Systems, methods, and computer-readable media for patient image analysis to identify new diseases

Inventors

Gelbman, Dekel • Gurovich, Yaron

Assignees

FDNA Inc

Abstract

Systems, methods, and computer-readable media are disclosed for performing image processing in connection with phenotypic analysis. For example, at least one processor may be configured to receive electronic numerical information corresponding to pixels reflective of at least one external soft tissue image of an individual and access geographically dispersed genetic information stored in a database. The geographically dispersed genetic information may include numerical data that correlates anomalies in pixels in soft tissue images of a plurality of geographically dispersed individuals to specific genes or to specific genetic variants. The at least one processor may also be configured to compare the electronic numerical information for the individual with the numerical data of the geographically dispersed genetic information stored in a database, to determine at least a likelihood that the individual has a specific genetic variant, and prioritize, based on the comparison, one or more genetic variants according to likelihood of pathogenicity.

Core Innovation

The invention provides an electronic image processing system and computer-implemented method for identifying one or more unknown genetic disorders by analyzing a series of pixels in a plurality of images of external soft tissue. The system identifies a first individual with an unknown genetic disorder by analyzing first electronic data reflective of first values corresponding to pixels of an external soft tissue image, where the first values correspond to relationships between at least one group of pixels. The method likewise identifies a second individual with another unknown genetic disorder by analyzing second electronic data reflective of second values corresponding to second pixels, where the second values correspond to relationships between at least one group of pixels.

The invention compares at least some of the analyzed data of the first individual with at least some of the analyzed data of the second individual, based on the pixel-derived electronic values reflecting relationships among groups of pixels. The system then determines that the first individual and the second individual are likely to share the unknown genetic disorder. In related aspects, the likelihood determination is performed without identifying the unknown genetic disorder, while still concluding that the individuals are likely to share it.

The disclosed system further extends the comparison to genetic confirmation and downstream association tasks, including receiving genetic data and determining shared common genetic anomalies. The disclosure also includes identifying an unknown genetic disorder as a new disease, clustering individuals into a common group likely to share the unknown genetic disorder, and identifying comparable genetic disorders using symptom overlap. In addition, the system may compare pixel-derived data between a first individual and a second individual with a known genetic disorder and determine that the first individual is likely to share the known genetic disorder based on the comparison.

Claims Coverage

The document includes four independent claims. The independent claims collectively cover pixel-based analysis of external soft tissue images to derive relationships among groups of pixels, comparison between individuals to determine likelihood of shared genetic disorder status, and computer-implementation via an electronic image processing system, method, or non-transitory computer-readable medium; one independent claim further anchors the likelihood to a comparison with a known genetic disorder.

Across the independent claims, the inventive concept is the use of electronic numerical pixel-derived relationships from external soft tissue images, followed by comparison of analyzed data between individuals to determine a likelihood of shared genetic disorder status. The coverage spans system, method, and non-transitory computer-readable medium implementations, and includes an aspect where the likelihood is determined relative to a known genetic disorder.

Stated Advantages

Documented Applications