2026 ASEE Annual Conference & Exposition

Breast cancer remains the most prevalent malignancy among women, yet its prognosis is highly dependent on the stage of detection. Following a comprehensive review of thirty peer-reviewed studies encompassing medical imaging modalities, diagnostic algorithms, and device-engineering innovations, this research seeks to evaluate whether emerging wearable, bra-shaped ultrasound systems can function as effective, population-level screening tools.

Current diagnostic technologies exhibit notable strengths and limitations. Mammography remains the gold standard, reducing mortality by approximately 32 percent in women aged 50–69 (Warner 2011), though its performance declines in patients with dense breast tissue (Nover 2009). Ultrasound and MRI improve sensitivity but require specialized personnel and infrastructure. Electrical-impedance and microstrip-antenna devices (Zou & Guo 2003; Çalışkan 2015) demonstrate promise as portable, radiation-free methods but have yet to reach clinical maturity. Machine-learning-driven systems (Übeyli 2007; Hussain 2011) and advanced AI frameworks (Pan 2025; Ward 2025) continue to enhance classification accuracy and segmentation precision. Epidemiologic analyses confirm that early-stage detection yields five-year survival rates exceeding 96 percent (Saadatmand 2015), while disparities in global access to screening persist (Barrios 2022).

Building upon this evidence, the current phase of investigation focuses on the MIT-developed wearable ultrasound scanner (Dagdeviren et al. 2023), a flexible, honeycomb-structured patch that conforms to the breast and attaches to a bra insert. The system enables the user to move a miniature tracker across six scanning zones, acquiring images with resolution comparable to clinical ultrasound probes. Designed to identify interval cancers that develop between standard mammograms, the device offers continuous, self-operated, and radiation-free monitoring.

The objective of this study is to determine whether such wearable systems can be integrated into large-scale screening frameworks, improving early-stage detection, accessibility, and adherence. If successful, this innovation could redefine preventive oncology by merging biomedical engineering precision with public-health impact.