Award Abstract #0427183
ITR: Collaborative Research - \(ASE\) - \(DMC\): DDDAS: A Novel Grid Architecture Integrating Real-Time Data and Intervention During Image Guided Therapy

NSF Org:	CNS Division of Computer and Network Systems
Initial Amendment Date:	September 15, 2004
Latest Amendment Date:	July 26, 2005
Award Number:	0427183
Award Instrument:	Continuing grant
Program Manager:	Anita J. LaSalle CNS Division of Computer and Network Systems CSE Directorate for Computer & Information Science & Engineering
Start Date:	October 1, 2004
Expires:	September 30, 2007 (Estimated)
Awarded Amount to Date:	$325000
Investigator(s):	Kim Baldridge kimb@sdsc.edu (Principal Investigator) Maryann Martone (Co-Principal Investigator) Amitava Majumdar (Co-Principal Investigator)
Sponsor:	University of California-San Diego Office of Contract & Grant Admin La Jolla, CA 92093 858/534-4896
NSF Program(s):	ITR-INFORMATION INTEGRATION, ITR FOR NATIONAL PRIORITIES
Field Application(s):	0000912 Computer Science
Program Reference Code(s):	HPCC, 9218
Program Element Code(s):	7373, 7314

ABSTRACT

The project's research involves development and deployment of an integrated and practical grid

architecture for data driven intra-operative volumetric simulation of brain deformation during

image guided therapy (IGT) and specifically for image guided neurosurgery (IGNS) to be

employed in the operating room of the future. Preliminary work has resulted in a prototype

dynamic data driven system, which resides locally in the operating room for IGNS that integrates

data acquisition, surgical navigation, quantitative monitoring and enhanced real-time control. The

proposed project will enable improvement in the safety and efficacy of brain tumor resection by

extending the current system with a tightly coupled capability for interactively steered and

adaptive data driven simulation of the dynamically shifting shape of the brain. Such simulation

capability, integrated with real-time intra-operative data acquisition capability and real-time

surgical resection, requires on-demand low latency fault tolerant robust and reliable access to

remotely located significant compute capacity and data management resources from the operating

room. Recent advances in grid infrastructure hold out the promise to pioneer such capability. The

overall objective of this projectl is the development of a novel grid architecture integrating real-

time data to allow intra-operative surgical decision-making and navigation during IGT. In

addition this will provide database infrastructure for post-surgical analysis and modeling of data

and image repositories. The project's information technology (IT) research is expected to have

broad impact on clinical practice within a period of a few years.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

100. Majumdar, A.; Birnbaum, A.; Choi, D.; Trivedi, A.; Warfield, S.K.; Baldridge, K.K.; Krysl, P.. "A Dynamic Data Driven Grid System for Intra-Operative Image Guided Neurosurgery," In Computational Science ? ICCS 2005: 5th International Conference, Proceedings, v.3515, 2005, p. 672.

C.~R. Dohrmann, M.~W. Heinstein, J.~Jung, S.~W. Key, and W.~W. Witkowski.. "Node-based uniform strain elements for three-node triangular and four-node tetrahedral meshes.," International Journal for Numerical Methods in Engineering,, v.47, 2000, p. 1549.

E. Grinspun, P. Krysl, and P. Schroder P. "CHARMS: A simple framework for adaptive simulation," ACM Transactions on Graphics,, v.21, 2002, p. 281.

G. Soza, R. Grosso, C. Nimsky, G. Greiner, P. Hastreiter. "Estimating mechanical brain tissue properties with simulation and registration," Medical Image Computing and Computer-Assisted Intervention, v.3217, 2004, p. 276.

L. Endres, P. Krysl. "Octasection-based refinement of finite element approximations of tetrahedral meshes that guarantees shape quality," International Journal for Numerical Methods in Engineering,, v.59, 2004, p. 69.

P. Krysl, A. Trivedi, and B. Z. Zhu. "Object-oriented hierarchical mesh refinement with CHARMS," International Journal for Numerical Methods in Engineering, v.60, 2004, p. 1401.

P. Krysl, E. Grinspun, and P Schroder. "Natural Hierarchical Refinement," International Journal of Numerical Methods in Engineering, v.56, 2003, p. 1109.

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