Transcript The Use of High-Energy Protons in Cancer Therapy

Applications of Silicon Detectors in Proton
Radiobiology and Radiation Therapy
Reinhard W. Schulte
Loma Linda University Medical Center
Outline
• Introduction to proton beam therapy
• Applications of silicon detectors
– Proton radiography and computed tomography
– Particle tracking silicon microscope
– Nanodosimetry
A Man - A Vision
• In 1946 Harvard physicist Robert
Wilson (1914-2000) suggested*:
– Protons can be used clinically
– Accelerators are available
– Maximum radiation dose can be
placed into the tumor
– Proton therapy provides sparing
of normal tissues
– Modulator wheels can spread
narrow Bragg peak
*Wilson, R.R. (1946), “Radiological use of fast protons,” Radiology 47, 487.
Short History of Proton Beam Therapy
•
•
•
•
•
•
1946
1954
1956
1958
1967
1974
• 1990
R. Wilson suggests use of protons
First treatment of pituitary glands in Berkeley, USA
Treatment of pituitary tumors in Berkeley, USA
First use of protons as a neurosurgical tool in Sweden
First large-field proton treatments in Sweden
Large-field fractionated proton treatments
program begins at HCL, Cambridge, MA
First hospital-based proton treatment center
opens at Loma Linda University Medical
Center
World Wide Proton Treatment Centers
LLUMC Proton Treatment Center
Hospital-based facility
40-250 MeV Synchrotron
Gantry beam line
Fixed beam line
Main Interactions of Protons
p
p
• Electronic (a)
– ionization
– excitation
• Nuclear (b-d)
e
(a)
p
(b)
– Multiple Coulomb scattering (b),
small q
p
– Elastic nuclear collision (c),
(c) p’
large q
– Nonelastic nuclear interaction (d)
p
(d)
p’
q
p’
nucleus
e
g, n
nucleus
Why Protons are advantageous
• Relatively low entrance dose
(plateau)
• Maximum dose at depth
(Bragg peak)
• Rapid distal dose fall-off
• Energy modulation
(Spread-out Bragg peak)
• RBE close to unity
Why Silicon Detectors
• Combined measurement of
position, angle and energy or LET
of single particles
• High spatial resolution (microns)
• Wide dynamic energy range
• radiation hardness
• compatibility with physiological
conditions of cells
Applications of Silicon Detectors
• Proton Treatment planning
– Proton radiography
– Proton computed tomography (CT)
• Proton Radiobiology
– Particle microscope
– Nanodosimetry
Proton Treatment Planning
• Acquisition of imaging data
(CT, MRI)
• Conversion of CT values into
stopping power
• Delineation of regions of
interest
• Selection of proton beam
directions
• Design of each beam
• Optimization of the plan
Computed Tomography (CT)
• Faithful reconstruction of
patient’s anatomy
• Stacked 2D maps of linear
X-ray attenuation
• Electron density relative to
water can be derived
• Calibration curve relates
CT numbers to relative
proton stopping power
X-ray tube
Detector array
Processing of Imaging Data
H = 1000
mtissue /mwater
SP = dE/dxtissue /dE/dxwater
CT
Hounsfield
values (H)
Calibration
curve
Relative
proton
stopping
power (SP)
SP
Dose
calculation
H
Isodose
distribution
CT Calibration Curve
Stoichiometric Method*
– Choose tissue substitutes
– Obtain best-fitting parameters A,
B, C
H = Nerel {A (ZPE)3.6 + B (Zcoh)1.9 + C}
Rel.
electron
density
Photo
electric
effect
Coherent
scattering
KleinNishina
cross section
Hounsfield value (observed
• Step 1: Parameterization of H
2000
1800
1600
1400
1200
1000
800
800
1000 1200 1400 1600 1800 2000
Hounsfield value (expected)
*Schneider U. (1996), “The calibraion of CT
Hounsfield units for radiotherapy treatment planning,”
Phys. Med. Biol. 47, 487.
CT Calibration Curve
Stoichiometric Method
1.8
• Step 2: Define Calibration Curve
1.4
Fat
1.2
SP
– select different standard tissues
with known composition (e.g.,
ICRP)
– calculate H using parametric
equation for each tissue
– calculate SP using Bethe Bloch
equation
– fit linear segments through data
points
1.6
1
0.8
0.6
0.4
0.2
0
0
500
1000
1500
H value
2000
2500
Problems with the Current Method
• Proton interaction  Photon interaction
• Multi-segmental calibration curve required
• No unique SP values for soft tissue Hounsfield
range
• Tissue substitutes  real tissues
• Uncertainty requires larger range to cover tumor
• Risk for sensitive structures
Proton Transmission Radiography - PTR
MWPC 2
p
Energy detector
• First suggested by Wilson
(1946)
• Images contain residual
energy/range information
of individual protons
• Resolution limited by
multiple Coulomb
scattering
• Spatial resolution of 1mm
possible
MWPC 1
SC
Proton Range Uncertainties
Range Uncertainties
(measured with PTR)
> 5 mm
> 10 mm
> 15 mm
Schneider U. (1994), “Proton
radiography as a tool for quality control
in proton therapy,” Med Phys. 22, 353.
Alderson Head Phantom
Proton Beam Computed Tomography
• Proton CT for diagnosis
– first studied for diagnostic use during the 1970s
– dose advantage over x rays for similar resolution
– not further developed after development of x-ray CT
• Proton CT for treatment planning and delivery
– renewed interest during the 1990s (2 Ph.D. theses)
– fast data acquisition and proton gantries available
– further R&D needed
Proton Beam Computed Tomography
• Applications
– Precise calculation of dose distributions
– 3D verification of dose patient treatment position
– tumor delineation without need of contrast media
Proton Beam Computed Tomography
• Conceptual design
–
–
–
–
–
–
–
single particle resolution
3D track reconstruction
Si microstrip detectors
p cone beam geometry
multiple beam directions
energy loss measurement
analysis of scattering and
nuclear interactions
SSD 3
SSD 1
p cone
beam
Trigger logic
DAQ
SSD 2 SSD 4 ED
Development of Proton Beam
Computed Tomography
• Experimental Study
– two detector planes
– water phantom on
turntable
Si
module 1
Si
module 2
Scattering
foil
• Theoretical Study
– GEANT MC simulation
– influence of MCS and
range straggling
– importance of angular
measurements
Proton
beam
Turntable
Water phantom
Applications of Silicon Detectors
• Proton Treatment Planning
– Proton radiography
– Proton computed tomography (CT)
• Proton Radiobiology
– Particle microscope
– Nanodosimetry
Proton Radiobiology in Perspective
D = 1 Gy
n = 416
dE/dx per mm
1.3 keV
50 MeV
protons
36 ionizations
n = 112
4.7 keV
10 MeV
protons
134 ionizations
n = 54
10 keV
4 MeV
protons
10 mm
276 ionizations
RBE*
1.1
1.4
2.0
* rel to 60 Co g rays
Study of Cellular Radiation Responses
in vitro (in glass ware):
• single cell suspension seeded in culture flasks or
Petri dishes
• immortalized cell lines
• exponential or stationary phase
in vivo (in a living organism):
• tumor growth in animals
• normal tissue response in animals (e.g., crypt cells)
• response of microscopic animals (e.g., nematodes)
Study of Cell Survival in vitro
Study of cell survival in vitro
• seeded cells are incubated for 3 - 14 days
• ‘surviving cells’ form large colonies (> 50 cells)
• surviving fraction is defined as
Surviving Fract ion( S ) 
# coloniescount ed
# cells seeded  (P E(%)/100
)
• plating efficiency (PE) is defined as the fraction
(%) of cells in an unirradiated culture that form
colonies
1-
S
0.1 -
0.01 -
Dose
Applications of Silicon Detectors
• Proton Treatment Planning
– Proton radiography
– Proton computed tomography (CT)
• Proton Radiobiology
– Particle microscope
– Nanodosimetry
Particle Tracking Silicon Microscope
• Conventional radiobiological
experiment
– random traversal of cells by a
broad particle beam
– only average number of hits per
cell is known
• Particle-tracking radiobiological
experiment
– number of particles per cell is
exactly known
– broad beam or microbeam setup
l = 1.5 P(n) = ln/n! e-l
SSD
n=2
1 3
0
collimator
SSD
n=0
0 3
0
Particle Tracking Silicon Microscope
• Conceptual design
– biological targets located
on detector surface
– single-particle tracking
– energy or LET
measurement
– ASIC and controller
design adapted to
application
– dedicated data acquisition
system
MCM
DSSD
ASIC
RO Control
Cables
DAQ
Low-Dose Cell Survival
• Low-dose studies with a
proton microbeam
– precise low-dose/fluence
cell survival curves
– hypersensitive region at
low doses
– more pronounced at higher
proton energies (3.2 MeV
vs. 1 MeV)
Dose (Gy)
3.2 MeV
protons
Schettino et al. Radiation Res. 156, 526-534, 2001
Adaptive Response & Bystander Effect
• Low-dose studies with an
alpha particle microbeam
– only 10% of cells exposed
– more cells inactivated than
traversed (bystander effect)
– previous exposure to low
level of DNA damage
increases resistance
(adaptive response)
--- expected
-o- 6 hrs after priming g dose
-•- 6 hrs after priming g dose
Sawant et al. Radiation Res. 156, 177-180, 2001
Goals of the LLU/SCIPP Particle
Tracking Microscope Project
• Develop a versatile and inexpensive broad-beam
and microbeam particle tracking system for
–
–
–
–
–
protons and alpha particles
wide range of energies (1 MeV - 70 MeV protons)
in vitro and in vivo radiobiological studies
research studies for radiation therapy and protection
support of DOE and NASA low-dose research
programs
Applications of Silicon Detectors
• Proton Treatment Planning
– Proton radiography
– Proton computed tomography (CT)
• Proton Radiobiology
– Particle microscope
– Nanodosimetry
Nanodosimetry Collaboration
Loma Linda University
Medical Center (1997)
Weizmann Institute
of Science (1997)
UCSD (1998)
UCSC (2000)
SCIPP
Nanodosimetry Concepts
• DNA is the principle
target in radiobiology
• Radiation interaction with
DNA is a stochastic event
• Single damages (break or
base oxidation) are easily
repaired
• Clustered damages are
difficult or impossible to
repair
Single damage
reparable
charged
particle
d electron
50 base pair
DNA segment
Clustered
damage
irreparable
~2nm
Conceptual Approaches
Track Structure Imaging
Single-Volume Sampling
Mean Free Path versus Gas Pressure
• Mean free path:
1 Torr Propane (C3H8)
l = 1 / (n s)
– n, targets per unit volume
– s, interaction cross section
target
projectile
l
• Assumptions:
– same atomic composition
– s is independent of density
• Density Scaling:
lgas = (rref / rgas) lref
1 mm in 1 Torr propane  2.4 nm
in unit density material
Ion Counting Nanodosimetry
E1
ions
SV
particle
gas
E2
aperture
vacuu
m
trigger
Ion counter
DAQ
0.1
Signal [V]
• Ionization volume filled
with low-pressure gas
• single particle detection
• ion drift through
aperture
• wall-less sensitive
volume
• evacuated ion detection
volume
SSD
SSD
0.0
-0.1
-0.2
-0.3
28
29
30
31
Ion drift time [msec]
32
33
The Ion Counting Nanodosimeter
• Pulsed drift field
• differential pumping
system
• electron multiplier
• internal alpha source
50mm
Anode
E1
1 Torr
e-
particle
ion
Cathode
E2
Intermediate
vacuum
High vacuum
to pump 1
EM
to pump 2
Single Charge Counting
E1
ions
SV
Particle
detector
gas
E2
aperture
vacuum
Ion counter
0.0
-0.1
-0.2
-0.3
trigger
DAQ
0.1
Signal [V]
• Ionization volume filled
with low-pressure gas
• single particle detection
• ion drift through
aperture
• wall-less sensitive
volume
• evacuated ion detection
volume
28
29
30
31
Ion drift time [msec]
32
33
The Ion Counting Nanodosimeter
• Pulsed drift field
• differential pumping
system
• electron multiplier
• four SS detector
planes for particle
tracking and energy
reconstruction
Anode
50mm
SSD1
SSD2
E1
1 Torr
e-
particle
ion
Cathode
E2
Intermediate
vacuum
High vacuum
to pump 1
EM
to pump 2
Nanodosimetric Spectra
• average cluster size
increases with
increasing LET
1.E+02
Abs. Frequency (%)
• ND spectra change
with particle type
and energy
protons
alpha
1.E+01
carbon
1.E+00
1.E-01
1.E-02
0
20
40
Cluster size
60
80
Applications
• New Standard of Radiation Quality in Mixed Fields
• Radiation Treatment Planning: biological weighting
factor
• Radiation Protection: risk-related weighting factors
• Manned Space Flight: Risk prediction (cancer &
inherited diseases)
Acknowledgements
• LLUMC
Vladimir Bashkirov
George Coutrakon
Pete Koss
• WIS
Amos Breskin
Rachel Chechik
Sergei Shchemelinin
Guy Garty
Itzik Orion
Bernd Grosswendt - PTB
• UCSD - Radiobiology
– John Ward
– Jamie Milligan
– Joe Aguilera
• UCSC - SCIPP
–
–
–
–
–
Abe Seiden
Hartmut Sadrozinsky
Brian Keeney
Wilko Kroeger
Patrick Spradlin
The nanodosimetry project has been funded by the National Medical Technology Testbed (NMTB) and the
US Army under the U.S. Department of the Army Medical Research Acquisition Activity, Cooperative
Agreement # DAMD17-97-2-7016. The views and conclusions contained in this presentation are those of
the presenter and do not necessarily reflect the position or the policy of the U.S. Army or NMTB.