The overall goal of this procedure is to obtain quantitative microstructural information of the hippocampus in a rat with mild traumatic brain injury. This is done using an advanced diffusion-weighted magnetic resonance imaging protocol and region-of-interest based analysis of parametric diffusion maps.
Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous variability and heterogeneity (age, gender, type of trauma, other possible pathologies, etc.), animal models play a key role in unraveling factors that are limitations in clinical research. They provide a standardized and controlled setting to investigate the biological mechanisms of injury and repair following TBI. However, not all animal models mimic the diffuse and subtle nature of mTBI effectively. For example, the commonly used controlled cortical impact (CCI) and lateral fluid percussion injury (LFPI) models make use of a craniotomy to expose the brain and induce widespread focal trauma, which are not commonly seen in mTBI. Therefore, these experimental models are not valid to mimic mTBI. Thus, an appropriate model should be used to investigate mTBI. The Marmarou weight drop model for rats induces similar microstructural alterations and cognitive impairments as seen in patients who sustain mild trauma; therefore, this model was selected for this protocol. Conventional computed tomography and magnetic resonance imaging (MRI) scans commonly show no damage following a mild injury, because mTBI induces often only subtle and diffuse injuries. With diffusion weighted MRI, it is possible to investigate microstructural properties of brain tissue, which can provide more insight into the microscopic alterations following mild trauma. Therefore, the goal of this study is to obtain quantitative information of a selected region-of-interest (i.e., hippocampus) to follow up disease progression after obtaining a mild and diffuse brain injury.
Traumatic brain injury (TBI) has gained more attention in recent years, as it has become clear that these brain injuries can result in lifelong cognitive, physical, emotional, and social consequences1. Despite this increasing awareness, mild TBI (mTBI, or concussion) is still often underreported and undiagnosed. MTBI has been referred to as a silent epidemic, and individuals with a history of mTBI show higher rates of substance abuse or psychiatric problems2. Several patients with mTBI go undiagnosed every year due to the diffuse and subtle nature of the injuries, which are often not visible on conventional computed tomography (CT) or magnetic resonance imaging (MRI) scans. This lack of radiological evidence of brain injury has led to the development of more advanced imaging techniques such as diffusion MRI, which are more sensitive to microstructural changes3.
Diffusion MRI allows in vivo mapping of the microstructure, and this MRI technique has been used extensively in TBI studies4,5,6. From the diffusion tensor, fractional anisotropy (FA) and mean diffusivity (MD) are computed to quantify alteration in the microstructural organization following injury. Recent reviews in mTBI patients report increases in FA and decreases in MD following injury, which can be indicative of axonal swelling7. Contrary, increases in MD and decreases in FA are also found and have been suggested to underlie disruptions in parenchymal structure following edema formation, axonal degeneration, or fiber misalignment/disruption8. These mixed findings can be partially explained by the significant clinical heterogeneity of mTBI caused by different types of impact and severity (e.g., rotation-acceleration, blunt force trauma, blast injury or combination of the former). However, currently there is no clear consensus about the underlying pathology and biological/cellular basis underpinning alterations in the microstructural organization.
Animal models provide a standardized and controlled setting to investigate biological mechanisms of injury and repair following TBI in greater detail. Several experimental models for TBI have been developed and represent different aspects of human TBI (e.g., focal vs. diffuse trauma or trauma caused by rotational forces)9,10. Commonly used animal models include the controlled cortical impact (CCI) and lateral fluid percussion injury (LFPI) models11,12. Although the experimental parameters can be well-controlled, these models make use of a craniotomy to expose the brain. Craniotomies or skull fractures are not commonly seen in mTBI; therefore, these experimental models are not valid to mimic mTBI. The impact acceleration model developed by Marmarou et al.13 makes use of a weight that is dropped from a certain height onto the rat's head, which is protected by a helmet. This animal model induces similar microstructural alterations and cognitive impairments as seen in patients who sustain mild trauma. Therefore, this Marmarou weight drop model is appropriate to investigate imaging biomarkers for diffuse mTBI14,15.
This report demonstrates the application of advanced diffusion MRI in an mTBI rat model using the Marmarou weight drop model. First shown is how to induce a mild and diffuse trauma, and analysis using diffusion tensor imaging (DTI) model is then provided. Specific biological information is obtained with the use of more advanced diffusion models [i.e., diffusion kurtosis imaging (DKI) and white matter tract integrity (WMTI) model]. Specifically, mild trauma is inflicted and microstructural changes are then evaluated in the hippocampus using conventional T2-weighted MRI and an advanced diffusion imaging protocol.
The protocol has been approved by the Animal Ethics Committee at the University of Ghent (ECD 15/44Aanv), and all experiments were conducted in accordance with the guidelines of the European Commission (Directive 2010/63/EU).
1. Animal preparation and helmet attachment
2. Induction of traumatic brain injury (TBI)
3. Diffusion magnetic resonance imaging (MRI)
NOTE: Diffusion-weighted imaging is performed before and 1 day following trauma induction.
4. Image processing
NOTE: In the following sections, the processing of the diffusion images is described in MRtrix3, ExploreDTI19 and Amide software20 which are open access toolboxes. However, the preprocessing steps can be performed in other toolboxes (e.g., FSL, MedInria, DTIStudio).
5. Statistical analysis
NOTE: In the following sections, we describe processing of the diffusion images in SPSS Statistics 24; however, the statistical analysis can be performed in other statistical toolboxes.
In the study, all TBI rats (n = 10) survived the impact and were able to recover from the impact and anesthesia within 15 min after detachment from anesthesia23. On the CT images, there was no evidence of skull fractures and the T2 images did not show any abnormalities such as bleeding, enlarged ventricles, or edema formation at the contusion site 1 day after trauma (Figure 5). Thus, based on these visual inspections of the anatomical images, large focal lesions were not detected, confirming the diffuse and mild nature of the injury.
The quality of the coregistration (non-rigid) step between the T2 image and diffusion data set (step 4.4) was examined by adding an overlay of the T2 image to the color-encoded FA map (Figure 6). Then, the FA, MD, AD, and RD parametric maps were calculated (Figure 1) and loaded into the Amide software. Based on the FA map, a ROI including the hippocampal structure was drawn (Figure 4). Statistical values of the diffusion metrics were calculated averaged over all voxels within the region of interest and the mean values of each DTI metric were exported for further analysis. Another quality check of the diffusion data can be performed by inspecting the outliers in the DTI metrics. For example, FA values in the hippocampus should be around 0.15; therefore, values of <0.10 (denoting isotropic diffusion) or >0.30 (values are seen in white matter) can be regarded as biologically implausible values. These datapoints should be rejected from further analysis. Also, the mean values for AK, RK, and MK of the diffusion kurtosis model as well as the AWF, AxEAD, RadEAD, and TORT of the WMTI model were calculated (Figure 2, Figure 3).
In our study, analysis of the DTI metrics revealed significant increased FA values (p = 0.007), and decreased diffusivity values (MD and RD) (p = 0.007 and p = 0.007, respectively) following impact in the mTBI group (Figure 7). These decreases in RD and MD were significantly different from the sham group (p = 0.005 and p = 0.004, respectively). Diffusion kurtosis metrics showed a significant decrease in RK (p = 0.005) following impact but no changes in AK or MK (Figure 8). Using the WMTI model, RadEAD (p = 0.007) and TORT (p = 0.007) displayed a significant decrease and increase, respectively, in the mTBI group 1 day after the impact (Figure 9C,D). The values in the sham group did not show any significant changes.
Figure 1: Representative parametric maps for fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Please click here to view a larger version of this figure.
Figure 2: Representative parametric maps for mean kurtosis (MK), axial kurtosis (AK), and radial kurtosis (RK). Please click here to view a larger version of this figure.
Figure 3: Representative parametric maps for axonal water fraction (AWF), axial and radial extra axonal diffusivity (AxEAD, RadEAD), and tortuosity (TORT). Please click here to view a larger version of this figure.
Figure 4: Creating a mask in MRtrix3. A ROI is drawn around the hippocampus on all slices containing the volume of the hippocampus, and the volume is saved as a mask file. This can either be done for each rat individually or by using a study specific template mask file to which each of the parametric maps can be co-registered. Please click here to view a larger version of this figure.
Figure 5: CT and T2 weighted images of a representative mTBI animal 1 day after impact. The CT images (top row) do not show any skull fractures. On the T2-weighted images (bottom row) no bleeding, enlarged ventricles, or edema formation were demonstrated. Of note, edema formation is clearly visible as a hyperintense area around the wound area from the surgical intervention. Please click here to view a larger version of this figure.
Figure 6: Color encoded FA map of diffusion data set overlaid with the anatomical image after correction for EPI, motion, and Eddy current correction in ExploreDTI. Shown is a bad correction and co-registration on the left and good examples on the right. It should be ensured that the color encoding is correct: left-right direction in red (e.g., corpus callosum), anterior-posterior direction in green, and inferior-superior direction in blue (e.g., cingulum). Additionally, the color encoded FA image should be perfectly aligned with the anatomical image. Please click here to view a larger version of this figure.
Figure 7: Changes in diffusion tensor metrics of hippocampus for sham (n = 10) and mTBI animals (n = 10). Following impact, there was a significant increase in FA (A) and significant decreases in mean diffusivity (B) and radial diffusivity (D) in the mTBI animals (B,D). No significant differences were observed for axial diffusivity (C) in the mTBI rats. The sham animals did not show any significant DTI changes (*p < 0.0125). Please click here to view a larger version of this figure.
Figure 8: Changes in diffusion kurtosis metrics of hippocampus for sham (n = 10) and mTBI animals (n = 10). Following impact, there was a significant decrease in RK (C) of the mTBI animals but no changes in AK (B) or MK (A). The sham animals did not show any changes (*p < 0.0166). Please click here to view a larger version of this figure.
Figure 9: Changes in white matter tract integrity metrics of hippocampus for sham (n = 10) and mTBI animals (n = 10). Following impact, there was a significant decrease in RadEAD (C) and significant increase in TORT (D) of the mTBI animals but no change in AWF or AxEAD (A,B). The sham animals did not show any changes (*p < 0.0125). Please click here to view a larger version of this figure.
Since mTBI often is the result of a diffuse and subtle injury that shows no abnormalities on CT and conventional MRI scans, the evaluation of microstructural damage after a mild trauma remains a challenge. Therefore, more advanced imaging techniques are needed to visualize the full extent of the trauma. The application of diffusion magnetic resonance imaging in TBI research has gained more interest during the last decade, where diffusion tensor imaging is most frequently used5. A limitation of the DTI model is the assumption of a Gaussian diffusion process that is not a precise assumption for brain microstructure (consisting of a complex network of axons and cells with membranes acting as barriers), resulting in DTI metrics non-specific to the underlying biological microstructure24. Diffusion kurtosis imaging is an extension of the DTI model and attempts to characterize the degree of non-Gaussian diffusion17. This may provide additional information about tissue heterogeneity or complexity.
Though, a drawback of DTI and DKI models is that they are only a representation of the diffusion signal, which characterizes the probabilistic water displacement profile but is not specific to microstructure6. On the other hand, the white matter tract integrity model based on the kurtosis tensor is a microstructural mapping technique that incorporates a priori biological information (assumptions) into the model18. It attributes the diffusion signal to tissue compartments and can assess biological attributes more directly. These biophysical models may thus offer new information for describing abnormalities after mTBI and overcome this non-specificity issue6. Using these three different models, microstructural alterations and biological processes were able to be visualized following mTBI in more detail, specifically by using the Marmarou weight drop model.
The Marmarou weight drop model is easy to use and requires only minor surgery; however, a second experimenter is recommended to move the rat away from the glass tube immediately after the first impact to avoid a second one. Additionally, it is sometimes required to help the rat regain its breathing reflex following the impact. The rather long MRI protocol, with a total acquisition time of around 80 min, is well-tolerated by both the sham and mTBI rats. Though, during scanning, it is important to monitor breathing cycle and adjust the anesthesia if the animal is sleeping too deeply or lightly. It is also important to keep the animal warm both during and after the acquisition until the rat is fully awake to avoid hypothermia.
In advanced diffusion MRI, movement artifacts should be avoided as much as possible. A simple solution to reduce movement during scanning is to make use of a teeth bar and fixate the head with a small piece of tape or two ear bars, if available. This ensures that the head will not move up and down every time the rat takes a breath.
Using advanced diffusion MRI protocols, the acquired images must pass through several (pre-) processing steps, mostly using different software tools, before they can be used for further analysis. A drawback of using different software tools to process the diffusion-weighted images is that (often) each tool uses its own data format to encode the gradient directions table. MRtrix3 stores the gradient information together with the diffusion weighted image in a .mif file, while ExploreDTI makes use of a separate file (B-matrix) to store the gradient directions. Therefore, it is important to check that the gradient directions are correctly transferred from MRtrix3 to ExploreDTI. This can be done by checking that color encoding is correct on color encoded FA images [i.e., left-right direction in red (e.g., corpus callosum), anterior-posterior direction in green, and inferior-superior direction in blue (e.g., cingulum)]. The color encoded FA images can also be used to check the quality of the non-rigid co-registration process between the diffusion-weighted images and structural T2- weighted images.
Using ExploreDTI, parametric maps were extracted using the DTI, DKI, and WMTI models. The DTI model provided parametric maps for MD, AD, RD, and FA, while the DKI model provides parametric maps for MK, AK, and RK. Although four metrics of the WMTI model were calculated (i.e., AWF, AxEAD, RadEAD, TORT), it was not possible to extract intra-axonal diffusivity (IAD) within ExploreDTI. IAD can be obtained using a MATLAB tool provided by the developers of the WMTI model25. To do so, the diffusion-weighted images and gradient information must be transferred again from ExploreDTI into Matlab. This step is again prone to errors concerning the encoding of gradient information. Additionally, the kurtosis tensor and the WMTI parameters must be estimated and calculated again.
Preprocessing of the acquired images, estimation of the tensors, and calculation of the parametric maps requires a long period of computing time. Corrections for EPI, motion, and eddy current required ~40 min per data set on a server with eight cores and 16 GB RAM. Using a ROI analysis, mean values within the hippocampus were calculated before and 1 day after impact. Changes in the DTI, DKI and WMTI metrics were then quantified in the mTBI group. However, in the DKI metrics and AWF of the WMTI model, large inter-subject variability was observed, which resulted in an unexpected difference in baseline values between the sham and mTBI groups. This is most likely the result of voxels containing biologically implausible values (outliers) within the investigated region and may be filtered out in future studies before calculation of the mean values in Amide.
In conclusion, this protocol demonstrates the feasibility of advanced diffusion MRI for investigating and quantifying microstructural alterations in the hippocampus in a rat model of mTBI. Using three different diffusion models, complementary information can be obtained about the underlying biological processes that contribute to the conditions after mTBI. This represents a step forward in the development of biomarkers for mTBI that may be sensitive enough to identify specific microstructural changes in the early phase after mild impact.
The authors have nothing to disclose.
The authors would like to thank Research Foundation – Flanders (FWO) for supporting this work (Grant number: G027815N).
Induction of trauma | |||
0.9% NaCl physiologic solution | B Braun | 394496 | |
brass weight 450g | custom made | custom made | diamter 18mm and 210 mm height |
catheter | Terumo | Versatus-W | 26G |
ethilon II | Ethicon | EH7824 | FS-3, 4-0, 3/8, 16mm |
Matrass | Foam to Size | Type E | |
Plexiglas tube | ISPA Plastics | 416564 | M1 PMMA XT GOO tube 25×19 mm (inner diamter 19 mm, minimal length of 1.50 m) |
Preclinical CT scanner | Molecubes | X-cube | |
Steel helmet | custom made | custom made | diameter 10 mm and 3 mm thickness |
Vetbond Tissue Adhesive | 3M | 1469SB | |
Vetergesic (buprenorphin) | EcuPhar | VETERG20 | 0.05 mk/kg |
Xylocaine 2% gel | AstraZeneca | Xylocaine 2% | gel |
Xylocaine (lidocain 2%) | Aspen/AstraZeneca | Xylocaine 2% gel | 100 μl injection |
Diffusion MRI | |||
Preclinical MRI acquisition software | Bruker Biospin MRI GmbH | Z400_PV51_CENTOS55 | ParaVision 5.1 MRI software |
Preclinical MRI scanner | Bruker Biospin MRI GmbH | PharmaScan 70/16 | 7T MRI scanner |
Quadrature volume coil | Bruker Biospin MRI GmbH | RF RES 300 1H 075/040 QSN TR | Model No: 1P T13161C3 |
Small animal physiological monitoring unit | Rapid Biomedical | EKGHR02-0571-043C01 | Unit for respiratory monitoring |
Water-based heating unit | Thermo Fisher Scientific | Haake S 5P | Model No: 1523051 |
Anaesthesia | |||
Anaesthesia movable unit | Veterenary technics | BDO – Medipass, Ijmuiden | |
isoflurane: Isoflo | Zoetis | B506 | |
Oxygen generator | Veterenary technics | 7F-3 | BDO – Medipass, Ijmuiden |
Diffusion image processing | |||
Amide | http://amide.sourceforge.net | Version 1.0.5. | Medical Imaging Data Examiner Toolbox (Loening AM, Gambhir SS, " AMIDE: A Free Software Tool for Multimodality Medical Image Analysis", Molecular Imaging, 2(3):131-137, 2003) |
ExploreDTI | http://www.exploredti.com | Version 4.8.6 | Toolbox for (pre-)processing and analysis of diffusion weighted MR images (Leemans A, Jeurissen B, Sijbers J, and Jones DK. ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. In: 17th Annual Meeting of Intl Soc Mag Reson Med, p. 3537, Hawaii, USA, 2009) |
MRtrix3 | http://www.mrtrix.org | Version 3.0_RC3-86-g4b523b41 | Toolbox for (pre-)processing and analysis of diffusion weighted MR images |