Three-dimensional Brain Model Research Articles

Simulation Method for the Physical Deformation of a Three-Dimensional Soft Body in Augmented Reality-Based External Ventricular Drainage.

Intraoperative navigation reduces the risk of major complications and increases the likelihood of optimal surgical outcomes. This paper presents an augmented reality (AR)-based simulation technique for ventriculostomy that visualizes brain deformations caused by the movements of a surgical instrument in a three-dimensional brain model. This is achieved by utilizing a position-based dynamics (PBD) physical deformation method on a preoperative brain image. An infrared camera-based AR surgical environment aligns the real-world space with a virtual space and tracks the surgical instruments. For a realistic representation and reduced simulation computation load, a hybrid geometric model is employed, which combines a high-resolution mesh model and a multiresolution tetrahedron model. Collision handling is executed when a collision between the brain and surgical instrument is detected. Constraints are used to preserve the properties of the soft body and ensure stable deformation. The experiment was conducted once in a phantom environment and once in an actual surgical environment. The tasks of inserting the surgical instrument into the ventricle using only the navigation information presented through the smart glasses and verifying the drainage of cerebrospinal fluid were evaluated. These tasks were successfully completed, as indicated by the drainage, and the deformation simulation speed averaged 18.78 fps. This experiment confirmed that the AR-based method for external ventricular drain surgery was beneficial to clinicians.

A Deep Learning-Based Automatic Segmentation and 3D Visualization Technique for Intracranial Hemorrhage Detection Using Computed Tomography Images.

Intracranial hemorrhage (ICH) occurs when blood leaks inside the skull as a result of trauma to the skull or due to medical conditions. ICH usually requires immediate medical and surgical attention because the disease has a high mortality rate, long-term disability potential, and other potentially life-threatening complications. There are a wide range of severity levels, sizes, and morphologies of ICHs, making accurate identification challenging. Hemorrhages that are small are more likely to be missed, particularly in healthcare systems that experience high turnover when it comes to computed tomography (CT) investigations. Although many neuroimaging modalities have been developed, CT remains the standard for diagnosing trauma and hemorrhage (including non-traumatic ones). A CT scan-based diagnosis can provide time-critical, urgent ICH surgery that could save lives because CT scan-based diagnoses can be obtained rapidly. The purpose of this study is to develop a machine-learning algorithm that can detect intracranial hemorrhage based on plain CT images taken from 75 patients. CT images were preprocessed using brain windowing, skull-stripping, and image inversion techniques. Hemorrhage segmentation was performed using multiple pre-trained models on preprocessed CT images. A U-Net model with DenseNet201 pre-trained encoder outperformed other U-Net, U-Net++, and FPN (Feature Pyramid Network) models with the highest Dice similarity coefficient (DSC) and intersection over union (IoU) scores, which were previously used in many other medical applications. We presented a three-dimensional brain model highlighting hemorrhages from ground truth and predicted masks. The volume of hemorrhage was measured volumetrically to determine the size of the hematoma. This study is essential in examining ICH for diagnostic purposes in clinical practice by comparing the predicted 3D model with the ground truth.

Safety and therapeutic effects of personalized transcranial direct current stimulation based on electrical field simulation for prolonged disorders of consciousness: study protocol for a multi-center, double-blind, randomized controlled trial.

Disorders of consciousness (DOC) resulting from acquired brain injury (ABI) increase the mortality rate of patients, complicate rehabilitation, and increase the physical and economic burden that DOC imposes on patients and their families. Thus, treatment to promote early awakening from DOC is vital. Transcranial direct current stimulation (tDCS) has shown great potential for promoting neuro-electrochemical activity. However, previous tDCS studies did not consider structural damage or head and brain lesions, so the applicability of the results to all DOC patients was limited. In this study, to establish a patient-specific tDCS treatment plan considering the brain lesions of and damage sustained by DOC patients, we considered the electric field calculated by a the "finite electric" three-dimensional brain model based on magnetic resonance images. This protocol was developed to aid tDCS treatment of actual patients, and to verify its safety and effectiveness. Twenty-four patients with DOC after ABI will be enrolled in this cross-over trial. All participants will receive typical rehabilitation combined with sham tDCS and typical rehabilitation plus personalized tDCS (P-tDCS). Each interventional period will last 2 weeks (30 min/day, 5 days/week). The primary outcome [score on the Korean version of the Coma Recovery Scale-Revised (K-CRS-R)] will be assessed at baseline and the end of the first day of the intervention. Secondary outcomes (K-CRS-R at 1 week and 2 weeks after experimental session and quantitative EEG changes quantitative electroencephalography changes) will be measured at baseline and the end of week 4. Adverse events will be recorded during each treatment session. For patients with neurological disorders, tDCS has served as a painless, non-invasive, easily applied, and effective therapy for several decades, and there is some evidence that it can improve the level of consciousness of patients with DOC. However, variability in the effects on consciousness among subjects have been reported and personalized strategies are lacking. This protocol is for a randomized controlled trial designed to validate the effectiveness and safety of P-tDCS combined with typical rehabilitation for DOC. https://cris.nih.go.kr, identifier KCT0007157.

An adaptive semi-implicit finite element solver for brain cancer progression modeling.

Glioblastoma is the most aggressive and infiltrative glioma, classified as Grade IV, with the poorest survival rate among patients. Accurate and rigorously tested mechanistic in silico modeling offers great value to understand and quantify the progression of primary brain tumors. This paper presents a continuum-based finite element framework that is built on high performance computing, open-source libraries to simulate glioblastoma progression. We adopt the established proliferation invasion hypoxia necrosis angiogenesis model in our framework to realize scalable simulations of cancer, and has demonstrated to produce accurate and efficient solutions in both two- and three-dimensional brain models. The in silico solver can successfully implement arbitrary order discretization schemes and adaptive remeshing algorithms. A model sensitivity analysis is conducted to test the impact of vascular density, cancer cell invasiveness and aggressiveness, the phenotypic transition potential, including that of necrosis, and the effect of tumor-induced angiogenesis in the evolution of glioblastoma. Additionally, individualized simulations of brain cancer progression are carried out using pertinent magnetic resonance imaging data, where the in silico model is used to investigate the complex dynamics of the disease. We conclude by arguing how the proposed framework can deliver patient-specific simulations of cancer prognosis and how it could bridge clinical imaging with modeling.

Functional Characterization of Human Pluripotent Stem Cell-Derived Models of the Brain with Microelectrode Arrays.

Human pluripotent stem cell (hPSC)-derived neuron cultures have emerged as models of electrical activity in the human brain. Microelectrode arrays (MEAs) measure changes in the extracellular electric potential of cell cultures or tissues and enable the recording of neuronal network activity. MEAs have been applied to both human subjects and hPSC-derived brain models. Here, we review the literature on the functional characterization of hPSC-derived two- and three-dimensional brain models with MEAs and examine their network function in physiological and pathological contexts. We also summarize MEA results from the human brain and compare them to the literature on MEA recordings of hPSC-derived brain models. MEA recordings have shown network activity in two-dimensional hPSC-derived brain models that is comparable to the human brain and revealed pathology-associated changes in disease models. Three-dimensional hPSC-derived models such as brain organoids possess a more relevant microenvironment, tissue architecture and potential for modeling the network activity with more complexity than two-dimensional models. hPSC-derived brain models recapitulate many aspects of network function in the human brain and provide valid disease models, but certain advancements in differentiation methods, bioengineering and available MEA technology are needed for these approaches to reach their full potential.

On the Sensitivity Analysis of Porous Finite Element Models for Cerebral Perfusion Estimation

Computational physiological models are promising tools to enhance the design of clinical trials and to assist in decision making. Organ-scale haemodynamic models are gaining popularity to evaluate perfusion in a virtual environment both in healthy and diseased patients. Recently, the principles of verification, validation, and uncertainty quantification of such physiological models have been laid down to ensure safe applications of engineering software in the medical device industry. The present study sets out to establish guidelines for the usage of a three-dimensional steady state porous cerebral perfusion model of the human brain following principles detailed in the verification and validation (V&V 40) standard of the American Society of Mechanical Engineers. The model relies on the finite element method and has been developed specifically to estimate how brain perfusion is altered in ischaemic stroke patients before, during, and after treatments. Simulations are compared with exact analytical solutions and a thorough sensitivity analysis is presented covering every numerical and physiological model parameter. The results suggest that such porous models can approximate blood pressure and perfusion distributions reliably even on a coarse grid with first order elements. On the other hand, higher order elements are essential to mitigate errors in volumetric blood flow rate estimation through cortical surface regions. Matching the volumetric flow rate corresponding to major cerebral arteries is identified as a validation milestone. It is found that inlet velocity boundary conditions are hard to obtain and that constant pressure inlet boundary conditions are feasible alternatives. A one-dimensional model is presented which can serve as a computationally inexpensive replacement of the three-dimensional brain model to ease parameter optimisation, sensitivity analyses and uncertainty quantification. The findings of the present study can be generalised to organ-scale porous perfusion models. The results increase the applicability of computational tools regarding treatment development for stroke and other cerebrovascular conditions.

Derivation, Expansion, Cryopreservation and Characterization of Brain Microvascular Endothelial Cells from Human Induced Pluripotent Stem Cells

Brain microvascular endothelial cells (BMECs) can be differentiated from human induced pluripotent stem cells (iPSCs) to develop ex vivo cellular models for studying blood-brain barrier (BBB) function. This modified protocol provides detailed steps to derive, expand, and cryopreserve BMECs from human iPSCs using a different donor and reagents than those reported in previous protocols. iPSCs are treated with essential 6 medium for 4 days, followed by 2 days of human endothelial serum-free culture medium supplemented with basic fibroblast growth factor, retinoic acid, and B27 supplement. At day 6, cells are sub-cultured onto a collagen/fibronectin matrix for 2 days. Immunocytochemistry is performed at day 8 for BMEC marker analysis using CLDN5, OCLN, TJP1, PECAM1, and SLC2A1. Western blotting is performed to confirm BMEC marker expression, and absence of SOX17, an endodermal marker. Angiogenic potential is demonstrated with a sprouting assay. Trans-endothelial electrical resistance (TEER) is measured using chopstick electrodes and voltohmmeter starting at day 7. Efflux transporter activity for ATP binding cassette subfamily B member 1 and ATP binding cassette subfamily C member 1 is measured using a multi-plate reader at day 8. Successful derivation of BMECs is confirmed by the presence of relevant cell markers, low levels of SOX17, angiogenic potential, transporter activity, and TEER values ~2000 Ω x cm2. BMECs are expanded until day 10 before passaging onto freshly coated collagen/fibronectin plates or cryopreserved. This protocol demonstrates that iPSC-derived BMECs can be expanded and passaged at least once. However, lower TEER values and poorer localization of BMEC markers was observed after cryopreservation. BMECs can be utilized in co-culture experiments with other cell types (neurons, glia, pericytes), in three-dimensional brain models (organ-chip and hydrogel), for vascularization of brain organoids, and for studying BBB dysfunction in neuropsychiatric disorders.

A Potential Solution to Minimally Invasive Device for Oral Surgery: Evaluation of Surgical Outcomes in Rat

The objective of the present research was to investigate the thermal injury in the brain after minimally invasive electrosurgery using instruments with copper-doped diamond-like carbon (DLC-Cu) surface coating. The surface morphologies of DLC-Cu thin films were characterized using scanning electron microscopy and atomic force microscopy. Three-dimensional brain models were reconstructed using magnetic resonance imaging to simulate the electrosurgical operation. In adult rats, a monopolar electrosurgical instrument coated with the DLC-Cu thin film was used to generate lesions in the brain. Animals were sacrificed for evaluations on postoperative days 0, 2, 7, and 28. Data indicated that the temperature decreased significantly when minimally invasive electrosurgical instruments with nanostructure DLC-Cu thin films were used and continued to decrease with increasing film thickness. On the other hand, the DLC-Cu-treated device created a relatively small thermal injury area and lateral thermal effect in the brain tissues. These results indicated that the DLC-Cu thin film minimized excessive thermal injury and uniformly distributed the temperature in the brain. Taken together, our study results suggest that the DLC-Cu film on copper electrode substrates is an effective means for improving the performance of electrosurgical instruments.

Susceptibility mapping of air, bone, and calcium in the head.

To demonstrate the mapping of structures with high susceptibility values, such as the sinuses, bones and teeth, using short echo times. Four in vivo datasets were collected with a gradient-echo sequence (TE1 = 2.5 ms, TE2 = 5 ms and TE3 = 7.5 ms). Complex division was performed to remove the phase offset term and generate the phase at TE = 2.5 ms. Susceptibility maps were generated from unwrapped phase images, using a geometry-constrained iterative algorithm, by preserving phase information in the extracerebral tissues. The susceptibility results were improved by updating the missing phase information inside structures with no signal using the predicted phase at each iteration step. Simulated phase images of a three-dimensional brain model and tooth phantom were used to validate the proposed method. Improved susceptibility maps were obtained once the phase information in the extracerebral tissue region was incorporated, for both the model and in vivo data. For in vivo data, the average susceptibilities of air (sphenoid sinus), bone and calcium (teeth) were found to be (in ppm): Δχ(sinus-tissue) = +9.2 ± 1.3, Δχ(bone-tissue) = -2.1 ± 0.6 and Δχ(teeth-tissue) = -3.3 ± 1.2, respectively. High susceptibility structures with little or no signal can be imaged using quantitative susceptibility mapping and can be used to improve background field removal.

Modified Three-Dimensional Brain Model for Study of the Trans-sylvian Approach

The trans-sylvian approach is one of the most frequently employed neurosurgical procedures, but it is difficult for medical students to understand the approach stereoscopically. A three-dimensional model equipped with an arachnoid membrane and sylvian vein was developed which can be repeatedly used to simulate surgery for the education of medical students and residents in the trans-sylvian approach. The model was prepared using existing models of the skull bone, brain, and cerebral artery. Polyvinylidene chloride film, commonly used as plastic wrap for food, was adopted for the arachnoid membrane, and wetted water-insoluble tissue paper for the arachnoid trabeculae. The sylvian vein was prepared by ligating woolen yarn with cotton lace thread at several sites. Students and residents performed the trans-sylvian approach under a microscope, and answered a questionnaire survey. Using this model, simulation of division of the arachnoid membrane and arachnoid trabeculae, and dissection of the sylvian vein was possible. In the questionnaire, the subjects answered 8 questions concerning understanding of the stereoscopic anatomy of the sylvian fissure, usefulness of the simulation, and interest in neurosurgical operation using the following ratings: yes, very much; yes; somewhat; not very much; or not at all. All items rated as 'yes, very much' and 'yes' accounted for more than 70% of answers. This model was useful for medical students to learn the trans-sylvian approach. In addition, repeated practice is possible using cheap materials, which is advantageous for an educational model.

Automated reconstruction of a three-dimensional brain model from magnetic resonance images

Automated reconstruction of a three-dimensional brain model from magnetic resonance images

In vivo modeling of interstitial pressure in the brain under surgical load using finite elements.

Current brain deformation models have predominantly reflected solid constitutive relationships generated from empirical ex vivo data and have largely overlooked interstitial hydrodynamic effects. In the context of a technique to update images intraoperatively for image-guided neuronavigation, we have developed and quantified the deformation characteristics of a three-dimensional porous media finite element model of brain deformation in vivo. Results have demonstrated at least 75-85 percent predictive capability, but have also indicated that interstitial hydrodynamics are important. In this paper we investigate interstitial pressure transient behavior in brain tissue when subjected to an acute surgical load consistent with neurosurgical events. Data are presented from three in vivo porcine experiments where subsurface tissue deformation and interhemispheric pressure gradients were measured under conditions of an applied mechanical deformation and then compared to calculations with our three-dimensional brain model. Results demonstrate that porous-media consolidation captures the hydraulic behavior of brain tissue subjected to comparable surgical loads and that the experimental protocol causes minimal trauma to porcine brain tissue. Working values for hydraulic conductivity of white and gray matter are also reported and an assessment of transient pressure gradient effects with respect to deformation is provided.

Quantification of neurotoxicity and identification of cellular subsets in a three-dimensional brain model.

Imaging of cells in a large intact three-dimensional tissue remains difficult. Quantification and identification of cell damage in a mixed culture system has been limited by the inability of fluorescent probes to discriminate types of cellular death and penetrate tissue more that 100 microm thick. We have investigated several probes in combination with neural cell-specific antibodies to quantify cell damage in the presence of several toxins. Acridine orange and ethidium bromide were excellent for determination of cell viability, death by necrosis, or apoptosis in thick brain tissue aggregates. Calcein and ethidium homodimer were effective on live/ dead stains, and the Syto dyes 11 and 13 worked well for quantification of all cells in the brain aggregate model. By using these combinations of dyes in conjunction with confocal microscopy, we were able to quantify neural cell damage without disrupting the three-dimensional environment.

Retrospective fusion of radiographic and MR data for localization of subdural electrodes.

Prior to epilepsy surgery, subdural electrodes are often implanted and monitored for a few days to identify the focus of abnormal electrical activity. During the implantation and subsequent brain resection, there may be uncertainty about the exact location of the electrodes with respect to features of brain anatomy such as specific gyral convolutions or lesions. In experiments with a phantom and patients, implanted electrodes were imaged with multiplanar skull radiographs (or CT scans). After retrospective registration with preimplantation MR data, the electrodes were mapped from these studies onto an MR-derived three-dimensional brain model. The resulting multimodality displays showed the relationship of the electrodes to brain anatomy. In one patient the position of each electrode with respect to a metabolic lesion was also displayed by mapping preimplantation PET data onto the same brain model. This new display of electrode positions may strengthen the interpretation of subdural electrical recordings and thereby reduce uncertainty in planning the resection of epileptic tissue.

Towards a three-dimensional brain model stored in a computer.

The project of storing in a computer a three-dimensional brain model is undoubtedly ambitious. The object is to be able to help the neurosurgeon to visualise the structures encounted by a stereotactically directed probe. The technical problems involved in converting between atlas co-ordinates and the actual co-ordinates of a particular stereotactic machine on a particular patient are not very difficult and by themselves seem hardly to justify the use of a general purpose computer, although Dervin, Heywood et al. have demonstrated the possibilities of a dedicated portable mini-computer operating actually within the theatre. Our project must also be distinguished from that of storing in computer memory a brain atlas, in such a way that appropriate sections can be retrieved and displayed with an associated representation of the probe track. A system of this latter kind has been beautifully illustrated by Dr. Bertrand in this symposium.