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.
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.
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