An introduction to the Cyrcadia Breast Monitor: A wearable breast health monitoring device. (December 2020)

• Record Type: Journal Article
• Authors: S, Vinitha Sree; Royea, Rob; Buckman, Kevin J.; Benardis, Matt; Holmes, Jim; Fletcher, Ronald L.; EYK, Ng; Rajendra Acharya, U.; Ellenhorn, Joshua D.I.
• Is Part Of: Computer methods and programs in biomedicine. Volume 197(2020)
• Publication Date: 2020-12
• Subjects: Breast cancer -- Wearable device -- Thermal metabolomics -- Circadian rhythm -- Predictive analytics -- Machine learning -- Data mining; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2020.105758
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: There is a clear need for an affordable and effective adjunct breast cancer detection modality that can help reduce unnecessary biopsies, and therefore, reduce healthcare cost burden and patient anxiety. Cyrcadia Breast Monitor (CBM) is a non-invasive, non-compressive, and non-radiogenic wearable device that records thermodynamic metabolic data from the breast skin surface over a period of time using two wearable biometric patches and a data recorder. An Artificial Intelligence based predictive analytics framework was used to develop a predictive model that uses CBM data to determine the presence of breast tissue abnormalities. The initial clinical trial results indicate that the CBM system can potentially detect breast abnormalities with an accuracy comparable to that of mammography. Abstract: Background: The most common breast cancer detection modalities are generally limited by radiation exposure, discomfort, high costs, inter-observer variabilities in image interpretation, and low sensitivity in detecting cancer in dense breast tissue. Therefore, there is a clear need for an affordable and effective adjunct modality that can address these limitations. The Cyrcadia Breast Monitor (CBM) is a non-invasive, non-compressive, and non-radiogenic wearable device developed as an adjunct to current modalities to assist in the detection of breast tissue abnormalities in any type of breast tissue. Methods: The CBM records thermodynamic metabolic data from the breast skin surface over a period of time using two wearable biometric patches consisting of eight sensors each and a data recording device. The acquired multi-dimensional temperature time series data are analyzed to determine the presence of breast tissue abnormalities. The objective of this paper is to present the scientific background of CBM and also to describe the history around the design and development of the technology. Results: The results of using the CBM device in the initial clinical studies are also presented. Twenty four-hour long breast skin temperature circadian rhythm data was collected from 93 benign and 108 malignant female study subjects in the initial clinical studies. The predictive model developed using these datasets could differentiate benign and malignant lesions with 78% accuracy, 83.6% sensitivity and 71.5% specificity. A pilot study of 173 female study subjects is underway, in order to validate this predictive model in an independent test population. Conclusions: The results from the initial studies indicate that the CBM may be valuable for breast health monitoring under physician supervision for confirmation of any abnormal changes, potentially prior to other methods, such as, biopsies. Studies are being conducted and planned to validate the technology and also to evaluate its ability as an adjunct breast health monitoring device for identifying abnormalities in difficult-to-diagnose dense breast tissue.