The prospective, multi-center study was conducted at 16 centers in the United States.
- Prospective clinical study presented at the San Antonio Breast Cancer Symposium suggests Imagio findings may help clinicians tailor patient treatment regimens -
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[08-December-2017] |
SAN ANTONIO, Dec. 8, 2017 /PRNewswire/ -- Seno Medical, the leader in new technology for breast cancer diagnosis using opto-acoustic (OA/US) imaging to differentiate benign from malignant masses, reported clinical data from their clinical study demonstrating that its Imagio™ breast imaging system achieved significant differentiation among prognostic subtypes of breast cancer (PSBC). These prognostic subtypes provide important information about the genes that each patient’s cancer expresses. The data are being presented today at 5:00 p.m. during a poster presentation [#P5-02-04] at the San Antonio Breast Cancer Symposium taking place December 5 - 9. “Confirming a diagnosis of breast cancer is just the first step in understanding the pathology of a patient’s tumor,” said study presenter Stephen Grobmyer, M.D., Director, Breast Surgical Oncology, Cleveland Clinic. “Determining a patient’s prognostic subtype of breast cancer is essential for understanding how tumors will respond to specific therapies and selecting a treatment regimen that offers the patient the best chance of a positive outcome. The findings that OA/US may differentiate among several breast cancer subtypes suggest that this novel imaging methodology could potentially provide a non-invasive alternative to biopsy without sacrificing information about the molecular pathology of the tumor. This could be an important advance for women with breast cancer.” The prospective, multi-center study was conducted at 16 centers in the United States. A total of 1,808 breast masses in 1,739 subjects assessed as BI-RADS (Breast Imaging and Reporting Data System, or BR) category 3, 4 or 5 were imaged with OA/US, resulting in the identification of 678 malignant lesions. Eight blinded readers scored these 678 lesions based on three internal features of the tumor and two external features of the tumor boundary and surrounding tissue. An experienced central breast pathologist who was blinded to the OA/US assessment confirmed the pathologic diagnoses. Biopsy specimens were obtained and assessed for the expression of four genes that comprise the PSBC: estrogen receptor (ER), progesterone receptor (PR), HER2-neu (HER2) and Ki-67. The PSBCs are defined as follows:
Tumors not meeting the definition of any of these categories were deemed unclassified. Key findings from the study include:
“The results of this study underscore the clinical benefits that can be achieved with Imagio’s functional imaging technology,” said Tom Umbel, CEO of Seno Medical Instruments. “Unlike anatomical imaging techniques, such as mammography or conventional ultrasound, functional imaging provides important information about the growth and location of blood vessels in and around breast masses. These findings show that not only does this functional imaging data allow for more accurate diagnosis of breast cancer, it also correlates with existing prognostic breast cancer subtypes. This data may suggest that OA/US has the potential to provide physicians with a powerful tool for gaining insight into the molecular pathology of each patient’s tumor without the need for invasive biopsy procedures. Seno Medical is committed to improving the care and outcomes of women with breast cancer through improved non-invasive diagnostic approaches.” The Imagio™ OA/US breast imaging system was designed and is being studied to identify two functional hallmarks of cancer: the presence of abnormal blood vessels (tumor angiogenesis) and the relative reduction in oxygen content of blood that occurs in cancer compared to benign masses and normal tissues. The technology is the subject of a U.S. PMA filing with the FDA and does have European CE Mark. About Seno Medical Instruments, Inc. About Breast Cancer Media Contact [1] U.S. Breast Cancer Statistics | Breastcancer.org. (2016). Breastcancer.org. http://www.breastcancer.org/symptoms/understand_bc/statistics
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