Santa Cruz presentation 01-17-02 (1).ppt

silicon detectors

1. Applications of Silicon Detectors in Proton
Radiobiology and Radiation Therapy
Reinhard W. Schulte
Loma Linda University Medical Center

2. Outline
•Introduction to proton beam therapy
•Applications of silicon detectors
–Proton radiography and computed tomography
–Particle tracking silicon microscope
–Nanodosimetry

3. 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.

4. Short History of Proton Beam Therapy
•1946R. Wilson suggests use of protons
•1954First treatment of pituitary glands in Berkeley, USA
•1956Treatment of pituitary tumors in Berkeley, USA
•1958 First use of protons as a neurosurgical tool in Sweden
•1967First large-field proton treatments in Sweden
•1974Large-field fractionated proton treatments
program begins at HCL, Cambridge, MA
•1990First hospital-based proton treatment center
opens at Loma Linda University Medical
Center

5. World Wide Proton Treatment Centers

6. LLUMC Proton Treatment Center
Hospital-based facility
Fixed beam line
40-250 MeV Synchrotron
Gantry beam line

7. Main Interactions of Protons
•Electronic (a)
–ionization
–excitation
•Nuclear (b-d)
–Multiple Coulomb scattering (b),
small 
–Elastic nuclear collision (c),
large 
–Nonelastic nuclear interaction (d)
e
pp
p’
p
p
p’
nucleus

n
p’
p
e
nucleus
(b)
(c)
(d)
(a)


8. 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

9. 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

10. Applications of Silicon Detectors
•Proton Treatment planning
–Proton radiography
–Proton computed tomography (CT)
•Proton Radiobiology
–Particle microscope
–Nanodosimetry

11. 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

12. Computed Tomography (CT)
X-ray tube
Detector array
•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

13. Processing of Imaging Data
CT
Hounsfield
values (H)
Isodose
distribution
Calibration
curve
H = 1000 
tissue
/
water
Relative
proton
stopping
power (SP)
SP = dE/dx
tissue
/dE/dx
water
H
S
P
Dose
calculation

14. CT Calibration Curve
Stoichiometric Method*
•Step 1: Parameterization of H
–Choose tissue substitutes
–Obtain best-fitting parameters A,
B, C
800
1000
1200
1400
1600
1800
2000
800100012001400160018002000
Hounsfield value (expected)
H
o
u
n
s
f
i
e
l
d

v
a
l
u
e

(
o
b
s
e
r
v
e
d
H = N
e
rel
{A (Z
PE
)
3.6
+ B (Z
coh
)
1.9
+ C}
Klein-
Nishina
cross section
Rel.
electron
density
Photo
electric
effect
Coherent
scattering
*Schneider U. (1996), “The calibraion of CT
Hounsfield units for radiotherapy treatment
planning,” Phys. Med. Biol. 47, 487.

15. CT Calibration Curve
Stoichiometric Method
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 5001000150020002500
H value
S
P
•Step 2: Define Calibration Curve
–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
Fat

16. 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

17. Proton Transmission Radiography - PTR
•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 2MWPC 1
SC
p
E
n
e
r
g
y
d
e
t
e
c
t
o
r

18. Alderson Head Phantom
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.

19. 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

20. Proton Beam Computed Tomography
•Applications
–Precise calculation of dose distributions
–3D verification of dose patient treatment position
–tumor delineation without need of contrast media

21. 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
DAQ
Trigger logic
SSD 1 EDSSD 3 SSD 2SSD 4
p cone
beam

22. Development of Proton Beam
Computed Tomography
•Experimental Study
–two detector planes
–water phantom on turntable
•Theoretical Study
–GEANT MC simulation
–influence of MCS and
range straggling
–importance of angular
measurements
Proton
beam
Si
module 2
Si
module 1
Water phantom
Turntable
Scattering
foil

23. Applications of Silicon Detectors
•Proton Treatment Planning
–Proton radiography
–Proton computed tomography (CT)
•Proton Radiobiology
–Particle microscope
–Nanodosimetry

24. Proton Radiobiology in Perspective
D = 1 Gy
10 m
n = 112
10 MeV
protons
n = 54
4 MeV
protons
n = 416
50 MeV
protons
dE/dx per m
4.7 keV
134 ionizations
10 keV
276 ionizations
1.3 keV
36 ionizations
RBE*
1.4
2.0
1.1
* rel to
60
Co  rays

25. 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 Cellular Radiation Responses

26. 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

• plating efficiency (PE) is defined as the fraction
(%) of cells in an unirradiated culture that form
colonies
)(PE(%)/100seeded cells #
counted colonies#
)(Fraction Surviving

S
Dose
S
0.1 -
0.01 -
1 -

27. Applications of Silicon Detectors
•Proton Treatment Planning
–Proton radiography
–Proton computed tomography (CT)
•Proton Radiobiology
–Particle microscope
–Nanodosimetry

28. 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
SSD
n = 2 1 3 0
 = 1.5 P(n) = 
n
/n! e
-
SSD
n = 0 0 3 0
collimator

29. 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
DSSDASICRO ControlCables DAQ
MCM

30. 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

31. 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  dose
-- 6 hrs after priming

 dose
Sawant et al. Radiation Res. 156, 177-180, 2001

32. 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

33. Applications of Silicon Detectors
•Proton Treatment Planning
–Proton radiography
–Proton computed tomography (CT)
•Proton Radiobiology
–Particle microscope
–Nanodosimetry

34. Nanodosimetry Collaboration
Loma Linda University
Medical Center (1997)
UCSC (2000)
SCIPP
Weizmann Institute
of Science (1997) UCSD (1998)

35. 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
Clustered
damage
irreparable
Single damage
reparable charged
particle
~2nm
 electron 50 base pair
DNA segment

36. Conceptual Approaches
Track Structure ImagingSingle-Volume Sampling

37. Mean Free Path versus Gas Pressure

•Mean free path:
–n, targets per unit volume
– , interaction cross section
•Assumptions:
–same atomic composition
– is independent of density
•Density Scaling:

gas = (
ref / 
gas) 
ref
 = 1 / (n 
1 mm in 1 Torr propane  2.4 nm
in unit density material
1 Torr Propane (C
3H
8)
projectile
target

38. Ion Counting Nanodosimetry
•Ionization volume filled
with low-pressure gas
•single particle detection
•ion drift through aperture
•wall-less sensitive
volume
•evacuated ion detection
volume
trigger
E
1
Ion counter
SV ions
gas
E
2aperture
DAQ
vacuu
m
28 29 30 31 32 33
-0.3
-0.2
-0.1
0.0
0.1
S
i
g
n
a
l

[
V
]
Ion drift time [sec]
particle
SSD
SSD

39. The Ion Counting Nanodosimeter
•Pulsed drift field
•differential pumping
system
•electron multiplier
•internal alpha source
Anode
5
0
m
m
Cathode
E
1
E
2
e
-
ion
1 Torr
Intermediate
vacuum
particle
EM
to pump 2
to pump 1
High vacuum

40. Single Charge Counting
•Ionization volume filled
with low-pressure gas
•single particle detection
•ion drift through aperture
•wall-less sensitive
volume
•evacuated ion detection
volume
trigger
E
1
Ion counter
SV ions
gas
E
2aperture
Particle
detector
DAQ
vacuum
28 29 30 31 32 33
-0.3
-0.2
-0.1
0.0
0.1
S
i
g
n
a
l

[
V
]
Ion drift time [sec]

41. The Ion Counting Nanodosimeter
•Pulsed drift field
•differential pumping
system
•electron multiplier
•four SS detector
planes for particle
tracking and energy
reconstruction
Anode
5
0
m
m
Cathode
E
1
E
2
e
-
ion
1 Torr
Intermediate
vacuum
particle
EM
to pump 2
to pump 1
High vacuum
SSD2SSD1

42. Nanodosimetric Spectra
•ND spectra change
with particle type
and energy
•average cluster size
increases with
increasing LET
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
0 20 40 60 80
Cluster size
A
b
s
.

F
r
e
q
u
e
n
c
y

(
%
)
protons
alpha
carbon

43. 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)

44. 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.