Evolution of Magnetic Resonance Imaging as Predictors and Correlates of Functional Outcome after Spinal Cord Contusion Injury in the Rat.

Clinical methods for determining the severity of traumatic spinal cord injury (SCI) and long-term functional outcome in the acute setting are limited in their prognostic accuracy because of the heterogeneity of injury and dynamic injury progression. The aim of this study was to evaluate the time course and sensitivity of advanced magnetic resonance imaging (MRI) methods to neurological function after SCI in a rat contusion model. Rats received a graded contusion injury at T10 using a weight-drop apparatus. MRI consisted of morphological measures from T2-weighted imaging, quantitative T2 imaging, and diffusion-weighted imaging (DWI) at 1, 30, and 90 days post-injury (dpi). The derived metrics were compared with neurological function assessed using weekly Basso, Beattie, and Bresnahan (BBB) locomotor scoring and return of reflexive micturition function. At the acute time point (1 dpi), diffusion metrics sensitive to axonal injury at the injury epicenter had the strongest correlation with time-matched BBB scores and best predicted 90-dpi BBB scores. At 30 dpi, axonal water fraction derived from DWI and T2 values were both correlated with time-matched locomotor scores. At the chronic time point (90 dpi), cross-sectional area was most closely correlated to BBB. Overall, the results demonstrate differential sensitivity of MRI metrics at different time points after injury, but the metrics follow the expected pathology of acute axonal injury followed by continued degeneration and finally a terminal level of atrophy. Specificity of DWI in the acute setting may make it impactful as a prognostic tool while T2 imaging provided the most information about injury severity in chronic injury.

Longitudinal In Vivo Diffusion Magnetic Resonance Imaging Remote from the Lesion Site in Rat Spinal Cord Injury.

Diffusion tensor imaging (DTI) has demonstrated success as a biomarker of spinal cord injury (SCI) severity as shown from numerous pre-clinical studies. However, artifacts from stabilization hardware at the lesion have precluded its use for longitudinal assessments. Previous research has documented ex vivo diffusion changes in the spinal cord both caudal and cranial to the injury epicenter. The aim of this study was to use a rat contusion model of SCI to evaluate the utility of in vivo cervical DTI after a thoracic injury. Forty Sprague-Dawley rats underwent a thoracic contusion (T8) of mild, moderate, severe, or sham severity. Magnetic resonance imaging (MRI) of the cervical cord was performed at 2, 30, and 90 days post-injury, and locomotor performance was assessed weekly using the Basso, Bresnahan, and Beattie (BBB) scoring scale. The relationships between BBB scores and MRI were assessed using region of interest analysis and voxel-wise linear regression of DTI, and free water elimination (FWE) modeling to reduce partial volume effects. At 90 days, axial diffusivity (ADFWE), mean diffusivity (MDFWE), and free water fraction (FWFFWE) using the FWE model were found to be significantly correlated with BBB score. FWE was found to be more predictive of injury severity than conventional DTI, specifically at later time-points. This study validated the use of FWE technique in spinal cord and demonstrated its sensitivity to injury remotely.

Filter-probe diffusion imaging improves spinal cord injury outcome prediction.

OBJECTIVE: Diffusion-weighted imaging (DWI) is a powerful tool for investigating spinal cord injury (SCI), but has limited specificity for axonal damage, which is the most predictive feature of long-term functional outcome. In this study, a technique designed to detect acute axonal injury, filter-probe double diffusion encoding (FP-DDE), is compared with standard DWI for predicting long-term functional and cellular outcomes. METHODS: This study extends FP-DDE to predict long-term functional and histological outcomes in a rat SCI model of varying severities (n = 58). Using a 9.4T magnetic resonance imaging (MRI) system, a whole-cord FP-DDE spectroscopic voxel was acquired in 3 minutes at the lesion site and compared to DWI at 48 hours postinjury. Relationships with chronic (30-day) locomotor and histological outcomes were evaluated with linear regression. RESULTS: The FP-DDE measure of parallel diffusivity (ADC|| ) was significantly related to chronic hind limb locomotor functional outcome (R2 = 0.63, p < 0.0001), and combining this measurement with acute functional scores demonstrated prognostic benefit versus functional testing alone (p = 0.0007). Acute ADC|| measurements were also more closely related to the number of injured axons measured 30 days after the injury than standard DWI. Furthermore, acute FP-DDE images showed a clear and easily interpretable pattern of injury that closely corresponded with chronic MRI and histology observations. INTERPRETATION: Collectively, these results demonstrate FP-DDE benefits from greater specificity for acute axonal damage in predicting functional and histological outcomes with rapid acquisition and fully automated analysis, improving over standard DWI. FP-DDE is a promising technique compatible with clinical settings, with potential research and clinical applications for evaluation of spinal cord pathology. Ann Neurol 2018;83:37-50.

Diffusion MRI in acute nervous system injury.

Diffusion weighted magnetic resonance imaging (DWI) and related techniques such as diffusion tensor imaging (DTI) are uniquely sensitive to the microstructure of the brain and spinal cord. In the acute aftermath of nervous system injury, for example, DWI reveals changes caused by injury that remains invisible on other MRI contrasts such as T2-weighted imaging. This ability has led to a demonstrated clinical utility in cerebral ischemia. However, despite strong promise in preclinical models and research settings, DWI has not been as readily adopted for other acute injuries such as traumatic spinal cord, brain, or peripheral nerve injury. Furthermore, the precise biophysical mechanisms that underlie DWI and DTI changes are not fully understood. In this report, we review the DWI and DTI changes that occur in acute neurological injury of cerebral ischemia, spinal cord injury, traumatic brain injury, and peripheral nerve injury. Their associations with the underlying biology are examined with an emphasis on the role of acute axon and dendrite beading. Lastly, emerging DWI techniques to overcome the limitations of DTI are discussed as these may offer the needed improvements to translate to clinical settings.

Rapid in vivo detection of rat spinal cord injury with double-diffusion-encoded magnetic resonance spectroscopy.

PURPOSE: Diffusion-weighted imaging is a common experimental tool for evaluating spinal cord injury (SCI), yet it suffers from complications that decrease its clinical effectiveness. The most commonly used technique, diffusion tensor imaging (DTI), is often confounded by effects of edema accompanying acute SCI, limiting its sensitivity to the important functional status marker of axonal integrity. The purpose of this study is to introduce a novel diffusion-acquisition method with the goal of overcoming these limitations. METHODS: A double diffusion encoding (DDE) pulse sequence was implemented with a diffusion-weighted filter orthogonal to the spinal cord for suppressing nonneural signals prior to diffusion weighting parallel to the cord. A point-resolved spectroscopy readout (DDE-PRESS) was used for improved sensitivity and compared with DTI in a rat model of SCI with varying injury severities. RESULTS: The DDE-PRESS parameter, restricted fraction, showed a strong relationship with injury severity (P < 0.001, R2 = 0.67). Although the whole-cord averaged DTI parameter values exhibited only minor injury relationships, a weighted region of interest (ROI) based DTI analysis improved sensitivity to injury (P < 0.001, R2 = 0.66). CONCLUSIONS: In a rat model of SCI, DDE-PRESS demonstrated high sensitivity to injury with substantial decreases in acquisition time and data processing. This method shows promise for application in rapid evaluation of SCI severity. Magn Reson Med 77:1639-1649, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation.

Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the results and optimizations describe a protocol that mitigates several difficulties with DTI of the spinal cord. Detection of acute axonal damage in the injured or diseased spinal cord will benefit the optimized filter-probe diffusion MRI protocol outlined here.

Detection of acute nervous system injury with advanced diffusion-weighted MRI: a simulation and sensitivity analysis.

Diffusion-weighted imaging (DWI) is a powerful tool to investigate the microscopic structure of the central nervous system (CNS). Diffusion tensor imaging (DTI), a common model of the DWI signal, has a demonstrated sensitivity to detect microscopic changes as a result of injury or disease. However, DTI and other similar models have inherent limitations that reduce their specificity for certain pathological features, particularly in tissues with complex fiber arrangements. Methods such as double pulsed field gradient (dPFG) and q-vector magic angle spinning (qMAS) have been proposed to specifically probe the underlying microscopic anisotropy without interference from the macroscopic tissue organization. This is particularly important for the study of acute injury, where abrupt changes in the microscopic morphology of axons and dendrites manifest as focal enlargements known as beading. The purpose of this work was to assess the relative sensitivity of DWI measures to beading in the context of macroscopic fiber organization and edema. Computational simulations of DWI experiments in normal and beaded axons demonstrated that, although DWI models can be highly specific for the simulated pathologies of beading and volume fraction changes in coherent fiber pathways, their sensitivity to a single idealized pathology is considerably reduced in crossing and dispersed fibers. However, dPFG and qMAS have a high sensitivity for beading, even in complex fiber tracts. Moreover, in tissues with coherent arrangements, such as the spinal cord or nerve fibers in which tract orientation is known a priori, a specific dPFG sequence variant decreases the effects of edema and improves specificity for beading. Collectively, the simulation results demonstrate that advanced DWI methods, particularly those which sample diffusion along multiple directions within a single acquisition, have improved sensitivity to acute axonal injury over conventional DTI metrics and hold promise for more informative clinical diagnostic use in CNS injury evaluation.

Information content in fluorescence correlation spectroscopy: binary mixtures and detection volume distortion.

When properly implemented, fluorescence correlation spectroscopy (FCS) reveals numerous static and dynamic properties of molecules in solution. However, complications arise whenever the measurement scenario is complex. Specific limitations occur when the detection region does not match the ideal Gaussian geometry ubiquitously assumed by FCS theory, or when properties of multiple fluorescent species are assessed simultaneously. A simple binary solution of diffusers, where both mole fraction and diffusion constants are sought, can face interpretive difficulty. In order to better understand the limits of FCS, this study systematically explores the relationship between detection-volume distortion, diffusion constants, species mole fraction, and fitting methodology in analyses that utilize a two-component autocorrelation model. FCS measurements from solution mixtures of dye-labeled protein and free dye are compared to simulations, which predict the performance of FCS under a variety of experimental circumstances. The results reveal a range of conditions necessary for performing accurate measurements and describe experimental scenarios that should be avoided. The findings also provide guidelines for obtaining meaningful measurements when grossly distorted detection volumes are utilized and generally assess the latent information contained in FCS datasets.