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公开(公告)号：US09784665B1
公开(公告)日：2017-10-10
申请号：US14983296
申请日：2015-12-29
Applicant: Flagship Biosciences, Inc.
Inventor： Anthony J. Milici , George David Young , Holger Lange , Joseph Krueger , Nathan T. Martin
CPC classification number: G06T7/0012 , G01N1/30 , G01N33/6887 , G01N2333/4712 , G01N2800/10 , G06K9/0014 , G06K9/00147 , G06T2207/10056 , G06T2207/30004
Abstract: The disclosure concerns a method for assessing muscular dystrophy-linked protein expression in muscle fibers using digital image analysis of tissue. The method relates to assessing disease severity in individuals with muscular dystrophy. Muscle tissue samples are obtained from patients submitted for evaluation and processed to produce tissue sections mounted on glass slides which have been stained for a muscular dystrophy-linked protein. Digital images of the stained tissue sections are generated and analyzed by applying an algorithm process implemented by a computer to the images. The algorithm process extracts the morphometric and staining features of the muscular dystrophy-linked protein staining in the tissue, and parameters relating to these features are used to score the disease status for each patient submitted for evaluation. The score of disease status is ultimately used to infer disease severity, monitor the efficacy of a therapeutic approach, or select patients as candidates for a therapeutic approach.
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公开(公告)号：US20180040120A1
公开(公告)日：2018-02-08
申请号：US15220393
申请日：2016-07-27
Applicant: Flagship Biosciences, Inc.
Inventor： Crystal Dawn Faelan , Anthony J. Milici , Joshua C. Black , Nathan T. Martin
CPC classification number: G06T7/0012 , G01N1/30 , G01N33/6887 , G01N2333/4712 , G01N2800/10 , G06K9/0014 , G06K9/00147 , G06T11/60 , G06T2207/10024 , G06T2207/10056 , G06T2207/30024
Abstract: In accordance with the embodiment described herein, we describe a method for evaluating muscle fiber nuclei and non-muscle fiber mononuclear cells, and biomarkers expressed within these and muscle fibers, within the context of muscle tissue using digital tissue image analysis. An algorithm process is applied to histologically stained tissue sections to extract the morphometric, staining, and localization features of a plurality of tissue objects. These features can be further analyzed to describe relationships between tissue objects or tissue object image analysis features. One or more of these image analysis features or relationships between objects and features are summarized to derive a patient-specific score. Patient stratification criteria are applied to the patient-specific score and patient strata membership is evaluated to infer presence of disease, natural course of disease, disease severity, treatment efficacy, or response to a therapy and eligibility for said therapy.
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公开(公告)号：US20180011000A1
公开(公告)日：2018-01-11
申请号：US15696148
申请日：2017-09-05
Applicant: Flagship Biosciences, Inc.
Inventor： Anthony J. Milici , George David Young , Holger Lange , Joseph Krueger , Nathan T. Martin
CPC classification number: G06T7/0012 , G01N1/30 , G01N33/6887 , G01N2333/4712 , G01N2800/10 , G06K9/0014 , G06K9/00147 , G06T2207/10024 , G06T2207/10056 , G06T2207/10064 , G06T2207/30024
Abstract: The disclosure concerns a method for assessing muscular dystrophy-linked protein expression in muscle fibers using digital image analysis of tissue. The method relates to assessing disease severity in individuals with muscular dystrophy. Muscle tissue samples are obtained from patients submitted for evaluation and processed to produce tissue sections mounted on glass slides which have been stained for a muscular dystrophy-linked protein. Digital images of the stained tissue sections are generated and analyzed by applying an algorithm process implemented by a computer to the images. The algorithm process extracts the morphometric and staining features of the muscular dystrophy-linked protein staining in the tissue, and parameters relating to these features are used to score the disease status for each patient submitted for evaluation. The score of disease status is ultimately used to infer disease severity, monitor the efficacy of a therapeutic approach, or select patients as candidates for a therapeutic approach.
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