Table Of ContentALTERNATIVE
BREAST IMAGING
FOUR MODEL-BASED APPROACHES
THE KLUWER INTERNATIONAL SERIES IN
ENGINEERING AND COMPUTER SCIENCE
ALTERNATIVE
BREAST IMAGING
FOUR MODEL-BASED APPROACHES
edited by
Keith D. Paulsen, Ph.D.
Paul M. Meaney, Ph.D.
Thayer School of Engineering
Dartmouth College, Hanover, NH USA
with
Larry C. Gilman, Ph. D.
Springer
eBookISBN: 0-387-23364-4
Print ISBN: 0-387-23363-6
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TABLE OF CONTENTS
Contributors vii
Preface xiii
1. Four Alternative Imaging Modalities
Stephen Poplack, Wendy Wells, and Keith Paulsen 1
2. Computational Framework
Paul M. Meaney and Keith Paulsen 25
3. Magnetic Resonance Elastography: Theory
Elijah E. W. Van Houten and Marvin Doyley 49
4. Magnetic Resonance Elastography: Experimental Validation and
Performance Optimization
Marvin Doyley and John Weaver 69
5. Electrical Impedance Spectroscopy: Theory
Hamid Dehghani and Nirmal K. Soni 85
6. Electrical Impedance Spectroscopy: Translation to Clinic
Alex Hartov, Ryan J. Halter, and Todd E. Kerner 107
7. Microwave Imaging: A Model-Based Approach
Paul M. Meaney and Qianqian Fang 127
8. Microwave Imaging: Hardware and Results
Paul M. Meaney and Dun Li 155
9. Near Infrared Spectroscopic Imaging: Theory
Hamid Dehghani and Brian Pogue 183
10. Near Infrared Spectroscopic Imaging: Translation to Clinic
Brian Pogue, Shudong Jiang, Hamid Dehghani, and Keith Paulsen 201
11. Statistical Methods for Alternative Imaging Modalities in Breast
Cancer Clinical Research
Tor Tosteson 227
INDEX 245
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CONTRIBUTORS
Hamid Dehghani, Assistant Professor of Engineering at the
Thayer School of Engineering, Dartmouth College, received a
B.S. in Biomedical and Bioelectronic Engineering from the
University of Salford, UK, in 1994; an M.S. in Medical
Physics and Clinical Engineering from Sheffield University,
UK, in 1995; and a Ph.D. in Medical Imaging at Sheffield
Hallam University, UK, in 1999. For three years he was a research assistant
at University College, London, investigating near infrared imaging of the
neonatal brain. His research interests include numerical modeling and image
reconstruction with applications in both optical and electrical impedance to-
mography.
Marvin M. Doyley received a B.S. in Applied physics from
Brunel University, UK, in 1994, and a Ph.D. in Biophysics
from the University of London in 1999. From 1999 to 2001 he
worked on intravascular ultrasonic elastography at the
Department of Experimental Echocardiography of the
Thoraxcentre, Erasmus University of Rotterdam. In 2001, he
joined the Department of Radiology at the Dartmouth-Hitchcock Medical
Center to work on magnetic resonance elastographic imaging in breast appli-
cations. His research interests include ultrasonic and magnetic resonance im-
aging, tissue characterization, and inverse problem solution.
Alex Hartov, Associate Professor of Engineering at the Thayer
School of Engineering, Dartmouth College, and Associate Pro-
fessor of Surgery, Dartmouth Medical School, received a B.S.
in Electrical Engineering from Northeastern University in
1984, an M.S. in Engineering Sciences from Dartmouth Col-
lege in 1988, and a Ph.D. in Engineering Sciences from Dart-
mouth College in 1991. His research interests include biomedical engineer-
ing, electrical impedance tomography, image-guided surgery, cryosurgery,
ultrasound, control theory, microwave imaging, and tumor hyperthermia.
Contributors viii
Elijah E. W. Van Houten, Lecturer in Computational Solid
Mechanics at the University of Canterbury, Christchurch, New
Zealand, received a B.S. in Mechanical Engineering and a B.A.
in Music from Tufts University in 1997 and a Ph.D. in
Engineering Sciences from Dartmouth College in 2001. His
research interests include biomedical engineering, elasticity
imaging, reconstructive imaging methods, modeling of coupled fluid–solid
systems, and heart-valve dynamics.
Shudong Jiang received her Ph.D. in optoelectronics from the
Tokyo Institute of Technology in 1992. She was a research
scientist at the Tokyo Institute of Technology and at Japan
Science and Technology Corporation from 1992 to 1998. Her
major fields are high-sensitivity optical detection and nano-
etric-scale biosample observation and processing. She is
currently a research associate at Dartmouth College in the field of near infra-
red tomographic imaging of tissue.
Todd Kerner received a B.S. in physics from Haverford
College, Haverford, Pennsylvania, in 1994. He then worked at
the Philadelphia Heart Institute as part of a team studying
arrhythmias occurring after myocardial infarction. From 1995
to 2003 he was enrolled in the M.D./Ph.D. program at
Dartmouth College. He received his Ph.D. in Engineering in
2003 for a thesis involving the design, construction, and testing of an electri-
cal impedance tomography system. From 2003 to 2006 he is a resident in in-
ternal medicine at the Dartmouth-Hitchcock Medical Center.
Dun Li received a B.S. in Electrical Light Source Engineering
from Fudan University, Shanghai, in 1991; an M.S. in
Optoelectronics Engineering from the Shanghai Institute of
Technical Physics, the Chinese Academy of Science, Shanghai,
in 1997; and a Ph.D. in Biomedical Engineering from
Dartmouth College in 2003. He is currently a Research
Engineer at GE Medical Systems. His research interests include computa-
tional and experimental electromagnetics and biomedical imaging/navigation
system design and integration.
ix Model-Based Breast Imaging
Paul M. Meaney, Associate Professor of Engineering at the
Thayer School of Engineering, Dartmouth, received an A.B. in
Electrical Engineering and Computer Science from Brown
University in 1982, an M.S. in Electrical Engineering from the
University of Massachusetts in 1985, and a Ph.D. in Engi-
neering Sciences from Dartmouth College in 1995. His re-
search interests include microwave imaging for biomedical applications, mi-
crowave antenna design, ultrasound-based elasticity imaging, and thermal
modeling for focused-ultrasound surgery applications.
Keith D. Paulsen, Professor of Engineering at the Thayer
School of Engineering, Dartmouth College, received a B.S.
from Duke University in 1981 and M.S. and Ph.D. degrees
from Dartmouth in 1984 and 1986, all in biomedical engi-
neering. He was an assistant professor of electrical and com-
puter engineering at the University of Arizona from 1986 to
1988 and, jointly, an assistant professor in radiation oncology at the Univer-
sity of Arizona Health Sciences Center. He began teaching at Dartmouth
College in 1988. A recipient of numerous academic and research awards and
fellowships, he has carried out sponsored research for the National Science
Foundation, the Whitaker Foundation, and the National Institutes of Health
through the National Cancer Institute and the National Institute on Neuro-
logical Disorders and Stroke. He has served on numerous national advisory
committees for the National Cancer Institute, including membership on the
Radiation Study Section and the Diagnostic Imaging Study Section. At the
Thayer School of Engineering, Dartmouth College, he teaches biomedical
engineering and computational methods for engineering and scientific prob-
lems and is head of the Dartmouth Breast Imaging Group.
Brian Pogue is Associate Professor of Engineering at the
Thayer School of Engineering, Dartmouth College, and holds
research scientist positions at Harvard Medical School and
Massachusetts General Hospital. He received a B.S. in 1989
and an M.S. in 1991, both in physics, from York University,
Toronto, and a Ph.D. in medical physics from McMaster Uni-
versity, Ontario, in 1995. He worked as a research assistant professor at
Dartmouth for five years prior to his current position, and has been a scien-
tific review board member for the National Institutes of Health, National Sci-
ence Foundation, and the U.S. Department of Energy. He is the topical editor
for the journal Optics Letters and a conference organizer for the Optical So-
Description:Medical imaging has been transformed over the past 30 years by the advent of computerized tomography (CT), magnetic resonance imaging (MRI), and various advances in x-ray and ultrasonic techniques. An enabling force behind this progress has been the (so far) exponentially increasing power of compute
