Unmet Need / Invention Novelty: The identification of cancerous breast masses using traditional ultrasound imaging techniques is limited because ultrasounds typically cannot distinguish solid masses from fluid-filled regions in patients with dense breast tissue. Dense tissue results in increased acoustic clutter, which obscures lesions and contributes to false positive rates of breast cancer diagnosis. Short-lag spatial coherence (SLSC) and robust short-lag spatial coherence (R-SLSC) described herein are two advanced ultrasound beamforming techniques that when coupled with deep learning array signal processing can distinguish fluid-filled regions from solid masses without the need of unnecessary biopsies.
Technical Details: Johns Hopkins researchers have developed a coherence-based ultrasound imaging technique to distinguish suspicious fluid-filled lesions from solid masses for early breast cancer detection. By utilizing array signal processing and a deep neural network to predict coherent functions, backscattered ultrasound signals are used generate SLSC images in real time with reduced acoustic clutter. This coherence-based beamforming technique has successfully been applied to the in-vivo detection and identification of cysts, fibroadenoma, and ductal carcinoma masses in female breasts that are challenging to diagnose otherwise.
- Value Proposition:Novel array signal processing to distinguish solid from fluid-filled masses in dense tissues for breast cancer detection
- Provides real time SLSC imaging with the application of a deep neural network
- Can be readily applied to the detection of masses in other organs such as in the liver and testicles
Looking for Partners to: Develop & commercialize the technology as an ultrasound-based early detection modality for cancerous lesion detection
Stage of Development: Prototype
Data Availability: In-vivo data
Inventors: Muyinatu Bell, Alycen Wiacek
Patent Status: Provisional Patent [62/907,356]
Publication(s): A. Wiacek et al., "Clinical Feasibility of Coherence-Based Beamforming to Distinguish Solid from Fluid Hypoechoic Breast Masses," 2018 IEEE International Ultrasonics Symposium (IUS), Kobe, 2018, pp. 1-4.
doi: 10.1109/ULTSYM.2018.8579846
