Intro
Foreword
Preface
Contents
Part I: Basics
1: Nuclear Medicine Imaging Tracers for Neurology
1.1 Introduction
1.2 Glucose Consumption
1.3 Translocator Protein TSPO
1.4 GABA Receptor
1.5 Dopaminergic System
1.5.1 Dopamine Transporter (DAT)
1.5.2 D1 Receptor
1.5.3 D2 Receptor
1.5.4 D2/D3 Agonists
1.6 Beta-Amyloid Deposition
1.7 NMDA Receptor, Glycine Transport
1.8 P-Glycoprotein
1.9 Cholinergic System
1.10 Metabotropic Glutamate-5 Receptor
1.11 Vesicular Monoamine Transporter
1.12 Adenosine Receptors

1.13 Serotonergic System
1.13.1 Serotonin Transporter
1.13.2 5-HT Receptor Ligands
1.14 Nonadrenergic System
1.15 Opioid Receptors
1.16 Monoamine Oxidase
1.17 SV2A Receptors
1.18 Sigma Receptors
1.19 Tau Protein Deposition
1.20 Phosphodiesterase
1.21 P2X7 Receptor
1.22 (Re)Myelination
1.23 Cannabinoid Receptors
1.24 Conclusions
References
2: Tracer Kinetic Modelling
2.1 Introduction
2.2 Principles of Modelling
2.3 Single-Tissue Compartment Model
2.4 Principles and Practice of Quantification

2.5 An Example: Measurement of CBF Using [15O]H2O
2.6 Two-Tissue Compartment Model
2.7 Reference Tissue Models
2.8 Parametric Methods
2.9 Conclusions
References
3: Quantification in Brain SPECT: Noninvasive Cerebral Blood Flow Measurements Using 99mTc-Labeled Tracers
3.1 Introduction
3.2 Method
3.2.1 Theory of Graphical Analysis
3.2.2 Brain Perfusion Index (BPI)
3.2.3 Comparison of BPI and CBF Values Measured by Other Invasive Methods
3.2.4 Alternative Approach to Estimation of BPI
3.2.5 Calculation of Regional CBF from BPI

3.2.6 Consecutive rCBF Measurements at Baseline and Acetazolamide Challenge
3.3 Clinical Application
3.3.1 Cerebrovascular Diseases
3.3.2 Heart Failure
3.3.3 Idiopathic Normal Pressure Hydrocephalus
3.3.4 Neurodegenerative Disorders
3.3.5 Mood Disorders
3.3.6 Other Neuropsychiatric Diseases
3.4 Conclusion
References
4: From Positron to Pattern: A Conceptual and Practical Overview of 18F-FDG PET Imaging and Spatial Covariance Analysis
4.1 18F-FDG PET Imaging
4.1.1 Basic Concepts in PET
4.1.2 18F-FDG PET Imaging

4.1.3 Studying Brain Function with 18F-FDG PET
4.2 Analysis of Resting-State 18F-FDG PET Images
4.2.1 Image Registration
4.2.2 Normalization
4.2.3 Analysis of Variance and Covariance
4.2.4 Principal Component Analysis
4.3 SSM PCA
4.3.1 Defining the Data
4.3.2 Normalization with the Scaled Subprofile Model (SSM)
4.3.3 Calculating Eigenvectors from a Covariance Matrix
4.3.4 Calculating Subject Scores and Selecting Disease-Related Components
4.3.5 Prospective Application of the Pattern
4.3.6 Validation