US 12,232,843 B2
Method for early prediction of neurodegenerative decline
Nacim Betrouni, Lille (FR); and Régis Bordet, Lille (FR)
Assigned to INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM), Paris (FR); UNIVERSITE DE LILLE, Lille (FR); and CENTRE HOSPITALIER REGIONAL UNIVERSITAIRE DE LILLE, Lille (FR)
Appl. No. 16/977,980
Filed by INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM), Paris (FR); UNIVERSITE DE LILLE, Lille (FR); and CENTRE HOSPITALIER REGIONAL UNIVERSITAIRE DE LILLE, Lille (FR)
PCT Filed Mar. 6, 2019, PCT No. PCT/EP2019/055510
§ 371(c)(1), (2) Date Sep. 3, 2020,
PCT Pub. No. WO2019/170711, PCT Pub. Date Sep. 12, 2019.
Claims priority of application No. 18305244 (EP), filed on Mar. 7, 2018.
Prior Publication US 2021/0228079 A1, Jul. 29, 2021
Int. Cl. A61B 5/00 (2006.01); A61B 5/055 (2006.01); G06T 7/00 (2017.01); G06T 7/10 (2017.01); G06T 7/40 (2017.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01)
CPC A61B 5/0042 (2013.01) [A61B 5/055 (2013.01); A61B 5/4082 (2013.01); A61B 5/4088 (2013.01); A61B 5/7246 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); G06T 7/0012 (2013.01); G06T 7/10 (2017.01); G06T 7/40 (2013.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 2576/026 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/30016 (2013.01)] 26 Claims
OG exemplary drawing
 
1. A method for predicting risks of neurodegenerative decline of a patient, based on at least one medical brain image and at least one clinical and/or biological data of said patient, and using at least a classifier, trained beforehand to learn texture features extracted from a plurality of previously-acquired medical images of one or more areas of the brain and correlated with previously-acquired clinical and/or biological data, the method comprising:
extracting one or more texture features from said at least one medical brain image to obtain one or more extracted texture features,
correlating said one or more extracted texture features with said at least one clinical and/or biological data to obtain one or more correlated features, wherein the one or more extracted texture features are correlated with said clinical and/or biological data by using a statistical data modelling technique, and
based at least on said one or more correlated features, operating the trained classifier on the at least one medical brain image to generate a score representative of the risks of neurodegenerative decline of the patient,
said score being in the form of a probability for the patient for belonging to a predefined neurodegenerative profile or a predefined cognitive profile, said predefined profiles being used during the learning step of the classifier, in order that the latter can learn to associate the correlated features with such profiles, and/or
said score being in the form of a numerical value evaluating the risks of neurodegenerative decline at a term of six to 12 months for the patient, and/or
said score is in the form of a letter showing that the patient is thought to belong to a group of people having a predefined neurodegenerative profile.