Grant: Operating Grant
Research Institute of the McGill University Health Centre
$450,863.00
Diagnosis, prognosis and classification of retinopathies: Comparing time-amplitude domain (TAD) with time-frequency domain (TFD) analyses of the electroretinogram.
FY 2012-13
Summary
The electroretinogram (ERG) identifies the electrical response evoked by the retina in response to a light stimulus of adequate energy. The ERG is to the retina what the electrocardiogram is to the heart. The ERG is essential not only for the diagnosis but also for the proper management of patients affected with a variety of retinal distrophies. Clinical ERG protocols usually require that photopic and scotopic ERGs be obtained from patients in order to assess rod and cone functions separately, as there are some retinopathies that can hinder one of the two retinal pathways preferentially, at least in the initial phase of the disease. However, with progression usually one of the two retinal pathways is lost to the pathology, leaving the complementary one solely responsible for visually guided behaviors. Significantly reduced ERGs, with ill-defined morphologies, are often the only retinal signal remaining from patients affected with severe degenerative retinopathies. These residual retinal responses are often challenging to analyze. The aim of this research proposal is to demonstrate that use of newly developed mathematical tools can help in extracting, from residual ERGs, valuable clinical information. The possibility of using residual ERGs to stage the progression of severe debilitating retinopathies will allow us to construct a disease-symptoms classification system that will enable us to offer more accurate diagnoses and prognoses for the affected patients. This classification system will undoubtedly have a significant impact on the management of these patients, especially if cures become available.
Department
Program
Operating Grant
Location
Quebec, Canada
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
265998
Name
Lachapelle Pierre
Region
Québec
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Neurosciences, Mental Health and Addiction
Theme2
Biomedical
Prcname2
Systems & Circuits Neurosciences - A
Projecttitle
Diagnosis, prognosis and classification of retinopathies: Comparing time-amplitude domain (TAD) with time-frequency domain (TFD) analyses of the electroretinogram.
Programtype2
Operating Grants
Orgnameinp2
Research Institute of the McGill University Health Centre
Cihramount2
$450,863
Cihrequipment2
$0
Programname2
Operating Grant
Keyworddelim
Animal Models; Electroretinogram; Erg Model; Human; Mathematical Models; Residual Vision; Retinopathy; Time-Scale Analysis; Visiual Function
Abstract
The electroretinogram (ERG) identifies the electrical response evoked by the retina in response to a light stimulus of adequate energy. The ERG is to the retina what the electrocardiogram is to the heart. The ERG is essential not only for the diagnosis but also for the proper management of patients affected with a variety of retinal distrophies. Clinical ERG protocols usually require that photopic and scotopic ERGs be obtained from patients in order to assess rod and cone functions separately, as there are some retinopathies that can hinder one of the two retinal pathways preferentially, at least in the initial phase of the disease. However, with progression usually one of the two retinal pathways is lost to the pathology, leaving the complementary one solely responsible for visually guided behaviors. Significantly reduced ERGs, with ill-defined morphologies, are often the only retinal signal remaining from patients affected with severe degenerative retinopathies. These residual retinal responses are often challenging to analyze. The aim of this research proposal is to demonstrate that use of newly developed mathematical tools can help in extracting, from residual ERGs, valuable clinical information. The possibility of using residual ERGs to stage the progression of severe debilitating retinopathies will allow us to construct a disease-symptoms classification system that will enable us to offer more accurate diagnoses and prognoses for the affected patients. This classification system will undoubtedly have a significant impact on the management of these patients, especially if cures become available.
Competitiondate
201209
Approvedterm2
5 yrs 0 mth
Pinamesdelim
Lachapelle, Pierre
Approvedterm
5 ans 0 mois
Cihrcontribution2
~ $450,863~ $0~