Gemma Salvadó, PhD, is currently a post-doctoral researcher at Lund University (Sweden). She was awarded the prestigious Marie Skłodowska-Curie post-doctoral fellowship for her outstanding research. Gemma completed her PhD at the Barcelonaβeta Brain Research Center (Spain), where she focused on understanding the preclinical stages of Alzheimer’s disease through the use of neuroimaging and fluid biomarkers. During her training she also spent some months at the Vrije Universiteit Amsterdam (Netherlands) thanks to a competitive personal fellowship from Alzheimer Nederland (Dutch Alzheimer’s Association). Her current work involves studying plasma and cerebrospinal fluid biomarkers to gain insights into the disease progression. Throughout her career, she has received several fellowships, with two particularly notable ones: the Alzheimer’s Association Research Fellowship and the Alzheimerfonden (Swedish Alzheimer’s Association) Fellowship. She has presented her research at esteemed conferences in the field, including the Alzheimer’s Association International Conference (AAIC), the Human Amyloid Imaging conference (HAI) and the International Conference on Alzheimer’s and Parkinson’s Disease (AD/PD), for which she received the Junior Faculty Award.  She has actively contributed to two large European-funded (IMI) projects, namely EPAD and AMYPAD. Finally, Gemma has been engaged in teaching activities for the Human Biology bachelor’s program at Pompeu Fabra University (Spain).

Abstract

Background: Neuroimaging has become a pivotal tool in the diagnosis and research of neurodegenerative diseases, particularly Alzheimer’s disease (AD). In Europe, concerted efforts through collaborative networks and large-scale initiatives have propelled advancements in this field, providing deeper insights into disease mechanisms and potential therapeutic targets. This review aims to synthesize recent developments in neuroimaging technologies and methodologies used in Europe for studying Alzheimer’s disease and other neurodegenerative conditions.

Methods: A comprehensive literature search was conducted, covering peer-reviewed articles, clinical trials, and reports from major European neuroimaging consortia published over the last years. Key areas of progress, including innovations in imaging modalities, the integration of multimodal data, and the application of advanced analytical techniques were reviewed.

Results: PET imaging, particularly with novel tracers for amyloid and tau proteins, has enhanced the understanding of pathological progression in vivo. The integration of multimodal imaging data with genetic and biofluid markers has improved diagnostic accuracy and disease prediction. Additionally, the application of machine learning algorithms to neuroimaging data has facilitated the identification of subtle disease signatures and the development of individualized predictive models.

Conclusions: Europe’s contributions to neuroimaging in neurodegenerative diseases have been substantial, driven by collaborative research and technological innovation. These advancements are crucial for early diagnosis, monitoring disease progression, and evaluating therapeutic efficacy. Ongoing efforts to harmonize imaging protocols and share data across borders are expected to further accelerate progress in this field.

Keywords: Review, Imaging, Neurodegenerative diseases, Machine learning.