Development of Wireless Neuromodulation in a Sheep Model
In a collaboration with Scott Crosby at NeuroConnect, Dr. Jacob Robinson PhD at Rice Engineering and Dr. Sunil Sheth MD at UTHealth Neurology, we hope to provide an opportunity to develop new wireless neuromodulation therapy that may provide more effective care in patients. Neuromodulation is relatively a new frontier in the medical field and can provide an effective treatment for pain, psychiatric disorders and rehabilitation. By enhancing or suppressing certain stimuli of the nervous system, neuromodulation may provide patients with effective and less invasive means of treating disease. By deploying a wireless magnetoelectric stimulator into the subarachnoid space via lumbar puncture, we aim to effectively stimulate various spinal nerves and areas of the brain.
Development of Neurovascular Applications in the Siemens CIOS Spin
Angiographic imaging in neuro-interventional procedures has been primarily performed on fixed bi-plane angiography systems. These systems offer simultaneous acquisition of angiographic imaging of neuro-vasculature in two different views. This helps the operators localize the structures of interest, especially the depth information which helps them pass the wires deep into the brain. However, the penetration of these fixed biplane angio-systems is very low in a hybrid and/or environment is very minimal due to space constraints, hardware requirements from ceiling rails, cost etc. Often, a portable C-arm is brought into the OR for some basic imaging either during the procedure or towards the end of the procedure. Cios Spin is a mobile C-arm that offers unique 3D imaging capabilities with improved 2D imaging quality. This system has the potential to provide reliable and meaningful intra-operative imaging in the neuro-interventional or neuro-surgery space. In this collaboration with Siemens, the goal of this project is to understand and further develop the utility of intra-procedural imaging from the Cios Spin for a variety of neuro-interventional procedures.
Use of MCB-613 as a neuroprotectant in a Rodent Stroke Model
Stroke is the fifth leading cause of death and the leading cause of adult disability with an estimated cost of near $70 billion in the United States. A stroke is an interruption of the blood supply to any part of the brain, which can lead to brain cell death causing a myriad of symptoms, ranging from extremity weakness to death.
MCB-613 is a potent small molecule stimulator of SRC (steroid receptor coactivator) and has been shown to stimulate SRC-1, SRC-2 and SRC-3 that has been used to disrupt cancer cell homeostatic dependence on SRCs. In preliminary studies, MCB-613 has been shown to decrease the severity of myocardial infarction leading to decreased tissue damage with and the loss of cardiac function. In these studies, MCB-613 was shown to be highly concentrated in the brain parenchyma due to its lipophilic properties.
If proven to be effective, considering the similarity between myocardial infarction and stroke, it would be an important neuroprotective agent given at the onset of stroke-like symptoms thereby increasing the therapeutic window for effective treatment. At the moment, there are no effective neuroprotective treatments for stroke patients. The only medical treatment in acute ischemic stroke is tPA, which works by dissolving the clot and improving blood flow but must be given within three hours of onset or four and a half hours in eligible patients.
This project is a collaboration with Dr. Bert O'Malley MD, Chancellor at Baylor College of Medicine, Division of Molecular and Cellular Biology. Our first aim is to perform a preliminary experiment to demonstrate that MCB-613 has a positive therapeutic effect in the MCAo model. The purpose of this project is to (a) test the neuroprotective effects of MCB-613 on an established murine middle cerebral artery occlusion (MCAo) model and (b) develop an effective treatment regimen to lessen the negative impact of MCAo.
Performance Evaluation of Artificial Intelligence Applications in Neurosurgery
Artificial Intelligence, (AI) is quickly becoming a major component of many healthcare applications, including drug discovery, remote patient monitoring, medical diagnostics and imaging, wearables, and hospital management. Medical fields that rely on imaging data, including radiology, pathology, dermatology and ophthalmology, have already begun to benefit from the implementation of AI methods. Radiographic images, coupled with data on clinical outcomes, have led to the development of applications and tools that support clinical decision making, triage of emergent care, and patient transfers and referrals. Since timely identification can drive outcomes, efficient workflows must continue to be developed to expedite the detection, characterization, selection and triage of subjects with a variety of conditions or diseases. In a collaboration with Viz.ai, we aim to develop and evaluate the performance of investigational algorithms designed to utilize radiographic scans and artificial intelligence to detect conditions in order optimize clinical workflow, patient triage, and resource use in the field of neurosurgery.
Rodent Model for Gliomas and Other Tumors
Adopting the same principles as our Rabbit Model for Gliomas (mentioned above), we aim to create a rodent model that will mimic the typical clinical scenario, in this collaboration with Dr. Frederick Lang MD at MD Anderson. We will implant glioma cell lines, perform diagnostic imaging, and provide treatment intra-arterially via angiography in a rat and hamster model. One major drawback of a rodent model was the inability to perform angiograms in these small animals, but these has changed with the advent of microcatheters and new neuroendovascular technology. In addition, by using hamsters, we will be able to create an immunocompetent model that is clinically relevant and doesn’t have the disadvantages of drug induced immunosuppression.