Meeting Banner
Abstract #2812

On the prediction of cognitive impairment trajectories from anatomical MRI in ADNI: preliminary results

Bruno Hebling Vieira1,2,3 and Nicolas Langer1,2,3
1Methods of Plasticity Research, Department of Psychology, University of Zurich, Zürich, Switzerland, 2Neuroscience Center Zurich (ZNZ), UZH & ETHZ, Zürich, Switzerland, 3University Research Priority Program (URPP) Dynamic of Healthy Aging, University of Zurich, Zürich, Switzerland

Synopsis

Keywords: Alzheimer's Disease, NeurodegenerationWe predict yearly differences in MMSE and CDR-SOB using data from the ADNI cohort ranging from five years before to five years after the imaging session. We show that models that use embeddings from a deep-learning model trained to predict brain-age or models that use bilateral hippocampi, amygdalae, and accumbens perform approximately the same as models that use baseline cognitive scores as inputs. This has potential ramifications for both clinical machine learning applications and the neurobiology of cognitive decline. In future work, we will finetune the deep-learning model and substantially increase the sample size.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords