Alzheimer's disease (AD), a leading cause of dementia, exhibits notable heterogeneity in its pathology and clinical expression, suggesting the existence of distinct subtypes. This Research Topic aims to advance our understanding of these subtypes through the critical lens of neuroimaging. Recent advancements in neuroimaging techniques have allowed for detailed insights into the brain's structural and functional changes associated with different AD subtypes. Yet, significant disparities in neuroimaging outputs due to varied methodological approaches across studies present a challenge to forming a cohesive understanding of the disease.

This Research Topic aims to pave the way for a nuanced understanding of Alzheimer’s disease by consolidating global expertise on the variability in neuroimaging studies and fostering an interdisciplinary approach to resolve these issues. By providing a platform for the latest research and discussion, this topic seeks to refine diagnostic criteria and enhance therapeutic strategies for Alzheimer’s disease, ultimately leading to personalized and subtype-specific healthcare approaches.

We encourage researchers to submit original research papers, reviews, and method articles focusing on the neuroimaging of Alzheimer’s subtypes, the disparities in findings across different studies, and strategies for data harmonization. Encompassing rigorous multi-disciplinary approaches can lead to more standardized data interpretations and ultimately, more effective clinical interventions.

**Topics of interest include but are not limited to:**

1. **Identification and Validation of AD Subtypes:**
- Classify and delineate different subtypes based on structural, functional, and molecular imaging, as well as pathology related biomarkers.

2. **Disparities in Neuroimaging Practices:**
- Addressing the variability in neuroimaging techniques and results across different cohorts, geographic locations, and technological platforms.

3. **Harmonization and Standardization:**
- Developing methodologies to standardize subtype identification protocols and data analysis techniques to ensure consistent and comparable results.
- Promoting large-scale, multi-center studies to enhance the robustness of neuroimaging data.

4. **Advanced Analytical Techniques:**
- Leveraging machine learning and artificial intelligence for the analysis of complex biomarker data to enhance the accuracy and precision of Alzheimer's subtype diagnoses.

5. **Clinical and Translational Implications:**
- Translating subtyping findings into clinical practice to tailor therapeutic strategies based on subtype-specific pathophysiology/neuropathology.
- Exploring how a better understanding of AD subtypes and their coexistence with other neurodegenerative diseases, can inform prognostic outcomes and patient management strategies.

Are you interested in contributing a manuscript to this Research Topic?

Decoding Alzheimer’s Subtypes: Neuroimaging Disparities and Harmonization Strategies