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BIOFISICA MEDICA
Simulations and experimental verification of
medical X-ray sources: CT case
R. A. Miller C.
Department of Biophysics, Medical Biophysics Centre
University of Orient. Santiago of Cuba.
[email protected]
Workshop on Instruments and Sensors on the GRID
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Background
X-ray devices are important tools in various
medical applications. However, the x-rays
produced by such devices can pose a
hazard to human health depending on
radiation absorbed dose in tissue (ADT).
For this reason, ADT estimation
constitutes a key aspect in the use of
medical x-ray sources.
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Optimisation Principle (ALARA)
Doses involved in medical XR
applications must be As Low As
Reasonably As possible with
the best image quality
achievable.
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Instruments and Sensors used in
X-ray dosimetry
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Instruments and Sensors used in
X-ray (XR) dosimetry
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Instruments and Sensors used in
X-ray (XR) dosimetry
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Due to impossibility of detectors positioning
in most internal anatomical structures
where doses need to be known, absorbed
radiation doses are estimated by several
Simulation Approaches.
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Existing XR Simulation Approaches
• Monte Carlo Technique [1], [2], (following the path of
each photon).
• Deterministic, based on the integral photon transport
equation.[3]
• Computer Aided Drawing -CAD- models.[4], [5]
• Segmentation Method (a pencil beam is segmented both
in energy and solid angle).[6]
[1] Lazos, D., Bliznakova, K., Kolitsi, Z. And Pallikarakis, N. An integrated research tool for X-ray
imaging simulation. Comp. Meth. Prog. Biomed. 70, 241–251 (2003).
[2] Winslow, M., Xu, X. G., Huda, W., Ogden, K. M. And Scalzetti, E. M. Monte Carlo simulations of
patient X-ray images. Am. Nucl. Soc. Trans. 90, 459–460 (2004).
[3] Inanc, F. ACT image based deterministic approach to dosimetry and radiography simulations. Phys.
Med. Biol. 47, 3351–3368 (2002).
[4] Duvauchelle, P., Freud, N., Kaftandjian, V. And Babot, D. A computer code to simulate X-ray
imaging techniques. Nucl. Instrum. Methods Phys. Res. B 170, 245–258 (2000).
[5] Ahn, S. K., Cho, G., Chi, Y. K., Kim, H. K. And Jae, M. A computer code for the simulation of X-ray
imaging systems. In: Proceedings of the IEEE Nuclear Science Symposium. Conference Record,
Oregon, USA, 19–25 October 2003 (Piscataway, NJ: IEEE) pp. 838–842 (2004).
[6] Fanti V., Marzeddu R., Massazza G., Randaccio P., Brunetti A. and Golosio B. A SIMULATOR FOR
X-RAY IMAGES. Radiation Protection Dosimetry (2005), Vol. 114, Nos 1-3, pp. 350–354.
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Phantoms for Dosimetry
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Monte Carlo Simulation Systems
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Simulation & Validation
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Why CT?
CT Effective Dose Contribution to Colective Effective
Dose (United Kingdom)
USA
Percentage CT examinations vs.
total X rays imaging
40%
CT contribution to Effective Dose with
respect to every XR imaging
45%
35%
20%
25%
15%
5%
-5%
1990
WORLD SCENARIO
Percentage CT examinations vs.
total Radiological examinations
CT contribution to World’s
Collective Effective Dose
1999
CT & World Population
Average annual rate of CT
scanning per 1,000 people
CT examinations - Annual Rate in Developed
Countries (1985 - 1990)
Annual Global Rate of CT examinations per
1000 people
120
97
100
44
50
80
40
60
50
40
20
30
30
35
20
10
14.5
0
0
1970 - 1979
USA
Australia
Germany
Belgium
1985 - 1990
Japan
USA : 3.6x106 CT examinations in 1980
X 10
6.1
33 x106 CT examinations in 1998
2.7x106 examinations in children younger
than 15 years in 2000
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But…
• Whereas CT contributes to higher values
of Effective Dose, they are under the
threshold for deterministic or stochastic
effects, in which genetic effects depends
on absorbed dose.
• Cancer risk by abdominal CT scannings:
12,5/10 000.
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An Optimization Approach in
CT (AMAR)
• Attributes of patient,
• Modulation of scanning factors,
• Advances in Technology,
• Required diagnostic image quality.
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Attributes of Patient
Dosis relativa
2
1
0
-14
-12
-10
-8
-6
-4
-2
cm
0
2
4
6
8
10
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Axial single 360 scanning
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Advances in Technology
CARE Dose 4D – SIEMENS
(AMTC,z)
 - User selects an Eff. mAs
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Advances in Technology
Dose Right (DOM) – PHILIPS
(MACT,z)
 - Based on the squared root of  obtained in previous anterior angular
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projection
Advances in Technology
FlexmA – SHIMADZU (MACTz)
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Advances in Technology
3D Auto mA – General Electric
MS (MACT,z)
Z- Modulates mA to keep a user specified quantum noise. A pitch correction factor is used in
helical mode. Uses the standard kernel as a reference.
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Advances in Technology
Real E.C. – TOSHIBA (MACT,z)
The user selects a mA and quantum noise reference levels
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Required diagnostic image quality
• High Signal to Noise Ratio:
– Solid Lung Tumours (except ground glass tumours).
– Calcifications in Coronary Arteries.
– Lung emphysema.
• Low Signal to Noise Ratio:
– Abdominal scannings (liver or kidney).
– Diffuse Lung Illness.
• Medium Signal to Noise Ratio:
– Brain.
– Abdominal / Thoracic (except for bleeding).
• Lung illness.
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CT low dose protocols
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Challenges for XR sources
Simulations and Validation
• Personalized organ dose estimation and
protocol optimization.
• Acceptable clinical image quality threshold
identification to optimize dose.
• Initial mA user selection in some AMTC
introduces subjective restrictions La (e.g.
high mAs for big patients).
• Simultaneous Modulation of kV and mAs.