March 3, 2011 |
Troy, N.Y. — Recent research by doctoral student Sevan Goenezen holds the promise of becoming a powerful new weapon in the fight against breast cancer. His complex computational research has led to a fast, inexpensive new method for using ultrasound and advanced algorithms to differentiate between benign and malignant tumors with a high degree of accuracy.
Goenezen, a student in the Department of Mechanical, Aerospace, and Nuclear Engineering at Rensselaer, is one of three finalists for the 2011 $30,000 Lemelson-MIT Rensselaer Student Prize. A public ceremony announcing this year’s winner will be held at 7 p.m. on Wednesday, March 9 in the auditorium of the Rensselaer Center for Biotechnology and Interdisciplinary Studies. For more information on the ceremony visit: http://www.eng.rpi.edu/lemelson/
Goenezen’s project is titled “Breast Cancer Diagnosis with Nonlinear Elasticity Imaging,” and his faculty adviser is Assad Oberai, associate professor of mechanical, aerospace, and nuclear engineering at Rensselaer.
Nearly 200,000 women are diagnosed with breast cancer annually in the United States, and the disease takes the lives of more than 40,000 women every year, according to the National Institutes of Health. Early detection is crucial for combating cancer, and beginning at age 40 women are urged to undergo yearly mammograms, which cannot reliably distinguish between benign and malignant tumors. So if a tumor is found, a biopsy is required before the physician can make a final diagnosis.
Goenezen’s research offers the hope of dramatically reducing the need for invasive, uncomfortable, and stress-inducing biopsies, and perhaps even replacing mammograms. It uses a new technique to analyze images captured with a noninvasive, radiation-free ultrasound device, locate tumors, and determine if the tumor is malignant. The only required equipment is a specific type of ultrasound machine — which generally costs around $10,000, far less than X-ray equipment — and a common personal computer. Thanks to these new algorithms, results can be computed in less than five minutes on a high-end PC.
This new technique uses ultrasound images of breast tissue to infer the mechanical properties of the tissue as it is compressed. The structure of collagen fibers within malignant tissues is very different from the collagen fiber structure in benign tissue. This method quantifies the non-linear behavior of the tumor tissue to determine whether it is cancerous.
In a clinical study, Goenezen used this strategy to analyze 10 data sets, five of which were from patients with benign tumors, and five with malignant tumors. The system correctly diagnosed nine out of the 10 patients. The lone error was a false positive, meaning the system indicated the tumor was malignant when it was actually benign.
Goenezen is confident that this new method could lead to less expensive, more effective, and safer diagnosis of breast cancer, which holds the potential to save many lives and significantly trim the screening costs for patients, doctors, and hospitals. Additionally, he said he believes this new method could be adapted to diagnose other diseases, including prostate cancer, cervical cancer, liver cirrhosis, and atherosclerosis. His study was conducted in collaboration with scientists and engineers at Rensselaer, Boston University, University of Wisconsin, and Siemens Inc.
Born and raised in between the picturesque and historical German cities of Aachen and Cologne in Germany, Goenezen is the second youngest of three brothers and two sisters. His father, a retired carpenter, and mother are very proud and cheering for him to win the 2011 Lemelson-MIT Rensselaer Student Prize. A problem-solver from a very young age, Goenezen grew interested in science and engineering in high school. Outside of his studies and research, he enjoys swimming, jogging, and the outdoors. Since moving to the United States in 2007 to earn his doctoral degree, he has developed a passion for hiking.
Goenezen received his master’s degree in aeronautical engineering from the Rheinisch-Westfalische Technische Hochschule Aachen in Aachen, Germany. He expects to complete his doctorate and graduate from Rensselaer in May 2011 with a perfect 4.0 grade point average.
About the $30,000 Lemelson-MIT Rensselaer Student Prize
The $30,000 Lemelson-MIT Rensselaer Student Prize is funded through a partnership with the Lemelson-MIT Program, which has awarded the $30,000 Lemelson-MIT Student Prize to outstanding student inventors at MIT since 1995.
About the Lemelson-Mit Program
Celebrating innovation, inspiring youth
The Lemelson-MIT Program celebrates outstanding innovators and inspires young people to pursue creative lives and careers through invention.
Jerome H. Lemelson, one of U.S. history’s most prolific inventors, and his wife, Dorothy, founded the Lemelson-MIT Program at the Massachusetts Institute of Technology in 1994. It is funded by the Lemelson Foundation and administered by the School of Engineering. The Foundation sparks, sustains and celebrates innovation and the inventive spirit. It supports projects in the U.S. and developing countries that nurture innovators and unleash invention to advance economic, social and environmentally sustainable development. To date the Lemelson Foundation has donated or committed more than U.S. $150 million in support of its mission. http://web.mit.edu/invent/
For information on past winners of the $30,000 Lemelson-MIT Rensselaer Student Prize, visit:
- Helping Hydrogen: Student Inventor Tackles Challenge of Hydrogen Storage
Javad Rafiee’s graphene innovation could lead to more efficient hydrogen-powered vehicles
- Student Developer of Versatile “G-gels” Wins $30,000 Lemelson-Rensselaer Prize
Yuehua “Tony” Yu’s innovation could lead to new medical devices, drug-delivery technologies
- Student Develops New LED, Wins $30,000 Lemelson-Rensselaer Prize
Martin Schubert’s polarized LED could improve LCD displays, save energy
- Handheld “T-ray” Device Earns New $30,000 Lemelson-Rensselaer Student Prize
Brian Schulkin’s “Mini-Z” spots cracks in space shuttle foam, detects tumors in tissue
Visit the Rensselaer research and discovery blog: http://approach.rpi.edu
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