for measuring soft-tissue stiffness in vivo. The purpose of this study was to investigate the feasibility of assessing in vivo regional myocardial stiffness with high-frequency 3D cardiac MRE in a porcine model of myocardial infarction, and compare the results with ex vivo uniaxial tensile testing.

METHODS

Myocardial infarct was induced in a porcine model by embolizing the left circumflex artery. Fourteen days postinfarction, MRE imaging was performed in diastole using an echocardiogram-gated spin-echo echo-planar-imaging sequence with 140-Hz vibrations and 3D MRE processing. The MRE stiffness and tensile modulus from uniaxial testing were compared between the remote and infarcted myocardium.

RESULTS

Myocardial infarcts showed increased in vivo MRE stiffness compared with remote myocardium (4.6 ± 0.7 kPa versus 3.0 ± 0.6 kPa, P = 0.02) within the same pig. Ex vivo uniaxial mechanical testing confirmed the in vivo MRE results, showing that myocardial infarcts were stiffer than remote myocardium (650 ± 80 kPa versus 110 ± 20 kPa, P = 0.01).

CONCLUSIONS

These results demonstrate the feasibility of assessing in vivo regional myocardial stiffness with high-frequency 3D cardiac MRE. Magn Reson Med 79:361-369, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Improved Shear Wave Group Velocity Estimation Method Based on Spatiotemporal Peak and Thresholding Motion Search

Quantitative ultrasound elastography is increasingly being used in the assessment of chronic liver disease. Many studies have reported ranges of liver shear wave velocity values for healthy individuals and patients with different stages of liver fibrosis. Nonetheless, ongoing efforts exist to stabilize quantitative ultrasound elastography measurements by assessing factors that influence tissue shear wave velocity values, such as food intake, body mass index, ultrasound scanners, scanning protocols, and ultrasound image quality. Time-to-peak (TTP) methods have been routinely used to measure the shear wave velocity. However, there is still a need for methods that can provide robust shear wave velocity estimation in the presence of noisy motion data. The conventional TTP algorithm is limited to searching for the maximum motion in time profiles at different spatial locations. In this paper, two modified shear wave speed estimation algorithms are proposed. The first method searches for the maximum motion in both space and time [spatiotemporal peak (STP)]; the second method applies an amplitude filter [spatiotemporal thresholding (STTH)] to select points with motion amplitude higher than a threshold for shear wave group velocity estimation. The two proposed methods (STP and STTH) showed higher precision in shear wave velocity estimates compared with TTP in phantom. Moreover, in a cohort of 14 healthy subjects, STP and STTH methods improved both the shear wave velocity measurement precision and the success rate of the measurement compared with conventional TTP.

Accelerated Singular Value-Based Ultrasound Blood Flow Clutter Filtering With Randomized Singular Value Decomposition and Randomized Spatial Downsampling

Singular value decomposition (SVD)-based ultrasound blood flow clutter filters have recently demonstrated substantial improvement in clutter rejection for ultrafast plane wave microvessel imaging, and have become the commonly used clutter filtering method for many novel ultrafast imaging applications such as functional ultrasound and super-resolution imaging. At present, however, the computational burden of SVD remains as a major hurdle for practical implementation and clinical translation of this method. To address this challenge, in the study we present two blood flow clutter filtering methods based on randomized SVD (rSVD) and randomized spatial downsampling to accelerate SVD clutter filtering with minimal compromise to the clutter filter performance. rSVD accelerates SVD computation by approximating the k largest singular values, while random downsampling accelerates both full SVD and rSVD by decomposing the original large data matrix into small matrices that can be processed in parallel. An in vitro blood flow phantom study with the presence of heavy tissue clutter showed significantly improved computational performance using the proposed methods with minimal deterioration to the clutter filter performance (less than 3-dB reduction in blood to clutter ratio, less than 0.2-cm²/s² increase in flow mean squared error, less than 0.1-cm/s increase in the standard deviation of the vessel blood flow signal, and less than 0.3-cm/s increase in tissue clutter velocity for both full SVD and rSVD when the downsampling factor was less than 20× ). The maximum acceleration was about threefold from randomized spatial downsampling, and approximately another threefold from rSVD. An in vivo rabbit kidney perfusion study showed that rSVD provided comparable performance to full SVD in clutter rejection in vivo (maximum difference of blood to clutter ratio was less than 0.6 dB), and random downsampling provided artifact-free perfusion imaging results when combined with both full SVD and rSVD. The blood to clutter ratio was still above 10 dB with a downsampling factor of 60× . We also demonstrated real-time microvessel imaging feasibility (~40-ms processing time) by combining rSVD with random downsampling. The findings and methods presented in this paper may greatly facilitate the new area of ultrafast microvessel imaging research.

Automated Liver Elasticity Calculation for 3D MRE

Magnetic Resonance Elastography (MRE) is a phase-contrast MRI technique which calculates quantitative stiffness images, called elastograms, by imaging the propagation of acoustic waves in tissues. It is used clinically to diagnose liver fibrosis. Automated analysis of MRE is difficult as the corresponding MRI magnitude images (which contain anatomical information) are affected by intensity inhomogeneity, motion artifact, and poor tissue- and edge-contrast. Additionally, areas with low wave amplitude must be excluded. An automated algorithm has already been successfully developed and validated for clinical 2D MRE. 3D MRE acquires substantially more data and, due to accelerated acquisition, has exacerbated image artifacts. Also, the current 3D MRE processing does not yield a confidence map to indicate MRE wave quality and guide ROI selection, as is the case in 2D. In this study, extension of the 2D automated method, with a simple wave-amplitude metric, was developed and validated against an expert reader in a set of 57 patient exams with both 2D and 3D MRE. The stiffness discrepancy with the expert for 3D MRE was -0.8% ± 9.45% and was better than discrepancy with the same reader for 2D MRE (-3.2% ± 10.43%), and better than the inter-reader discrepancy observed in previous studies. There were no automated processing failures in this dataset. Thus, the automated liver elasticity calculation (ALEC) algorithm is able to calculate stiffness from 3D MRE data with minimal bias and good precision, while enabling stiffness measurements to be fully reproducible and to be easily performed on the large 3D MRE datasets.

Cardiac MR elastography for quantitative assessment of elevated myocardial stiffness in cardiac amyloidosis

Purpose

To evaluate if cardiac magnetic resonance elastography (MRE) can measure increased stiffness in patients with cardiac amyloidosis. Myocardial tissue stiffness plays an important role in cardiac function. A noninvasive quantitative imaging technique capable of measuring myocardial stiffness could aid in disease diagnosis, therapy monitoring, and disease prognostic strategies. We recently developed a high‐frequency cardiac MRE technique capable of making noninvasive stiffness measurements.

Materials and Methods

In all, 16 volunteers and 22 patients with cardiac amyloidosis were enrolled in this study after Institutional Review Board approval and obtaining formal written consent. All subjects were imaged head‐first in the supine position in a 1.5T closed‐bore MR imager. 3D MRE was performed using 5 mm isotropic resolution oblique short‐axis slices and a vibration frequency of 140 Hz to obtain global quantitative in vivo left ventricular stiffness measurements. The median stiffness was compared between the two cohorts. An octahedral shear strain signal‐to‐noise ratio (OSS‐SNR) threshold of 1.17 was used to exclude exams with insufficient motion amplitude.

Results

Five volunteers and six patients had to be excluded from the study because they fell below the 1.17 OSS‐SNR threshold. The myocardial stiffness of cardiac amyloid patients (median: 11.4 kPa, min: 9.2, max: 15.7) was significantly higher (P = 0.0008) than normal controls (median: 8.2 kPa, min: 7.2, max: 11.8).

Conclusion

This study demonstrates the feasibility of 3D high‐frequency cardiac MRE as a contrast‐agent‐free diagnostic imaging technique for cardiac amyloidosis.

Level of Evidence: 2

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2017;46:1361–1367.

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.

Mammographic breast density and risk of breast cancer in women with atypical hyperplasia: an observational cohort study from the Mayo Clinic Benign Breast Disease (BBD) cohort

Background

Atypical hyperplasia (AH) and mammographic breast density (MBD) are established risk factors for breast cancer (BC), but their joint contributions are not well understood. We examine associations of MBD and BC by histologic impression, including AH, in a subcohort of women from the Mayo Clinic Benign Breast Disease Cohort.

Methods

Women with a diagnosis of BBD and mammogram between 1985 and 2001 were eligible. Histologic impression was assessed via pathology review and coded as non-proliferative disease (NP), proliferative disease without atypia (PDWA) and AH. MBD was assessed clinically using parenchymal pattern (PP) or BI-RADS criteria and categorized as low, moderate or high. Percent density (PD) was also available for a subset of women. BC and clinical information were obtained by questionnaires, medical records and the Mayo Clinic Tumor Registry. Women were followed from date of benign biopsy to BC, death or last contact. Standardized incidence ratios (SIRs) compared the observed number of BCs to expected counts. Cox regression estimated multivariate-adjusted MBD hazard ratios.

Results

Of the 6271 women included in the study, 1132 (18.0%) had low MBD, 2921 (46.6%) had moderate MBD, and 2218 (35.4%) had high MBD. A total of 3532 women (56.3%) had NP, 2269 (36.2%) had PDWA and 470 (7.5%) had AH. Over a median follow-up of 14.3 years, 528 BCs were observed. The association of MBD and BC risk differed by histologic impression (p-interaction = 0.03), such that there was a strong MBD and BC association among NP (p < 0.001) but non-significant associations for PDWA (p = 0.27) and AH (p = 0.96). MBD and BC associations for AH women were not significant within subsets defined by type of MBD measure (PP vs. BI-RADS), age at biopsy, number of foci of AH, type of AH (lobular vs. ductal) and body mass index, and after adjustment for potential confounding variables. Women with atypia who also had high PD (>50%) demonstrated marginal evidence of increased BC risk (SIR 4.98), but results were not statistically significant.

Conclusion

We found no evidence of an association between MBD and subsequent BC risk in women with AH.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3082-2) contains supplementary material, which is available to authorized users.

Distinguishing between Hepatic Inflammation and Fibrosis with MR Elastography

Purpose To investigate the utility of magnetic resonance (MR) elastography-derived mechanical properties in the discrimination of hepatic inflammation and fibrosis in the early stages of chronic liver diseases. Materials and Methods All studies were approved by the institutional animal care and use committee. A total of 187 animals were studied, including 182 mice and five pigs. These animals represented five different liver diseases with a varying combination and extent of hepatic inflammation, fibrosis, congestion, and portal hypertension. Multifrequency three-dimensional MR elastography was performed, and shear stiffness, storage modulus, shear loss modulus, and damping ratio were calculated for all animals. Necroinflammation, fibrosis, and portal pressure were either histologically scored or biochemically and physically quantified in all animals. Two-sided Welch t tests were used to evaluate mean differences between disease and control groups. Spearman correlation analyses were used to evaluate the relationships between mechanical parameters and quantitative fibrosis extent (hydroxyproline concentration) and portal pressure. Results Liver stiffness and storage modulus increased with progressively developed fibrosis and portal hypertension (mean stiffness at 80 Hz and 48-week feeding, 0.51 kPa ± 0.12 in the steatohepatitis group vs 0.29 kPa ± 0.01 in the control group; P = .02). Damping ratio and shear loss modulus can be used to distinguish inflammation from fibrosis at early stages of disease, even before the development of histologically detectable necroinflammation and fibrosis (mean damping ratio at 80 Hz and 20-week feeding, 0.044 ± 0.012 in the steatohepatitis group vs 0.014 ± 0.008 in the control group; P < .001). Damping ratio and liver stiffness vary differently with respect to cause of portal hypertension (ie, congestion- or cirrhosis-induced hypertension). These differentiation abilities have frequency-dependent variations. Conclusion Liver stiffness and damping ratio measurements can extend hepatic MR elastography to potentially enable assessment of necroinflammatory, congestive, and fibrotic processes of chronic liver diseases. ^© RSNA, 2017 Online supplemental material is available for this article.

Clinical Correlation of Abnormal Findings on Magnetic Resonance Elastography in Idiopathic Normal Pressure Hydrocephalus

BACKGROUND

Idiopathic normal pressure hydrocephalus (iNPH) is a ventriculomegaly syndrome characterized by dementia, urinary incontinence, and gait disturbance, which is potentially reversible after ventriculoperitoneal shunting (VPS). Magnetic resonance elastography (MRE) is an evolving imaging technology that noninvasively measures tissue viscoelasticity. We studied iNPH patients using MRE prior to shunting, compared them with normal controls, and analyzed associations between MRE findings and clinical features, as a pilot assessment of MRE in iNPH.

METHODS

Stiffness values were measured on preoperative MRE in 10 iNPH patients scheduled for VPS and compared with those in 20 age- and sex-matched controls. Stiffness results were correlated with clinical iNPH symptoms.

RESULTS

MRE demonstrated significantly increased stiffness in iNPH in cerebrum (P = 0.04), occipital (P = 0.002), and parietal (P = 0.01) regions of interest (ROIs) and significantly decreased stiffness in periventricular ROIs (P < 0.0001). Stiffness was not significantly different in frontal (P = 0.1) and deep gray ROIs (P = 0.4). Univariate analysis showed associations between preoperative iNPH symptoms and abnormally increased stiffness, including urinary incontinence with cerebrum (P = 0.005), frontal (P = 0.04), and cerebellum (P = 0.03) ROIs, and Parkinsonism with occipital ROI (P = 0.04). Postoperative improvement was associated with increased deep gray stiffness (P = 0.01); failure was associated with increased temporal (P = 0.0002) stiffness.

CONCLUSIONS

Based on the preliminary results of this small, limited analysis, brain stiffness may be altered in iNPH, and these alterations in parenchymal viscoelastic properties may be correlated with clinical symptoms. Increased temporal stiffness may predict surgical failure and potentially suggest an alternative dementing pathology underlying the iNPH-like symptoms. These findings highlight the potential future utility of MRE in iNPH management.