Overview
- New ways of detecting breast tumors
- Physicians and engineers work together
- Dartmouth physicians and engineers are collaborating to test three new imaging techniques to find breast abnormalities, including cancer. Results from the first stage of their research, information about the electro-magnetic characteristics of healthy breast tissue, appears in the May 2004 issue of Radiology, the journal of the Radiological Society of North America.
- The interdisciplinary team, which includes researchers from Dartmouth's Thayer School of Engineering and Dartmouth Medical School working with experts at the Norris Cotton Cancer Center and the Department of Radiology at Dartmouth-Hitchcock Medical Center (DHMC), is developing and testing imaging techniques to learn about breast tissue structure and behavior. The techniques are electrical impedance spectral imaging (EIS), microwave imaging spectroscopy (MIS), and near infrared (NIR) spectral imaging.
- This study offers the foundation for future research and clinical trials," says Steven Poplack, Associate Professor of Radiology and Obstetrics and Gynecology at Dartmouth Medical School, doctor of diagnostic radiology and Co-Director for Breast Imaging/Mammography at DHMC, and the lead author of the paper. "We're establishing normal ranges for healthy breast tissue characteristics in order to more easily recognize the abnormalities."
- The study of 23 healthy women offers baseline data from the three techniques. The methods are not invasive or particularly uncomfortable for participants, and they all provide detailed information about different properties of breast tissue.
- EIS: This painless test uses a very low-voltage electrode system to examine how the breast tissue conducts and stores electricity. Living cell membranes carry an electric potential that affects the way a current flows, and different cancer cells have different electrical characteristics.
- MIS: This exam involves the propagation of very low levels (1,000 times less than a cell phone) of microwave energy through breast tissue to measure electrical properties. This technique is particularly sensitive to water. Generally, tumors have been found to have more water and blood than regular tissue.
- NIR: Infrared light is sensitive to blood, so by sending infrared light through breast tissue with a fiber optic array, the researchers are able to locate and quantify regions of oxygenated and deoxygenated hemoglobin. This may help detect early tumor growth and characterize the stage of a tumor by learning about its vascular makeup.
- Keith D. Paulsen, Professor of Engineering and a co-author of the study, is the principal investigator of this research program, which is funded by the National Cancer Institute. Other authors on the paper include Alexander Hartov, Paul M. Meaney, Brian W. Pogue, Tor D. Tosteson, Margaret R. Grove, Sandra K. Soho, and Wendy A. Wells, all associated with Dartmouth's Thayer School of Engineering or DMS.
- Includes supplementary material: sn.pub/extras
Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 778)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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 computers, which has made it practical to explore fundamentally new approaches. In particular, what our group terms "model-based" modalities-which produce tissue property images from data using nonlinear, iterative numerical modeling techniques-have become increasingly feasible.
Alternative Breast Imaging: Four Model-Based Approaches explores our research on four such modalities, particularly with regard to imaging of the breast: (1) MR elastography (MRE), (2) electrical impedance spectroscopy (EIS), (3) microwave imaging spectroscopy (MIS), and (4) near infrared spectroscopic imaging (NIS). Chapter 1 introduces the present state of breast imaging and discusses how our alternative modalities can contribute to the field. Chapter 2 looks at the computational common ground shared by all four modalities. Chapters 2 through 10 are devoted to the four modalities, with each modality being discussed first in a theory chapter and then in an implementation-and-results chapter. The eleventh and final chapter discusses statistical methods for image analysis in the context of these four alternative imaging modalities.
Imaging for the detection of breast cancer is a particularly interesting and relevant application of the four imaging modalities discussed in this book. Breast cancer is an extremely common health problem for women; the National Cancer Institute estimates that one in eight US women will develop breast cancer at least once in her lifetime. Yet the efficacy of the standard (and notoriously uncomfortable) early-detection test, the x-ray mammogram, has been disputed of late, especially for younger women. Conditions are thus ripe for the development of affordable techniques that replace or complement mammography. The breast is both anatomically accessible and small enough that the computing power required to model it, is affordable.
Reviews
From the reviews:
"This well-organized and constructed work explores … . There are 11 chapters’ beginning with an excellent overview of the four approaches … . It is, by itself, a very nice review of the topic, and is useful as a guide … . It is all the more useful because it compares … in a meaningful context. … the use of models and simulation, physical and mathematical throughout the work, is impressive … . This text would be best used in graduate-level courses … ." (A.G. Greenburg, Computing Reviews, February, 2005)
Authors and Affiliations
Bibliographic Information
Book Title: Alternative Breast Imaging
Book Subtitle: Four Model-Based Approaches
Authors: Keith D. Paulsen, Paul M. Meaney, Larry C. Gilman
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/b101336
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag US 2005
Hardcover ISBN: 978-0-387-23363-5Published: 29 October 2004
Softcover ISBN: 978-1-4419-3616-5Published: 06 December 2010
eBook ISBN: 978-0-387-23364-2Published: 11 January 2006
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XVI, 254
Topics: Image Processing and Computer Vision, Ultrasound, Imaging / Radiology, Biomedical Engineering and Bioengineering, Computer Imaging, Vision, Pattern Recognition and Graphics