Connectomic imaging reveals Huntington-related pathological and pharmaceutical effects in a mouse model.

Recent studies suggest that neurodegenerative diseases could affect brain structure and function in disease-specific network patterns; however, how spontaneous activity affects structural covariance network (SC) is not clear. We hypothesized that hyper-excitability in Huntington disease (HD) disrupts the coordinated structural and functional connectivity, and treatment with memantine helps to reduce excitotoxicity and normalize the connectivity. MRI was conducted to measure somatosensory activation, resting-state functional-connectivity (rsFC), SC, amplitude of low frequency fluctuation (ALFF) and ALFF covariance (ALFFC) in the YAC128 mouse model of HD. We found somatosensory activation was unchanged but the subcortical ALFF was increased in HD mice, indicating subcortical but not cortical hyperactivity. The reduced sensorimotor rsFC but spared hippocampal and default mode networks in the HD mice was consistent with the more pronounced impairment in motor function compared with cognitive performance. The disease suppressed SC globally and reduced ALFFC in the basal ganglia network as well as its anti-correlation with the default mode network. By comparing these connectivity measures, we found that the originally coupled rsFC-SC relationship was impaired whereas SC-ALFFC correlation was increased by HD, suggesting disease facilitated covariation of brain volume and activity amplitude but not neural synchrony. The comparison with mono-synaptic axonal projection supports the hypothesis that rsFC, but not SC or ALFFC, is highly dependent on structural connectivity under healthy conditions. Treatment with memantine had a strong effect on normalizing the SC and reducing ALFF while slightly increasing other connectivity measures and restoring the rsFC-SC coupling, which is consistent with its effect on alleviating hyper-excitability and improving the coordinated neural growth. These results indicate that HD affects the cerebral structure-function relationship which could be partially reverted by NMDA antagonism. These connectivity measures provide unique insights into pathological and pharmaceutical effects in brain circuitry, and could be translatable biomarkers for evaluating drug effect and refining its efficacy.

Quantification of the human cerebrovasculature: a 7Tesla and 320-row CT in vivo study.

OBJECTIVE: Human cerebrovasculature has not been quantified in volume, length, and vascular-brain relationships. We investigated this using imaging. METHODS: From 0.5-mm 7T and 320-row CT acquisitions, 6 arterial and 4 venous systems were reconstructed, measured, and analyzed. RESULTS: The ratio of the volume of arterial to venous system is approximately 1:3. The ratio of the volume of dural sinuses to vasculature is 1:2. The ratio of the posterior (PCA) to anterior (ACA) to middle cerebral artery (MCA) is 1:2:4 in volume and length. Ratios of left to right vessels are 1:1 for arteries and veins. Ratios of branching frequency for the ACA, MCA, and PCA are 1:1:1. The branching frequency ratio for superficial to deep veins is 1:2. The MCA occupies 1/2 of arterial length and 1/4 of vascular length. The ratio of the length of superficial to deep veins is 1:1 and each is equal to 1/4 of the vascular length. The ratio of cerebrovasculature to brain volume is 2.5%. CONCLUSIONS: Despite its enormous complexity, cerebrovasculature is characterized by 4 approximate proportions, 1:1, 1:2, 1:3, 1:4, and their combinations, 1:1:1 and 1:2:4.

Ventricle Boundary in CT: Partial Volume Effect and Local Thresholds.

We present a mathematical frame to carry out segmentation of cerebrospinal fluid (CSF) of ventricular region in computed tomography (CT) images in the presence of partial volume effect (PVE). First, the image histogram is fitted using the Gaussian mixture model (GMM). Analyzing the GMM, we find global threshold based on parameters of distributions for CSF, and for the combined white and grey matter (WGM). The parameters of distribution of PVE pixels on the boundary of ventricles are estimated by using a convolution operator. These parameters are used to calculate local thresholds for boundary pixels by the analysis of contribution of the neighbor pixels intensities into a PVE pixel. The method works even in the case of an almost unimodal histogram; it can be useful to analyze the parameters of PVE in the ground truth provided by the expert.

Simulation and assessment of cerebrovascular damage in deep brain stimulation using a stereotactic atlas of vasculature and structure derived from multiple 3- and 7-tesla scans.

OBJECT: The most severe complication of deep brain stimulation (DBS) is intracranial hemorrhage. Detailed knowledge of the cerebrovasculature could reduce the rate of this disorder. Morphological scans typically acquired in stereotactic and functional neurosurgery (SFN) by using 1.5-T (or sometimes even 3-T) imaging units poorly depict the vasculature. Advanced angiographic imaging, including 3- and 7-T 3D time-of-flight and susceptibility weighted imaging as well as 320-slice CT angiography, depict the vessels in great detail. However, these acquisitions are not used in SFN clinical practice, and robust methods for their processing are not available yet. Therefore, the authors proposed the use of a detailed 3D stereotactic cerebrovascular atlas to assist in SFN planning and to potentially reduce DBS-induced hemorrhage. METHODS: A very detailed 3D cerebrovascular atlas of arteries, veins, and dural sinuses was constructed from multiple 3- and 7-T scans. The atlas contained>900 vessels, each labeled with a name and diameter with the smallest having a 90-µm diameter. The cortical areas, ventricular system, and subcortical structures were fully segmented and labeled, including the main stereotactic target structures: subthalamic nucleus, ventral intermediate nucleus of the thalamus, and internal globus pallidus. The authors also developed a computer simulator with the embedded atlas that was able to compute the effective electrode trajectory by minimizing penetration of the cerebrovascular system and vital brain structures by a DBS electrode. The simulator provides the neurosurgeon with functions for atlas manipulation, target selection, trajectory planning and editing, 3D display and manipulation, and electrode-brain penetration calculation. RESULTS: This simulation demonstrated that a DBS electrode inserted in the middle frontal gyrus may intersect several arteries and veins including 1) the anteromedial frontal artery of the anterior cerebral artery as well as the prefrontal artery and the precentral sulcus artery of the middle cerebral artery (range of diameters 0.4-0.6 mm); and 2) the prefrontal, anterior caudate, and medullary veins (range of diameters 0.1-2.3 mm). This work also shows that field strength and pulse sequence have a substantial impact on vessel depiction. The numbers of 3D vascular segments are 215, 363, and 907 for 1.5-, 3-, and 7-T scans, respectively. CONCLUSIONS: Inserting devices into the brain during microrecording and stimulation may cause microbleeds not discernible on standard scans. A small change in the location of the DBS electrode can result in a major change for the patient. The described simulation increases the neurosurgeon's awareness of this phenomenon. The simulator enables the neurosurgeon to analyze the spatial relationships between the track and the cerebrovasculature, ventricles, subcortical structures, and cortical areas, which allows the DBS electrode to be placed more effectively, and thus potentially reducing the invasiveness of the stimulation procedure for the patient.

A three-dimensional interactive atlas of cerebral arterial variants.

The knowledge of cerebrovascular variants is essential in education, training, diagnosis and treatment. The current way of presentation of vasculature and, particularly, vascular variants is insufficient. Our purpose is to construct a three-dimensional (3D) interactive atlas of cerebral arterial variants along with exploration tools allowing the investigator just with a few clicks to better and faster understand the variants and their spatial relationships. A 3D model of the cerebral arterial system created earlier, fully labeled with names and diameters, is used as a reference. As the vast material about vascular variability is incomplete and not fully documented, our approach synthesizes variants in 3D based on existing knowledge. The variants are created from literature using a dedicated vascular editor and embedded into the reference model. Sixty 3D variants and branching patterns are created including the internal carotid, middle cerebral, anterior cerebral, posterior cerebral, vertebral and basilar arteries, and circle of Willis. Their prevalence rates are given. The atlas is developed to explore the variants individually or embedded into the reference vasculature. Real-time interactive manipulation of variants and reference vasculature (rotate/zoom/pan/view) is provided. This atlas facilitates the investigator to easily get familiarized with the variants and rapidly explore them. It aids in presentation of vascular variants and understanding their spatial relationships either individually or embedded into the surrounding reference cerebrovasculature. It is useful for medical students, educators to prepare teaching materials, and clinicians for scan interpretation. It is easily extensible with additional variant instances, new variants, branching patterns, and supporting textual materials.

Robust calculation of the midsagittal plane in CT scans using the Kullback-Leibler's measure.

OBJECTIVE: The identification of the interhemispheric fissure (IF) is important in clinical applications for brain landmark identification, registration, symmetry assessment, and pathology detection. The IF is usually approximated by the midsagittal plane (MSP) separating the brain into two hemispheres. We present a fast accurate, automatic, and robust algorithm for finding the MSP for CT scans acquired in emergency room (ER) with a large slice thickness, high partial volume effect, and substantial head tilt. MATERIALS AND METHODS: An earlier algorithm for MSP identification from MRI using the Kullback-Leibler's measure was extended for CT by estimating patient's head orientation using model fitting, image processing, and atlas-based techniques. The new algorithm was validated on 208 clinical scans acquired mainly in the ER with slice thickness ranging from 1.5 to 6 mm and severe head tilt. RESULTS: The algorithm worked robustly for all 208 cases. An angular discrepancy (degrees) and maximum distance (mm) between the calculated MSP and ground truth have the mean value (SD) 0.0258 degrees (0.9541 degrees) and 0.1472 (0.7373) mm, respectively. In average, the algorithm takes 10 s to process of a typical CT case. CONCLUSION: The proposed algorithm is robust to head rotation, and correctly identifies the MSP for a standard clinical CT scan with a large slice thickness. It has been applied in our several CT stroke CAD systems.

A new presentation and exploration of human cerebral vasculature correlated with surface and sectional neuroanatomy.

The increasing complexity of human body models enabled by advances in diagnostic imaging, computing, and growing knowledge calls for the development of a new generation of systems for intelligent exploration of these models. Here, we introduce a novel paradigm for the exploration of digital body models illustrating cerebral vasculature. It enables dynamic scene compositing, real-time interaction combined with animation, correlation of 3D models with sectional images, quantification as well as 3D manipulation-independent labeling and knowledge-related meta labeling (with name, diameter, description, variants, and references). This novel exploration is incorporated into a 3D atlas of cerebral vasculature with arteries and veins along with the surrounding surface and sectional neuroanatomy derived from 3.0 Tesla scans. This exploration paradigm is useful in medical education, training, research, and clinical applications. It enables development of new generation systems for rapid and intelligent exploration of complicated digital body models in real time with dynamic scene compositing from highly parcellated 3D models, continuous navigation, and manipulation-independent labeling with multiple features.