Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects
Wearable Devices for Precision Medicine and Health State Monitoring
Wearable technologies will play an important role in advancing precision medicine by enabling measurement of clinically-relevant parameters that define an individual’s health state. The lifestyle and fitness markets have provided the driving force for the development of a broad range of wearable technologies that can be adapted for use in healthcare. Here we review existing technologies currently used for measurement of the four primary vital signs along with other clinically-relevant parameters. We review the relevant physiology that defines the measurement needs, and evaluate the different methods of signal transduction and measurement modalities for use in healthcare.
Optogenetic Excitation of Ipsilesional Sensorimotor Neurons is Protective in Acute Ischemic Stroke: a Laser Speckle Imaging Study
Specifically activating the sensorimotor neurons in acute stroke has been found to be protective. Laser speckle contrast imaging technique was used to quantify the neurovascular response to optogenetic stimulation within the first 24 hrs after stroke, in the aspect of cerebral blood flow changes. The results demonstrated that neuronal-specific excitation at acute stage could successfully compromise the expansion of the ischemic core and promote the neurovascular response after stroke. The results implied the neuron-specific modulation as a potential therapeutic intervention for the acute ischemic brain injury.
Epilepsy-on-a-chip System for Antiepileptic Drug Discovery
Hippocampal slice cultures spontaneously develop chronic epilepsy several days after dissection and are used as an in vitro model of post-traumatic epilepsy. This work describes the development of a hybrid microfluidic-microelectrode array device that improves the throughput of chronic recordings in hippocampal slice cultures and facilitates antiepileptic drug discovery. Our technology allows miniaturization of large and expensive multiple-slice electrophysiology systems to a single scalable chip. We used this epilepsy-on-a-chip device to carry out a screen of Receptor Tyrosine Kinases (RTKs) inhibitors and discovered two novel antiepileptic compounds. These ‘hits’ represent a promising first step in developing new antiepileptic drugs.
3D Measurements of Acceleration-Induced Brain Deformation via Harmonic Phase Analysis and Finite-Element Models
Measuring brain deformation enables researchers to better understand traumatic brain injuries and develop methods for injury prevention. However, quantifying three-dimensional motion prevent in the intact human brain poses significant challenges. We present a new technique to estimate tissue deformation by combining data from tagged magnetic resonance images with a biomechanical model of the brain itself. This approach provides direct quantification of brain deformation from in vivo data during accelerative events that are typical of everyday activities, and provides insight into the brain’s behavior in more severe impacts.
Generation of Patient-Specific Cardiac Vascular Networks: a Hybrid Image-Based and Synthetic Geometric Model
The image resolution of CT angiography currently precludes vessel segmentation of coronary arteries smaller than approximately 1 mm in size and affects blood flow analysis. We propose an algorithm for the generation of patient-specific vascular networks starting from segmented epicardial vessels. We extend a tree generation method based on functional principles to account for multiple, competing vascular trees. From segmented vascular tree models of several patients, we generate networks (~50 vascular trees) filling the entire left ventricle myocardium down to the arteriole size level. All vascular models match morphometry properties previously described and enable potential applications for blood flow simulation and disease modeling.
A New Modeling Method to Characterize the Stance Control Function of Prosthetic Knee Joints
A new method is presented to characterize the function of lower-limb prosthetic stance control under mobility conditions associated with activities of daily living. The method is based on a model of the gait modes corresponding to finite stance control states. Empirical data from amputee and simulated gait were acquired using a custom built wearable instrument and input into the model. The modeling approach was shown to be robust, responsive and capable of accurate characterization of controller function under diverse of locomotor and prosthetic setup conditions.