Medical imaging grows to be a broad and modern scientific field. Imaging principles, methods and applications are important topics in this field. While applications and the generalization of techniques start with and rely on theoretical development and novel methodology, introduction and instructions of relatively new ideas, concepts and methods are of pivotal importance to students, beginners and general clinical practitioners in this field. Functional MRI (fMRI) has been widely used for the past 30 years to investigate brain functional changes under physiologic challenges or disease conditions in contrast to a resting state. The physiological contributors to the fMRI signal changes include the blood-oxygenation-dependent level (BOLD) effect and in-flow effect such as the increment in local CBF and arterial oxygenation. Improvement of spatiotemporal resolution of fMRI to enhance neuronal activity specificity and pinpoint the microvasculature activation is the ultimate goal. fMRI functional activity/connectivity and graph theory-based connectome analyses with a multiplex fast imaging technique are recently developed new techniques to provide both a whole-picture and regional specialization of brain resource utilization in a systematic way. The integration of neuroscience and mathematical as well as physical and physiological metrics also promote the innovation and applications of multi-modal imaging equipment development and multi-parametric utilizations in clinical environments, including disease diagnosis and treatment.The aim of this book is intended to provide a whole picture of new fMRI imaging methodological developments from principles to applications, to both beginners and experts in biomedical imaging and healthcare. Several fundamental principles and metrics including BOLD, microvasculature detection and fMRI/EEG coupling will be presented together with some new and up-to-date analytical methods. The conventional statistical methods and relatively new methods of wavelets, dynamic linear correlation coefficients, independent component analysis, EEG source imaging and multi-modal integration will be covered. The authors hope that this book will capture the interests of colleagues in the medical imaging field and could help convey the methodological, technical and developmental resources of neuroimaging applications. This book will provide the current state-of-the-art and frontiers of neuroimaging techniques in basic science and clinical neuroscience research. The authors will present some forefront and interesting multi-dimensional imaging techniques to serve as a textbook and reference manual in fMRI methodological training as well as in the research field. Several distinct imaging perspectives, including cutting-edge imaging methods from acquisition to data analysis as well as multi-modal and multi-parametric quantifications will be described. The relatively new and advanced principles and methods together with interesting examples and application demonstrations would hopefully contribute to the medical imaging teaching and research field and could help facilitate the generalization, interpretation and applications of the proposed neuroimaging methods.

Maintaining good metabolic profile plays a significant role in improving the quality of life at aging. Widely recommended physical and psychological strategies include exercise, calorie restriction (such as healthy diet), anti-aging neuroprotective and anti-inflammation therapy. Most occurring risks at middle age range (45-65 years old) are obesity, insulin resistance, inflammation, alteration in the hypothalamus-hypophysis suprarenal axis activity, stress and hypertension that could increase the prevalence of metabolic syndrome. Metabolic syndrome increases with age, particularly for women. Significant associations were seen between imaging measures and cardiovascular risk factors at both baseline and 18-month follow-ups. Both baseline and longitudinal imaging analysis and correlations with neurocogntive tests as well as cardiovascular risk factors could provide distinct and confirmative perspectives relating to the pathophysiology of aging-related diseases such as dementia and diabetes. Significant baseline and longitudinal effects of age, smoking and neuropathological burdens such as amyloid, tau and glucose metabolism provide a complete imaging, neurocognitive and cardiovascular profile for better staging and differentiating different diseases. Together with accurate imaging guidance, early detection and treatment could be achieved with the ultimate goal of improving quality of life at middle age and extending longevity. The aim of this book is intended to provide both beginners and experts in biomedical imaging and health care a broad picture as well as new development in brain function and metabolism of aging using innovative neuroimaging techniques and advanced longitudinal /correlational analyses. Methods and data presented in this book with novel experimental designs and protocols, especially longitudinal investigation of multiple imaging metrics from microvascular, micro-structural to systematic functional, metabolic and neuropathological perspectives will help improving diagnosis and early prevention of common diseases at middle age such as metabolic syndrome and early dementia. Some promising prevention strategies such as arts therapy, aerobic exercise and calorie restriction will be introduced additionally with imaging evidence. Results presented will help improving diagnosis accuracy, staging, and determining phases and trajectories of disease progression with age, endothelial dysfunction and deficits in metabolic syndrome. This book will provide the current state-of-the-art and new frontiers of brain function and metabolic changes at age using multi-parametric functional, structural and molecular imaging techniques in detection, diagnosis and treatment. We will present some forefront and interesting multi-dimensional baseline and longitudinal imaging techniques to serve as a reference and resource book in neuroimaging application and research field. Several distinct detection and application perspectives, including cutting-edge imaging methods from baseline evaluations to longitudinal applications as well as multi-modal and multi-parametric quantifications will be described. The relatively new and advanced data and results together with interesting examples and application demonstrations could help facilitate the generalization, interpretation and applications of these techniques to improve disease diagnosis, quality of life and treatment for metabolic syndrome and brain dysfunction.

Neuroimaging techniques that can help elucidate and characterize the nature and mechanism of tissue injury and disease progression in neurodegenerative disease are of particular importance given its their roles in seeking successful preventive and therapeutic treatments. Studying large-scale samples with various disease mechanisms using multi-parametric imaging, as well as revealing the correlations between the neuroimaging metrics and clinical data including neurocognitive function and neuropsychological inventories to elucidate multiple factors affecting the neurodegeneration processes in brain are the main topics of this book. In addition, the neural underpins of cognitive and psychological functions with advanced functional imaging techniques can provide better cross-validation and clinical symptom relevance of multi-parametric data. Expanding the current findings with higher diagnosis accuracy and detection specificity in multiple neurodegenerative diseases as well as better differentiation of each type are the ultimate goal. The results in this book will extend the current notion of diagnosis value of various relatively new imaging techniques in multiple neurodegenerative diseases including traumatic brain injury, post-traumatic stress disorder, multiple sclerosis and early stage of Alzheimer’s disease such as mild cognitive impairment. Specifically, the neurobiology and related imaging findings of the four representative neurodegenerative diseases will be introduced and reviewed, including brain region-specific and disease-related alterations, unique clinical symptom of each disease, as well as previous findings and challenges. There is an increasing body of literature suggesting that damage to the default mode network, hypothalamus, thalamus and hippocampus neuronal networks and local injuries might be under-diagnosed and may account for some of the sequelae following the neurodegenerative injuries including trauma and dementia. The relatively novel imaging results to differentiate each disease using advanced functional connectivity, neuronal activity, microstructure integrity analysis based on structural connectivity, multi-dimensional morphometry and molecular imaging tracers including amyloid and tau for neuropathological burden quantification were presented to differentiate each type of disease. We then briefly reviewed some of the therapeutic effects of traditional Chinese medicine with neuroimaging quantifications to help treating neurodegenerative diseases. Finally, our work proves that the multi-parametric neuroimaging methods with more than twelve metrics and numerous tight clinical association data presented in this book are the most forefront and up-to-date with enough sensitivity, precision and resolution. Taken together, multiple neuroimaging metrics haved been demonstrated in this book to identify and quantify significant and distinct brain alterations at function, microstructure, morphology and molecular scales in different types of neurodegenerative diseases with high sensitivity and specificity. These comprehensive imaging features could be combined to improve disease diagnosis accuracy. The aim of this book is thus intended to provide both beginners and experts in biomedical imaging and health care a broad and complete picture as well as the new developments of using multiple metrics in improving disease identification and diagnosis accuracy. This book would hopefully capture the interests of colleagues interested in neurodegenerative disease diagnosis and treatment, and could help convey the methodological and integrative perspectives of multi-parametric neuroimaging applications.

The well-known Alzheimer’s Disease Neuroimaging Initiative (ADNI) Center provides the most advanced, comprehensive, multiparametric and up-to-date biomarkers for mild cognitive impairment (MCI) and early Alzheimer’s disease (AD) projects, including neuroimaging, clinical assessments, biospecimens and genetic data. Recent developments in imaging techniques, including new molecular tracers for imaging disease burden and systematic multi-modal integration, have emerged to overcome the limitations of each single modality and individual-dependent variability. The MRI-based high-resolution structural and morphological changes in the brain, such as atrophy, and the abnormal activity/connectivity patterns of the hippocampus subfields and default mode network (DMN) modulation, together with the amyloid and tau neuropathological quantification using PET molecular tracers, could be used to predict brain changes and cognitive performance declines in early AD, including transitional MCI. Finally, a generalized and integrative model with multiple biomarkers could be built to target disease progression and symptom prediction as well as to optimize patient management. Multiomics investigates metabolomic, lipidomic, genomic, transcriptomic and proteomic perspectives by presenting an accurate biochemical profile of the organism in health and disease. The Alzheimer''s Disease Metabolomics Consortium (ADMC) in partnership with ADNI is creating a comprehensive biochemical database for patients in the ADNI1 cohort, consisting of eight metabolomics datasets. The vast majorities of biospecimen data provide rich biological information to the human brain at normal and dementia status. One of the purposes is to reveal the connections between disease and multiomics such as obesity, hypertension, cholesterol imbalance and inflammation risks that might lead to neurodegenerative disease. Multiomic biomarker developments in the dementia field have provided earlier clues to novel treatments that help correct metabolic dysfunction and delay disease progression. Furthermore, the assembling of multiomics-based biomarkers including metabolites and lipids, cholesterol biosynthesis, purine metabolism, lipoprotein, bile acids, and genetics as well as their relation to the pathological amyloid and tau network could improve disease diagnosis sensitivity and reveal more diverse and complementary molecular pathways to allow for the advancement of early AD diagnosis and therapeutic prevention. In this book, we report on the significant differences of multiple biomarkers from the ADNI database including neuroimaging, clinical assessments and multiomic biospecimen/genetic data in MCI and early probable AD (pAD), and elucidate the interconnections among different metrics at various domains. Classification results with high accuracies (0.95-1) for each early dementia subtype including early MCI (EMCI), late MCI (LMCI) and pAD, and better prediction of clinical symptoms is achieved with these comprehensive biomarkers. Further longitudinal changes of imaging and neuropsychological biomarkers, and inter-correlations with baseline parameters are examined for a better illustration of disease progression association. Additionally, an analysis of the post-traumatic stress disorder biomarkers is performed with high classification accuracy. With illustrative and rigorous data analyses and confirmative results, this book provides readers with a full spectrum of biomarker research for early dementia diagnosis and treatment, and helps convey the technical development and data evaluation perspectives in advanced medical imaging and various disease application fields.

Multiple advanced neuroimaging applications in various neurodegenerative diseases including Parkinson’s disease (PD), frontotemporal dementia (FTD), vascular dementia (VaD) and autism spectrum disorder (ASD) are covered in this book. Relatively novel techniques such as integrated PET/MRI and independent component analysis (ICA)-based dual regression (DR) methods were developed to capture multi-level molecular/functional and structural/microstructural as well as high-order inter-network coordination abnormalities. For instance, both PET dopamine transporter and striatal binding ratio reductions in the caudate and putamen were found in PD, consistent with the diffusion tensor imaging (DTI) fractional anisotropy (FA) reduction and fMRI voxel-mirrored homotopic correlation (VMHC) in the substantia nigra (swallow tail sign signature of PD). Furthermore, dopamine storage and pathway labeled with the vesicular monoamine transporter tracer identified decreased densities in the bilateral mesial temporal cortex, caudate, orbitofrontal cortex, left frontal and occipital cortices, consistent with the morphological atrophy, functional connectivity and conductivity deficits in PD. Similarly in FTD patients, the advanced MRI methods such as ICA-DR, VMHC, voxel-based morphometry (VBM) as well as PET tracer for amyloid accumulation and FDG glucose uptake identified typical brain atrophy, structural dis-connectivity, glucose hypometabolism, higher neuropathological burden, lower interhemispheric correlation as well as disrupted intra- and inter-network modulation in the orbitofrontal and anterior temporal cortices together with insular and frontoparietal networks, with the cerebellum and dorsolateral attentional network as typical compensations. Functional and structural abnormalities had further been elucidated in the VaD dependent participants and autistic children. For instance, both lower FA and VMHC, brain atrophy and functional connectivity deficits, demyelination, axonal degeneration and white matter integrity damage in several white matter tracts were present in the dependent compared to independent participants in VaD data cohort. Increased neuronal activity with higher global fractional amplitude of low frequency fluctuation (fALFF) in the conventional and slow-wave sub-band was confirmed with less efficiency of systematic integration in VaD dependent group. Moreover, in ASD compared to controls, regional gray matter volume and cortical thickness in all four brain lobes increased, whereas white matter volume were decreased in addition to the lower temporal, visual and superior frontal but higher inferior and dorsolateral prefrontal cortical functional connectivities exhibited in ASD. The differences in each type of disease could also be revealed with the same imaging method based on either unique region or distinct brain circuit inter-connection, using VMHC, ICA-DR, DTI, VBM, fALFF and graph-theory based small-worldness analysis. In this book, we have developed and generalized conventional and advanced imaging methodologies to several common neurodegenerative diseases. For instance, we have identified the unique imaging signature for each disease type and the underlying neuropathological mechanism connections with conductivity, structural and microstructural connectivity, intra- and inter-network correlation, systematic integration and efficiency analyses. Our objective, comprehensive and confirmative results indicated great potential in utilizing these quantifications for accurate disease classification and staging. With solid imaging evidence, thorough analysis and generalized applications, this book should capture the interests of readers in the broad fields of brain science, disease diagnosis and effective treatment.

The aim of this new book is to provide readers some new insights into applying various imaging techniques to diagnose and distinguish subtypes and rare/comorbid cases of several brain disorders more accurately. Specific and comprehensive imaging features utilized that could pinpoint the exact abnormalities of these atypical and/or rare diseases are the highlights of this book, which will provide guidance for better disease mechanism interpretation.

Medical imaging grows to be a broad and modern scientific field. Imaging principles, methods and applications are important topics in this field. While applications and the generalization of techniques start with and rely on theoretical development and novel methodology, introduction and instructions of relatively new ideas, concepts and methods are of pivotal importance to students, beginners and general clinical practitioners in this field. Functional MRI (fMRI) has been widely used for the past 30 years to investigate brain functional changes under physiologic challenges or disease conditions in contrast to a resting state. The physiological contributors to the fMRI signal changes include the blood-oxygenation-dependent level (BOLD) effect and in-flow effect such as the increment in local CBF and arterial oxygenation. Improvement of spatiotemporal resolution of fMRI to enhance neuronal activity specificity and pinpoint the microvasculature activation is the ultimate goal. fMRI functional activity/connectivity and graph theory-based connectome analyses with a multiplex fast imaging technique are recently developed new techniques to provide both a whole-picture and regional specialization of brain resource utilization in a systematic way. The integration of neuroscience and mathematical as well as physical and physiological metrics also promote the innovation and applications of multi-modal imaging equipment development and multi-parametric utilizations in clinical environments, including disease diagnosis and treatment.The aim of this book is intended to provide a whole picture of new fMRI imaging methodological developments from principles to applications, to both beginners and experts in biomedical imaging and healthcare. Several fundamental principles and metrics including BOLD, microvasculature detection and fMRI/EEG coupling will be presented together with some new and up-to-date analytical methods. The conventional statistical methods and relatively new methods of wavelets, dynamic linear correlation coefficients, independent component analysis, EEG source imaging and multi-modal integration will be covered. The authors hope that this book will capture the interests of colleagues in the medical imaging field and could help convey the methodological, technical and developmental resources of neuroimaging applications. This book will provide the current state-of-the-art and frontiers of neuroimaging techniques in basic science and clinical neuroscience research. The authors will present some forefront and interesting multi-dimensional imaging techniques to serve as a textbook and reference manual in fMRI methodological training as well as in the research field. Several distinct imaging perspectives, including cutting-edge imaging methods from acquisition to data analysis as well as multi-modal and multi-parametric quantifications will be described. The relatively new and advanced principles and methods together with interesting examples and application demonstrations would hopefully contribute to the medical imaging teaching and research field and could help facilitate the generalization, interpretation and applications of the proposed neuroimaging methods.

Maintaining good metabolic profile plays a significant role in improving the quality of life at aging. Widely recommended physical and psychological strategies include exercise, calorie restriction (such as healthy diet), anti-aging neuroprotective and anti-inflammation therapy. Most occurring risks at middle age range (45-65 years old) are obesity, insulin resistance, inflammation, alteration in the hypothalamus-hypophysis suprarenal axis activity, stress and hypertension that could increase the prevalence of metabolic syndrome. Metabolic syndrome increases with age, particularly for women. Significant associations were seen between imaging measures and cardiovascular risk factors at both baseline and 18-month follow-ups. Both baseline and longitudinal imaging analysis and correlations with neurocogntive tests as well as cardiovascular risk factors could provide distinct and confirmative perspectives relating to the pathophysiology of aging-related diseases such as dementia and diabetes. Significant baseline and longitudinal effects of age, smoking and neuropathological burdens such as amyloid, tau and glucose metabolism provide a complete imaging, neurocognitive and cardiovascular profile for better staging and differentiating different diseases. Together with accurate imaging guidance, early detection and treatment could be achieved with the ultimate goal of improving quality of life at middle age and extending longevity. The aim of this book is intended to provide both beginners and experts in biomedical imaging and health care a broad picture as well as new development in brain function and metabolism of aging using innovative neuroimaging techniques and advanced longitudinal /correlational analyses. Methods and data presented in this book with novel experimental designs and protocols, especially longitudinal investigation of multiple imaging metrics from microvascular, micro-structural to systematic functional, metabolic and neuropathological perspectives will help improving diagnosis and early prevention of common diseases at middle age such as metabolic syndrome and early dementia. Some promising prevention strategies such as arts therapy, aerobic exercise and calorie restriction will be introduced additionally with imaging evidence. Results presented will help improving diagnosis accuracy, staging, and determining phases and trajectories of disease progression with age, endothelial dysfunction and deficits in metabolic syndrome. This book will provide the current state-of-the-art and new frontiers of brain function and metabolic changes at age using multi-parametric functional, structural and molecular imaging techniques in detection, diagnosis and treatment. We will present some forefront and interesting multi-dimensional baseline and longitudinal imaging techniques to serve as a reference and resource book in neuroimaging application and research field. Several distinct detection and application perspectives, including cutting-edge imaging methods from baseline evaluations to longitudinal applications as well as multi-modal and multi-parametric quantifications will be described. The relatively new and advanced data and results together with interesting examples and application demonstrations could help facilitate the generalization, interpretation and applications of these techniques to improve disease diagnosis, quality of life and treatment for metabolic syndrome and brain dysfunction.

Neuroimaging techniques that can help elucidate and characterize the nature and mechanism of tissue injury and disease progression in neurodegenerative disease are of particular importance given its their roles in seeking successful preventive and therapeutic treatments. Studying large-scale samples with various disease mechanisms using multi-parametric imaging, as well as revealing the correlations between the neuroimaging metrics and clinical data including neurocognitive function and neuropsychological inventories to elucidate multiple factors affecting the neurodegeneration processes in brain are the main topics of this book. In addition, the neural underpins of cognitive and psychological functions with advanced functional imaging techniques can provide better cross-validation and clinical symptom relevance of multi-parametric data. Expanding the current findings with higher diagnosis accuracy and detection specificity in multiple neurodegenerative diseases as well as better differentiation of each type are the ultimate goal. The results in this book will extend the current notion of diagnosis value of various relatively new imaging techniques in multiple neurodegenerative diseases including traumatic brain injury, post-traumatic stress disorder, multiple sclerosis and early stage of Alzheimer’s disease such as mild cognitive impairment. Specifically, the neurobiology and related imaging findings of the four representative neurodegenerative diseases will be introduced and reviewed, including brain region-specific and disease-related alterations, unique clinical symptom of each disease, as well as previous findings and challenges. There is an increasing body of literature suggesting that damage to the default mode network, hypothalamus, thalamus and hippocampus neuronal networks and local injuries might be under-diagnosed and may account for some of the sequelae following the neurodegenerative injuries including trauma and dementia. The relatively novel imaging results to differentiate each disease using advanced functional connectivity, neuronal activity, microstructure integrity analysis based on structural connectivity, multi-dimensional morphometry and molecular imaging tracers including amyloid and tau for neuropathological burden quantification were presented to differentiate each type of disease. We then briefly reviewed some of the therapeutic effects of traditional Chinese medicine with neuroimaging quantifications to help treating neurodegenerative diseases. Finally, our work proves that the multi-parametric neuroimaging methods with more than twelve metrics and numerous tight clinical association data presented in this book are the most forefront and up-to-date with enough sensitivity, precision and resolution. Taken together, multiple neuroimaging metrics haved been demonstrated in this book to identify and quantify significant and distinct brain alterations at function, microstructure, morphology and molecular scales in different types of neurodegenerative diseases with high sensitivity and specificity. These comprehensive imaging features could be combined to improve disease diagnosis accuracy. The aim of this book is thus intended to provide both beginners and experts in biomedical imaging and health care a broad and complete picture as well as the new developments of using multiple metrics in improving disease identification and diagnosis accuracy. This book would hopefully capture the interests of colleagues interested in neurodegenerative disease diagnosis and treatment, and could help convey the methodological and integrative perspectives of multi-parametric neuroimaging applications.

The well-known Alzheimer’s Disease Neuroimaging Initiative (ADNI) Center provides the most advanced, comprehensive, multiparametric and up-to-date biomarkers for mild cognitive impairment (MCI) and early Alzheimer’s disease (AD) projects, including neuroimaging, clinical assessments, biospecimens and genetic data. Recent developments in imaging techniques, including new molecular tracers for imaging disease burden and systematic multi-modal integration, have emerged to overcome the limitations of each single modality and individual-dependent variability. The MRI-based high-resolution structural and morphological changes in the brain, such as atrophy, and the abnormal activity/connectivity patterns of the hippocampus subfields and default mode network (DMN) modulation, together with the amyloid and tau neuropathological quantification using PET molecular tracers, could be used to predict brain changes and cognitive performance declines in early AD, including transitional MCI. Finally, a generalized and integrative model with multiple biomarkers could be built to target disease progression and symptom prediction as well as to optimize patient management. Multiomics investigates metabolomic, lipidomic, genomic, transcriptomic and proteomic perspectives by presenting an accurate biochemical profile of the organism in health and disease. The Alzheimer''s Disease Metabolomics Consortium (ADMC) in partnership with ADNI is creating a comprehensive biochemical database for patients in the ADNI1 cohort, consisting of eight metabolomics datasets. The vast majorities of biospecimen data provide rich biological information to the human brain at normal and dementia status. One of the purposes is to reveal the connections between disease and multiomics such as obesity, hypertension, cholesterol imbalance and inflammation risks that might lead to neurodegenerative disease. Multiomic biomarker developments in the dementia field have provided earlier clues to novel treatments that help correct metabolic dysfunction and delay disease progression. Furthermore, the assembling of multiomics-based biomarkers including metabolites and lipids, cholesterol biosynthesis, purine metabolism, lipoprotein, bile acids, and genetics as well as their relation to the pathological amyloid and tau network could improve disease diagnosis sensitivity and reveal more diverse and complementary molecular pathways to allow for the advancement of early AD diagnosis and therapeutic prevention. In this book, we report on the significant differences of multiple biomarkers from the ADNI database including neuroimaging, clinical assessments and multiomic biospecimen/genetic data in MCI and early probable AD (pAD), and elucidate the interconnections among different metrics at various domains. Classification results with high accuracies (0.95-1) for each early dementia subtype including early MCI (EMCI), late MCI (LMCI) and pAD, and better prediction of clinical symptoms is achieved with these comprehensive biomarkers. Further longitudinal changes of imaging and neuropsychological biomarkers, and inter-correlations with baseline parameters are examined for a better illustration of disease progression association. Additionally, an analysis of the post-traumatic stress disorder biomarkers is performed with high classification accuracy. With illustrative and rigorous data analyses and confirmative results, this book provides readers with a full spectrum of biomarker research for early dementia diagnosis and treatment, and helps convey the technical development and data evaluation perspectives in advanced medical imaging and various disease application fields.

Multiple advanced neuroimaging applications in various neurodegenerative diseases including Parkinson’s disease (PD), frontotemporal dementia (FTD), vascular dementia (VaD) and autism spectrum disorder (ASD) are covered in this book. Relatively novel techniques such as integrated PET/MRI and independent component analysis (ICA)-based dual regression (DR) methods were developed to capture multi-level molecular/functional and structural/microstructural as well as high-order inter-network coordination abnormalities. For instance, both PET dopamine transporter and striatal binding ratio reductions in the caudate and putamen were found in PD, consistent with the diffusion tensor imaging (DTI) fractional anisotropy (FA) reduction and fMRI voxel-mirrored homotopic correlation (VMHC) in the substantia nigra (swallow tail sign signature of PD). Furthermore, dopamine storage and pathway labeled with the vesicular monoamine transporter tracer identified decreased densities in the bilateral mesial temporal cortex, caudate, orbitofrontal cortex, left frontal and occipital cortices, consistent with the morphological atrophy, functional connectivity and conductivity deficits in PD. Similarly in FTD patients, the advanced MRI methods such as ICA-DR, VMHC, voxel-based morphometry (VBM) as well as PET tracer for amyloid accumulation and FDG glucose uptake identified typical brain atrophy, structural dis-connectivity, glucose hypometabolism, higher neuropathological burden, lower interhemispheric correlation as well as disrupted intra- and inter-network modulation in the orbitofrontal and anterior temporal cortices together with insular and frontoparietal networks, with the cerebellum and dorsolateral attentional network as typical compensations. Functional and structural abnormalities had further been elucidated in the VaD dependent participants and autistic children. For instance, both lower FA and VMHC, brain atrophy and functional connectivity deficits, demyelination, axonal degeneration and white matter integrity damage in several white matter tracts were present in the dependent compared to independent participants in VaD data cohort. Increased neuronal activity with higher global fractional amplitude of low frequency fluctuation (fALFF) in the conventional and slow-wave sub-band was confirmed with less efficiency of systematic integration in VaD dependent group. Moreover, in ASD compared to controls, regional gray matter volume and cortical thickness in all four brain lobes increased, whereas white matter volume were decreased in addition to the lower temporal, visual and superior frontal but higher inferior and dorsolateral prefrontal cortical functional connectivities exhibited in ASD. The differences in each type of disease could also be revealed with the same imaging method based on either unique region or distinct brain circuit inter-connection, using VMHC, ICA-DR, DTI, VBM, fALFF and graph-theory based small-worldness analysis. In this book, we have developed and generalized conventional and advanced imaging methodologies to several common neurodegenerative diseases. For instance, we have identified the unique imaging signature for each disease type and the underlying neuropathological mechanism connections with conductivity, structural and microstructural connectivity, intra- and inter-network correlation, systematic integration and efficiency analyses. Our objective, comprehensive and confirmative results indicated great potential in utilizing these quantifications for accurate disease classification and staging. With solid imaging evidence, thorough analysis and generalized applications, this book should capture the interests of readers in the broad fields of brain science, disease diagnosis and effective treatment.

The aim of this new book is to provide readers some new insights into applying various imaging techniques to diagnose and distinguish subtypes and rare/comorbid cases of several brain disorders more accurately. Specific and comprehensive imaging features utilized that could pinpoint the exact abnormalities of these atypical and/or rare diseases are the highlights of this book, which will provide guidance for better disease mechanism interpretation.