Ponencia
Multi-stage Biomarker Models for Progression Estimation in Alzheimer’s Disease
Autor/es | Schmidt-Richberg, Alexander
Guerrero, Ricardo Ledig, Christian Molina Abril, Helena Frangi, Alejandro F. Rueckert, Daniel |
Departamento | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Fecha de publicación | 2015 |
Fecha de depósito | 2020-02-26 |
Publicado en |
|
ISBN/ISSN | 978-3-319-19991-7 0302-9743 |
Resumen | The estimation of disease progression in Alzheimer’s disease
(AD) based on a vector of quantitative biomarkers is of high interest
to clinicians, patients, and biomedical researchers alike. In this work,
quantile ... The estimation of disease progression in Alzheimer’s disease (AD) based on a vector of quantitative biomarkers is of high interest to clinicians, patients, and biomedical researchers alike. In this work, quantile regression is employed to learn statistical models describing the evolution of such biomarkers. Two separate models are constructed using (1) subjects that progress from a cognitively normal (CN) stage to mild cognitive impairment (MCI) and (2) subjects that progress from MCI to AD during the observation window of a longitudinal study. These models are then automatically combined to develop a multi-stage disease progression model for the whole disease course. A probabilistic approach is derived to estimate the current disease progress (DP) and the disease progression rate (DPR) of a given individual by fitting any acquired biomarkers to these models. A particular strength of this method is that it is applicable even if individual biomarker measurements are missing for the subject. Employing cognitive scores and image-based biomarkers, the presented method is used to estimate DP and DPR for subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Further, the potential use of these values as features for different classification tasks is demonstrated. For example, accuracy of 64% is reached for CN vs. MCI vs. AD classification. |
Cita | Schmidt-Richberg, A., Guerrero, R., Ledig, C., Molina Abril, H., Frangi, A.F. y Rueckert, D. (2015). Multi-stage Biomarker Models for Progression Estimation in Alzheimer’s Disease. En IPMI 2015: 24th International Conference on Information Processing in Medical Imaging (387-398), Sabhal Mor Ostaig, Isle of Skye, UK: Springer. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
Multi-stage Biomarker Models.pdf | 5.645Mb | [PDF] | Ver/ | |