Oscillating-gradient diffusion magnetic resonance imaging detects acute subcellular structural changes in the mouse forebrain after neonatal hypoxia-ischemia

Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging

Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.

Intestinal microbiota modulates neuroinflammatory response and brain injury after neonatal hypoxia-ischemia

Premature infants lack a normal intestinal microbial community and also at risk of perinatal hypoxic-ischemic (HI) brain injury, which is considered to be one of the major factors for motor, sensory, and cognitive deficits. We hypothesized that neonatal gut microbiota composition modulated the immune reaction and severity of neonatal H-I brain injury. Neonatal C57BL/6J mouse pups were exposed to H-I protocol consisting of permanent left carotid artery ligation, followed by 8% hypoxia for 60 min. Microbial manipulation groups included 1) antibiotic treatment, E18 (maternal) to P5; 2) antibiotic treatment E18 to P5 + E. coli gavage; 3) antibiotic treatment E18 to P5 + B. infantis gavage; and 4) saline to pups with dams getting fresh water. The extent of brain injury and recovery was measured on MRI. Edematous injury volume was significantly higher in E. coli group than that in B. infantis group and in fresh water group. Gene expression in brains of pro-inflammatory cytokines (IL1β, IL6, IL2, TNF-α and toll-like receptors 2-6) were elevated to a greater extent in the E. coli group at P10, no injury, and at P13, 72 hours after H-I relative to sham control and B. infantis groups. Significant effects of microbiome and brain injury and interaction of these factors were found in abundance of major phyla. The neuroinflammatory response and brain injury after neonatal hypoxia-ischemia are affected by intestinal microbiota, providing opportunities for therapeutic intervention through targeting the early colonization and development of the gut microbiota.

In vivo Mapping of Cellular Resolution Neuropathology in Brain Ischemia by Diffusion MRI

Non-invasive mapping of cellular pathology can provide critical diagnostic and prognostic information. Recent developments in diffusion MRI have produced new tools for examining tissue microstructure at a level well below the imaging resolution. Here, we report the use of diffusion time ( t )-dependent diffusion kurtosis imaging ( t DKI) to simultaneously assess the morphology and transmembrane permeability of cells and their processes in the context of pathological changes in hypoxic-ischemic brain (HI) injury. Through Monte Carlo simulations and cell culture organoid imaging, we demonstrate feasibility in measuring effective size and permeability changes based on the peak and tail of t DKI curves. In a mouse model of HI, in vivo imaging at 11.7T detects a marked shift of the t DKI peak to longer t in brain edema, suggesting swelling and beading associated with the astrocytic processes and neuronal neurites. Furthermore, we observed a faster decrease of the t DKI tail in injured brain regions, reflecting increased membrane permeability that was associated with upregulated water exchange upon astrocyte activation at acute stage as well as necrosis with disrupted membrane integrity at subacute stage. Such information, unavailable with conventional diffusion MRI at a single t, can predict salvageable tissues. For a proof-of-concept, t DKI at 3T on an ischemic stroke patient suggested increased membrane permeability in the stroke region. This work therefore demonstrates the potential of t DKI for in vivo detection of the pathological changes in microstructural morphology and transmembrane permeability after ischemic injury using a clinically translatable protocol.

Temporal Diffusion Ratio (TDR) for imaging restricted diffusion: Optimisation and pre-clinical demonstration

Temporal Diffusion Ratio (TDR) is a recently proposed dMRI technique (Dell'Acqua et al., proc. ISMRM 2019) which provides contrast between areas with restricted diffusion and areas either without restricted diffusion or with length scales too small for characterisation. Hence, it has a potential for informing on pore sizes, in particular the presence of large axon diameters or other cellular structures. TDR employs the signal from two dMRI acquisitions obtained with the same, large, b-value but with different diffusion gradient waveforms. TDR is advantageous as it employs standard acquisition sequences, does not make any assumptions on the underlying tissue structure and does not require any model fitting, avoiding issues related to model degeneracy. This work for the first time introduces and optimises the TDR method in simulation for a range of different tissues and scanner constraints and validates it in a pre-clinical demonstration. We consider both substrates containing cylinders and spherical structures, representing cell soma in tissue. Our results show that contrasting an acquisition with short gradient duration, short diffusion time and high gradient strength with an acquisition with long gradient duration, long diffusion time and low gradient strength, maximises the TDR contrast for a wide range of pore configurations. Additionally, in the presence of Rician noise, computing TDR from a subset (50% or fewer) of the acquired diffusion gradients rather than the entire shell as proposed originally further improves the contrast. In the last part of the work the results are demonstrated experimentally on rat spinal cord. In line with simulations, the experimental data shows that optimised TDR improves the contrast compared to non-optimised TDR. Furthermore, we find a strong correlation between TDR and histology measurements of axon diameter. In conclusion, we find that TDR has great potential and is a very promising alternative (or potentially complement) to model-based approaches for informing on pore sizes and restricted diffusion in general.

IMPULSED model based cytological feature estimation with U-Net: Application to human brain tumor at 3T

PURPOSE

This work introduces and validates a deep-learning-based fitting method, which can rapidly provide accurate and robust estimation of cytological features of brain tumor based on the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model fitting with diffusion-weighted MRI data.

METHODS

The U-Net was applied to rapidly quantify extracellular diffusion coefficient (D_ex ), cell size (d), and intracellular volume fraction (v_in ) of brain tumor. At the training stage, the image-based training data, synthesized by randomizing quantifiable microstructural parameters within specific ranges, was used to train U-Net. At the test stage, the pre-trained U-Net was applied to estimate the microstructural parameters from simulated data and the in vivo data acquired on patients at 3T. The U-Net was compared with conventional non-linear least-squares (NLLS) fitting in simulations in terms of estimation accuracy and precision.

RESULTS

Our results confirm that the proposed method yields better fidelity in simulations and is more robust to noise than the NLLS fitting. For in vivo data, the U-Net yields obvious quality improvement in parameter maps, and the estimations of all parameters are in good agreement with the NLLS fitting. Moreover, our method is several orders of magnitude faster than the NLLS fitting (from about 5 min to <1 s).

CONCLUSION

The image-based training scheme proposed herein helps to improve the quality of the estimated parameters. Our deep-learning-based fitting method can estimate the cell microstructural parameters fast and accurately.

Correlation Tensor MRI deciphers underlying kurtosis sources in stroke

Noninvasively detecting and characterizing modulations in cellular scale micro-architecture remains a desideratum for contemporary neuroimaging. Diffusion MRI (dMRI) has become the mainstay methodology for probing microstructure, and, in ischemia, its contrasts have revolutionized stroke management. Diffusion kurtosis imaging (DKI) has been shown to significantly enhance the sensitivity of stroke detection compared to its diffusion tensor imaging (DTI) counterparts. However, the interpretation of DKI remains ambiguous as its contrast may arise from competing kurtosis sources related to the anisotropy of tissue components, diffusivity variance across components, and microscopic kurtosis (e.g., arising from cross-sectional variance, structural disorder, and restriction). Resolving these sources may be fundamental for developing more specific imaging techniques for stroke management, prognosis, and understanding its pathophysiology. In this study, we apply Correlation Tensor MRI (CTI) - a double diffusion encoding (DDE) methodology recently introduced for deciphering kurtosis sources based on the unique information captured in DDE's diffusion correlation tensors - to investigate the underpinnings of kurtosis measurements in acute ischemic lesions. Simulations for the different kurtosis sources revealed specific signatures for cross-sectional variance (representing neurite beading), edema, and cell swelling. Ex vivo CTI experiments at 16.4 T were then performed in an experimental photothrombotic stroke model 3 h post-stroke (N = 10), and successfully separated anisotropic, isotropic, and microscopic non-Gaussian diffusion sources in the ischemic lesions. Each of these kurtosis sources provided unique contrasts in the stroked area. Particularly, microscopic kurtosis was shown to be a primary "driver" of total kurtosis upon ischemia; its large increases, coupled with decreases in anisotropic kurtosis, are consistent with the expected elevation in cross-sectional variance, likely linked to beading effects in small objects such as neurites. In vivo experiments at 9.4 T at the same time point (3 h post ischemia, N = 5) demonstrated the stability and relevance of the findings and showed that fixation is not a dominant confounder in our findings. In future studies, the different CTI contrasts may be useful to address current limitations of stroke imaging, e.g., penumbra characterization, distinguishing lesion progression form tissue recovery, and elucidating pathophysiological correlates.

Feasibility of oscillating and pulsed gradient diffusion MRI to assess neonatal hypoxia-ischemia on clinical systems

Diffusion-time- (t_d) dependent diffusion MRI (dMRI) extends our ability to characterize brain microstructure by measuring dMRI signals at varying t_d. The use of oscillating gradient (OG) is essential for accessing short t_d but is technically challenging on clinical MRI systems. This study aims to investigate the clinical feasibility and value of t_d-dependent dMRI in neonatal hypoxic-ischemic encephalopathy (HIE). Eighteen HIE neonates and six normal term-born neonates were scanned on a 3 T scanner, with OG-dMRI at an oscillating frequency of 33 Hz (equivalent t_d ≈ 7.5 ms) and pulsed gradient (PG)-dMRI at a t_d of 82.8 ms and b-value of 700 s/mm². The t_d-dependence, as quantified by the difference in apparent diffusivity coefficients between OG- and PG-dMRI (ΔADC), was observed in the normal neonatal brains, and the ΔADC was higher in the subcortical white matter than the deep grey matter. In HIE neonates with severe and moderate injury, ΔADC significantly increased in the basal ganglia (BG) compared to the controls (23.7% and 10.6%, respectively). In contrast, the conventional PG-ADC showed a 12.6% reduction only in the severe HIE group. White matter edema regions also demonstrated increased ΔADC, where PG-ADC did not show apparent changes. Our result demonstrated that t_d-dependent dMRI provided high sensitivity in detecting moderate-to-severe HIE.

Time-dependent diffusion MRI probes cerebellar microstructural alterations in a mouse model of Down syndrome

The cerebellum is a complex system with distinct cortical laminar organization. Alterations in cerebellar microstructure are common and associated with many factors such as genetics, cancer and ageing. Diffusion MRI (dMRI) provides a non-invasive tool to map the brain structural organization, and the recently proposed diffusion-time (td )-dependent dMRI further improves its capability to probe the cellular and axonal/dendritic microstructures by measuring water diffusion at multiple spatial scales. The td -dependent diffusion profile in the cerebellum and its utility in detecting cerebellar disorders, however, are not yet elucidated. Here, we first deciphered the spatial correspondence between dMRI contrast and cerebellar layers, based on which the cerebellar layer-specific td -dependent dMRI patterns were characterized in both euploid and Ts65Dn mice, a mouse model of Down syndrome. Using oscillating gradient dMRI, which accesses diffusion at short td 's by modulating the oscillating frequency, we detected subtle changes in the apparent diffusivity coefficient of the cerebellar internal granular layer and Purkinje cell layer of Ts65Dn mice that were not detectable by conventional pulsed gradient dMRI. The detection sensitivity of oscillating gradient dMRI increased with the oscillating frequency at both the neonatal and adult stages. The td -dependence, quantified by ΔADC map, was reduced in Ts65Dn mice, likely associated with the reduced granule cell density and abnormal dendritic arborization of Purkinje cells as revealed from histological evidence. Our study demonstrates superior sensitivity of short-td diffusion using oscillating gradient dMRI to detect cerebellar microstructural changes in Down syndrome, suggesting the potential application of this technique in cerebellar disorders.

Targeting the mitochondrial permeability transition pore for neuroprotection in a piglet model of neonatal hypoxic-ischemic encephalopathy

Neonatal hypoxic-ischemic encephalopathy (HIE) causes significant morbidity despite treatment with therapeutic hypothermia. Mitochondrial dysfunction may drive the mechanisms underlying neuronal cell death, thereby making mitochondria prime targets for neuroprotection. The mitochondrial permeability transition pore (mPTP) is one such target within mitochondria. In adult animal models, mPTP inhibition is neuroprotective. However, evidence for mPTP inhibition in neonatal models of neurologic disease is less certain. We tested the therapeutic efficacy of the mPTP small molecule inhibitor GNX-4728 and examined the developmental presence of brain mPTP proteins for drug targeting in a neonatal piglet model of hypoxic-ischemic brain injury. Male neonatal piglets were randomized to hypoxia-ischemia (HI) or sham procedure with GNX-4728 (15 mg/kg, IV) or vehicle (saline/cyclodextrin/DMSO, IV). GNX-4728 was administered as a single dose within 5 min after resuscitation from bradycardic arrest. Normal, ischemic, and injured neurons were counted in putamen and somatosensory cortex using hematoxylin and eosin staining. In separate neonatal and juvenile pigs, western blots of putamen mitochondrial-enriched fractions were used to evaluate mitochondrial integrity and the presence of mPTP proteins. We found that a single dose of GNX-4728 did not protect putamen and cortical neurons from cell death after HI. However, loss of mitochondrial matrix integrity occurred within 6h after HI, and while mPTP components are present in the neonatal brain their levels were significantly different compared to that of a mature juvenile brain. Thus, the neonatal brain mPTP may not be a good target for current neurotherapeutic drugs that are developed based on adult mitochondria.

Probing neural tissues at small scales: Recent progress of oscillating gradient spin echo (OGSE) neuroimaging in humans

The detection sensitivity of diffusion MRI (dMRI) is dependent on diffusion times. A shorter diffusion time can increase the sensitivity to smaller length scales. However, the conventional dMRI uses the pulse gradient spin echo (PGSE) sequence that probes relatively long diffusion times only. To overcome this, the oscillating gradient spin echo (OGSE) sequence has been developed to probe much shorter diffusion times with hardware limitations on preclinical and clinical MRI systems. The OGSE sequence has been previously used on preclinical animal MRI systems. Recently, several studies have translated the OGSE sequence to humans on clinical MRI systems and achieved new information that is invisible using conventional PGSE sequence. This paper provides an overview of the recent progress of the OGSE neuroimaging in humans, including the technical improvements in the translation of the OGSE sequence to human imaging and various applications in different neurological disorders and stroke. Some possible future directions of the OGSE sequence are also discussed.

Mean Diffusivity in Striatum Correlates With Acute Neuronal Death but Not Lesser Neuronal Injury in a Pilot Study of Neonatal Piglets With Encephalopathy

BACKGROUND

Diffusion MRI is routinely used to evaluate brain injury in neonatal encephalopathy. Although abnormal mean diffusivity (MD) is often attributed to cytotoxic edema, the specific contribution from neuronal pathology is unclear.

PURPOSE

To determine whether MD from high-resolution diffusion tensor imaging (DTI) can detect variable degrees of neuronal degeneration and pathology in piglets with brain injury induced by excitotoxicity or global hypoxia-ischemia (HI) with or without overt infarction.

STUDY TYPE

Prospective.

ANIMAL MODEL

Excitotoxic brain injury was induced in six neonatal piglets by intrastriatal stereotaxic injection of the glutamate receptor agonist quinolinic acid (QA). Three piglets underwent global HI or a sham procedure. Piglets recovered for 20-96 hours before undergoing MRI (n = 9).

FIELD STRENGTH/SEQUENCE

3.0T MRI with DTI, T₁ - and T₂ -weighted imaging.

ASSESSMENT

MD, fractional anisotropy (FA), and qualitative T₂ injury were assessed in the putamen and caudate. The cell bodies of normal neurons, degenerating neurons (excitotoxic necrosis, ischemic necrosis, or necrosis-apoptosis cell death continuum), and injured neurons with equivocal degeneration were counted by histopathology.

STATISTICAL TESTS

Spearman correlations were used to compare MD and FA to normal, degenerating, and injured neurons. T₂ injury and neuron counts were evaluated by descriptive analysis.

RESULTS

The QA insult generated titratable levels of neuronal pathology. In QA, HI, and sham piglets, lower MD correlated with higher ratios of degenerating-to-total neurons (P < 0.05), lower ratios of normal-to-total neurons (P < 0.05), and greater numbers of degenerating neurons (P < 0.05). MD did not correlate with abnormal neurons exhibiting nascent injury (P > 0.99). Neuron counts were not related to FA (P > 0.30) or to qualitative injury from T₂ -weighted MRI.

DATA CONCLUSION

MD is more accurate than FA for detecting neuronal degeneration and loss during acute recovery from neonatal excitotoxic and HI brain injury. MD does not reliably detect nonfulminant, nascent, and potentially reversible neuronal injury.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2020;52:1216-1226.

The Johns Hopkins Neurosciences Intensive Care Nursery Tenth Anniversary (2009-2019): A Historical Reflection and Vision for the Future

Since 2009, the Neurosciences Intensive Care Nursery at Johns Hopkins Children’s Center has provided a multidisciplinary approach toward the care of newborns with neurological disorders. The program’s cornerstone is an interdisciplinary approach that involves the primary neonatology team plus experts from more than 10 specialties who convene at a weekly team conference at which newborns with neurological problems are discussed in detail. This interdisciplinary approach fosters in-depth discussion of clinical issues to optimize the management of neonates with neurological problems as well as the opportunity to generate research ideas and provide education about neonatal neuroscience at all levels (faculty, nurses, and trainees). The purpose of this article is to provide a 10-year reflection of our Neurosciences Intensive Care Nursery with a view toward expanding efforts in the 3 areas of our mission: clinical care, research, and education. We hope that our experience will enhance the spread of neonatal neuroscience education, care, and research as widely as possible.

Neonatal Hypoxic-Ischemic Encephalopathy Yields Permanent Deficits in Learning Acquisition: A Preclinical Touchscreen Assessment

Neonatal hypoxic-ischemic encephalopathy (HIE) remains a common problem world-wide for infants born at term. The impact of HIE on long-term outcomes, especially into adulthood, is not well-described. To facilitate identification of biobehavioral biomarkers utilizing a translational platform, we sought to investigate the impact of HIE on executive function and cognitive outcomes into adulthood utilizing a murine model of HIE. HIE mice (unilateral common carotid artery occlusion to induce ischemia, followed by hypoxia with a FiO₂ of 0.08 for 45 min) and control mice were tested on discrimination and reversal touchscreen tasks (using their noses) shown to be sensitive to loss of basal ganglia or cortical function, respectively. We hypothesized that the HIE injury would result in deficits in reversal learning, revealing complex cognitive and executive functioning impairments. Following HIE, mice had a mild discrimination impairment as measured by incorrect responses but were able to learn the paradigm to similar levels as controls. During reversal, HIE mice required significantly more total trials, errors and correction trials across the paradigm. Analysis of specific stages showed that reversal impairments in HIE were driven by significant increases in all measured parameters during the late learning, striatal-mediated portion of the task. Together, these results support the concept that HIE occurring during the neonatal period results in abnormal neurodevelopment that persists into adulthood, which can impact efficient associated learning. Further, these data show that utilization of an established model of HIE coupled with touchscreen learning provides valuable information for screening therapeutic interventions that could mitigate these deficits to improve the long-term outcomes of this vulnerable population.

Neonatal Brain Injury and Genetic Causes of Adult-Onset Neurodegenerative Disease in Mice Interact With Effects on Acute and Late Outcomes

Neonatal brain damage and age-related neurodegenerative disease share many common mechanisms of injury involving mitochondriopathy, oxidative stress, excitotoxicity, inflammation, and neuronal cell death. We hypothesized that genes causing adult-onset neurodegeneration can influence acute outcome after CNS injury at immaturity and on the subsequent development of chronic disability after early-life brain injury. In two different transgenic (Tg) mouse models of adult-onset neurodegenerative disease, a human A53T-α-synuclein (hαSyn) model of Parkinson's disease (PD) and a human G93A-superoxide dismutase-1(hSOD1) model of amyotrophic lateral sclerosis (ALS), mortality and survivor morbidity were significantly greater than non-Tg mice and a Tg mouse model of Alzheimer's disease after neonatal traumatic brain injury (TBI). Acutely after brain injury, hαSyn neonatal mice showed a marked enhancement of protein oxidative damage in forebrain, brain regional mitochondrial oxidative metabolism, and mitochondriopathy. Extreme protein oxidative damage was also observed in neonatal mutant SOD1 mice after TBI. At 1 month of age, neuropathology in forebrain, midbrain, and brainstem of hαSyn mice with neonatal TBI was greater compared to sham hαSyn mice. Surviving hαSyn mice with TBI showed increased hαSyn aggregation and nitration and developed adult-onset disease months sooner and died earlier than non-injured hαSyn mice. Surviving hSOD1 mice with TBI also developed adult-onset disease and died sooner than non-injured hSOD1 mice. We conclude that mutant genes causing PD and ALS in humans have significant impact on mortality and morbidity after early-life brain injury and on age-related disease onset and proteinopathy in mice. This study provides novel insight into genetic determinants of poor outcomes after acute injury to the neonatal brain and how early-life brain injury can influence adult-onset neurodegenerative disease during aging.