Download presentation
Presentation is loading. Please wait.
Published byArabella Hines Modified over 9 years ago
2
Verification Arthur Boyer Stanford University School of Medicine Stanford, California Clinical Aspects Radiobiological Aspects Planning Delivery
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
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
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
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
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
82
Instance 12
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
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
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
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.