NEUROIMAGING AND BIOMARKER-BASED ASSESSMENT OF DISEASE PROGRESSION IN NEURODEGENERATIVE DISORDERS

Abstract

Neurodegenerative diseases are typified by progressive structural, functional, and molecular changes, which come before clinically. The purpose of this paper was to find the nature of the illness on the basis of a composite model, which is a synthesis of the most recent neuroimaging, as well as fluid biomarkers. We used multimodal measures that included structural and functional neuroimaging and biochemical measures of neurodegeneration and synaptic dysfunction and neuroinflammation of longitudinal cohorts. Its results suggest that integrated imaging-biomarker models are better than unit-modality in the measurement of tracking disease progression because it is sensitive to the early pathological changes and can identify the difference between the disease stages. Biomarker pathways, such as increased neurofilament light chain, amyloid- 2 imbalance, and tau pathology, were significantly related to changes in the structure of the brain, such as shrinkage, microstructural disturbance, and altered connectivity. It was proved that integrated metrics were capable of predicting progression and clinical rates of decline based on predictive modeling. Such results make clear that multimodal evaluation techniques of early diagnosis, patient classification and outcome monitoring are translational. The paper advocates the use of neuroimaging and biomarkers combination as a fundamental element of an accuracy instrument in the research and treatment of neurodegenerative diseases.