Abnormalities in cardiac-induced brain tissue deformations are now detectable with MRI: A case-report of a patient who underwent craniotomy after trauma.

BACKGROUND: Heartbeat and respiration induce cyclic brain tissue deformations, which receive increasing attention as potential driving force for brain clearance. These deformations can now be assessed using a novel 3D strain tensor imaging (STI) method at 7 T MRI. METHODS: An 18-year-old man had suffered a traumatic brain injury and was treated with a craniotomy with a maximal diameter of 12 cm. STI was employed to capture cardiac-induced brain tissue deformations and additional time-resolved 2D flow measurements were acquired to capture cerebrospinal fluid (CSF) flow towards the spinal canal. RESULTS: The craniotomy caused major changes in all aspects of the brain's mechanical dynamics as compared to healthy volunteer references. Tissue strains increased, particularly around the craniotomy, and directionality of deformations showed large abnormalities, also in the contralateral hemisphere. As the brain tissue could pulsate outward from the skull, physiological pulsatile CSF flow at the foramen magnum was abolished. CONCLUSIONS: This work illustrates how STI can assess physiological patterns of brain tissue deformation and how craniotomy leads to widespread deformation abnormalities that can be detected at a single patient level. While this case is meant to provide proof of concept, application of STI in other conditions of abnormal brain mechanical dynamics warrants further study.

Dynamic brain ADC variations over the cardiac cycle and their relation to tissue strain assessed with DENSE at high-field MRI.

PURPOSE: The ADC of brain tissue slightly varies over the cardiac cycle. This variation could reflect physiology, including mixing of the interstitial fluid, relevant for brain waste clearance. However, it is known from cardiac diffusion imaging that tissue deformation by itself affects the magnitude of the MRI signal, leading to artificial ADC variations as well. This study investigates to what extent tissue deformation causes artificial ADC variations in the brain. THEORY AND METHODS: We implemented a high-field MRI sequence with stimulated echo acquisition mode that simultaneously measures brain tissue deformation and ADC. Based on the measured tissue deformation, we simulated the artificial ADC variation by combining established theoretical frameworks and compared the results with the measured ADC variation. We acquired data in 8 healthy volunteers with diffusion weighting b = 300 and b = 1000 s/mm2 . RESULTS: Apparent diffusion coefficient variation was largest in the feet-to-head direction and showed the largest deviation from the mean ADC at peak systole. Artificial ADC variation estimated from tissue deformation was 1.3 ± 0.37·10-5  mm2 /s in the feet-to-head direction for gray matter, and 0.75 ± 0.29·10-5  mm2 /s for white matter. The measured ADC variation in the feet-to-head direction was 5.6·10-5 ± 1.5·10-5  mm2 /s for gray matter and 3.2·10-5 ± 1.0·10-5  mm2 /s for white matter, which was a factor of 3.5 ± 0.82 and 3.4 ± 0.57 larger than the artificial diffusion variations. The measured diffusion variations in the right-to-left/anterior-to-posterior direction were a factor of 1.5 ± 1.0/1.7 ± 1.4 and 2.0 ± 0.91/2.5 ± 0.94 larger than the artificial diffusion variations for gray matter and white matter, respectively. CONCLUSION: Apparent diffusion coefficient variations in the brain likely largely reflect physiology.

Strain Tensor Imaging: Cardiac-induced brain tissue deformation in humans quantified with high-field MRI.

The cardiac cycle induces blood volume pulsations in the cerebral microvasculature that cause subtle deformation of the surrounding tissue. These tissue deformations are highly relevant as a potential source of information on the brain's microvasculature as well as of tissue condition. Besides, cyclic brain tissue deformations may be a driving force in clearance of brain waste products. We have developed a high-field magnetic resonance imaging (MRI) technique to capture these tissue deformations with full brain coverage and sufficient signal-to-noise to derive the cardiac-induced strain tensor on a voxel by voxel basis, that could not be assessed non-invasively before. We acquired the strain tensor with 3 mm isotropic resolution in 9 subjects with repeated measurements for 8 subjects. The strain tensor yielded both positive and negative eigenvalues (principle strains), reflecting the Poison effect in tissue. The principle strain associated with expansion followed the known funnel shaped brain motion pattern pointing towards the foramen magnum. Furthermore, we evaluate two scalar quantities from the strain tensor: the volumetric strain and octahedral shear strain. These quantities showed consistent patterns between subjects, and yielded repeatable results: the peak systolic volumetric strain (relative to end-diastolic strain) was 4.19⋅10-4 ± 0.78⋅10-4 and 3.98⋅10-4 ± 0.44⋅10-4 (mean ± standard deviation for first and second measurement, respectively), and the peak octahedral shear strain was 2.16⋅10-3 ± 0.31⋅10-3 and 2.31⋅10-3 ± 0.38⋅10-3, for the first and second measurement, respectively. The volumetric strain was typically highest in the cortex and lowest in the periventricular white matter, while anisotropy was highest in the subcortical white matter and basal ganglia. This technique thus reveals new, regional information on the brain's cardiac-induced deformation characteristics, and has the potential to advance our understanding of the role of microvascular pulsations in health and disease.

Cardiac and respiration-induced brain deformations in humans quantified with high-field MRI.

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain's waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3mm isotropic spatial resolution. Heartbeat and respiration-induced volumetric strain were significantly different from zero in the basal ganglia (median (25-75% interquartile range): 0.85·10-3 (0.39·10-3-1.05·10-3), p â€‹= â€‹0.0008 and -0.28·10-3 (-0.41·10-3-0.06·10-3), p â€‹= â€‹0.047, respectively. Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10-3 (0-0.59·10-3) and -0.06·10-3 (-0.17·10-3-0.20·10-3)), which was only significant for the heartbeat (p â€‹= â€‹0.02 and p â€‹= â€‹0.7, respectively). Furthermore, heartbeat-induced volumetric strain was about three times larger than respiration-induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system.