Background Magnetic resonance imaging (MRI) has been used to acutely visualize radiofrequency ablation lesions, but its accuracy in predicting chronic lesion size is unknown. The main goal of this study was to characterize different areas of enhancement in late gadolinium enhancement MRI done immediately after ablation to predict acute edema and chronic lesion size.
Methods and Results In a canine model (n=10), ventricular radiofrequency lesions were created using ThermoCool SmartTouch (Biosense Webster) catheter. All animals underwent MRI (late gadolinium enhancement and T2-weighted edema imaging) immediately after ablation and after 1, 2, 4, and 8 weeks. Edema, microvascular obstruction, and enhanced volumes were identified in MRI and normalized to chronic histological volume. Immediately after contrast administration, the microvascular obstruction region was 3.2±1.1 times larger than the chronic lesion volume in acute MRI. Even 60 minutes after contrast administration, edema was 8.7±3.31 times and the enhanced area 6.14±2.74 times the chronic lesion volume. Exponential fit to the microvascular obstruction volume was found to be the best predictor of chronic lesion volume at 26.14 minutes (95% prediction interval, 24.35–28.11 minutes) after contrast injection. The edema volume in late gadolinium enhancement correlated well with edema volume in T2-weighted MRI with an R2 of 0.99.
Conclusion Microvascular obstruction region on acute late gadolinium enhancement images acquired 26.1 minutes after contrast administration can accurately predict the chronic lesion volume. We also show that T1-weighted MRI images acquired immediately after contrast injection accurately shows edema resulting from radiofrequency ablation.
Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.
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.
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.
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. 31, December, 2008.
S. Lew, C. Wolters, A. Anwander, S. Makeig, R.S. MacLeod. Low Resolution Conductivity Estimation to Improve Source Localization, In New Frontiers in Biomagnetism. Proceedings of the 15th International Conference on Biomagnetism, Vancouver, BC, Canada, August 21-25, 2006., International Congress Series, Vol. 1300, pp. 149--152. June, 2007.
C.H. Wolters, H. Köstler, C. Möller, J. Härtlein, L. Grasedyck, W. Hackbusch. Numerical Mathematics of the Subtraction Method for the Modeling of a Current Dipole in EEG Source Reconstruction Using Finite Element Head Models, In SIAM J. on Scientific Computing, Vol. 30, No. 1, pp. 24--45. 2007.
C.H. Wolters, H. Köstler, C. Möller, J. Härdtlein, A. Anwander. Numerical Approaches for Dipole Modeling in Finite Element Method Based Source Analysis, In New Frontiers in Biomagnetism. Proceedings of the 15th International Conference on Biomagnetism, Vancouver, BC, Canada, August 21-25, 2006., International Congress Series, Vol. 1300, pp. 189--192. June, 2007.
C.H. Wolters, A. Anwander, X. Tricoche, D.M. Weinstein, M.A. Koch, R.S. MacLeod. Influence of Tissue Conductivity Anisotropy on EEG/MEG Field and Return Current Computation in a Realistic Head Model: A Simulation and Visualization Study Using High-Resolution Finite Element Modeling, In Neuroimage, Vol. 30, No. 3, pp. 813--826. April, 2006.
C.H. Wolters, A. Anwander, G. Berti, U. Hartmann. Geometry-Adapted Hexahedral Meshes Improve Accuracy of Finite Element Method Based EEG Source Analysis, In IEEE Transactions on Biomedical Engineering, Vol. 54, No. 8, pp. 1446--1453. August, 2006.
D. Güllmar, J. Haueisen, M. Eiselt, F. Giessler, L. Flemming, A. Anwander, T. Knösche, C.H. Wolters, M. Dümpelmann, D.S. Tuch, J.R. Reichenbach. Influence of Anisotropic Conductivity on EEG Source Reconstruction: Investigations in a Rabbit Model, In IEEE Trans. Biomed. Eng., Vol. 53, No. 9, pp. 1841--1850. 2006.
D. Gullmar, J.R. Reichenbach, A. Anwander, T. Knosche, C.H. Wolters, M. Eiselt, J. Haueisen. Influence of Anisotropic Conductivity of the White Matter Tissue on EEG Source Reconstruction - An FEM Simulation Study, In Int. J. Bioelectromag., Vol. 7, No. 1, pp. 108--110. 2005.
S. Lew, C. Wolters, K. Lee, S. Makeig, G. Worrell, R.S. MacLeod. Epileptogenic Source Localization For Open Skull Head Model of Epilepsy By Independent Component Analysis And Inverse Dipole Fit Method, In 1st Annual Mountain West Biomedical Engineering Conference, 2005.
C. H. Wolters, A. Anwander, X. Tricoche, S. Lew, C.R. Johnson. Influence of Local and Remote White Matter Conductivity Anisotropy for a Thalamic Source on EEG/MEG Field and Return Current Computation, In Int.Journal of Bioelectromagnetism, Vol. 7, No. 1, pp. 203--206. 2005.
U. Schmitt, C.H. Wolters, A. Anwander, T. Knoesche. STR: A New Spatio-Temporal Approach for Accurate and Efficient Current Density Reconstruction, In Proceedings of The 14th International Conference on Biomagnetism, pp. 591--592. 2004.
C.H. Wolters, L. Grasedyck, A. Anwander, H. Hackbusch. Efficient Computation of Lead Field Bases and Influence Matrix for the FEM-Based EEG and MEG Inverse Problem, In Proceedings of The 14th International Conference on Biomagnetism, Boston, MA, pp. 104--107. August, 2004.
C.H. Wolters, L. Grasedyck, W. Hackbusch. Efficient Computation of Lead Field Bases and Influence Matrix for the FEM-Based EEG and MEG Inverse Problem, In Inverse Problems, Vol. 20, No. 4, pp. 1099--1116. 2004.
C.H. Wolters, A. Anwander, B. Maess, R.S. MacLeod, A.D. Friederici. The Influence of Volume Conduction Effects on the EEG/MEG Reconstruction of the Sources of the Early Left Anterior Negativity, In Proceedings of the IEEE Engineering in Medicine and Biology Society 26th Annual International Conference, San Francisco, CA, Vol. 5, pp. 3569--3572. September, 2004.
C.H. Wolters, A. Anwander, S. Reitzinger, G. Haase. Algebraic Multigrid with Multiple Right-Hand-Side Treatment for an Efficient Computation of EEG and MEG Lead Field Bases, In Proceedings of The 14th International Conference on Biomagnetism, Boston, MA, pp. 465--466. August, 2004.