Imaging biomarkers in neurodegeneration: current and future practices

Area of Science:

• Neuroscience
• Medical Imaging
• Biomarkers

Background:

• Biomarkers are increasingly vital for diagnosing neurodegenerative disorders.
• In vivo imaging biomarkers have significantly advanced the study of these conditions.
• This review is part of a series from a University College London/University of Gothenburg course.

Purpose of the Study:

• To review the role of neuroimaging biomarkers in neurodegenerative diseases.
• To cover established and emerging techniques in PET and MRI.
• To discuss the integration of machine learning in neuroimaging analysis.

Main Methods:

• Focus on positron emission tomography (PET) and magnetic resonance imaging (MRI).
• Overview of current clinical and research practices.
• Exploration of new and developing neuroimaging techniques.
• Discussion of machine learning applications in neuroimaging.

Main Results:

• Neuroimaging provides substantial benefits for diagnosis and understanding.
• Established PET and MRI practices are key clinical and research tools.
• Emerging techniques and machine learning offer new diagnostic insights.
• Multimodal analysis using ML can improve diagnostic accuracy.

Conclusions:

• Neuroimaging biomarkers, particularly PET and MRI, are essential for neurodegenerative disease research and clinical practice.
• The integration of machine learning with neuroimaging data promises enhanced early diagnosis and comprehensive patient analysis.
• Continued development in these areas will further improve patient outcomes and disease comprehension.