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Joshua Coon December 7, 2011

Treatment Time Reduction through Parameter Optimization in Magnetic Resonance Guided High Intensity Focused Ultrasound Therapy. Joshua Coon December 7, 2011. Part one: overview and theory. High Intensity Focused Ultrasound (HIFU): Overview. Ultrasound energy used to heat/ablate tissue

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Joshua Coon December 7, 2011

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  1. Treatment Time Reduction through Parameter Optimization in Magnetic Resonance Guided High Intensity Focused Ultrasound Therapy Joshua Coon December 7, 2011

  2. Part one: overview and theory

  3. High Intensity Focused Ultrasound (HIFU): Overview • Ultrasound energy used to heat/ablate tissue • Magnifying glass and light • Clinical use as cancer therapy • Several advantages over traditional therapies • Area of active research • Extensive clinical trials in China and Europe

  4. Why Use HIFU? • No poisonous chemicals • Chemotherapy • No ionizing radiation • However, sometimes HIFU used with radiation • Relatively non-invasive • Compared to surgery • Shorter recovery time • Outpatient procedure; short repetition time

  5. HIFU Transducer

  6. Safety, Efficacy and Treatment Time • Safety • Reduce healthy tissue heating • Efficacy • Ensure entire tumor treated • Treatment Time • Long treatments reduce safety and efficacy • Patient movement • Permanent tissue property changes • Attenuation coefficient • Cost Ultrasound Transducer

  7. Treatment Parameters Controllable Non-Controllable Physiological parameters Perfusion and conduction Tissue composition Tumor geometry Tumor location • Transducer manufacturing • Central beam frequency • Number of elements • Size and radius of curvature • Transducer state • Power level • Power on and off times • Characteristics of focal zones • Focal zone size(s) • Focal zone shape(s) • Duty cycle for diluted focal zones • Spacing(s) between focal zones • Focal zone packing • Path of focal zones through tumor • Axial and transverse Ultrasound Transducer

  8. Components of HIFU Treatment Simulations • Ultrasound Attenuation Equation • Models how ultrasound energy is converted to heat • Heat Flow Equation • Models flow of heat through the body • Thermal Damage Equation • Models how much tissue is damaged due to heating

  9. Treatment Time • Objective function for optimization routines • Has additional constraints to ensure treatment efficacy and patient safety

  10. Treatment Time Optimization • Run computer simulated treatments to optimize user controllable parameters – to minimize treatment time • Large number of possible treatments ~ • Well in excess of 200,00 computer hours lifetime • Confine investigations to parameters likely to realize the greatest gains • Trajectory of focal zone • Focal zone size • Focal zone spacing

  11. Part two: my research

  12. First Paper: Treatment Time Reduction through Treatment Path Optimization • Coon J, Payne A, Roemer R. HIFU treatment time reduction in superficial tumours through focal zone path selection. International Journal of Hyperthermia. 2011;27(5):465-81.

  13. Study Motivation • Reduce MRgHIFU treatment times • Strategies for treatment path selection • Develop a model of the physics behind treatment time reductions • Role of thermal superposition • Tumor • Normal tissue • Role of non-linear rate of thermal damage

  14. 3.3 cm 3.3 cm z Normal tissue constraints at +/- 1cm x y 3.3 cm 11.2 cm Simulation Geometry • Tumor = 1.8cm x 1.8cm x 0.8cm • 43 °C Normal tissue limit • 37 °C Region boundary • Pennesequation • Homogeneous\constant • tissue properties • 240 CEM in tumor

  15. Ultrasound Modeling • Ultrasound beam from transducer modeled via Hybrid Angular Spectrum (HAS) method • Modeled with parameters taken from a 256 element phased array used in experiments • Developed by Dr. Christensen of the Bioengineering department

  16. Thermal and Tissue Damage Modeling • Thermal modeling via finite difference time domain approximation of bioheat equation • Region broken into small cubes with constant physical and acoustic properties • Cubes start with temperature at time • Conduction, perfusion, and heat deposition (via calculated for each cube • and started again • Tissue damage (thermal dose) integrated from generated temperature maps

  17. Treatment Path • Tumor ablated using three treatment planes • Conservative spacings of 3mm for planes • Planes 15 or 36 positions each • Paths divided into two major categories • Axially Stacked • Non-Axially Stacked • Transverse paths were investigated with the best pathfrom the first part of the study

  18. PL (BMF); XY Ra AS (MBF); XY Ra Back Simulation Region Middle Tumor Front

  19. Results

  20. 58% 2200 50% 2000 1800 63% 47% 1600 1400 32% 1200 Treatment Time (s) 30% 1000 38% 800 0% 600 0% 400 200 0 AS (MFB) XYRa AS (MBF) XYRa PL (MFB) XYRa AS (FBM) XYRa AS (FMB) XYRa PL (FBM) XYKn AS (BFM) XYRa AS (BMF) XYRa PL (BFM) XYKn Pl (BMF) XYRa Pl (BMF) XZRa 3D Max Last 3D Max First 3D Kn Focal Zone Path Treatment Path • Conclusion: • Treatment path selection reduces treatment time

  21. Additional Path Studies • Also ran for subset of paths and several perfusion and transducer power levels • The ordering of the paths remained unchanged

  22. 20 18 16 14 12 Temperature Rise (C) 10 8 6 4 2 0 0 5 10 15 20 25 Time (s) Single Pulse Heating: Middle Plane Middle Front Back Adjacent

  23. Transverse Paths • Extensions: • Take best axial stack and study transverse paths Inner-Middle-Outer (IMO) Knight Jumps (Kn) Small Squares (Sq) Large Rectangles (Rec)

  24. 79% Transverse Path Study 3500 * 3000 5 Degree Constraint 2500 • Conclusions: • Adjacency of axial stacks desirable for higher normal tissue temperature limit • Adjacency of axial stacks undesirable for lower normal tissue temperature limit 2000 72% * Treatment Time (s) 1500 57% * 43% 43% 1000 39% * * 29% 11% 10% 6 Degree Constraint 500 0 Kn IOM IMO Ra MOI OMI OIM Rec MIO Sq Transverse Path

  25. Additional Studies • Over 125 paths studied in total, including over 100 random paths (not shown) • Two additional tumor models studied: • Large superficial tumor • Medium deep tumor • Results consistent across several paths and tumor models

  26. Conclusions • Treatment path selection can greatly reduce treatment times • Axial stacking provides largest treatment time reduction • Middle-Front-Back stack ordering always fastest • Effective use of thermal superposition • Transverse stack “adjacency” selection depends on normal tissue constraints • High adjacency for higher temperature limit • Low adjacency for lower temperature limit • Effects hold for range of perfusions, transducer power levels, and tumor sizes and depths

  27. Second Paper: In Preparation • HIFU Treatment Time Reduction through Optimal Scanning, Coon J, Todd N, Roemer R.

  28. Goals of Second Paper • Compare “Concentrated” versus “Diluted” focal zone treatment strategies • Study optimal focal zone spacing and packing • Verify concentrated vs. diluted results in phantom model

  29. 7.0 cm 7.0 cm z Temperature/dose constraints at +/- 1cm from tumor edge x y 7.0 cm 9.5 cm Simulation Region Axial Tumor Close-up Simulation Schematic 1.0mm Tumor x 16, 30mm Skin/Water Interface Focal Zone Spacing x

  30. Concentrated vs. Diluted Focal Zones Concentrated Diluted 100% 0% 50% x x x Next Position Next Position 0% 100% 50% x x x

  31. 220 200 68/32% 180 64/35% 160 74/26% Treatment Time (sec) 140 40/60% 40/60% 43/57% 120 66/34% 40/60% 100 69/31% 59/41% 80 73/27% 60 0 2 4 6 8 10 12 14 Distance between Focal Zone Centers (mm) Small Axial Tumor • Conclusions: • Optimal spacing around 8 or 10mm • Concentrated focal zones faster than diluted focal zones

  32. Multi-Position Axial Treatments x x 3 Position 2 Position x x x x x x 4 Position 17 Position

  33. Concentrated vs. Diluted Focal Zones: Small Axial Tumor • Conclusion: • Concentrated focal zones treatments faster than diluted for treatments using wide range of focal zone packings • Diminishing returns with increased packing in concentrated treatments

  34. Transverse Spacing Optimization 1, 2, 3, 4, 5, 6mm Treatment Approach: • Both stacks & volume between treated • Vary stack transverse distance • Compare ablation rates (mm3/sec) because treatment volumes unequal x x 16mm x x Volume Treated

  35. 0.35 /sec) 31/30/13/25% 33/30/9/26% 3 31/32/7/30% 0.3 54/21/11/14% 0.25 54/20/15/10% 43/41/0/16% Control Volume Ablation Rate (mm 0.2 0.15 0.1 1 2 3 4 5 6 Distance Between Axial Stack Centers (mm) 2 Adjacent Axial Stacks: Control Volume Ablation Rates • Conclusions: • Concentrated treatments faster than diluted across range of transverse spacings • Optimal transverse spacing at 3mm 25/25/25/25% 25/25/25/25% 25/25/25/25% 25/25/25/25% 25/25/25/25% 25/25/25/25%

  36. Concentrated vs. Diluted Scanning: Agar Phantom Concentric Circles 25 points Circles with 1,8 and 16 points Radii of 0mm, 2.25mm and 4.5mm Cartesian Grid 25 points 5x5 grid 2mm between points Concentrated vs. Diluted • MR temperature data used to calculate thermal dose • Concentrated scans had 15 seconds of heating per point with one repeat • Diluted scans had 0.1 seconds of heating per point with 150 repeats

  37. 600 YZ Plane 500 XZ Plane 400 Number of Voxels Treated to 240 300 200 XY Plane 100 Concentrated Cartesian Diluted Cartesian Concentrated Circles Diluted Circles Phantom Treatment Type Phantom Experiment: Dose Comparison • Conclusions: • Concentrated treatments have higher ablation rates than diluted treatments

  38. Simulation to Phantom Matching Method: 1.Simulate treatments with variable transducer power and conduction 2. Match dose 240/30 CEM dose contour lines between simulation/phantom 3. Use matched power/conduction to treat volume with different dwell times at each position

  39. Simulation/Phantom Matching • Conclusions: • Reasonable match between simulation/phantom dose possible • The best match for the 30 CEM line corresponds to “literature value” for agar phantom conduction

  40. Dwell Time Study Method • Use data from simulation/phantom matching study to set transducer power/conduction coefficient • Reproduce phantom treatments modified to treat a small control volume • Compare treatments with different dwell times per position

  41. 290 Dwell Time Results 280 270 260 250 Heating Time 240 Conclusion: Making treatments increasingly concentrated shortens treatment times 230 220 210 200 Diluted FZ 0.1 Sec Optimized Concentrated FZ Non-Optimed Concentrated FZ 1.0 Sec Dwell Time

  42. Conclusions • Concentrated focal zones treatments faster than diluted focal zones • Verified in agar phantom • Verified in simulations matched to phantom • Optimal axial spacing has small amount of overlap between focal zones • Optimal transverse spacing with small gap between axial stacks • Diminishing returns with increased packing

  43. Future Work • Verify axial path, concentrated vs. diluted, and optimal spacing results in phantom/animal models • Expand simulations to patient specific geometries and changing ultrasound attenuation and blood perfusion values • Preliminary work done with axial path and “worst-case” attenuation change model

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