SBIR/STTR Award attributes
The long-term goal of this application is to advance full noncontact laser ultrasound (LUS) imaging from first in the world human demonstration to an instrument able to image the wounded at the point of care on the battlefield, and to deploy a new clinical imaging modality to provide new insight about the body. The military field medic must rapidly triage the wounded soldier. Ultrasound is an imaging tool which can help the medic to assess the wounds of the soldier and direct urgent evacuation and prioritize care. Ultrasound imaging advantages include that it is non-invasive, employs no radiation or contrast agents, and is inexpensive. Modern electronics enable the creation of small systems. Nevertheless, ultrasound limitations include required contact between probe and patient, the use of gel to serve as a coupling agent, and the skill level of the provider and variability in probe placement. Laser Ultrasound (LUS) addresses these limitations. LUS employs a completely different signal generation and detection technology, with advantages for the battlefield and other clinical uses. LUS uses only light, transmitted through air, to both generate and detect acoustic vibrations in the body. It only needs to be moved above the patient, with no connecting medium required, no physical contact. This is advantageous in cases where skin contact is prohibited due to burns or blast debris wounds. In LUS, we restrict optical to acoustic conversion to the tissue surface and solely interrogate underlying tissue with sound. We demonstrated the first fully eye- and skin-safe non-contact US imaging technique, enabled by laser generation and detection of sound. LUS is a groundbreaking addition to the arsenal of tools available to the medic, radiologist, surgeon, and general clinician, and enables new uses for ultrasound while addressing current ultrasound limitations. We propose to perform a feasibility study for the development of a handheld LUS scanning device – hardware and software subsystems, interfaces, and integrated system. We combine our commercialization experience, foundational work and detailed understanding of the LUS technology required, and work to translate LUS from our lab to the battlefield, to the field hospital, and to general clinical use. We propose to 1) evaluate the feasibility of the miniaturization, and integration of the optical and electronics hardware and software components and subsystems, that are the unique to LUS; 2) design the front-end interface and back-end data acquisition electronics and image reconstruction pipeline for LUS - similar to conventional US, but with some critical differences; 3) analyze the tradeoffs between techniques for image acquisition and image reconstruction; 4) evaluate the feasibility of a fully integrated compact design. We highlight the framework and roadmap for how to apply machine learning to the automated analysis of the LUS images.
