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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 - PowerPoint PPT Presentation
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Treatment Time Reduction through Parameter Optimization in Magnetic Resonance Guided High Intensity Focused Ultrasound Therapy
Joshua CoonDecember 7, 2011
PART ONE: OVERVIEW AND THEORY
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
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
HIFU Transducer
Safety, Efficacy and Treatment Time
Ultrasound Transducer
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
Treatment Parameters
Controllable• 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
Non-Controllable• Physiological parameters
– Perfusion and conduction– Tissue composition– Tumor geometry– Tumor location
Ultrasound Transducer
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
Treatment Time
• Objective function for optimization routines• Has additional constraints to ensure treatment
efficacy and patient safety
𝒕 𝒕𝒓𝒆𝒂𝒕𝒎𝒆𝒏𝒕=∑𝒏=𝟏
𝑵𝒕𝒉𝒆𝒂 𝒕𝒏+𝒕𝒄𝒐𝒐𝒍𝒏
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
PART TWO: MY RESEARCH
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.
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
11.2 cm
3.3 cm
3.3 cm3.3 cm
x y
z
Normal tissue constraintsat +/- 1cm
Simulation Geometry Tumor = 1.8cm x 1.8cm x 0.8cm
43 °C Normal tissue limit
37 °C Region boundary
Pennes equation
Homogeneous\constant tissue properties
240 CEM in tumor
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
Thermal and Tissue Damage Modeling
• Thermal modeling via finite difference time domain approximation of bioheat equation1. Region broken into small cubes with constant physical and
acoustic properties2. Cubes start with temperature at time 3. Conduction, perfusion, and heat deposition (via calculated for
each cube4. and started again
• Tissue damage (thermal dose) integrated from generated temperature maps
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 path from the first part of the study
Simulation Region
Back
Middle
Front
Tumor
1 2 3 4 5 6
7 8 9 10 11 12
13 14 15 16 17 18
19 20 21 22 23 24
25 26 27 28 29 30
31 32 33 34 35 36
37 38 39 40 41 42
43 44 45 46 47 48
49 50 51 52 53 54
55 56 57 58 59 60
61 62 63 64 65 66
67 68 69 70 71 72
73 74 75 76 77 78
79 80 81 82 83 84
85 86 87 88 89 90
91 92 93 94 95 96
97 98 99 100 101 102
103 104 105 106 107 108
PL (BMF); XY Ra AS (MBF); XY Ra 2 5 8 11 14 17
20 23 26 29 32 35
38 41 44 47 50 53
56 59 62 65 68 71
74 77 80 83 86 89
92 95 98 101 104 107
1 4 7 10 13 16
19 22 25 28 31 34
37 40 43 46 49 52
55 58 61 64 67 70
73 76 79 82 85 88
91 94 97 100 103 106
3 6 9 12 15 18
21 24 27 30 33 36
39 42 45 48 51 54
57 60 63 66 69 72
75 78 81 84 87 90
93 96 99 102 105 108
Results
AS (MFB)XYRa
AS (MBF) XYRa
PL (MFB)XYRa
AS (FBM) XYRa
AS (FMB) XYRa
3D Max Last
3D Max First
3D Kn
PL (FBM) XYKn
AS (BFM) XYRa
AS (BMF) XYRa
PL (BFM)XYKn
Pl (BMF) XYRa
Pl (BMF) XZRa
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2200
Focal Zone Path
Trea
tmen
t Tim
e (s
)
58%
0%0%
38%30%
32%
50%
63%47%
Treatment Path
Conclusion:
• Treatment path selection reduces treatment time
Additional Path Studies
• Also ran for subset of paths and several perfusion and transducer power levels
• The ordering of the paths remained unchanged
0 5 10 15 20 250
2
4
6
8
10
12
14
16
18
20
Time (s)
Tem
pera
ture
Ris
e (C
)
Middle
Back
Front
Adjacent
Single Pulse Heating: Middle Plane
17 18 19 20 21 22
36 5 6 7 8 23
35 16 1 2 9 24
34 15 4 3 10 25
33 14 13 12 11 26
32 31 30 29 28 27
1 22 34 8 29 16
33 13 30 15 23 7
21 2 9 6 17 28
12 31 14 24 35 5
25 20 3 10 27 18
32 11 26 19 4 36
1 2 3 10 11 12
8 9 4 17 18 13
7 6 5 16 15 14
19 20 21 28 29 30
26 27 22 35 36 31
25 24 23 34 33 32
1 2 3 4 5 6
14 15 16 17 18 7
13 12 11 10 9 8
19 20 21 22 23 24
32 33 34 35 36 25
31 30 29 28 27 26
Transverse PathsExtensions:
• Take best axial stack and study transverse paths
Inner-Middle-Outer (IMO) Knight Jumps (Kn)
Small Squares (Sq) Large Rectangles (Rec)
Trea
tmen
t Tim
e (s
)
Transverse Path
* *
*
*
*
10% 11% 29%39% 43% 43%
57%
72%
79%
6 Degree Constraint
5 Degree Constraint2500
3000
3500
1500
2000
1000
500
0Kn IOM IMO Ra MOI OMI OIM Rec MIO Sq
Transverse Path Study
Conclusions: • Adjacency of axial
stacks desirable for higher normal tissue temperature limit
• Adjacency of axial stacks undesirable for lower normal tissue temperature limit
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
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
Second Paper: In Preparation
• HIFU Treatment Time Reduction through Optimal Scanning,
Coon J, Todd N, Roemer R.
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
9.5 cm
7.0 cm
7.0 cm7.0 cm
x y
z
Temperature/dose constraintsat +/- 1cm from tumor edge
Skin/Water Interface
Focal Zone Spacing
x
x
Tumor
Simulation Schematic
Axial Tumor Close-up1.0mm
16, 30mm
Simulation Region
Concentrated vs. Diluted Focal Zones
x
x
x
x
x
x
Next Position Next Position
100%
0%
0%
100% 50%
50%
Concentrated Diluted
Small Axial Tumor
0 2 4 6 8 10 12 1460
80
100
120
140
160
180
200
220
Distance between Focal Zone Centers (mm)
Trea
tmen
t Tim
e (s
ec)
69/31%
40/60%
40/60%
40/60% 43/57%
59/41%
74/26%
68/32%
66/34%
64/35%
73/27%
Conclusions:
• Optimal spacing around 8 or 10mm
• Concentrated focal zones faster than diluted focal zones
x xx x
x x x x
Multi-Position Axial Treatments
3 Position2 Position
4 Position 17 Position
Concentrated vs. Diluted Focal Zones: Small Axial Tumor
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1860
80
100
120
140
160
180
200
220
Number of Focal Zone Locations
Hea
ting
Tim
e
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
Transverse Spacing Optimization
x
x
x
x
Volume Treated
•Both stacks & volume between treated•Vary stack transverse distance•Compare ablation rates (mm3/sec) because treatment volumes unequal
Treatment Approach:1, 2, 3, 4, 5, 6mm
16mm
2 Adjacent Axial Stacks: Control Volume Ablation Rates
1 2 3 4 5 60.1
0.15
0.2
0.25
0.3
0.35
Distance Between Axial Stack Centers (mm)
Con
trol V
olum
e A
blat
ion
Rat
e (m
m3 /s
ec)
54/20/15/10%
31/30/13/25%33/30/9/26%
31/32/7/30%
43/41/0/16%
54/21/11/14%
25/25/25/25%
25/25/25/25%
25/25/25/25% 25/25/25/25%25/25/25/25%
25/25/25/25%
Conclusions:
• Concentrated treatments faster than diluted across range of transverse spacings
• Optimal transverse spacing at 3mm
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 scans had 15 seconds of heating per point with one repeat
• Diluted scans had 0.1 seconds of heating per point with 150 repeats
Concentrated vs. Diluted
• MR temperature data used to calculate thermal dose
Concentrated Cartesian
Diluted Cartesian Concentrated Circles Diluted Circles
100
200
300
400
500
600
Phantom Treatment Type
Num
ber o
f Vox
els
Trea
ted
to 2
40
YZ Plane
XZ Plane
XY Plane
Phantom Experiment: Dose Comparison
Conclusions:
• Concentrated treatments have higher ablation rates than diluted treatments
Simulation to Phantom Matching
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
Method:
Distance (mm)
Dis
tanc
e (m
m)
20 40 60 80 100
20
40
60
80
100
Simulation/Phantom Matching
0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.720
40
60
80
100
120
140
160
180
Simulation Conduction Coefficient [W/(m*C)]
Vox
els
Diff
eren
t Bet
wee
n S
imul
atio
n/P
hant
om
3.02.3
3.22.72.62.5 2.8 2.8
240 CEM Dose Line
30 CEM Dose Line
Conclusions:
• Reasonable match between simulation/phantom dose possible
• The best match for the 30 CEM line corresponds to “literature value” for agar phantom conduction
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
Dwell Time Results
Diluted FZ 0.1 Sec 1.0 Sec Non-Optimed Concentrated FZ
Optimized Concentrated FZ
200
210
220
230
240
250
260
270
280
290
Hea
ting
Tim
e
Conclusion: Making treatments increasingly concentrated shortens treatment times
Dwell Time
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
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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