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).
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
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