Neuromorphometric signatures of diseases affecting the brain
Title: Neuromorphometric signatures of diseases affecting the brain
SNIC Project: SNIC 2020/14-105
Project Type: SNIC Small Storage
Principal Investigator: Rolf A Heckemann <rolf.heckemann@medtechwest.se>
Affiliation: Göteborgs universitet
Duration: 2021-01-04 – 2022-02-01
Classification: 20603
Homepage: https://soundray.org/metrimorphics
Keywords:

Abstract

This application for storage accompanies application SNIC 2020/5-683 for a medium compute allocation. The abstracts are identical apart from this paragraph. Various conditions -- brain diseases as well as systemic diseases -- affect the human brain's structural configuration. For each condition, this raises the question whether quantifying such changes through morphometric analysis of brain images can yield biomarkers for predicting diagnosis, disease progression, and therapy response. I have developed image segmentation software (MAPER and Pincram, featured in IVA's 100-list of 2020, https://www.iva.se/projekt/research2business/ivas-100-lista-2020/) that automatically determines morphometric quantities on magnetic resonance images of the brain. With this application, I seek an allocation of computation time and storage to continue processing of images from several other studies: ESOP (epilepsy surgery outcome prediction, PI Prof. Bertil Rydenhag, GU), CogThy (a controlled study of Graves' disease and its impact on the brain, PI Helena Filipsson-Nyström PhD, GU), childhood dystonia (PI Daniel Lumsden PhD, Kings College London), Mega Donna Mega (a study of retinopathy in newborns; imaging arm led by Prof. Isabella Björkman-Burtscher, GU). In addition, I am planning to process images of healthy volunteers from publicly available repositories (e.g. the Human Connectome Project) to obtain normative morphometric reference data.