Exploring Angiogenesis and Artificial Intelligence in Alzheimer’s Disease: Implications for Early Detection and Therapeutic Strategies

S. Alagumuthukrishnan ¹* , Ganga Sanuvala ¹, Bibiana Jenifer J ², M.J.D Ebinezer ³, B Veda Vidhya ⁴, Srithar S ⁵

This review discusses the understanding the interplay of angiogenesis and Aβ in Alzheimer’s could lead to innovative AI-driven diagnostics, enhancing early intervention strategies.

Abstract

Background: Alzheimer’s disease (AD) presents a significant global health challenge, affecting millions and imposing substantial socioeconomic burdens, with healthcare costs exceeding US$100 billion annually. The disease's complexity is underscored by its slow progression and the pivotal role of amyloid plaques in its pathology. Despite advancements in understanding AD, critical questions regarding the mechanisms of amyloid plaque development and their relationship with neuroinflammation and angiogenesis remain. Methods: This study employed advanced imaging techniques and artificial intelligence (AI) to investigate the interplay between amyloid beta (Aβ) accumulation, neuroinflammation, and angiogenesis in AD. Magnetic resonance imaging (MRI) facilitated detailed assessments of brain structure alterations, while machine learning models enhanced diagnostic accuracy by analyzing imaging data and identifying patterns linked to disease progression. Results: The findings revealed a significant association between Aβ deposition and increased angiogenesis, contributing to neurovascular dysfunction and exacerbating neuroinflammation. AI-driven analyses demonstrated improved diagnostic capabilities, detecting early changes in brain structure associated with mild cognitive impairment (MCI) and AD. Specifically, convolutional neural networks (CNNs) such as AlzheimerNet achieved remarkable accuracy in distinguishing AD from other neurodegenerative conditions. Conclusion: This research underscores the multifaceted nature of AD, highlighting the critical roles of amyloid plaques, neuroinflammation, and angiogenesis. The integration of AI and advanced imaging modalities offers promising avenues for early diagnosis and intervention, potentially transforming patient management strategies. Continued exploration of these pathways may yield effective therapeutic targets to mitigate the progression of AD and enhance patient outcomes.

Keywords: Alzheimer’s Disease, Angiogenesis, Artificial Intelligence, Early Detection, Neuroinflammation

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