Imaging of Neurodegeneration within the NIA-AA Research Framework: The ‘N’ in the AT(N) Scheme

Alzheimer’s disease (AD) is the most common form of dementia, affecting millions globally. As research shifts increasingly toward earlier diagnosis and targeted interventions, including of risk factors, biomarker-based frameworks have become essential tools for guiding both clinical research and drug development. The AT(N) scheme within the National Institute on Aging and Alzheimer’s Association (NIA-AA) Research Framework classifies biomarkers into three categories: A (amyloid pathology), T (tau pathology), and N (neurodegeneration or neuronal injury) [Jack et al., 2018].

While the A and T components are defined through molecular imaging and cerebrospinal fluid (CSF) measures, the N category considers structural magnetic resonance imaging (MRI) evidence of brain atrophy, as well as CSF total tau (t-tau) and [¹⁸F]-fluorodeoxyglucose (FDG)-PET hypometabolism.

Imaging plays a central role in the assessment of the N, providing quantitative biomarkers for the use of the AT(N) in research, or as part of participant selection and outcome measurement in clinical trials.

Imaging Modalities for the ‘N’

The primary imaging technique used to capture neurodegeneration is structural MRI, particularly 3D T1-weighted sequences. These allow for detailed measurements of brain atrophy, in regions vulnerable to AD. Volumetric analyses, including automated segmentation tools, quantify regional brain volume loss, which correlates with cognitive decline and disease progression [Frisoni et al., 2010].

FDG-PET is integrated into the N category, because ‘typical AD’ (amnestic multidomain dementia) is associated with a characteristic regional pattern of reduced glucose metabolism [Jagust et al., 2009], which reflects synaptic dysfunction and neuronal loss.

In addition to volumetrics and FDG-PET, diffusion MRI provides information on white matter microstructural integrity, while task-based and resting-state functional MRI can be used to explore functional network-level disruptions associated with neurodegeneration.

Imaging Biomarkers of Neurodegeneration

Among the imaging biomarkers commonly used to assess neurodegeneration are hippocampal, medial temporal lobe and whole-brain volume loss, ventricular enlargement, reduced cortical thickness, and hypometabolism in the posterior cingulate and temporoparietal cortex. These markers offer complementary perspectives on the extent and pattern of neuronal loss and related disruption.

As emerging treatments target the earlier stages of AD, it is important to consider factors that can complicate the interpretation of biomarkers. For example, recent studies have underscored the heterogeneity of conditions with dementia. These include AD and its clinical variants and imaging subtypes, but also diseases such as frontotemporal dementia and dementia with Lewy bodies. The patterns of neurodegeneration can partially overlap in different conditions. There is also a need to consider mixed pathologies, especially concurrent cerebrovascular disease. Neuroimaging, particularly MRI, provides markers of both neurodegeneration and cerebrovascular changes, which can help build a more detailed picture of a person’s condition [Haller et al., 2023].

Emerging Trends: Multimodal Imaging and Disease Differentiation

Advances in multimodal imaging offer new possibilities for improving specificity and sensitivity in AD research. Combining structural MRI with molecular imaging, functional techniques, and advanced image analytics allows for a more comprehensive assessment of neurodegenerative changes across different stages and phenotypes of the disease. Such approaches are increasingly being incorporated into clinical trials as well as observational studies [Loftus et al., 2023].

Moreover, the recognition of AD variants, mixed dementias and co-pathologies has driven the development of more nuanced imaging solutions and analytical strategies. These aim not only to track neurodegeneration but to do so in a way that reflects the true biological complexity of AD and related diseases.

The AT(N) scheme was designed to be flexible in that new biomarkers can be added to the existing components, and in that new biomarker groups, beyond the A, T and N, can be added as they become available.

Advancing the Science of Neurodegeneration

As our understanding of AD continues to evolve, so too must the tools and methodologies used to study it. Imaging biomarkers are playing an increasingly central role in revealing the complexities of neurodegeneration - from early detection to tracking disease progression.

The field is moving forward through collaboration, innovation, and a shared commitment to scientific excellence. With major gatherings like the Alzheimer’s Association International Conference (AAIC) 2025 on the horizon, the global research community remains united in its pursuit of deeper insights and more effective interventions.

References:

• Jack, C. R., Bennett, D. A., Blennow, K., et al. (2018). NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimer's & Dementia, 14(4), 535–562. https://doi.org/10.1016/j.jalz.2018.02.018
• Frisoni, G. B., Fox, N. C., Jack, C. R., et al. (2010). The clinical use of structural MRI in Alzheimer disease. Nature Reviews Neurology, 6, 67–77. https://doi.org/10.1038/nrneurol.2009.215
• Jagust, W. J., Landau, S. M., Shaw, L. M., et al. (2009). Relationships between biomarkers in aging and dementia. Neurology, 73(15), 1193-1199. https://doi.org/10.1212/WNL.0b013e3181bc010c
• Haller, S. Jäger, H. R., Vernooij, M. W. & Barkhof, F. (2023). Neuroimaging in dementia: More than typical Alzheimer disease. Radiology, 308(3), e230173. https://doi.org/10.1148/radiol.230173
• Loftus, J.R., Puri, S. & Meyers, S.P. (2023). Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging. Insights into Imaging, 14(8). https://doi.org/10.1186/s13244-022-01358-6

 

 

 

 

 

 

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