Next generation axonal quantification and classification using AI

Abstract This Phase II project describes the commercial development of HyperAxon™, highly innovative software for performing automated segmentation, tracing, reconstruction and quantitative analysis of all axonal fibers (with and without signs of acute axonal injury) visible in two- and three-dimensional (2D and 3D) microscopy images of central nervous system (CNS) areas, even those with extremely high axonal fiber density. Accurate and rigorous analysis of all axonal fibers visible in 3D and 2D microscopy images of CNS tissue of non-transgenic and transgenic animal models as well as in human post mortem CNS tissue promises to enable researchers to gain novel insights into physiological neural network connectivity patterns as well as into the neuropathological underpinnings of alterations in connectivity associated with human neuropsychiatric and neurological disorders. However, this cannot be achieved with contemporary, computer-assisted tracing and reconstruction methods, which currently are the gold standard for investigating axonal fibers, because these methods primarily address tracing and reconstruction of only a limited number of individual axonal fibers. During Phase I we created HyperAxon prototype software by leveraging the original, lab-built technology Learning-based Tracing of Dense Axonal Fibers created at MIT Lincoln Laboratory (MIT LL) (Lexington, MA) and extending this technology with several new, specialized deep neural networks. Furthermore, we validated that our approach will be successful in research applications. All specific aims of Phase I were fully completed, demonstrating feasibility of successfully developing HyperAxon. The game-changing innovation in HyperAxon is the ability to automatically (i) segment, trace and reconstruct all axonal fibers visible in 3D and 2D microscopy images of CNS areas with high axonal fiber density, (ii) identify axonal branch points, (iii) resolve axonal fibers of passage in fiber tracts from those in axonal terminal fields, (iv) identify axonal fibers showing acute axonal injury and (v) precisely quantify alterations in number and density of axonal fibers in CNS tissue. For widespread dissemination of this important new technology we plan to commercialize the HyperAxon software at the end of Phase II as both a cloud-based “software as a service” running on Amazon Web Services (AWS) and traditional software application running on local institutional computers. We are convinced that HyperAxon will be impactful in the field of neuroscience research and will enable substantial advancements in research on alterations in CNS circuitry associated with neurodevelopmental, neuropsychiatric, neurodegenerative and neurological disorders. Ultimately, this will result in an improved basis for developing novel treatment strategies for a wide spectrum of complex brain diseases. In Phase I we demonstrated feasibility of this novel technology by developing prototype software; work in Phase II will focus on creating the full functionality of HyperAxon for commercial release. During Phase II we will perform extensive product validation and usability studies of HyperAxon in close collaboration with MIT LL and our academic collaboration partners. A competing technology is not available.