Verificat ion Arthur Boyer Stanford University School of Medicine Stanford, California Clinical Aspects Radiobiological Aspects Plannin g Delivery
Transcript
Slide 1
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Verification Arthur Boyer Stanford University School of
Medicine Stanford, California Clinical Aspects Radiobiological
Aspects Planning Delivery
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Complexity Time IMRT planning Conventional planning
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Establish the Correspondence Between Output and Input Input
Output Desired output Specify a dose distribution--dose based model
Specify quantities that describe a patients quality of life (e.g.,
Karnofsky status) Specify TCP and NTCP--biological model
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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
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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:
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~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.
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Optimization of a multi-dimensional objective function Matrix
Inversion Iterative methods Computer simulated annealing Genetic
optimization Filtered backprojection
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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
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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
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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
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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:
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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:
Planning Parameters Number of beams Beam/Coll orientation
Isocenter placement Beamlet size Intensity levels Margins &
Targets Tuning structure
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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
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Beam Orientation 9 equi-spaced beams
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Beam Orientation 9 selected beams
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Collimator Orientation
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180 o collimator angle
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Collimator Orientation Collimator angle
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Isocenter Placement Issues Can a better plan be achieved by
isocenter placement ? Dosimetry and/or QA Patient setup
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Isocenter Placement Isocenter in geometric center of
targets
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Isocenter Placement Isocenter in geometric center of GTV
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Beamlet Size Yi et al. 2000
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Intensity Levels Lehmann et al. 2000
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Margins & Targets
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Tuning Structure A structure added to control the dose
distribution in IMRT plans Reduce normal tissue dose
Reduce/Increase target dose
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Tuning Structure
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Summary of Planning Parameters Number of beams Beam/Coll
orientation Isocenter placement Beamlet size Intensity levels
Margins & Targets Tuning structure
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Verification
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a bc def specially designed intensity patterns Planning System
Commissioning
Quantitative Comparison of Two Fluence Maps 1.Maximum
difference in pixel values---local quantity. 2.Correlation
coefficient global quantity. Patient Specific Field
Verification
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QUANTITATIVE FILM ANALYSIS Film Courtesy, Tim Solbert
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White = measurement Red = calculation Quantitative Film
Analysis Courtesy, Tim Solberg
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Quantitative Film Analysis - Profiles Horizontal and vertical
profiles of measured data, calculated data, and index. Calculated
Measured Courtesy, Tim Solberg
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Measurement Tissue Equivalent Phantom 30 cm 40 cm 1.5 cm4.5
cm
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Cylindrical Phantom Dose Verification Measured in Plane of
Isocenter -3.5% 2mm -1.8% 1mm 70% 90% 50%
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BANG gel Dosimetry Courtesy, Tim Solberg
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Periodic IMRT QA
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Test Pattern with Leaf ErrorTest Pattern after leaf replacement
and MLC calibration Periodic IMRT QA
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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
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...
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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
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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
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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
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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
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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
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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
File Structure Ensures file data integrity Against file
corruption Against unintentional editing outside of authorized data
editing tools Uses industry-standard algorithm CRC
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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
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Clinical Applications of IMRT
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IMRT Process Immobilization Aquaplast CT/MRI Acquisition PQ
5000 Structure Segmentation AcQsim Inverse Planning Corvus Planning
Network File Management Varis Plan Verification Wellhfer 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
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To what clinical cases can IMRT be applied ?
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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
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90% 55% 80 %
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90% 55% 85%
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90% 55% 80 %
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90% 55% 80%
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55% 90% 85%
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90% 55% 80%
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IMRT: Clinical Aims in Prostate Cancer Improve conformality;
dose escalation Reduce high dose volumes in rectalwall &
bladder Reduced small bowel dose in nodal therapy
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Irradiate Prostate and Nodal Region in Pelvis 0o0o 40 o 280 o
320 o 80 o ProstateNodes
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IMRT: Prostate Cancer CTVSV Bladder Rectum
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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
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Field Intensity Maps Intensity Modulated Plan IMRT: Prostate
and Nodes
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40% 90% 10% 20% 30% 60% 70% 80% 50% 40%
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10% 20% 30% 60% 70% 50% 40% 90% 80%
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10% 20% 30% 60% 70% 50% 40% 90% 80%
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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 MeanSDMeanMax Min Steven Hancock, 2002
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P = 0.05 Steven Hancock, 2002
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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
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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
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
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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)
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SPECT-CT Image Fusion Based on image fusion, highest intensity
BM was contoured and used in planning process Mundt, 2002
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BM-Sparing Plan IM-WPRT Plan Isodose Comparison Mid Pelvis 100%
90% 70% 50% 100% 90% 70% 50% Mundt, 2002
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Localization of the prostate can also be achieved with
cone-beam CT.
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Tumor Motion During Respiraton Courtesy, David Faffray
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Lt Lung cord Rt Lung heart
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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
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Radiobiology for IMRT and SRT
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Phenomenological Lyman Model for NTCP (Note: The Lyman model
does not explicitly take fraction size into consideration.)
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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
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For a uniformly irradiated partial volume, Lyman Model for NTCP
then the upper limit of integration is define
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The ntcp curve moves to the right vs. D for partial volume
irradiation. Lyman Model for NTCP for n > 0
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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.
[KutcherBurman]
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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
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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
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climbing the TCP curve Tumor Control Probability Dose where we
are where we should be complication curve
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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
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Radiobiology 101 s dose Linear-Quadratic equation s = exp(- d-
d 2 ) cell survival curve
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Radiobiology 101 Fractionated radiotherapy: n x d = D S ss = s
n S = exp(- d- d 2 ) n S = exp(- BED) BED = D(1+ d/( )) Biologic
Equivalent Dose
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Radiobiology 101 BED = D(1+ d/( ))units of Gy intrinsic
radiosensitivity repair of sub-lethal damage sensitivity to
dose-per-fraction
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Radiobiology 101 BED = D(1+ d/( )) tumors > NTLE tumors ~ 10
normal tissue late effects ~ 3
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tumors vs. NTLE surviving fraction dose Normal Tissue late
effects ~ 3 Tumors & early- responding tissues ~ 10
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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
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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]
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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
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why hypo-fractionate? Hypo-fractionation for CaP will: escalate
dose biologically reduce acute sequelae keep same normal tissue
late-effects reduce overall treatment course
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potential tumor control Tumor Control Probability Dose (Gy)
6070805090 100 50 0 43% 62% 90% SRS hypo-fractionation 100
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Radiobiology Other Tumors ~ 10 Normal Tissues ~ 3 Prostate
cancer ~ 1.5 Sensitivity to dose fraction size