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HIFU Treatment Time Reduction by User Controlled Parameter Search

HIFU Treatment Time Reduction by User Controlled Parameter Search. Joshua Coon, Bob Roemer December 13, 2010. Axial Study. Start with 2 Position Study:. Several Factor to Consider:. 1. Heating Times. Treatment Order / Time Sharing. Amount of Overlap. Offset from Tumor Center. 2.

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HIFU Treatment Time Reduction by User Controlled Parameter Search

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  1. HIFU Treatment Time Reduction by User Controlled Parameter Search Joshua Coon, Bob Roemer December 13, 2010

  2. Axial Study Start with 2 Position Study: Several Factor to Consider: 1 Heating Times Treatment Order / Time Sharing Amount of Overlap Offset from Tumor Center 2 Distance to Tumor Boundary

  3. Treatment Time Reduction: Mathematical Formulation Minimize: • T_Heat,n and T_Cool,n are the sum of the nth heating and cooling times. • N is the number of positions • Thermal Dose (TD) is a metric for tissue damage as a function of temperature and time • Temp Limit Impose in healthy tissue • Can Solve with Matlab Optimization Toolbox (fmincon) Constraints:

  4. Minimizing Treatment Times Algorithmically

  5. Treatment Treatment Treatment fmincon fmincon fmincon Compare final times Lowest Time

  6. What Does “fmincon” Do? fmincon = “Function minimization with constraints” Different “solvers” to select next point: Interior Point, SQP, Active Set, etc. • Function = sum(x) where x is vector of heating and cooling times at each position • Constraints = Dose inside tumor > 240 CEM • = NT temp limit < 6 degrees C • Both evaluated in terms of external functions I wrote by fmincon solver

  7. What Does Constraint Function Do? Time / spatial resolution for temps a consideration

  8. Optimal Axial Overlap Dependences: FZ Path (F->B, B->F) Tumor Size Perfusion Spacing • Spacing: 0, 2, 4, 6, 8, 10, 12, 14, 16 mm

  9. Results: Axial Spacing (1x1x16mm^3 tumor) • Strong Minimum around 10 mm separation

  10. Problem: Convergence To Solution • Fmincon may not always converge to a solution from a given starting point • Can happen in cases where starting point is too far away from function minimum • Must restart from another pointor use another fmincon “solver”

  11. Problem: Local vs. Global Minima

  12. Problem: Computing Resources Limits • More than >20,000 hours of computer time used in last 3 months • Optimizations run with 2-3 per computer (larger CPU than CPU on GPU) • Requires about 3 days to run to completion • Extensive Study may require even more time • Best CPUs at CHPC limited to 24 hour checkout

  13. Future Directions • Vary offset, power level, perfusion, tumor size for 2 positions • Expand Study to 3 positions, 4 positions, and more if needed. • Solve computer memory issues currently limiting region size. • Will require a lot of computer time

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