Can the colors of your brain identify your impairment after stroke?

As a physiotherapist, you were taught to screen, evaluate and re-evaluate your patients functions after stroke. This provides you with information about the symptoms caused by the stroke. Additionally, you make up a rehabilitation plan based on this information. However, little information tells you about the cause of the symptoms, why somebody shows certain disabilities but also if your rehabilitation plan will have an effect and how long you should keep implementing the same technique. All these questions cause uncertainties about the future possibilities of your patient. But what if we could provide more information which could decrease these uncertainties and could result in a better understanding and planning of your rehabilitation planning. 

Diffusion MRI (Magnetic Resonance Imaging)

Currently, conventional MRI is used to detect lesion locations. However, lesion location does not provide us with information about white matter integrity. The white matter pathways can be visualised via diffusion MRI, and more specifically multi-tissue constrained spherical deconvolution. This technique could provide possible useful information regarding the potential and course of recovery. The lack of information about the recovery results in uncertainties regarding selection of rehabilitation techniques and their period of application.

Fig. 1: Multi-shell Multi-tissue constrained spherical deconvolution (CSD) with white matter fibre orientation distribution function (fODF)

How does diffusion MRI work?

Diffusion MRI measures the movement of protons in water molecules. Diffusion properties are determined alongside multiple axes. This multi-directional shape is used to create an anisotropy map whereby the darkness of regions is dependent of their anisotropic value. During ischemia, sodium-potassium pumps shut down resulting in intracellular sodium accumulations. Due to osmotic gradient, water transfers from extra- to intracellular resulting in a bright signal on diffusion weighted images. Because of this, dMRI increases the sensitivity to 88%-100% and specificity to 95%-100% for the accuracy of diagnosis of acute cerebral ischemic changes. 1-3

The colors visualized during dMRI are dependent on orientation due to motion sensitization. Green tracts represent an antero-posterior predominant direction of the fibers, red/pink tracts represent a latero-lateral predominant direction and blue tracts represent an inferior-superior predominant direction of the fibers. By identifying the predominant direction of each tract, identification of pathways can be visualized more accurately during pathway crossing by using constrained spherical deconvolution (CSD).1,4

How can we use diffusion MRI in Stroke Rehabilitation?

White matter tract injury is a direct result of stroke or an indirect result due to Wallerian Degeneration, the accompanied degeneration of axons distal to the injury and their surrounding myelin. Via diffusion MRI, relevant information regarding white matter integrity can be visualized. One of the most investigated tracts is the corticospinal tract (CST). The CST derives from the frontoparietal cortices and travels down to innervate distal extremities and muscle groups in order to provide voluntary motor functions.8-9

​Previous literature has already came to the consensus that integrity measures of the CST strongly correlate with upper limb motor recovery after stroke. However, no clear consensus is defined when correlated to lower limb motor recovery after stroke. In addition, for the lower limb, several studies suggest that integrity of the CST itself is insufficient to predict lower limb motor function. Therefore, more studies are investigating the CST in combination with other areas or tracts (e.g.; primary motor cortex, somatosensory cortex, corticoreticular pathway, dorsolateral prefrontal cortex) in order to get a complete image of all structures associated with lower limb motor recovery.10–13  A first step is to determine associations between different brain tracts and regions and lower limb motor function. If associations are valid, predictive biomarkers can be identified to form a robust way to predict patients recovery potential of lower limb function.11,12,14 This will result in a better understanding of a patients course of recovery, which will aid in drawing up a personalized rehabilitation plan.


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6.              Puig J, Pedraza S, Blasco G, et al. Wallerian Degeneration in the Corticospinal Tract Evaluated by Diffusion Tensor Imaging Correlates with Motor Deficit 30 Days after Middle Cerebral Artery Ischemic Stroke. doi:10.3174/ajnr.A2038

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10.           Choi KT, Kwak SG, Chang MC. Does injury of the thalamocortical connection between the mediodorsal nucleus of the thalamus and the dorsolateral prefrontal cortex affect motor recovery after cerebral infarct? Acta Neurol Belg. 2021;121(4):921-926. doi:10.1007/S13760-020-01309-2

11.           Jun S, Hong B, Kim Y, Lim S. Does Motor Tract Integrity at 1 Month Predict Gait and Balance Outcomes at 6 Months in Stroke Patients? Brain Sci. 2021;11(7). doi:10.3390/BRAINSCI11070867

12.           Soulard J, Huber C, Baillieul S, et al. Motor tract integrity predicts walking recovery: A diffusion MRI study in subacute stroke. Neurology. 2020;94(6):e583-e593. doi:10.1212/WNL.0000000000008755

13.           Peters DM, Fridriksson J, Stewart JC, et al. Cortical Disconnection of the Ipsilesional Primary Motor Cortex is Associated With Gait Speed and Upper Extremity Motor Impairment in Chronic Left Hemispheric Stroke. Human Brain Mapping. 2018;39(1):120-132. doi:10.1002/hbm.23829

14.           Zolkefley MKI, Firwana YMS, Hatta HZM, et al. An overview of fractional anisotropy as a reliable quantitative measurement for the corticospinal tract (CST) integrity in correlation with a Fugl-Meyer assessment in stroke rehabilitation. J Phys Ther Sci. 2021;33(1):75-83. doi:10.1589/jpts.33.75

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17.           Christiaens D, Reisert M, Dhollander T, Sunaert S, Suetens P, Maes F. Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model. Neuroimage. 2015;123:89-101. doi:10.1016/J.NEUROIMAGE.2015.08.008

 Amber van Hinsberg

PhD student (Research Group MOVANT, Department of Rehabilitation Sciences and Physiotherapy (REVAKI), University of Antwerp)

2021 MOVANTresearch