Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

SCI Publications

2010


S.S. Kuppahally, N. Akoum, T.J. Badger, N.S. Burgon, T. Haslam, E. Kholmovski, R.S. Macleod, C. McGann, N.F. Marrouche. “Echocardiographic left atrial reverse remodeling after catheter ablation of atrial fibrillation is predicted by preablation delayed enhancement of left atrium by magnetic resonance imaging,” In American Heart Journal, Vol. 160, No. 5, pp. 877--884. 2010.
DOI: 10.1016/j.ahj.2010.07.003
PubMed ID: 21095275
PubMed Central ID: PMC2995281

ABSTRACT

BACKGROUND:
Atrial fibrosis is a hallmark of atrial structural remodeling (SRM) and leads to structural and functional impairment of left atrial (LA) and persistence of atrial fibrillation (AF). This study was conducted to assess LA reverse remodeling after catheter ablation of AF in mild and moderate-severe LA SRM.

METHODS:
Catheter ablation was performed in 68 patients (age 62 ± 14 years, 68% males) with paroxysmal (n = 26) and persistent (n = 42) AF. The patients were divided into group 1 with mild LA SRM (10%, n = 37) by delayed enhancement magnetic resonance imaging (DEMRI). Two-dimensional echocardiography, LA strain, and strain rate during left ventricular systole by velocity vector imaging were performed pre and at 6 ± 3 months postablation. The long-term outcome was monitored for 12 months.

RESULTS:
Patients in group 1 were younger (57 ± 15 vs 66 ± 13 years, P = .009) with a male predominance (80% vs 57%, P < .05) as compared to group 2. Postablation, group 1 had significant increase in average LA strain (??: 14% vs 4%, P < .05) and strain rate (??: 0.5 vs 0.1 cm/s, P < .05) as compared to group 2. There was a trend toward more patients with persistent AF in group 2 (68% vs 55%, P = .2), but it was not statistically significant. Group 2 had more AF recurrences (41% vs 16%, P = .02) at 12 months after ablation.

CONCLUSION:
Mild preablation LA SRM by DEMRI predicts favorable LA structural and functional reverse remodeling and long-term success after catheter ablation of AF, irrespective of the paroxysmal or persistent nature of AF.



J.A. Levine, D.J. Swenson, Z. Fu, R.S. MacLeod, R.T. Whitaker. “A Comparison of Delaunay Based Meshing Algorithms for Electrophysiological Cardiac Simulations,” In Virtual Physiological Human, pp. 181--183. 2010.



C. Mahnkopf, T.J. Badger, N.S. Burgon, M. Daccarett, T.S. Haslam, C.T. Badger, C.J. McGann, N. Akoum, E. Kholmovski, R.S. Macleod, N.F. Marrouche. “Evaluation of the left atrial substrate in patients with lone atrial fibrillation using delayed-enhanced MRI: implications for disease progression and response to catheter ablation,” In Heart Rhythm, Vol. 7, No. 10, pp. 1475--1481. 2010.
PubMed ID: 20601148



T.A. Pilcher, J.D. Tate, J.G. Stinstra, E.V. Saarel, M.D. Puchalski, and R.S. MacLeod. “Partially extracted defibrillator coils and pacing leads alter defibrillation thresholds,” In Proceedings of the 15th International Academy of Cardiology World Congress of Cardiology, 2010.



N.M. Segerson, M. Daccarett, T.J. Badger, A. Shabaan, N. Akoum, E.N. Fish, S. Rao, N.S. Burgon, Y. Adjei-Poku, E. Kholmovski, S. Vijayakumar, E.V. DiBella, R.S. MacLeod, N.F. Marrouche. “Magnetic resonance imaging-confirmed ablative debulking of the left atrial posterior wall and septum for treatment of persistent atrial fibrillation: rationale and initial experience,” In Journal of Cardiovascular Electrophysiology, Vol. 21, No. 2, pp. 126--132. 2010.
PubMed ID: 19804549



J.G. Stinstra, R.S. MacLeod, C.S. Henriquez. “Incorporating Histology into a 3D Microscopic Computer Model of Myocardium to Study Propagation at a Cellular Level,” In Annals of Biomedical Engineering (ABME), Vol. 38, No. 4, pp. 3399--1414. 2010.
DOI: 10.1007/s10439-009-9883-y



D. Swenson, J.A. Levine, Z. Fu, J.D. Tate, R.S. MacLeod. “The Effect of Non-Conformal Finite Element Boundaries on Electrical Monodomain and Bidomain Simulations,” In Computing in Cardiology, Vol. 37, IEEE, pp. 97--100. 2010.
ISSN: 0276-6547



J.D. Tate, J.G. Stinstra, T.A. Pilcher, R.S. MacLeod. “Implantable Cardioverter Defibrillator Predictive Simulation Validation,” In Computing in Cardiology, pp. 853-–856. September, 2010.

ABSTRACT

Despite the growing use of implantable cardioverter defibrillators (ICDs) in adults and children, there has been little progress in optimizing device and electrode placement. To facilitate effective placement of ICDs, especially in unique cases of children with congenital heart defects, we have developed a predictive model that evaluates the efficacy of a delivered shock. Most recently, we have also developed and carried out an experimental validation approach based on measurements from clinical cases. We have developed a method to obtain body surface potential maps of ICD discharges during implantation surgery and compared these measured potentials with simulated surface potentials to determine simulation accuracy.

Each study began with an full torso MRI or CT scan of the subject, from which we created patient specific geometric models. Using a customized limited leadset applied to the anterior surface of the torso away from the sterile field, we recorded body surface potentials during ICD testing. Subsequent X-ray images documented the actual location of ICD and electrodes for placement of the device in the geometric model. We then computed the defibrillation field, including body surface potentials, and compared them to the measured values.

Comparison of the simulated and measured potentials yielded very similar patterns and a typical correlation between 0.8 and 0.9 and a percentage error between 0.2 and 0.35. The high correlation of the potential maps suggest that the predictive simulation generates realistic potential values. Ongoing sensi- tivity studies will determine the robustness of the results and pave the way for use of this approach for predictive computational optimization studies before device implantation.



D.F. Wang, R.M. Kirby, R.S. MacLeod, C.R. Johnson. “A New Family of Variational-Form-Based Regularizers for Reconstructing Epicardial Potentials from Body-Surface Mapping,” In Computing in Cardiology, 2010, pp. 93--96. 2010.



C.H. Wolters, S. Lew, R.S. MacLeod, M.S. Hämäläinen. “Combined EEG/MEG source analysis using calibrated finite element head models,” In Proc. of the 44th Annual Meeting, DGBMT, Note: to appear, http://conference.vde.com/bmt-2010, Rostock-Warnemünde, Germany, Oct.5-8, 2010 2010.


2009


T.J. Badger, R.S. Oakes, M. Daccarett, N.S. Burgon, N. Akoum, E.N. Fish, J.J. Blauer, S.N. Rao, Y. Adjei-Poku, E.G. Kholmovski, S. Vijayakumar, E.V. Di Bella, R.S. MacLeod, N.F. Marrouche. “Temporal Left Atrial Lesion Formation After Ablation of Atrial Fibrillation,” In Heart Rhythm, Vol. 6, No. 2, pp. 161--168. February, 2009.



T.J. Badger, Y.A. Adjei-Poku, N.S. Burgon, S. Kalvaitis, A. Shaaban, D.N. Sommers, J.J.E. Blauer, E.N. Fish N. Akoum, T.S. Haslem, E.G. Kholmovski, R.S. MacLeod, D.G. Adler, N.F. Marrouche. “Initial Experience of Assessing Esophageal Tissue Injury and Recovery Using Delayed-Enhancement MRI After Atrial Fibrillation Ablation,” In Circulation: Arrhythmia and Electrophysiology, Vol. 2, pp. 620--625. 2009.



B.M. Isaacson, J.G. Stinstra, R.S. MacLeod, J.B. Webster, J.P. Beck, R.D. Bloebaum. “Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees,” In JoVE, Vol. 29, 2009.



S. Lew, C.H. Wolters, T. Dierkes, C. Röer, R.S. MacLeod. “Accuracy and run-time comparison for different potential approaches and iterative solvers in finite element method based EEG source analysis,” In Applied Numerical Mathematics, Vol. 59, pp. 1970--1988. 2009.



S. Lew, C.H. Wolters, A. Anwander, S. Makeig, R.S. MacLeod. “Improved EEG Source Analysis Using Low-Resolution Conductivity Estimation in a Four-Compartment Finite Element Head Model,” In Human Brain Mapping, Vol. 30, pp. 2862--2878. 2009.



R.S. MacLeod, J.G. Stinstra, S. Lew, R.T. Whitaker, D.J. Swenson, M.J. Cole, J. Krüger, D.H. Brooks, C.R. Johnson. “Subject-specific, multiscale simulation of electrophysiology: a software pipeline for image-based models and application examples,” In Philosophical Transactions of The Royal Society A, Mathematical, Physical & Engineering Sciences, Vol. 367, No. 1896, pp. 2293--2310. 2009.



M. Milanic, V. Jazbinsek, D.F. Wang, J. Sinstra, R.S. Macleod, D.H. Brooks, R. Hren. “Evaluation of Approaches of Solving Electrocardiographic Imaging Problem,” In Proceeding of Computers in Cardiology 2010, Park City, Utah, September, 2009.



R.S. Oakes, T.J. Badger, E.G. Kholmovski, N. Akoum, N.S. Burgon, E.N. Fish, J.J. Blauer, S.N. Rao, E.V. DiBella, N.M. Segerson, M. Daccarett, J. Windfelder, C.J. McGann, D.L. Parker, R.S. MacLeod, N.F. Marrouche. “Detection and quantification of left atrial structural remodeling with delayed-enhancement magnetic resonance imaging in patients with atrial fibrillation,” In Circulation, Vol. 119, No. 13, pp. 1758--1767. 2009.



N.M. Segerson, M. Daccarett, T.J. Badger, A. Shabaan, N. Akoum, E.N. Fish, S. Rao, N.S. Burgon, Y. Adjei-Poku, E.G. Kholmovski, S. Vijayakumar, E.V.R. Dibella, R.S. Macleod, N.F. Marrouche. “Magnetic Resonance Imaging-Confirmed Ablative Debulking of the Left Atrial Posterior Wall and Septum for Treatment of Persistent Atrial Fibrillation: Rationale and Initial Experience,” In Journal of Cardiovascular Electrophysiology, Vol. 21, No. 2, pp. 126--132. 2009.



J.D. Tate, J.G. Stinstra, T. Pilcher, and R.S. MacLeod. “Measuring Implantable Cardioverter Defibrillators (ICDs) During Implantation Surgery: Verification of a Simulation,” In Computers in Cardiology, pp. 473--476. 2009.
ISSN: 0276-6547

ABSTRACT

Implantable cardioverter defibrillators (ICDs) are increasing used in abnormal configurations. We have developed a patient specific forward simulation model to predict efficacy of the defibrillation shock. Our goal was to develop a method of measuring the ICD surface potentials as the devices are tested during implantation surgery to use as verification of the simulation. A lead selection algorithm was used to develop a surface potential mapping system with 32 recording sites that do not interfere with implantation surgery. ICD discharge recordings were compared at similar locations to corresponding patient models. The reconstructed simulated surface potentials showed