1. Surgical Planning Laboratory Brigham and Women’s Hospital Boston, Massachusetts USA a teaching affiliate of Harvard Medical School Functional Data Analysis for Neurosurgical Applications William Wells PhD

2. ©2005 Surgical Planning Laboratory, ARR Slide 2 Research Problems Compare and contrast Functional MRI (fMRI) and Electrocorticography (EC) –Validate fMRI for surgical mapping From fMRI, Identify brain systems in patients and the normal population –Build functional atlas –Find important system structure in surgical patients

3. ©2005 Surgical Planning Laboratory, ARR Slide 3 Science Questions: fMRI / EC Different types of info –fMRI 3D information observe activity –EC Usually analyzed in 2D observe inhibition of activity –Approach: 3D simulation of stimulaiton

4. ©2005 Surgical Planning Laboratory, ARR Slide 4 Science Questions: fMRI System Identification fMRI connectivity analysis is challenging –Relatively poor spatial and temporal resolution Population level analysis is important –Characterize “normals” –Statistical power from averaging –New area of research Approach –Bayesian Modeling of Effective Connectivity

5. ©2005 Surgical Planning Laboratory, ARR Slide 5 Compare Electro-Corticography and fMRI in 3D MIT MS December 2003: Sara E. Larsen –Quantitative Comparison of Functional MRI and Electro-Cortical Stimulation for Functional Mapping Programmatic Aspects: –In Collaboration with BioPSE (Utah P41) –NAC: develop algorithms for neurosurgical and neurological image analysis –IGT: deploy in neurosurgery Modeling of Direct-Electro Cortical Stimulation

6. ©2005 Surgical Planning Laboratory, ARR Slide 6 Background EC is established method for intraoperative functional mapping fMRI is attractive –pre-operative –non-invasive –sub-surface information display both in 3D visualizations (eventually) validate fMRI for neurosurgical functional mapping

7. ©2005 Surgical Planning Laboratory, ARR Slide 7 Surgical Case male seizures some word finding and other expressive problems diffuse astrocytoma partial resection no post-operative deficit

8. ©2005 Surgical Planning Laboratory, ARR Slide 8 Pre-op SPGR

9. ©2005 Surgical Planning Laboratory, ARR Slide 9 Brain Segmentation

10. ©2005 Surgical Planning Laboratory, ARR Slide 10 Patient-Specific Brain Geometry Provided by Sara Larsen

11. ©2005 Surgical Planning Laboratory, ARR Slide 11 Estimate Electrical Conductivity from observed Diffusion Tensors Provided by Sara Larsen

12. ©2005 Surgical Planning Laboratory, ARR Slide 12 Load mesh with conductivity tensors from DTI Provided by Sara Larsen

13. ©2005 Surgical Planning Laboratory, ARR Slide 13 Approach Incorporate stimulator coordinates and current solve for 3D current density –SCIRUN software: BioPSE, Chris Johnson, U. Utah display results

14. ©2005 Surgical Planning Laboratory, ARR Slide 14 Solved Current Densities Provided by Sara Larsen

15. ©2005 Surgical Planning Laboratory, ARR Slide 15 EC Isosurface and fMRI Activation Provided by Sara Larsen

16. ©2005 Surgical Planning Laboratory, ARR Slide 16 Detail... Provided by Sara Larsen

17. ©2005 Surgical Planning Laboratory, ARR Slide 17 EC / fMRI status Development of method Initial demonstration by Larsen IGT: deploy in OR NAC: Further development of methodology for joint statistical analysis

18. ©2005 Surgical Planning Laboratory, ARR Slide 18 fMRI Population Connectivity Analysis Effective Connectivity among brain regions Populations of Subjects MIT PhD August ’05: Eric Cosman: Bayesian Population Inference for the Multivariate Autoregressive Process Programmatic Aspects NAC: develop algorithms for neurosurgical and neurological image analysis IGT: deploy in neurosurgery fBIRN: deploy on multi-site fMRI data(Schizophrenia) NAMIC: disseminate to collaborator DBPs

19. ©2005 Surgical Planning Laboratory, ARR Slide 19 Approach MultiVariate Autoregressive (MAR) modeling at individual level –Frequently used time series model, finance, etc Random Effects (RFX) modeling of population –Standard methodology for group analysis –Individual MAR models drawn from statistical model of the population

20. ©2005 Surgical Planning Laboratory, ARR Slide 20 Connectivity Inference V1Fus V5 Infer directional influence among brain regions based on local measurements of brain activity Data from EEG, MEG, fMRI or electrical recording Eric Cosman, Jr.

21. ©2005 Surgical Planning Laboratory, ARR Slide 21 Language fMRI Visual Word Presentation Spoken Antonym Language function is left lateralized Event-related paradigm Work with Ralph Suarez & Alex Golby (BWH) Visually-presented antonym generation task:

22. ©2005 Surgical Planning Laboratory, ARR Slide 22 Language fMRI Visually-presented antonym generation task Event-related Paradigm: (1)Primary VisualBA 17 (2)Wernicke’s AreaBA 40 & 22 (3)Broca’s AreaBA 44 & 45 (4)Primary MotorBA 6 Average ISI = 8.75 sec 7 right-handed subjects TR = 1 sec 420 sec / run Homologous ROIs in both hemispheres:

23. ©2005 Surgical Planning Laboratory, ARR Slide 23 Connectivity Statistics and P-Values The connectivity statistic (top) and the permutation p-value (bottom) for each interaction in both hemispheric networks

24. ©2005 Surgical Planning Laboratory, ARR Slide 24 RFX-MAR Connectivity Analysis Left HemisphereRight Hemisphere Graphical representation of inferred population-level connectivity for the left and right hemisphere networks

25. ©2005 Surgical Planning Laboratory, ARR Slide 25 RFX-MAR status Substantial Methodological Development in Cosman Thesis NAC: solidify implementation fBIRN: apply to fBIRN data –Populations: normal, schiz NAMIC: –Application Collaborations with DBPs

26. ©2005 Surgical Planning Laboratory, ARR Slide 26 Conclusions Described two new approaches to neurological functional analysis Both address important application problems Future –deployment of technology –Additional development