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Last Updated: July 03, 2026
Authors: Felix Carbonell, Ph.D., Jean-Philippe Coutu, Ph.D., Simone P. Zehntner, Ph.D., Cecile Monpays, M.Sc., Alex P. Zijdenbos, Ph.D., Barry J. Bedell, M.D., Ph.D., and for the Alzheimer’s Disease National Initiative (ADNI).
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Section 1

Key Takeaways

  • The shape of subcortical structures provides an accurate quantification of brain atrophy in Mild Cognitive Impairment (MCI).

  • The shape of the hippocampus is a sensitive biomarker for tracking the longitudinal progression of atrophy in MCI.

  • Morphological changes in the hippocampus can serve an effective biomarker that accurately reflect strong associations with Tau PET SUVR.

  • Hippocampal shape is a sensitive biomarker able to predict increase in Tau PET SUVR in the hippocampus itself and in the entorhinal cortex.

  • The hippocampus and amygdala shape reflect strong associations with CSF and plasma biomarkers of AD pathology and neurodegeneration.

Subcortical brain regions, such as the hippocampus and amygdala, are critical for various cognitive, emotional, and motor functions. Atrophy in Alzheimer’s disease (AD) and other neurodegenerative diseases are typically assessed through volumetric measurements of these subcortical structures. Since atrophy is usually detected at later stages of AD progression, subtle disease-related changes in the shape, cortical folding, or surface deformation of subcortical structures are better detected by applying morphological shape analysis techniques.

In the current study, we applied a morphological surface shape analysis for characterizing the longitudinal patterns of subcortical structures in Alzheimer’s disease. For that purpose, we used a local shape metric that is estimated from the nonlinear deformations that measure the spatial displacement of individual outer surfaces of subcortical regions with respect to a reference anatomical model. We also used this surface-based metric to perform associations and actual out-of-the-sample predictions of other imaging and non-imaging AD biomarkers, such as tau accumulation as measured by PET imaging, as well as CSF and plasma biomarkers. 

Our findings revealed that local deformations in the shape of subcortical structures, like the hippocampus, is a sensitive biomarker for tracking the longitudinal progression of anatomical morphological changes in MCI. We also showed that the hippocampus and amygdala surface deformations are highly correlated with other hallmarks of AD, including early tau accumulation within the entorhinal cortex and abnormal fluid biomarkers of Aβ pathology and neurodegeneration. Finally, we also derived predictive models that accurately recovered observed Tau PET SUVR measurements, suggesting the possibility to use anatomical T1-weighted MRI data as a surrogate of Tau PET for eligibility screening in clinical trials of disease-modifying therapeutics.

Slide Presentation

Background

Background

Morphological biomarkers of the brain, particularly in subcortical structures, refer to measurable changes in brain anatomy that can indicate disease processes or alterations in cognitive and motor functions. Structural changes in these regions, particularly in hippocampus and amygdala, have been implicated in Alzheimer’s disease (AD) and other age-related and neurodegenerative diseases.

The volumetric quantification of subcortical structures has been the conventional and widely accepted technique for tracking anatomical changes. Complementarily, surface-based biomarkers of subcortical areas focus on their outer surface morphology of and are particularly useful in detecting local atrophy, cortical folding, or surface deformation along spatial directions. Indeed, it has been consistently reported that subcortical structures may undergo subtle, but significant, morphological changes in several diseases that might not be apparent through volumetric measures alone. 

Subcortical structures, such as the hippocampus, are core elements in Alzheimer’s disease. Indeed, the hippocampus is typically associated with AD-characteristic episodic memory syndrome and downstream neurodegeneration, and hippocampal atrophy is closely linked to tau-related medial temporal pathology. Apart from the hippocampus, there has been a recent interest in studying the role of other subcortical structures in the progression of AD pathology and cognitive decline. For instance, several studies have recently identified the amygdala as a region showing early neurofibrillary tau pathology and describe the thalamus as a key region in dementia due to thalamic pathology that may contribute to cognitive decline and behavioral symptoms. However, very little is known about the ability of using morphological shape analysis of these structures to track the disease progression and detect significant changes in longitudinal settings. 

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Data Sources

Data used in the preparation of this article were obtained from the ADNI database (http://adni.loni.usc.edu). The ADNI was launched in 2003 by the National Institute on Aging (NIA), the National Institute of Biomedical Imaging and Bioengineering (NIBIB), the Food and Drug Administration (FDA), private pharmaceutical companies, and non-profit organizations, as a $60 million, 5-year public-private partnership, which has since been extended. ADNI is the result of the efforts of many co-investigators from a broad range of academic institutions and private corporations, and subjects have been recruited from over 55 sites across the U.S. and Canada. To date, the ADNI, AND-GO, ADNI-2, ADNI-3 and ADNI-4 protocols have recruited over 2,500 adults, ages 55 to 90, to participate in the research, consisting of cognitively normal (CN) older individuals, people with early or late Mild Cognitive Impairment (MCI), and people with dementia due to AD. For up-to-date information, see www.adni-info.org.

Keywords

Aβ42/Aβ40 Ratio: a biomarker ratio used to assess amyloid pathology and Alzheimer’s disease risk. 

Alzheimer’s Disease (AD): a neurodegenerative disorder marked by cognitive decline, hippocampal atrophy, and amyloid‑β and tau pathology.

Alzheimer’s Disease Biomarkers: measurable biological or imaging indicators that help detect, track, or predict Alzheimer’s disease and its progression. 

Atrophy: a reduction in tissue size or volume, often caused by cell loss or degeneration. 

Biomarker: a measurable indicator of a biological state or condition. Biomarkers are often used in medicine and research to detect or monitor the presence, progress, or severity of a disease, as well as to assess the effectiveness of a treatment. 

FDG: a PET imaging marker of glucose metabolism in the brain, often used as an indicator of neuronal activity or hypometabolism. 

GFAP: Glial Fibrillary Acidic Protein, a biomarker associated with astrocyte activation and neuroinflammation. 

Mild Cognitive Impairment (MCI): an early cognitive decline state that may precede Alzheimer’s disease while daily function remains intact.

MRI-based Biomarkers: quantitative indicators derived from MRI scans that provide evidence of structural brain change linked to disease. 

NfL: Neurofilament Light Chain, a biomarker of axonal injury and neurodegeneration. 

pTau181: a phosphorylated tau biomarker associated with Alzheimer’s disease pathology, measurable in CSF or plasma. 

Surface-Based Morphology: markers derived from the shape and local surface structure of brain regions, used to detect subtle anatomical changes that may not appear in standard volume measures. 

Subcortical Surface Deformation: a shape analysis method that quantifies local inward or outward changes on the surfaces of subcortical brain structures, such as the hippocampus, amygdala, thalamus, caudate, and putamen. 

Tau PET SUVR: a quantitative PET imaging measure used to estimate tau protein accumulation in specific brain regions, measured using Standardized Uptake Value Ratio (SUVR) . 

Tau PET Prediction: the estimation of tau accumulation patterns using computational models based on MRI or other biomarkers.

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