Dr. Kung-Shan Cheng Profile

Dr. Kung-Shan Cheng

at Duke Univ Medical Ctr

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Publications (2)

Proceedings Article | 25 February 2009 Paper

Clinical utility of magnetic resonance thermal imaging (MRTI) for realtime guidance of deep hyperthermia

P. Stauffer, Oana Craciunescu, P. Maccarini, Cory Wyatt, K. Arunachalam, O. Arabe, V. Stakhursky, B. Soher, J. MacFall, Z. Li, William Joines, S. Rangarao, K. Cheng, S. Das, Carlos Martins, Cecil Charles, Mark Dewhirst, T. Wong, E. Jones, Z. Vujaskovic

Proceedings Volume 7181, 71810I (2009) https://doi.org/10.1117/12.812188

KEYWORDS: Tumors, Magnetic resonance imaging, Tissues, Temperature metrology, Antennas, Magnetism, Phased arrays, Sensors, Fiber optics sensors, Breast

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Proceedings Article | 12 February 2009 Paper

Control time reduction using virtual source projection for treating a leg sarcoma with nonlinear perfusion

Kung-Shan Cheng, Yu Yuan, Zhen Li, Paul Stauffer, William Joines, Mark Dewhirst, Shiva Das

Proceedings Volume 7181, 71810F (2009) https://doi.org/10.1117/12.808499

KEYWORDS: Tumors, Tissues, Blood, Antennas, Feedback control, Device simulation, Thermal modeling, Systems modeling, Bone, HVAC controls

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Purpose: Blood perfusion is a well-known factor that complicates accurate control of heating during hyperthermia treatments of cancer. Since blood perfusion varies as a function of time, temperature and location, determination of appropriate power deposition pattern from multiple antenna array Hyperthermia systems and heterogeneous tissues is a difficult control problem. Therefore, we investigate the applicability of a real-time eigenvalue model reduction (virtual source - VS) reduced-order controller for hyperthermic treatments of tissue with nonlinearly varying perfusion. Methods: We impose a piecewise linear approximation to a set of heat pulses, each consisting of a 1-min heat-up, followed by a 2-min cool-down. The controller is designed for feedback from magnetic resonance temperature images (MRTI) obtained after each iteration of heat pulses to adjust the projected optimal setting of antenna phase and magnitude for selective tumor heating. Simulated temperature patterns with additive Gaussian noise with a standard deviation of 1.0°C and zero mean were used as a surrogate for MRTI. Robustness tests were conducted numerically for a patient's right leg placed at the middle of a water bolus surrounded by a 10-antenna applicator driven at 150 MHz. Robustness tests included added discrepancies in perfusion, electrical and thermal properties, and patient model simplifications. Results: The controller improved selective tumor heating after an average of 4-9 iterative adjustments of power and phase, and fulfilled satisfactory therapeutic outcomes with approximately 75% of tumor volumes heated to temperatures >43°C while maintaining about 93% of healthy tissue volume < 41°C. Adequate sarcoma heating was realized by using only 2 to 3 VSs rather than a much larger number of control signals for all 10 antennas, which reduced the convergence time to only 4 to 9% of the original value. Conclusions: Using a piecewise linear approximation to a set of heat pulses in a VS reduced-order controller, the proposed algorithm greatly improves the efficiency of hyperthermic treatment of leg sarcomas while accommodating practical nonlinear variation of tissue properties such as perfusion.

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