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Verification Arthur Boyer Stanford University School of Medicine Stanford, California Clinical Aspects Radiobiological Aspects Planning Delivery.

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Presentation on theme: "Verification Arthur Boyer Stanford University School of Medicine Stanford, California Clinical Aspects Radiobiological Aspects Planning Delivery."— Presentation transcript:

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2 Verification Arthur Boyer Stanford University School of Medicine Stanford, California Clinical Aspects Radiobiological Aspects Planning Delivery

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4 Complexity Time IMRT planning Conventional planning

5 Establish the Correspondence Between Output and Input Input Output Desired output Specify a dose distribution--dose based model Specify quantities that describe a patient’s quality of life (e.g., Karnofsky status) Specify TCP and NTCP--biological model

6 Procedures of Inverse Planning Computation Construct an objective function F = F (input parameters) = F (w 1,w 2,w 3,….,w J ) Optimize F and find the optimal beam profiles Optimal Input Output Convert beam profiles into MLC leaf sequences

7 Beam profile D c (1) D 0 (1) D c (2) D 0 (2) w1w1 F = [D c (1)-D 0 (1)] 2 + [D c (2)-D 0 (2)] 2 +... Dosimetric:

8 ~2000 pencil beam weights, non-linear system. An objective function is a mathematical “measurement” of radiation treatment. It should, ideally, include all of our knowledge of radiotherapy: dosimetry based and biological model based objective function.

9 Optimization of a multi-dimensional objective function † Matrix Inversion † Iterative methods † Computer simulated annealing † Genetic optimization † Filtered backprojection

10 1.0 0.5w2w2 F =  [D c (n)-D 0 (n)] 2 n=1 n=4 1.0 Prescribed dose Calculated dose 34 12 w1w1 w3w3 w4w4 D3D3 D1D1 D2D2 D4D4 Direct Matrix Inversion

11 w2w2 w1w1 w3w3 w4w4 D1D1 D2D2 D4D4 D3D3 F =  [D c (n)-D 0 (n)] 2 n=1 n=4 D 1 = w 1 d 11 + w 2 d 21 + w 3 d 31 + w 4 d 41 D 2 = w 1 d 12 + w 2 d 22 + w 3 d 32 + w 4 d 42 D 4 = w 1 d 14 + w 2 d 24 + w 3 d 34 + w 4 d 44 D 3 = w 1 d 13 + w 2 d 23 + w 3 d 33 + w 4 d 43 Direct Matrix Inversion

12 d n = w 1 d 1n + w 2 d 2n + w 3 d 3n Dose to point n: organ target A Simple Iterative Algorithm 1 2 3

13 Initial beam profiles Calculate dose at a voxel n Compare D c (n) with D 0 (n) D c (n) > D 0 (n) ? YesNo Increase w i Decrease w i n+ 1 Algebraic Iterative Method:

14 1.0 0.5 F =  [D c (n)-D 0 (n)] 2 n=1 n=6 1.0 Prescribed dose Calculated dose Algebraic Iterative Method:

15 1.00 0.99 0.97 0.50 0.490.50 Iteration step = 1 0.99 0.50 0.49 1.01 0.95 0.90 0.50 0.450.51 0.50 0.44 Iteration step = 5 0.95 1.02 Algebraic Iterative Method:

16 F =  [D c (i)-D 0 (i)] 2 i=1 i=6 Iteration step = 10 0.92 1.020.92 0.82 0.51 0.420.51 0.41 0.91 1.02 Algebraic Iterative Method: 0 2040 60 80 100 0.25 0.15 0.05 0.10 0.20 0 0.30 Objective function Iteration step

17 Planning Parameters Number of beams Beam/Coll orientation Isocenter placement Beamlet size Intensity levels Margins & Targets Tuning structure

18 Beam Orientation Coplanar vs Non-coplanar –Ease of setup –Ease of planning –Speed of treatment Equi-spaced vs Selected angles –Entrance through table/immobilization device

19 Beam Orientation 9 equi-spaced beams

20 Beam Orientation 9 selected beams

21 Collimator Orientation

22 180 o collimator angle

23 Collimator Orientation Collimator angle

24 Isocenter Placement Issues –Can a better plan be achieved by isocenter placement ? –Dosimetry and/or QA –Patient setup

25 Isocenter Placement Isocenter in geometric center of targets

26 Isocenter Placement Isocenter in geometric center of GTV

27 Beamlet Size Yi et al. 2000

28 Intensity Levels Lehmann et al. 2000

29 Margins & Targets

30 Tuning Structure A structure added to control the dose distribution in IMRT plans –Reduce normal tissue dose –Reduce/Increase target dose

31 Tuning Structure

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33 Summary of Planning Parameters Number of beams Beam/Coll orientation Isocenter placement Beamlet size Intensity levels Margins & Targets Tuning structure

34 Verification

35 a bc def specially designed intensity patterns Planning System Commissioning

36 10% 20% 40% 50% 90% 50% 10% 90% 30% 50% 30% 10% 20% 40% 70% 80% 90% specially designed intensity patterns Calculated Measured Planning System Commissioning

37 Quantitative Comparison of Two Fluence Maps 1.Maximum difference in pixel values---local quantity. 2.Correlation coefficient— global quantity. Patient Specific Field Verification

38 QUANTITATIVE FILM ANALYSIS Film Courtesy, Tim Solbert

39 White = measurement Red = calculation Quantitative Film Analysis Courtesy, Tim Solberg

40 Quantitative Film Analysis - Profiles Horizontal and vertical profiles of measured data, calculated data, and  index. Calculated Measured  Courtesy, Tim Solberg

41 Measurement Tissue Equivalent Phantom 30 cm 40 cm 1.5 cm4.5 cm

42 Cylindrical Phantom Dose Verification Measured in Plane of Isocenter -3.5% 2mm -1.8% 1mm 70% 90% 50%

43 BANG gel Dosimetry Courtesy, Tim Solberg

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45 Periodic IMRT QA

46 Test Pattern with Leaf ErrorTest Pattern after leaf replacement and MLC calibration Periodic IMRT QA

47 QUALITY ASSURANCE OF IMRT TREATMENT PLAN DEPARTMENT OF RADIATION ONCOLOGY,STANFORD UNIVERSITY SCHOOL OF MEDICINE PATIENT NAME: xxx, xxxxxxx PATIENT ID: xxx-xx-xx TPS PLAN #: 2512 Treatment Machine: LA7 Beam Energy: 15 MV Calibration Setup: SSD Delivery Mode: Step and Shoot Beamlet Size: 1.0 x 1.0 (cm x cm) Calibration Factor: 1.000 Isocenter Dose Verification Report Field MU x1 x2 y1 y2 SSD beam-dose F 180-000 170 7.80 6.80 4.20 16.20 88.79 50.2 F 180-080 118 4.80 6.80 4.20 17.20 82.03 40.6 F 180-145 108 8.00 1.00 5.00 18.00 90.87 24.0 F 180-145a 101 1.00 8.00 4.00 18.00 90.87 17.9 F 180-215 80 9.00 0.00 3.00 18.00 90.49 1.6 F 180-215a 107 2.00 7.00 5.00 18.00 90.49 48.7 F 180-280 115 6.80 5.80 4.20 17.20 81.68 41.2 IMRT MU Checks

48 Calculated Isocenter Dose: 224.2 cGy TPS Isocenter Dose: 221.3 cGy Percentage Difference: 1.3 (%). Leaf Sequence Verification Report Field ID Gantry Angle Correlation Coefficient Maximum Difference 1 0 1.0000 0.5112 (%) 2 80 1.0000 0.4017 (%) 3 145 1.0000 0.6799 (%) 4 215 1.0000 0.7275 (%) 5 280 1.0000 0.4034 (%) Physicist: _________________________ DATE: 7/20/2001 IMRT MU Checks

49 Anterior Isocenter Verification Isocenter Setup Verification with DRRs

50 Lateral Isocenter Verification Isocenter Setup Verification with DRRs

51 Align DRR with EPID Image To Verify Patient Positioning DRR ImageAmSi EPID Image

52 DELIVERY OF IMRT BY COMPUTER CONTROLLED MLC

53 T l,m, k m 1 cm Beam Modulation Patterns

54 Velocity Modulation Step and Shoot

55 Fluence Profile Required for IMCRT Velocity Modulation

56  (x) =  (x) [t A (x) - t B (x)]. A B Velocity Modulation

57  (x) = t A (x) - t B (x) > 0  (x) =  (x) [t A (x) - t B (x)].  (x)  (x) =  (x). Velocity Modulation

58 Gradient Regions Between Extrema “Velocity” leaf sequencing

59 Interpretation as Trajectories  (x) 40 0 50 100 150 200 250 05101520253035 Position, X (cm) Leaf A Leaf B “Velocity” leaf sequencing

60  (x) =    (x) -    Reflection Operation to Remove Time Reversals “Velocity” leaf sequencing

61  (x) =  (x) +  (x) Translation Operation to Remove Discontinuities “Velocity” leaf sequencing

62 0 50 100 150 200 250 0510152025303540 Position, X (cm)  (x) Reflection Operation to Remove Time Reversal “Velocity” leaf sequencing

63  (x) =  (x) + x/v max Shear Operation to Remove Infinite Velocity “Velocity” leaf sequencing

64  (x)  (x) =  (x). d  (x) = dx d  (x)/dx  (x). Differentiation of Opening Time “Velocity” leaf sequencing

65  (x) =  (x) + x/v max d  (x) = 1 dx  v(x) d  (x) = d  (x) + 1 dx dx  v max Differentiation of Shear Operation “Velocity” leaf sequencing

66 1 v max v(x) 1  (x) d  (x)/dx. = + v(x) = v max d  (x)/dx  (x ). v max 1  Substitutions to Obtain Velocity Relation “Velocity” leaf sequencing

67 0 10 20 30 40 50 60 70 80 05101520253035 Position (cm) Time (sec) Leaf A Leaf B “Velocity” leaf sequencing

68 Step and Shoot “Step-and-Shoot” leaf sequencing

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70 Leaf Pair 12 -3 -2 -1 0 +1 +2 +3 Leaf Pair 14 -3 -2 -1 0 +1 +2 +3 Leaf Pair 13 -3 -2 -1 0 +1 +2 +3 Leaf Pair 15 -3 -2 -1 0 +1 +2 +3

71 0 1 2 3 4 5 ---123 Levels -3 -2 -1 0 +1 +2 +3 Position 1 2 3 4 5 6 7 8 2 3 4 5 6 7 8 AB 1 Instance 1

72 0 1 2 3 4 5 ---123 Levels -3 -2 -1 0 +1 +2 +3 Position 1 2 3 4 5 6 7 8 2 3 4 5 6 7 8 AB 1 Instance 2

73 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels -3 -2 -1 0 +1 +2 +3 Position 1 2 3 4 5 B A 1 2 4 6 8 7 5 7 8 6 Instance 3

74 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels -3 -2 -1 0 +1 +2 +3 Position 1 2 3 4 5 B A 1 2 4 6 8 7 5 7 8 6 Instance 4

75 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels Position 1 2 3 4 5 BA 1 2 4 6 8 7 5 7 8 6 -3 -2 -1 0 +1 +2 +3 Instance 5

76 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels Position 1 2 3 4 5 BA 1 2 4 6 8 7 5 7 8 6 -3 -2 -1 0 +1 +2 +3 Instance 6

77 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels Position 1 2 3 4 5 BA 1 2 4 6 8 7 5 7 8 6 -3 -2 -1 0 +1 +2 +3 Instance 7

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79 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels Position 1 2 3 4 5 BA 1 2 4 6 8 7 5 7 8 6 -3 -2 -1 0 +1 +2 +3 Instance 9

80 Instance 10

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82 Instance 12

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84 7 0 1 2 3 4 5 ---123 Levels Position 1 2 3 4 5 BA 1 2 4 6 8 7 5 7 8 6 -3 -2 -1 0 +1 +2 +3 Instance 14

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86 7 0 1 2 3 4 5 - 3 - 2 - 1 123 Levels Position 1 2 3 4 5 BA 1 2 4 6 8 7 5 7 8 6 -3 -2 -1 0 +1 +2 +3 Instance 16

87 Leaf Pair 12Leaf Pair 13 Leaf Pair 14 Leaf Pair 15

88 1&2 12 13 14 15

89 3&4 12 13 14 15

90 5&6 12 13 14 15

91 7&8 12 13 14 15

92 9&10 12 13 14 15

93 11&12 12 13 14 15

94 13&14 12 13 14 15

95 15&16 12 13 14 15

96 17&18 12 13 14 15

97 19&20 12 13 14 15

98 File Structure

99 Static File Structure For conventional MLC treatments, the STATIC mode is used. File Rev = G Treatment = Static Last Name = Collimator First Name = M.L. Patient ID = 555-1212 Number of Fields = 13 Number of Leaves = 52 Tolerance = 0.3 Field = Left Lung Index = 0.0 Carriage Group = 1 Operator = DNR Collimator = 0.0 Leaf 1A = 0.00 Leaf 2A = 1.00 Leaf 3A = 2.00 Leaf 4A = 3.00 Leaf 5A = 4.00 Leaf 6A = 5.00 Leaf...

100 Identical file format and syntax as for static treatment Identical file format and syntax as for static treatment Each specified leaf pattern is correlated to value of some Clinac parameter Each specified leaf pattern is correlated to value of some Clinac parameter “Treatment = ” and “Index = ” file entries determine behavior “Treatment = ” and “Index = ” file entries determine behavior File Rev = G Treatment = Dynamic dose Last Name = Patient First Name = QA Patient ID = 555-1212 Number of Fields = 12 Number of Leaves = 120 Tolerance = 0.3 Field = Shape1 Index = 0.000 Carriage Group = 1 Operator = DNR Collimator = 0.0 Leaf 1A = 0.00 Leaf 2A = 1.00 Leaf 3A = 2.00 Leaf 4A = 3.00 Leaf 5A = 4.00 Leaf 6A = 5.00 Leaf... Field = Shape2 Index = 0.050 Carriage Group = 1 Operator = DNR Collimator = 0.0 Leaf 1A = 0.00 Leaf 2A = 1.00 Leaf 3A = 2.00 Leaf 4A = 3.00 Leaf 5A = 4.00 Leaf 6A = 5.00 Leaf... Field = Shape3 Index = 0.072 Carriage Group = 1 Operator = DNR Collimator = 0.0 Leaf 1A = 0.00 Leaf 2A = 1.00 Leaf 3A = 2.00 Leaf 4A = 3.00 Leaf 5A = 4.00 Leaf 6A = 5.00 Leaf... Dynamic Treatment Files

101 Treatment Field Index The file must specify the total number of instances that will be used. File Rev = G Treatment = Dynamic Dose Last Name = John First Name = Smith Patient ID = 1234 Number of Fields = 20 Number of Leaves = 80 Tolerance = 0.1 Field = 1 of 20 Index = 0.0000 Carriage Group = 1 Operator = Physicist Collimator = 180.0 Leaf 1A = 0.00 Leaf 2A = 0.00 Leaf 3A = 3.00

102 Treatment Field Index Varian has 52- leaf, 80-leaf, and 120-leaf MLCs. The file must identify the MLC. File Rev = G Treatment = Dynamic Dose Last Name = John First Name = Smith Patient ID = 1234 Number of Fields = 20 Number of Leaves = 80 Tolerance = 0.1 Field = 1 of 20 Index = 0.0000 Carriage Group = 1 Operator = Physicist Collimator = 180.0 Leaf 1A = 0.00 Leaf 2A = 0.00 Leaf 3A = 3.00

103 Treatment Field Index Tolerance parameter is in units of centimeters. File Rev = G Treatment = Dynamic Dose Last Name = John First Name = Smith Patient ID = 1234 Number of Fields = 20 Number of Leaves = 80 Tolerance = 0.1 Field = 1 of 20 Index = 0.0000 Carriage Group = 1 Operator = Physicist Collimator = 180.0 Leaf 1A = 0.00 Leaf 2A = 0.00 Leaf 3A = 3.00

104 Treatment Field Index Dose (MU) fraction ranging from 0.0 (beginning of treatment) to 1.0 (end of treatment). File Rev = G Treatment = Dynamic Dose Last Name = John First Name = Smith Patient ID = 1234 Number of Fields = 20 Number of Leaves = 80 Tolerance = 0.1 Field = 1 of 20 Index = 0.0000 Carriage Group = 1 Operator = Physicist Collimator = 180.0 Leaf 1A = 0.00 Leaf 2A = 0.00 Leaf 3A = 3.00

105 Treatment Field Index Dose (MU) fraction ranging from 0.0 (beginning of treatment) to 1.0 (end of treatment). Leaf positions (cm) are specified as a function of dose fraction. File Rev = G Treatment = Dynamic Dose Last Name = John First Name = Smith Patient ID = 1234 Number of Fields = 20 Number of Leaves = 80 Tolerance = 0.1 Field = 1 of 20 Index = 0.0000 Carriage Group = 1 Operator = Physicist Collimator = 180.0 Leaf 1A = 0.00 Leaf 2A = 0.00 Leaf 3A = 3.00

106 File Footer - CRC Leaf 51B = 2.25 Leaf 52B = 2.25 Leaf 53B = 1.75 Leaf 54B = -6.20 Leaf 55B = -6.20 Leaf 56B = -6.20 Leaf 57B = -6.20 Leaf 58B = -6.20 Leaf 59B = -6.20 Leaf 60B = -6.20 Note = 0 Shape = 0 Magnification = 0.00 CRC = CF95 

107 File Structure Ensures file data integrity –Against file corruption –Against unintentional editing outside of authorized data editing tools Uses industry-standard algorithm CRC

108 Step-and-shoot fMU=0.0 1st MLC position fMU=0.14 1st MLC position fMU=0.14 2nd MLC position fMU=0.25 2nd MLC position step shoot step shoot Dynamic delivery fMU=0.0 1st MLC position fMU=0.14 2nd MLC position fMU=0.25 3rd MLC position fMU=0.33 4th MLC position

109 Clinical Applications of IMRT

110 IMRT Process Immobilization Aquaplast CT/MRI Acquisition PQ 5000 Structure Segmentation AcQsim Inverse Planning Corvus Planning Network File Management Varis Plan Verification Wellhöfer Position Verification Ximatron Treatment Delivery C-Series Clinac Dynamic MLC Delivery 20 o 60 o 100 o 140 o 180 o 260 o 240 o 300 o 340 o

111 To what clinical cases can IMRT be applied ?

112 180 o 300 o 340 o 20 o 60 o 100 o 140 o 260 o 220 o 9-field Head and neck Treatment Example

113 90% 55% 80 %

114 90% 55% 85%

115 90% 55% 80 %

116 90% 55% 80%

117 55% 90% 85%

118 90% 55% 80%

119 IMRT: Clinical Aims in Prostate Cancer Improve conformality; dose escalation Reduce high dose volumes in rectalwall & bladder Reduced small bowel dose in nodal therapy

120 Irradiate Prostate and Nodal Region in Pelvis 0o0o 40 o 280 o 320 o 80 o ProstateNodes

121 IMRT: Prostate Cancer CTVSV Bladder Rectum

122 GU or GI Toxicity 0 10 20 30 40 50 60 70 80 0123 Maximum RTOG Score IMRT-Prostate and Nodes 3D-Prostate and Nodes P = 0.002 Steven Hancock, 2002

123 Field Intensity Maps Intensity Modulated Plan IMRT: Prostate and Nodes

124 40% 90% 10% 20% 30% 60% 70% 80% 50% 40%

125 10% 20% 30% 60% 70% 50% 40% 90% 80%

126 10% 20% 30% 60% 70% 50% 40% 90% 80%

127 3D-CRT v. IMRT: Dose Delivery Prostate and Seminal Vesicles Small field: Prostate: 74.0 ± 1.5 75.7 82.8 65.3 Seminal Vesicles:50.0 ± 1.0 63.5 79.1 50.1 Large field: Prostate:50.0 ± 1.0 55.1 61.8 + Boost:70.0 ± 1.4 77.3 87.7 Nodes:50.0 ± 1.0 54.2 63.5 Organ3D CRTIMRT Mean±SDMeanMax Min Steven Hancock, 2002

128 P = 0.05 Steven Hancock, 2002

129 Prostate IMRT: Prescription Doses MSKCC: Dose to 98 ± 2% of CTV: 81. Gy Dose to 95% of PTV:78. Gy 5% of Bladder > 83. Gy 25-30% Rectum> 75.6 Gy Dose per fraction 1.8 Gy 2 yr risk of GI bleeding: 2% IMRT v. 10% 3D-CRT Zelefsky et al. Radiother & Oncol 55:241

130 IMRT for Gynecological Cancers CTV in a cervical cancer pt s/p hysterectomy Note the posteriorly and laterally placed lymph nodes regions The central region is where the small bowel is now located Mundt, 2002

131 Intensity Modulated-WPRT 100% 90% 70% 50% Mundt, 2002

132 Acute GI toxicity IM-WPRT vs. WPRT IM-WPRT 0 10 20 30 40 50 60 70 80 90 100 Grade 0Grade 1Grade 2Grade 3 WPRT P = 0.002 Mundt et al. Int J Radiat Oncol Biol Phys 52:1330-1337, 2002

133 Chronic GI Toxicity IM-WPRT vs. WPRT 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 0123 IM-WPRT WPRT Multivariate analysis controlling for age, chemo, stage and site, IMRT remained statistically significant ( p = 0.002) Mundt et al. ASTRO 2002 (New Orleans)

134 SPECT-CT Image Fusion Based on image fusion, highest intensity BM was contoured and used in planning process Mundt, 2002

135 BM-Sparing Plan IM-WPRT Plan Isodose Comparison – Mid Pelvis 100% 90% 70% 50% 100% 90% 70% 50% Mundt, 2002

136 Localization of the prostate can also be achieved with cone-beam CT.

137 Tumor Motion During Respiraton Courtesy, David Faffray

138 Lt Lung cord Rt Lung heart

139 Conclusions IMRT with MLCs can be implemented in the clinic. “Step-and-Shoot” or sliding window leaf sequence with dynamic MLCs can be used for IMRT. Dose distributions can be computed and delivered that provide treatment options for particularly difficult presentations. Imaging is required for variations in daily set-up. Special procedures are required to compensation for respiration motion

140 Radiobiology for IMRT and SRT

141 Phenomenological Lyman Model for NTCP (Note: The Lyman model does not explicitly take fraction size into consideration.)

142 For a biological target uniformly irradiated to dose D, the upper limit of integration is expressed as where is the dose at which the complication probability is 50%, and m is a slope parameter. Lyman Model for NTCP

143

144 For a uniformly irradiated partial volume, Lyman Model for NTCP then the upper limit of integration is define

145 The ntcp curve moves to the right vs. D for partial volume irradiation. Lyman Model for NTCP for n > 0

146 Lyman Model : non-uniform irradiation Multiple sub-volumes, at different doses d i are each translated to effective sub-volumes at some reference dose, such as the maximum dose in a dvh or TD 50 (1). The relationship must be reducible, i.e., the NTCP of two equal sub-volumes at a given dose must be the same as that of a single volume of twice the size at the same dose. [Kutcher–Burman]

147 Equivalent Uniform Dose (EUD) is the uniform dose that gives the same cell kill as a non-uniformly irradiated target. (Niemierko, Med Phys. 24:103-110; 1997.) Equivalent Uniform Dose

148 For the simplest model of exponential cell kill, and uniformly distributed cells, where really means the surviving fraction at dose D ref, which is often taken as 2 Gy

149 climbing the TCP curve Tumor Control Probability Dose where we are where we should be complication curve

150 the unique biology of CaP Striking similarities with slowly proliferating normal tissues  Extremely low proportion of cycling cells (< 2.5%)  Regression following RT is very slow PSA nadir times > 1 year regression of post-RT biopsies up to 3 years  Potential doubling times median 40 days (range 15 – 170 days)  PSA doubling times of untreated CaP median 4 years

151 Radiobiology 101 s dose Linear-Quadratic equation s = exp(-  d-  d 2 ) cell survival curve

152 Radiobiology 101 Fractionated radiotherapy: n x d = D S  s…s = s n S = exp(-  d-  d 2 ) n S = exp(-  BED) BED = D(1+ d/(  )) Biologic Equivalent Dose

153 Radiobiology 101 BED = D(1+ d/(  ))units of Gy  intrinsic radiosensitivity  repair of sub-lethal damage  sensitivity to dose-per-fraction

154 Radiobiology 101 BED = D(1+ d/(  ))  tumors >  NTLE tumors  ~ 10 normal tissue late effects  ~ 3

155 tumors vs. NTLE surviving fraction dose Normal Tissue late effects  ~ 3 Tumors & early- responding tissues  ~ 10

156 tumor vs. NTLE BED (Gy) = D(1+ d/(  )) D / d / n (Gy)BED  =10 BED  =3 tumorNTLE 74 / 2 / 3788.8123.3 70 / 2.5 / 2887.5128.3 69 / 3 / 2389.7138 64 / 4 / 1689.6149.3 NTLE: Normal Tissue Late Effects

157 the  ratio for CaP seriesmethod  95% CI Brenner & Hall (1999)LDR / EBRT data1.5[0.8 – 2.2] King & Fowler (2001)LDR / EBRT model1.8/2 Fowler et al. (2001)LDR / EBRT data1.49[1.25 – 1.76] Brenner et al. (2002)HDR data1.2[0.03 – 4.1]

158 what if  is that low? D (Gy) / d / nBED  =1.5 BED  =3 BED  =10 tumorNTLEacute effects 74 / 2 / 37172.6123.388.8 NTLE: Normal Tissue Late Effects 36.25 / 7.25 / 5211.5123.862.5 90 / 2 / 45210150108

159 why hypo-fractionate? Hypo-fractionation for CaP will:  escalate dose biologically  reduce acute sequelae  keep same normal tissue late-effects  reduce overall treatment course

160 potential tumor control Tumor Control Probability Dose (Gy) 6070805090 100 50 0 43% 62% 90% SRS hypo-fractionation 100

161 Radiobiology Other Tumors  ~ 10 Normal Tissues  ~ 3 Prostate cancer  ~ 1.5 Sensitivity to dose fraction size


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