T. Fogal, H. Childs, S. Shankar, J. Krüger, R.D. Bergeron, P. Hatcher. Large Data Visualization on Distributed Memory Multi-GPU Clusters, In Proceedings of High Performance Graphics 2010, pp. 57--66. 2010.
B.M. Isaacson, J.G. Stinstra, R.S. MacLeod, P.F. Pasquina, R.D. Bloebaum.
Developing a Quantitative Measurement System for Assessing Heterotopic Ossification and Monitoring the Bioelectric Metrics from Electrically Induced Osseointegration in the Residual Limb of Service Members, In Annals of Biomedical Engineering, Vol. 38, No. 9, pp. 2968-–2978. 2010.
PubMed ID: 20458630
F. Jiao, J.M. Phillips, J.G. Stinstra, J. Kueger, R. Varma, E. Hsu, J. Korenberg, C.R. Johnson. Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images, In Proceedings of the 5th international conference on Medical imaging and augmented reality (MIAR), Beijing, China, Springer-Verlag, Berlin, Heidelberg pp. 179--190. September, 2010.
Total subcutaneous implantable subcutaneous defibrillators are in development, but optimal electrode configurations are not known.
In this paper we present a novel approach to generate proxy geometry for slice based volume rendering. The basic idea is derived from the behavior of a ray-caster and is a simple extension of the well known 2D object-aligned texture stack based technique. From this our novel scheme inherits the advantage that it enables hardware-based volume rendering for devices that do not support 3D textures. On these devices previous object-aligned 2D texture based approaches suffered from disturbing view angle dependent stack-switching artifacts which are avoided by our novel method. Our approach also shows benefits compared to the widely used view aligned slicing algorithm as it avoids jagged boundary artifacts and increases performance.
S.S. Kuppahally, N. Akoum, N.S. Burgon, T.J. Badger, E.G. Kholmovski, S. Vijayakumar, S.N. Rao, J. Blauer, E.N. Fish, E.V. Dibella, R.S. Macleod, C. McGann, S.E. Litwin, N.F. Marrouche.
Left atrial strain and strain rate in patients with paroxysmal and persistent atrial fibrillation: relationship to left atrial structural remodeling detected by delayed-enhancement MRI, In Circ Cardiovasc Imaging, Vol. 3, No. 3, pp. 231--239. 2010.
PubMed ID: 20133512
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.
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.
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.
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.
In this paper we propose a supervised 3D segmentation algorithm to locate the esophagus in thoracic CT scans using a variational framework. To address challenges due to low contrast, several priors are learned from a training set of segmented images. Our algorithm first estimates the centerline based on a spatial model learned at a few manually marked anatomical reference points. Then an implicit shape model is learned by subtracting the centerline and applying PCA to these shapes. To allow local variations in the shapes, we propose to use nonlinear smooth local deformations. Finally, the esophageal wall is located within a 3D level set framework by optimizing a cost function including terms for appearance, the shape model, smoothness constraints and an air/contrast model.
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.
K. Potter, J.M. Kniss, R. Riesenfeld, C.R. Johnson. Visualizing Summary Statistics and Uncertainty, In Computer Graphics Forum, Vol. 29, No. 3, Wiley-Blackwell, pp. 823--831. Aug, 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
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.
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.
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.