Cancer-detecting Bra

Principal Investigator: Associate Professor Ng Yin Kwee, Eddie

Email:

mykng@ntu.edu.sg

Office:

N3.2-02-70

Tel:

(65) 6790 4455

Last Update: Dec 2015

PROJECT DESCRIPTION:

Dense breast tissue presents a higher risk of breast cancer developing than breast tissue with low density. Moreover, denser breast tissue is also related to higher rates of false positive and false negative results from mammography or ultrasound, leading to unnecessary breast biopsy surgeries or failure to detect abnormal tissue. Furthermore, millions of women from rural areas of countries such as India have limited or no access to these early diagnostic tools.

Together with US medical technology Cyrcadia Health, Inc. (http://cyrcadiahealth.com/), we developed a new tool to provide early diagnosis of breast cancer and validation of the diagnosis. The “First Warning Systems” (FWS) intelligent wearable biofeedback device is non-invasive, non-compressive and non-radiogenic, and projected to raise the accuracy of breast cancer assessment to over 75%. Integrated into a comfortable bra that needs to be worn for up to 48 hours but can be 2 hours duration for the commercial high end option, the FWS Circadian Biometric Recorder (CBRTM) dynamically monitors thermal metabolic changes that reflect circadian changes in breast tissue cells. Wireless transfer of the patient’s biometric data to FWS’s exclusive Breast Cancer Core Lab for comparison with databases and cancer “fingerprint” data allows the technology to be used even in geographically-remote places.

The original device has achieved FDA 510K clearance with 650 patients and the on-going final 173 BI-RADS 4/5 patient trail at JamesCare Comprehensive Breast Center in Ohio State University and The El Camino Hospital in Silicon Valley is positively tested and is being commercialized for product release in 2016.

PUBLICATIONS:

  1. Tan, JMY, Ng, E. Y-K., R Acharya U, Keith, L.G., and Holmes, J., “Comparative Study on the use of Analytical Software to Identify the Different Stages of Breast Cancer using Discrete Temperature Data”, Journal of Medical Systems, Springer, Vol. 33, No. 2 (2009), Pp. 141 -- 153. (DOI: 10.1007/s10916-008-9174-4)
  2. Ng, E. Y-K., R Acharya U, Keith, L.G., and Lockwood, S., “Detection and Classification of Breast Cancer using Neural Classifiers with First Warning Thermal Sensors”, Information Sciences, Vol. 177, No. 20, Elsevier, (2007), Pp. 4526--4538. DOI: 10.1016/j.ins.2007.03.027
  3. Ng E.Y.K., Tan MS, Lockwood S, Keith LG, ANN based Classification of Breast Cancer with Discrete Temperature Screening: Facts and Myths, pp. 403-439. Chp. 21, Book Chapters in Emerging Technologies in Breast Imaging and Mammography, J.S. Suri, R.M. Rangayyan and S Laxminarayan (Eds.), American Scientific Publishers, USA, ISBN: 1-58883-090-X2008
  4. S Vinitha Sree, Ng, E. Y-K., R Acharya U, and Jim Holmes “Evaluation of First Warning Systems Circadian Biometric Recorder TM, a wearable breast cancer detection device - A Predictive Analytics Paradigm”, (Internal Report @ 2014© Cyrcadia Health, Inc)

The reference numbers to the 3 US granted patents are:

12/198,967 (Method/Process); 12/583,969 (Utility: System) and 12/583,951 (Utility: Methods)