Flexible metasurface for improving brain imaging at 7T.

PURPOSE: Ultra-high field MRI offers unprecedented detail for noninvasive visualization of the human brain. However, brain imaging is challenging at 7T due to the B 1 + $$ {}_1^{+} $$ field inhomogeneity, which results in signal intensity drops in temporal lobes and a bright region in the brain center. This study aims to evaluate using a metasurface to improve brain imaging at 7T and simplify the investigative workflow. METHODS: Two flexible metasurfaces comprising a periodic structure of copper strips and parallel-plate capacitive elements printed on an ultra-thin substrate were optimized for brain imaging and implemented via PCB. We considered two setups: (1) two metasurfaces located near the temporal lobes and (2) one metasurface placed near the occipital lobe. The effect of metasurface placement on the transmit efficiency and specific absorption rate was evaluated via electromagnetic simulation studies with voxelized models. In addition, their impact on signal-to-noise ratio (SNR) and diagnostic image quality was assessed in vivo for two male and one female volunteers. RESULTS: Placement of metasurfaces near the regions of interest led to an increase in homogeneity of the transmit field by 5% and 10.5% in the right temporal lobe and occipital lobe for a male subject, respectively. SAR efficiency values changed insignificantly, dropping by less than 8% for all investigated setups. In vivo studies also confirmed the numerically predicted improvement in field distribution and receive sensitivity in the desired ROI. CONCLUSION: Optimized metasurfaces enable homogenizing transmit field distribution in the brain at 7T. The proposed lightweight and flexible structure can potentially provide MR examination with higher diagnostic value images.

Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI.

OBJECTIVE: This study aims to assess the statistical significance of training parameters in 240 dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and undersampled MRI in various acquisition protocols. The objective is to determine the validity of differences between different DUNet configurations and their impact on image quality metrics. MATERIALS AND METHODS: To achieve this, we trained all DUNets using the same learning rate and number of epochs, with variations in 5 acquisition protocols, 24 loss function weightings, and 2 ground truths. We calculated evaluation metrics for two metric regions of interest (ROI). We employed both Analysis of Variance (ANOVA) and Mixed Effects Model (MEM) to assess the statistical significance of the independent parameters, aiming to compare their efficacy in revealing differences and interactions among fixed parameters. RESULTS: ANOVA analysis showed that, except for the acquisition protocol, fixed variables were statistically insignificant. In contrast, MEM analysis revealed that all fixed parameters and their interactions held statistical significance. This emphasizes the need for advanced statistical analysis in comparative studies, where MEM can uncover finer distinctions often overlooked by ANOVA. DISCUSSION: These findings highlight the importance of utilizing appropriate statistical analysis when comparing different deep learning models. Additionally, the surprising effectiveness of the UNet architecture in enhancing various acquisition protocols underscores the potential for developing improved methods for characterizing and training deep learning models. This study serves as a stepping stone toward enhancing the transparency and comparability of deep learning techniques for medical imaging applications.

Brain imaging with portable low-field MRI.

The advent of portable, low-field MRI (LF-MRI) heralds new opportunities in neuroimaging. Low power requirements and transportability have enabled scanning outside the controlled environment of a conventional MRI suite, enhancing access to neuroimaging for indications that are not well suited to existing technologies. Maximizing the information extracted from the reduced signal-to-noise ratio of LF-MRI is crucial to developing clinically useful diagnostic images. Progress in electromagnetic noise cancellation and machine learning reconstruction algorithms from sparse k-space data as well as new approaches to image enhancement have now enabled these advancements. Coupling technological innovation with bedside imaging creates new prospects in visualizing the healthy brain and detecting acute and chronic pathological changes. Ongoing development of hardware, improvements in pulse sequences and image reconstruction, and validation of clinical utility will continue to accelerate this field. As further innovation occurs, portable LF-MRI will facilitate the democratization of MRI and create new applications not previously feasible with conventional systems.

Low-field MRI: A report on the 2022 ISMRM workshop.

In March 2022, the first ISMRM Workshop on Low-Field MRI was held virtually. The goals of this workshop were to discuss recent low field MRI technology including hardware and software developments, novel methodology, new contrast mechanisms, as well as the clinical translation and dissemination of these systems. The virtual Workshop was attended by 368 registrants from 24 countries, and included 34 invited talks, 100 abstract presentations, 2 panel discussions, and 2 live scanner demonstrations. Here, we report on the scientific content of the Workshop and identify the key themes that emerged. The subject matter of the Workshop reflected the ongoing developments of low-field MRI as an accessible imaging modality that may expand the usage of MRI through cost reduction, portability, and ease of installation. Many talks in this Workshop addressed the use of computational power, efficient acquisitions, and contemporary hardware to overcome the SNR limitations associated with low field strength. Participants discussed the selection of appropriate clinical applications that leverage the unique capabilities of low-field MRI within traditional radiology practices, other point-of-care settings, and the broader community. The notion of "image quality" versus "information content" was also discussed, as images from low-field portable systems that are purpose-built for clinical decision-making may not replicate the current standard of clinical imaging. Speakers also described technical challenges and infrastructure challenges related to portability and widespread dissemination, and speculated about future directions for the field to improve the technology and establish clinical value.

Image registration and mutual thresholding enable low interimage variability across dynamic MRI measurements of supraclavicular brown adipose tissue during mild cold exposure.

PURPOSE: Activated brown adipose tissue (BAT) enhances lipid catabolism and improves cardiometabolic health. Quantitative MRI of the fat fraction (FF) of supraclavicular BAT (scBAT) is a promising noninvasive measure to assess BAT activity but suffers from high scan variability. We aimed to test the effects of coregistration and mutual thresholding on the scan variability in a fast (1 min) time-resolution MRI protocol for assessing scBAT FF changes during cold exposure. METHODS: Ten volunteers (age 24.8 ± 3.0 years; body mass index 21.2 ± 2.1 kg/m2 ) were scanned during thermoneutrality (32°C; 10 min) and mild cold exposure (18°C; 60 min) using a 12-point gradient-echo sequence (70 consecutive scans with breath-holds, 1.03 min per dynamic). Dynamics were coregistered to the first thermoneutral scan, which enabled drawing of single regions of interest in the scBAT depot. Voxel-wise FF changes were calculated at each time point and averaged across regions of interest. We applied mutual FF thresholding, in which voxels were included if their FF was greater than 30% FF in the reference scan and the registered dynamic. The efficacy of the coregistration was determined by using a moving average and comparing the mean squared error of residuals between registered and nonregistered data. Registered scBAT ΔFF was compared with single-scan thresholding using the moving average method. RESULTS: Registered scBAT ΔFF had lower mean square error values than nonregistered data (0.07 ± 0.05% vs. 0.16 ± 0.14%; p < 0.05), and mutual thresholding reduced the scBAT ΔFF variability by 30%. CONCLUSION: We demonstrate that coregistration and mutual thresholding improve stability of the data 2-fold, enabling assessment of small changes in FF following cold exposure.

An integrated target field framework for point-of-care halbach array low-field MRI system design.

OBJECTIVE: Low-cost low-field point-of-care MRI systems are used in many different applications. System design has correspondingly different requirements in terms of imaging field-of-view, spatial resolution and magnetic field strength. In this work an iterative framework has been created to design a cylindrical Halbach-based magnet along with integrated gradient and RF coils that most efficiently fulfil a set of user-specified imaging requirements. METHODS: For efficient integration, target field methods are used for each of the main hardware components. These have not been used previously in magnet design, and a new mathematical model was derived accordingly. These methods result in a framework which can design an entire low-field MRI system within minutes using standard computing hardware. RESULTS: Two distinct point-of-care systems are designed using the described framework, one for neuroimaging and the other for extremity imaging. Input parameters are taken from literature and the resulting systems are discussed in detail. DISCUSSION: The framework allows the designer to optimize the different hardware components with respect to the desired imaging parameters taking into account the interdependencies between these components and thus give insight into the influence of the design choices.

Radiofrequency safety of high permittivity pads in MRI-Impact of insulation material.

PURPOSE: High permittivity dielectric pads are known to be effective for tailoring the RF field and improving image quality in high field MRI. Despite a number of studies reporting benign specific absorption rate (SAR) effects, their "universal" safety remains an open concern. In this work, we evaluate the impact of the insulation material in between the pad and the body, using both RF simulations as well as phantom experiments. METHODS: A 3T configuration with high permittivity material was simulated and characterized experimentally in terms of B1 + fields and RF power absorption, both with and without electrical insulation in between the high permittivity material and the sample. Different insulation conditions were compared, and electromagnetic analyses on the induced current density were performed to elucidate the effect. RESULTS: Increases in RF heating of up to 49% were observed experimentally in a tissue-mimicking phantom after removing the material insulation. The B1 + magnitude and RF transceive phase were not affected. Simulations indicated that an insulation thickness of 0.5-2 mm should be accounted for in numerical models in order to ensure reliable results. CONCLUSION: A reliable RF safety assessment of high permittivity dielectric pads requires accounting for the insulating properties of the plastic encasing. Ignoring the electrical insulation can lead to erroneous results with substantial increases in local SAR at the interface. Conversely, the material insulation does not need to be modeled to predict the B1 + effects during the design of the pad geometry.

A framework for advancing sustainable magnetic resonance imaging access in Africa.

Magnetic resonance imaging (MRI) technology has profoundly transformed current healthcare systems globally, owing to advances in hardware and software research innovations. Despite these advances, MRI remains largely inaccessible to clinicians, patients, and researchers in low-resource areas, such as Africa. The rapidly growing burden of noncommunicable diseases in Africa underscores the importance of improving access to MRI equipment as well as training and research opportunities on the continent. The Consortium for Advancement of MRI Education and Research in Africa (CAMERA) is a network of African biomedical imaging experts and global partners, implementing novel strategies to advance MRI access and research in Africa. Upon its inception in 2019, CAMERA sets out to identify challenges to MRI usage and provide a framework for addressing MRI needs in the region. To this end, CAMERA conducted a needs assessment survey (NAS) and a series of symposia at international MRI society meetings over a 2-year period. The 68-question NAS was distributed to MRI users in Africa and was completed by 157 clinicians and scientists from across Sub-Saharan Africa (SSA). On average, the number of MRI scanners per million people remained at less than one, of which 39% were obsolete low-field systems but still in use to meet daily clinical needs. The feasibility of coupling stable energy supplies from various sources has contributed to the growing number of higher-field (1.5 T) MRI scanners in the region. However, these systems are underutilized, with only 8% of facilities reporting clinical scans of 15 or more patients per day, per scanner. The most frequently reported MRI scans were neurological and musculoskeletal. The CAMERA NAS combined with the World Health Organization and International Atomic Energy Agency data provides the most up-to-date data on MRI density in Africa and offers a unique insight into Africa's MRI needs. Reported gaps in training, maintenance, and research capacity indicate ongoing challenges in providing sustainable high-value MRI access in SSA. Findings from the NAS and focused discussions at international MRI society meetings provided the basis for the framework presented here for advancing MRI capacity in SSA. While these findings pertain to SSA, the framework provides a model for advancing imaging needs in other low-resource settings.

Association of shivering threshold time with body composition and brown adipose tissue in young adults.

PURPOSE: Brown adipose tissue (BAT) increases metabolic heat production in response to cold exposure. Body size and composition are involved in the human cold response, yet the influence of BAT herein have not fully been explored. Here, we aimed to study the association of the cold-induced shivering threshold time with body composition, BAT, the perception of shivering and skin temperature in young adults. METHODS: 110 young healthy adults (81 females; age = 21.7 ± 2.1 years, BMI = 24.2 ± 4.3 kg/m2) underwent 2 h of individualized cooling, followed by the quantification of BAT using a18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography-computed tomography (PET-CT) scan. Body mass index (BMI), lean mass, fat mass and body surface area (BSA) were also measured. Shivering threshold time was defined as the time until shivering occurred using an individualized cooling protocol. RESULTS: The shivering threshold time was on average 116.1 min for males and 125.8 min for females, and was positively associated to BMI (ß = 3.106; R2 = 0.141; p = 0.001), lean mass (ß = 2.295; R2 = 0.128; p = 0.001) and fat mass (ß = 1.492; R2 = 0.121; p = 0.001) in females, but not in males (all p ≥ 0.409). The shivering threshold time was positively associated with BSA in males (p = 0.047) and females (p = 0.001), but it was not associated with BAT volume or [18F]FDG uptake nor with the perception of shivering and skin temperature perception in both sexes. CONCLUSION: The shivering threshold time is positively associated with whole-body adiposity and lean mass in females, but not in males. The shivering threshold time was positively associated with BSA, but no association was observed with BAT nor with the perception of shivering or skin temperature. Future research should consider the influence of body composition when applying cooling protocols among individuals with different phenotypical features.

Microvascular response to exercise varies along the length of the tibialis anterior muscle.

Microvascular function is an important component in the physiology of muscle. One of the major parameters, blood perfusion, can be measured noninvasively and quantitatively by arterial spin labeling (ASL) MRI. Most studies using ASL in muscle have only reported data from a single slice, thereby assuming that muscle perfusion is homogeneous within muscle, whereas recent literature has reported proximodistal differences in oxidative capacity and perfusion. Here, we acquired pulsed ASL data in 12 healthy volunteers after dorsiflexion exercise in two slices separated distally by 7 cm. We combined this with a Look-Locker scheme to acquire images at multiple postlabeling delays (PLDs) and with a multiecho readout to measure T2 *. This enabled the simultaneous evaluation of quantitative muscle blood flow (MBF), arterial transit time (ATT), and T2 * relaxation time in the tibialis anterior muscle during recovery. Using repeated measures analyses of variance we tested the effect of time, slice location, and their interaction on MBF, ATT, and T2 *. Our results showed a significant difference as a function of time postexercise for all three parameters (MBF: F = 34.0, p < .0001; T2 *: F = 73.7, p < .0001; ATT: F = 13.6, p < .001) and no average differences between slices over the total time postexercise were observed. The interaction effect between time postexercise and slice location was significant for MBF and T2 * (F = 5.5, p = 0.02, F = 6.1, p = 0.02, respectively), but not for ATT (F = 2.2, p = .16). The proximal slice showed a higher MBF and a lower ATT than the distal slice during the first 2 min of recovery, and T2 * showed a delayed response in the distal slice. These results imply a higher perfusion and faster microvascular response to exercise in the proximal slice, in line with previous literature. Moreover, the differences in ATT indicate that it is difficult to correctly determine perfusion based on a single PLD as is commonly performed in the muscle literature.

Improved detection limits of J-coupled neurometabolites in the human brain at 7 T with a J-refocused sLASER sequence.

In a standard spin echo, the time evolution due to homonuclear couplings is not reversed, leading to echo time (TE)-dependent modulation of the signal amplitude and signal loss in the case of overlapping multiplet resonances. This has an adverse effect on quantification of several important metabolites such as glutamate and glutamine. Here, we propose a J-refocused variant of the sLASER sequence (J-sLASER) to improve quantification of J-coupled metabolites at ultrahigh field (UHF). The use of the sLASER sequence is particularly advantageous at UHF as it minimizes chemical shift displacement error and results in relatively homogenous refocusing. We simulated the MRS signal from brain metabolites over a broad range of TE values with sLASER and J-sLASER, and showed that the signal of J-coupled metabolites was increased with J-sLASER with TE values up to ~80 ms. We further simulated "brain-like" spectra with both sequences at the shortest TE available on our scanner. We showed that, despite the slightly longer TE, the J-sLASER sequence results in significantly lower Cramer-Rao lower bounds (CRLBs) for J-coupled metabolites compared with those obtained with sLASER. Following phantom validation, we acquired spectra from two brain regions in 10 healthy volunteers (age 38 ± 15 years) using both sequences. We showed that using J-sLASER results in a decrease of CRLBs for J-coupled metabolites. In particular, we measured a robust ~38% decrease in the mean CRLB (glutamine) in parietal white matter and posterior cingulate cortex (PCC). We further showed, in 10 additional healthy volunteers (age 34 ± 15 years), that metabolite quantification following two separate acquisitions with J-sLASER in the PCC was repeatable. The improvement in quantification of glutamine may in turn improve the independent quantification of glutamate, the main excitatory neurotransmitter in the brain, and will simultaneously help to track possible modulations of glutamine, which is a key player in the glutamatergic cycle in astrocytes.

Personalized local SAR prediction for parallel transmit neuroimaging at 7T from a single T1-weighted dataset.

PURPOSE: Parallel RF transmission (PTx) is one of the key technologies enabling high quality imaging at ultra-high fields (≥7T). Compliance with regulatory limits on the local specific absorption rate (SAR) typically involves over-conservative safety margins to account for intersubject variability, which negatively affect the utilization of ultra-high field MR. In this work, we present a method to generate a subject-specific body model from a single T1-weighted dataset for personalized local SAR prediction in PTx neuroimaging at 7T. METHODS: Multi-contrast data were acquired at 7T (N = 10) to establish ground truth segmentations in eight tissue types. A 2.5D convolutional neural network was trained using the T1-weighted data as input in a leave-one-out cross-validation study. The segmentation accuracy was evaluated through local SAR simulations in a quadrature birdcage as well as a PTx coil model. RESULTS: The network-generated segmentations reached Dice coefficients of 86.7% ± 6.7% (mean ± SD) and showed to successfully address the severe intensity bias and contrast variations typical to 7T. Errors in peak local SAR obtained were below 3.0% in the quadrature birdcage. Results obtained in the PTx configuration indicated that a safety margin of 6.3% ensures conservative local SAR estimates in 95% of the random RF shims, compared to an average overestimation of 34% in the generic "one-size-fits-all" approach. CONCLUSION: A subject-specific body model can be automatically generated from a single T1-weighted dataset by means of deep learning, providing the necessary inputs for accurate and personalized local SAR predictions in PTx neuroimaging at 7T.

Baseline fat fraction is a strong predictor of disease progression in Becker muscular dystrophy.

In Becker muscular dystrophy (BMD), muscle weakness progresses relatively slowly, with a highly variable rate among patients. This complicates clinical trials, as clinically relevant changes are difficult to capture within the typical duration of a trial. Therefore, predictors for disease progression are needed. We assessed if temporal increase of fat fraction (FF) in BMD follows a sigmoidal trajectory and whether fat fraction at baseline (FFbase) could therefore predict FF increase after 2 years (ΔFF). Thereafter, for two different MR-based parameters, we tested the additional predictive value to FFbase. We used 3-T Dixon data from the upper and lower leg, and multiecho spin-echo MRI and 7-T 31 P MRS datasets from the lower leg, acquired in 24 BMD patients (age: 41.4 [SD 12.8] years). We assessed the pattern of increase in FF using mixed-effects modelling. Subsequently, we tested if indicators of muscle damage like standard deviation in water T2 (stdT2 ) and the phosphodiester (PDE) over ATP ratio at baseline had additional value to FFbase for predicting ∆FF. The association between FFbase and ΔFF was described by the derivative of a sigmoid function and resulted in a peak ΔFF around 0.45 FFbase (fourth-order polynomial term: t = 3.7, p < .001). StdT2 and PDE/ATP were not significantly associated with ∆FF if FFbase was included in the model. The relationship between FFbase and ∆FF suggests a sigmoidal trajectory of the increase in FF over time in BMD, similar to that described for Duchenne muscular dystrophy. Our results can be used to identify muscles (or patients) that are in the fast progressing stage of the disease, thereby facilitating the conduct of clinical trials.

In vivo T1 and T2 relaxation time maps of brain tissue, skeletal muscle, and lipid measured in healthy volunteers at 50 mT.

PURPOSE: Low-field (B0 < 0.1 T) MRI has generated much interest as a means of increased accessibility via reduced cost and improved portability compared to conventional clinical systems (B0 ≥ 1.5 Tesla). Here we measure MR relaxation times at 50 mT and compare results with commonly used models based on both in vivo and ex vivo measurements. METHODS: Using 3D turbo spin echo readouts, T1 and T2 maps of the human brain and lower leg were acquired on a custom-built 50 mT MRI scanner using inversion-recovery and multi-echo-based sequences, respectively. Image segmentation was performed based on a histogram analysis of the relaxation times. RESULTS: The average T1 times of gray matter, white matter, and cerebrospinal fluid (CSF) were 327 ± 10 ms, 275 ± 5 ms, and 3695 ± 287 ms, respectively. Corresponding values of T2 were 102 ± 6 ms, 102 ± 6 ms, and 1584 ± 124 ms. T1 times in the calf muscle were measured to be 171 ± 11 ms and were 130 ± 5 ms in subcutaneous and bone marrow lipid. Corresponding T2 times were 39 ± 2 ms in muscle and 90 ± 13 ms in lipid. CONCLUSIONS: For tissues except for CSF, the measured T1 times are much shorter than reported at higher fields and generally lie within the range of different models in the literature. As expected, T2 times are similar to those seen at typical clinical field strengths. Analysis of the relaxation maps indicates that segmentation of white and gray matter based purely on T1 or T2 will be quite challenging at low field given the relatively small difference in relaxation times.

Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus.

As low-field MRI technology is being disseminated into clinical settings around the world, it is important to assess the image quality required to properly diagnose and treat a given disease and evaluate the role of machine learning algorithms, such as deep learning, in the enhancement of lower quality images. In this post hoc analysis of an ongoing randomized clinical trial, we assessed the diagnostic utility of reduced-quality and deep learning enhanced images for hydrocephalus treatment planning. CT images of post-infectious infant hydrocephalus were degraded in terms of spatial resolution, noise, and contrast between brain and CSF and enhanced using deep learning algorithms. Both degraded and enhanced images were presented to three experienced pediatric neurosurgeons accustomed to working in low- to middle-income countries (LMIC) for assessment of clinical utility in treatment planning for hydrocephalus. In addition, enhanced images were presented alongside their ground-truth CT counterparts in order to assess whether reconstruction errors caused by the deep learning enhancement routine were acceptable to the evaluators. Results indicate that image resolution and contrast-to-noise ratio between brain and CSF predict the likelihood of an image being characterized as useful for hydrocephalus treatment planning. Deep learning enhancement substantially increases contrast-to-noise ratio improving the apparent likelihood of the image being useful; however, deep learning enhancement introduces structural errors which create a substantial risk of misleading clinical interpretation. We find that images with lower quality than is customarily acceptable can be useful for hydrocephalus treatment planning. Moreover, low quality images may be preferable to images enhanced with deep learning, since they do not introduce the risk of misleading information which could misguide treatment decisions. These findings advocate for new standards in assessing acceptable image quality for clinical use.

Lumbar Spine Surgery and What We Lost in the Era of the Coronavirus Pandemic: A Survey of the Lumbar Spine Research Society.

STUDY DESIGN: This was a survey of the surgeon members of the Lumbar Spine Research Society (LSRS). OBJECTIVE: The purpose of this study was to assess trends in surgical practice and patient management involving elective and emergency surgery in the early months of the coronavirus pandemic. SUMMARY OF BACKGROUND DATA: The novel coronavirus has radically disrupted medical care in the first half of 2020. Little data exists regarding the exact nature of its effect on spine care. METHODS: A 53-question survey was sent to the surgeon members of the LSRS. Respondents were contacted via email 3 times over a 2-week period in late April. Questions concentrated on surgical and clinical practice patterns before and after the pandemic. Other data included elective surgical schedules and volumes, as well as which emergency cases were being performed. Surgeons were asked about the status of coronavirus disease 2019 (COVID-19) virus testing. Circumstances for performing surgical intervention on patients with and without testing as well as patients testing positive were explored. RESULTS: A total of 43 completed surveys were returned of 174 sent to active surgeons in the LSRS (25%). Elective lumbar spine procedures decreased by 90% in the first 2 months of the pandemic, but emergency procedures did not change. Patients with "stable" lumbar disease had surgeries deferred indefinitely, even beyond 8 weeks if necessary. In-person outpatient visits became increasingly rare events, as telemedicine consultations accounted for 67% of all outpatient spine appointments. In total, 91% surgeons were under some type of confinement. Only 11% of surgeons tested for the coronavirus on all surgical patients. CONCLUSIONS: Elective lumbar surgery was significantly decreased in the first few months of the coronavirus pandemic, and much of outpatient spine surgery was practiced via telemedicine. Despite these constraints, spine surgeons performed emergency surgery when indicated, even when the COVID-19 status of patients was unknown. LEVEL OF EVIDENCE: Level IV.

Management of single-level thoracic disc herniation through a modified transfacet approach: A review of 86 patients.

BACKGROUND: Symptomatic thoracic disc herniation (TDH) is rare and does not typically resolve with conservative management. Traditional surgical management is the transthoracic approach; however, this approach can carry significant risk. Posterolateral approaches are less invasive, but no single approach has proven to be more effective than the other results are often dependent on surgeon experience with a particular approach, as well as the location and characteristics of the disc herniation. METHODS: This was retrospective review of a prospectively collected database. Eighty-six patients with TDH treated surgically through the modified transfacet approach were reviewed and evaluated for pain improvement, Nurick grade, and neurological symptoms. Patients were followed for 12 months postoperatively; estimated blood loss, length of hospital stay, hospital course, and postoperative complications were also assessed. RESULTS: All attempts at disc resection were successful. Most patients reported improvement in pain, sensory involvement, and strength. Seventy-nine patients had complete resolution of their symptoms while four patients had unchanged symptoms. Three patients experienced mild neurologic worsening postoperatively, but this resolved back to baseline. One patient experienced myelopathy during the postoperative period that resolved with steroid administration. The procedure was well tolerated with minimal complications. CONCLUSION: TDH can be managed surgically through a variety of approaches. The selection of approach is dependent on surgeon experience with an approach, the patient's health, and the location and type of disc. The transfacet approach is safe and efficacious.

Muscle architecture is associated with muscle fat replacement in Duchenne and Becker muscular dystrophies.

INTRODUCTION/AIMS: Duchenne and Becker muscular dystrophies (DMD and BMD, respectively) are characterized by fat replacement of different skeletal muscles in a specific temporal order. Given the structural role of dystrophin in skeletal muscle mechanics, muscle architecture could be important in the progressive pathophysiology of muscle degeneration. Therefore, the aim of this study was to assess the role of muscle architecture in the progression of fat replacement in DMD and BMD. METHODS: We assessed the association between literature-based leg muscle architectural characteristics and muscle fat fraction from 22 DMD and 24 BMD patients. Dixon-based magnetic resonance imaging estimates of fat fractions at baseline and 12 (only DMD) and 24 months were related to fiber length and physiological cross-sectional area (PCSA) using age-controlled linear mixed modeling. RESULTS: DMD and BMD muscles with long fibers and BMD muscles with large PCSAs were associated with increased fat fraction. The effect of fiber length was stronger in muscles with larger PCSA. DISCUSSION: Muscle architecture may explain the pathophysiology of muscle degeneration in dystrophinopathies, in which proximal muscles with a larger mass (fiber length × PCSA) are more susceptible, confirming the clinical observation of a temporal proximal-to-distal progression. These results give more insight into the mechanical role in the pathophysiology of muscular dystrophies. Ultimately, this new information can be used to help support the selection of current and the development of future therapies.

Compartmental diffusion and microstructural properties of human brain gray and white matter studied with double diffusion encoding magnetic resonance spectroscopy of metabolites and water.

Double diffusion encoding (DDE) of the water signal offers a unique ability to separate the effect of microscopic anisotropic diffusion in structural units of tissue from the overall macroscopic orientational distribution of cells. However, the specificity in detected microscopic anisotropy is limited as the signal is averaged over different cell types and across tissue compartments. Performing side-by-side water and metabolite DDE spectroscopic (DDES) experiments provides complementary measures from which intracellular and extracellular microscopic fractional anisotropies (µFA) and diffusivities can be estimated. Metabolites are largely confined to the intracellular space and therefore provide a benchmark for intracellular µFA and diffusivities of specific cell types. By contrast, water DDES measurements allow examination of the separate contributions to water µFA and diffusivity from the intra- and extracellular spaces, by using a wide range of b values to gradually eliminate the extracellular contribution. Here, we aimed to estimate tissue and compartment specific human brain microstructure by combining water and metabolites DDES experiments. We performed our DDES measurements in two brain regions that contain widely different amounts of white matter (WM) and gray matter (GM): parietal white matter (PWM) and occipital gray matter (OGM) in a total of 20 healthy volunteers at 7 Tesla. Metabolite DDES measurements were performed at b = 7199 s/mm2, while water DDES measurements were performed with a range of b values from 918 to 7199 s/mm2. The experimental framework we employed here resulted in a set of insights pertaining to the morphology of the intracellular and extracellular spaces in both gray and white matter. Results of the metabolite DDES experiments in both PWM and OGM suggest a highly anisotropic intracellular space within neurons and glia, with the possible exception of gray matter glia. The water µFA obtained from the DDES results at high b values in both regions converged with that of the metabolite DDES, suggesting that the signal from the extracellular space is indeed effectively suppressed at the highest b value. The µFA measured in the OGM significantly decreased at lower b values, suggesting a considerably lower anisotropy of the extracellular space in GM compared to WM. In PWM, the water µFA remained high even at the lowest b value, indicating a high degree of organization in the interstitial space in WM. Tortuosity values in the cytoplasm for water and tNAA, obtained with correlation analysis of microscopic parallel diffusivity with respect to GM/WM tissue fraction in the volume of interest, are remarkably similar for both molecules, while exhibiting a clear difference between gray and white matter, suggesting a more crowded cytoplasm and more complex cytomorphology of neuronal cell bodies and dendrites in GM than those found in long-range axons in WM.

Quantification of Myocardial Creatine and Triglyceride Content in the Human Heart: Precision and Accuracy of in vivo Proton Magnetic Resonance Spectroscopy.

BACKGROUND: Proton magnetic resonance spectroscopy (1 H-MRS) of the human heart is deemed to be a quantitative method to investigate myocardial metabolite content, but thorough validations of in vivo measurements against invasive techniques are lacking. PURPOSE: To determine measurement precision and accuracy for quantifications of myocardial total creatine and triglyceride content with localized 1 H-MRS. STUDY TYPE: Test-retest repeatability and measurement validation study. SUBJECTS: Sixteen volunteers and 22 patients scheduled for open-heart aortic valve replacement or septal myectomy. FIELD STRENGTH/SEQUENCE: Prospectively ECG-triggered respiratory-gated free-breathing single-voxel point-resolved spectroscopy (PRESS) sequence at 3 T. ASSESSMENT: Myocardial total creatine and triglyceride content were quantified relative to the total water content by fitting the 1 H-MR spectra. Precision was assessed with measurement repeatability. Accuracy was assessed by validating in vivo 1 H-MRS measurements against biochemical assays in myocardial tissue from the same subjects. STATISTICAL TESTS: Intrasession and intersession repeatability was assessed using Bland-Altman analyses. Agreement between 1 H-MRS measurements and biochemical assay was tested with regression analyses. RESULTS: The intersession repeatability coefficient for myocardial total creatine content was 41.8% with a mean value of 0.083% ± 0.020% of the total water signal, and 36.7% for myocardial triglyceride content with a mean value of 0.35% ± 0.13% of the total water signal. Ex vivo myocardial total creatine concentrations in tissue samples correlated with the in vivo myocardial total creatine content measured with 1 H-MRS: n = 22, r = 0.44; P < 0.05. Likewise, ex vivo myocardial triglyceride concentrations correlated with the in vivo myocardial triglyceride content: n = 20, r = 0.50; P < 0.05. DATA CONCLUSION: We validated the use of localized 1 H-MRS of the human heart at 3 T for quantitative assessments of in vivo myocardial tissue metabolite content by estimating the measurement precision and accuracy. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.