Handbook of Imaging in Multiple Sclerosis

Auteur
Dejan Jakimovski, MD, Ph.D., is a Research Assistant Professor at the Department of Neurology, University at Buffalo, the State University of New York and Clinical Research Unit Director at Buffalo Neuroimaging Analysis Center. In 2015, Dr. Jakimovski received his medical degree at Ss. Cyril and Methodius University, Skopje, Macedonia and in 2020 he also received Neuroscience Ph.D. degree at University at Buffalo. He performed research spanning from cardiovascular, environmental and genetic risk factors in multiple sclerosis (MS) and use of quantitative multimodal imaging techniques in predicting disease outcomes in MS and other neurodegenerative diseases. Furthermore, his focus included clinical, neuropsychological and optical coherence tomography (OCT) characterization of both adult and aging MS populations. Robert Zivadinov, MD, Ph.D., has served as Director of the Buffalo Neuroimaging Analysis Center (BNAC) since 2003. The Center is part of the Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, State University of New York, where he is Professor of Neurology. He also is Director of the University's Center for Biomedical Imaging at the Clinical Translational Science Institute.Having published more than 450 articles and 750 abstracts in leading peer-reviewed journals, Dr. Zivadinov's work is widely cited with H-index of 80.He is Honorary Professor of Neurology at the University of Sidney, Australia. Dr. Zivadinov was a founding member of the International Society for Neurovascular Disease and currently serves on its Executive Committee.

Texte du rabat
There is an increasing need for an imaging-specific handbook in the field of multiple sclerosis that provides the latest and most pertinent information to clinicians, radiologists, and researchers. Handbook of Imaging in Multiple Sclerosis provides an up-to-date introduction into multiple sclerosis disease, including new findings on the pathophysiological processes, the clinical presentation, diagnosis, and treatment of the disease. This book includes in-depth chapters exploring the use of conventional and non-conventional imaging methods. These chapters cover magnetic resonance imaging (MRI)-specific topics such as measurement of brain atrophy and susceptibility-weighted imaging. Additional chapters explore the use of additional imaging methods such as positron emission tomography (PET), optical coherence tomography (OCT) and high field MRI (use of >7T MRI scanners).

Contenu

Section 1: Introduction

1. Immunology and Pathophysiology of Multiple Sclerosis
2. Diagnosis and Clinical Features of Multiple Sclerosis
3. Cognition in Multiple Sclerosis
4. Multiple Sclerosis Treatment
5. Use of MRI and Quantitative MRI Reports in Clinical Care of Multiple Sclerosis
6. MRI Outcomes in MS Clinical Trials

Section 2: Imaging of Multiple Sclerosis

7. Conventional MRI use in Multiple Sclerosis
8. MRI Physics and Image Acquisition
9. Basics of Neuroimaging Analysis
10. Lesions Imaging in Multiple Sclerosis
11. Volumetry and Atrophy in Multiple Sclerosis
12. Spinal Cord Imaging in Multiple Sclerosis

Section 3: Non-conventional MRI use in Multiple Sclerosis

13. Diffusion Tensor Imaging in Multiple Sclerosis
14. Magnetization Transfer Imaging in Multiple Sclerosis
15. Susceptibility-Weighted Imaging in Multiple Sclerosis
16. Quantitative Susceptibility Mapping in Multiple Sclerosis
17. Functional MRI imaging in Multiple Sclerosis
18. Perfusion-Weighted Imaging in Multiple Sclerosis
19. Magnetic Resonance Spectroscopy in Multiple Sclerosis
20. High-Field Imaging in Multiple Sclerosis
21. Emerging MRI Biomarkers

Section 4: Use of Other Imaging Acquisition and Analysis Modalities in Multiple Sclerosis

22. Positron Emission Tomography in Multiple Sclerosis
23. Optical Coherence Tomography in Multiple Sclerosis - Elliot M Frohman
24. Imaging of Multiple Sclerosis in Resource-Poor Settings
25. Use of Artificial Intelligence in Multiple Sclerosis Imaging
26. Imaging of Experimental Models of Multiple Sclerosis