THE WHITAKERBIOMEDICAL IMAGINGLABORATORYTHE VINCELABORATORYINVESTIGATORSDevyani Bedekar, B.S.Jon D. Klingensmith, Ph.D.Barry D. Kuban, B.S.Anuja Nair, B.Eng., Ph.D.COLLABORATORSAaron J. Fleischman, Ph.D. 1Steven E. Nissen, M.D. 2Shuvo Roy, Ph.D. 1E. Murat Tuzcu, M.D. 21Dept. of BiomedicalEngineering, CCF2Dept. of CardiovascularMedicine, CCFIntravascular ultrasound (IVUS) is becomingaccepted as an imaging technique that allowsprecise tomographic assessment of thecoronary artery anatomy in vivo. <strong>Clinic</strong>al studieshave documented the sensitivity of IVUS indetecting atherosclerosis and in quantifying themorphology of coronary arterial lesions. Moreimportantly, IVUS can potentially quantify thestructure and composition of normal andatherosclerotic coronary arteries in the clinicalsetting rather than relying on histological data,which can only be obtained at autopsy.Many studies evaluating the efficacy ofIVUS in determining plaque composition havebeen limited by theirreliance on digitizingvideotape, which hasthree major limitations:(1) it is verytime consuming andtherefore not feasiblefor near real-timeanalysis; (2) it reducesthe resolution of theimage to that ofvideotape (approximately330 µm); and(3) parameters such asgain and intensity canbe adjusted by the operator, thereby addingvariability to the data set. More recent studieshave realized the importance of gaining access tothe ultrasound backscattered signal, often referredto as the radiofrequency (RF) signal or “backscatter”.Spectral analysis of the unprocessedultrasound signal allows a more detailed interro-The Department of Biomedical EngineeringIntravascular Ultrasound Offers InnovativeView on Atherosclerotic Plaque Buildupand Treatment Strategy OptionsTHETHEVINCELABO-RAgation of various vessel components thandigitization of videotape.We have developed software that usesspectral analysis methods to determine plaquecomposition from IVUS images and display a“Virtual Histology” map. This analysis tool hasbeen licensed to Volcano Therapeutics (LagunaHills, CA) and is currently undergoing trials inEurope.Harmonic ImagingOver the past several years, the technologyfor IVUS, in response to clinical pressure, hasmoved towards lower-profile probes withimproved handling. Not only does a lower-profileprobe allow one to exploremore of the coronary tree,but it is also less likely todisturb potentially unstableplaque at a stenosis site.Intravascumovtowardslower-profiprobes withImage quality has beenmuch less an issue thancatheter profile, and in fact,newer catheters usingsmaller, unfocused elementsactually offer poorerimaging performance thantheir predecessors.In collaboration withDrs. Shuvo Roy and Aaron Fleischman, wepropose to design and build high-frequencyultrasound transducers comprising traditionalceramic and novel polymeric materials fabricatedusing MEMS technology. The ability of thesetransducers to be used for high-frequencyharmonic imaging will be assessed.D. Geoffrey Vince, Ph.D.Nair, A., Kuban, B.D., Tuzcu, E.M., Schoenhagen, P., Nissen, S.E., and D.G. Vince (2002) Coronaryplaque classification using intravascular ultrasound radiofrequency data analysis. Circulation 106:2200-2206.Klingensmith, J.D., and D.G. Vince (2002) B-spline Methods for interactive segmentation and modeling oflumen and vessel surfaces in three-dimensional intravascular ultrasound. Comput. Med. Imaging Graph. 26429-438.Tajaddini, A., Kilpatrick, D., and D.G. Vince (2002) A Novel Experimental Method to Estimate Stress-StrainBehavior of Intact Coronary Arteries Using Intravascular Ultrasound (IVUS). Journal of Biomechanical Engineering125(1):120-123, 2002Klingensmith, J.D., Tuzcu, E.M., Nissen, S.E., and D.G. Vince (<strong>2003</strong>) Validation of an automated systemfor luminal and medial adventitial border detection in three-dimensional Intravascular ultrasound. Int. J.Cardiovasc. Imaging 19:93-104.Vince, D.G., Nair, A., Klingensmith, J.D., Moore, M.P., and V. Burgess (<strong>2003</strong>) Radiofrequency tissue characterization.In: Waksman R, Serruys P, eds. Handbook of the Vulnerable Plaque. London: Martin DunitzLtd., <strong>2003</strong>.30
Deep brain stimulation (DBS) of the thalamus orbasal ganglia represents an effective clinicaltreatment of several medically refractorymovement disorders, including Parkinson'sdisease and essential tremor. However, understandingof the mechanisms of action of DBSremains elusive. It is presently unclear whatelectrode designs and stimulation parameters areoptimal for maximum therapeutic benefit andminimal side effects. The goal of this laboratoryis to couple results from functional imaging,neurophysiology, and neuroanatomy to create atheoretical framework that enhances ourunderstanding of the effects of DBS andprovides a virtual testing ground for newstimulation paradigms.We are working to develop a quantitativeunderstanding of the effects of DBS using thetechniques of computational neuroscience andelectromagnetic field modeling. Our goal is toaugment experimental investigation in DBS ofthe parkinsonian non-human primate as well asimprove the electrode targeting and postoperativeparameter selection processes in thehuman. Our modeling process consists of threebasic steps. First we develop models of theelectric field generated by DBS electrodes. Weestimate the tissue electrical properties of thebrain region surrounding the electrode usingdiffusion tensor MRI. We then create a 3Drendering of the DBS electrode and surroundingtissue medium and solve for the electric fieldusing the finite element method. Our resultsshow that minor alterations in either theelectrode position in the brain or geometry of thestimulating contact can strongly affect the shapeof the field and subsequent neural response tostimulation. The second step consists ofcoupling the electric field to models of individualneurons. The neuron models consist of geometriesbased on 3D reconstructions, and ionchannel biophysics derived from experimentalrecordings. The neuron models are positioned inthe field and their response is measured as aThe Department of Biomedical EngineeringNew Program Investigates Deep BrainStimulation for Movement DisordersUsing Computational Modelingfunction of the stimulation parameters. Usingthese techniques, we have developed stimuluswaveforms that enable selective activation oftargeted neuronal populations surrounding theelectrode. The final step in our modeling processconsists of applying the stimulation effectspredicted at the single cell level to large scaleneuronal network models. The therapeutic effectsof DBS probably lie in its ability to disruptpathological network oscillations within differentsections of the brain. We are working tounderstand the origin of these oscillatory patternsin network models that consist of hundreds ofinteracting neurons. We apply the effects of DBSto our network models and address how thestimulation changes interactions between nuclei.Our results show that DBS can dramaticallyenhance the firing of nuclei upstream anddownstream from the site of stimulation and weare working to couple our results to PET/fMRIexperiments during DBS in the human.DBS technology is in its infancy. We areusing computer modelingcoupled to experimental andclinical investigation to buildthe foundation for the developmentof the next generation ofDBS devices. Our goal is todevelop a computationalframework that will generateexperimentally testablehypotheses on the mechanismsof DBS and provide a testingground for new electrodedesigns and stimulationparameters. In turn, we hope toimprove DBS for the treatmentof movement disorders andprovide fundamental technologynecessary for the application ofDBS to new clinical arenas suchas epilepsy and obsessivecompulsive disorder.NEURAL CONTROLTHE MCINTYRELABORATORYCOLLABORATORSNitish V. Thakor, Ph.D. 1Jerrold L. Vitek, M.D., Ph.D. 2Warren M. Grill, Ph.D. 3André Parent, Ph.D. 4Ali Rezai M.D. 5Mike Phillips, M.D. 61Dept. of Biomed. Engineering,Johns Hopkins Univ.Sch. of Med., Baltimore, MD2Dept. of Neurology, EmoryUniv. Sch. Of Med., Atlanta,GA3Dept. of Biomed. Eng., CaseWestern Reserve Univ.,<strong>Cleveland</strong>, OH4Dept. of Anatomy, Univ. ofLaval, Québec, Canada5Div. of Neurosurgery, CCF6Div. of Radiology, CCFCameron McIntyre, Ph.D.McIntyre, C.C., and W.M. Grill (2000) Selective microstimulation of central nervous system neurons.Ann. Biomed. Eng. 28:219-233.McIntyre, C.C., and W.M. Grill (2001) Finite element analysis of the current-density and electric fieldgenerated by metal microelectrodes. Ann. Biomed. Eng. 29:227-235.McIntyre, C.C., Richardson, A.G., and W.M. Grill (2002) Modeling the excitability of mammalian nervefibers: influence of afterpotentials on the recovery cycle. J. Neurophysiol. 87:995-1006.McIntyre, C.C., and W.M. Grill (2002) Extracellular stimulation of central neurons: influence of stimuluswaveform and frequency on neuronal output. J. Neurophysiol. 88:1592-1604.McIntyre, C.C., and N.V. Thakor (2002) Uncovering the mechanisms of deep brain stimulation for Parkinson'sdisease through functional imaging, neural recording, and neural modeling. Crit. Rev. Biomed.Eng. 30:249-281.31