| Literature DB >> 33568448 |
Thomas Edmund Cope1,2,3, Rimona Sharon Weil4,5,6,7, Emrah Düzel8,9,10,11, Bradford C Dickerson12,13, James Benedict Rowe14,2,3.
Abstract
Advances in neuroimaging are ideally placed to facilitate the translation from progress made in cellular genetics and molecular biology of neurodegeneration into improved diagnosis, prevention and treatment of dementia. New positron emission tomography (PET) ligands allow one to quantify neuropathology, inflammation and metabolism in vivo safely and reliably, to examine mechanisms of human disease and support clinical trials. Developments in MRI-based imaging and neurophysiology provide complementary quantitative assays of brain function and connectivity, for the direct testing of hypotheses of human pathophysiology. Advances in MRI are also improving the quantitative imaging of vascular risk and comorbidities. In combination with large datasets, open data and artificial intelligence analysis methods, new informatics-based approaches are set to enable accurate single-subject inferences for diagnosis, prediction and treatment that have the potential to deliver precision medicine for dementia. Here, we show, through the use of critically appraised worked examples, how neuroimaging can bridge the gaps between molecular biology, neural circuits and the dynamics of the core systems that underpin complex behaviours. We look beyond traditional structural imaging used routinely in clinical care, to include ultrahigh field MRI (7T MRI), magnetoencephalography and PET with novel ligands. We illustrate their potential as safe, robust and sufficiently scalable to be viable for experimental medicine studies and clinical trials. They are especially informative when combined in multimodal studies, with model-based analyses to test precisely defined hypotheses. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.Entities:
Keywords: MRI; PET; dementia; functional imaging; image analysis
Mesh:
Year: 2021 PMID: 33568448 PMCID: PMC8862738 DOI: 10.1136/jnnp-2019-322402
Source DB: PubMed Journal: J Neurol Neurosurg Psychiatry ISSN: 0022-3050 Impact factor: 10.154