Table of Contents
Overview
Definition and Scope
Neuropathology is a specialized branch of medicine focused on the study of diseases and disorders that affect the nervous system, particularly the brain and spinal cord. This field involves the examination of tissue samples obtained from autopsies, surgeries, or biopsies to diagnose neurological conditions and understand their underlying causes, which is essential for developing effective treatment strategies.[3.1] The scope of neuropathology encompasses a variety of key concepts and principles, including recent advances in the field, genetic factors, and classification systems for different neuropathological disorders. These elements are crucial for both practitioners and students who are new to the discipline, as they provide a foundational understanding necessary for further study and clinical application.[2.1] Furthermore, the Division of Neuropathology plays a vital role in clinical services, education, and research. It not only provides autopsy and surgical services but also trains future academic neuropathologists and teaches medical students and residents about the complexities of the nervous system.[4.1] The objectives of neuropathology include offering an overview for newcomers to the field and serving as a review framework for those preparing for examinations in neurology, neurosurgery, and pathology, all of which require a solid grasp of neuropathological principles.[5.1]Importance in Neurological Disorders
Neuropathology plays a crucial role in the diagnosis and understanding of various neurological disorders, integrating clinical findings with advanced diagnostic techniques. The integration of pathological findings with clinical data, including new imaging modalities, genetic tests, and in vivo biomarkers, is essential for optimizing patient diagnosis and prognosis. Future multidisciplinary meetings are proposed to enhance this integration, ultimately benefiting patient outcomes.[6.1] Recent advancements in artificial intelligence (AI) have significantly transformed neuropathology, enhancing diagnostic accuracy and personalizing treatment strategies. AI algorithms are capable of analyzing histopathological images with remarkable precision, which streamlines workflows and improves the overall quality of care for patients with neurological disorders.[7.1] Furthermore, AI technologies facilitate the analysis of diverse patient data, including medical history and genetic profiles, allowing for the identification of subtle markers of neurological disorders that may be overlooked by human observation.[21.1] This data-driven approach not only aids in early diagnosis but also optimizes treatment plans tailored to individual patients.[9.1] The integration of molecular diagnostic criteria into neuropathology has also advanced significantly, particularly in the classification of brain tumors. For example, the 2016 WHO Classification of Central Nervous System Tumors incorporated molecular diagnostic criteria based on genetic mutations, such as IDH1 and IDH2, which are associated with specific tumor types.[11.1] This shift towards molecular pathology enhances the understanding of disease mechanisms and informs therapeutic strategies. Moreover, the exploration of genetic factors linked to neurological disorders, such as Alzheimer’s disease and Parkinson’s disease, has led to the development of targeted therapeutic strategies. By identifying specific genetic mutations, researchers can better understand the underlying mechanisms of these conditions and develop personalized interventions.[13.1] Gene therapy, particularly through innovative techniques like CRISPR-Cas9, represents a promising avenue for treating neurological disorders with a genetic basis.[19.1]History
Early Developments in Neuropathology
Forensic neuropathology, a well-established subspecialty of neuropathology and forensic pathology, has its roots tracing back to ancient times, with documented cases of head trauma found in the Edwin Smith papyrus around 1600 BCE.[44.1] This early documentation laid the groundwork for the evolution of neuropathology as a formal discipline. The field began to take shape in the latter half of the nineteenth century, particularly in Europe, where systematic morphologic studies of the diseased human brain were conducted by neuroscientists, especially in Germany and France.[54.1] The establishment of neuropathology as a distinct discipline was significantly influenced by advancements in related fields such as neurosurgery, psychiatry, and anatomic pathology. The collaboration between neurologists and neurosurgeons, notably figures like Sir Victor Horsley and Harvey Cushing, played a crucial role in shaping neuropathological methodologies.[52.1] Furthermore, the foundation of the German Research Institute for Psychiatry in Munich and the contributions of Emil Kraepelin, who emphasized neuropathological morphology in psychiatry, were pivotal in advancing the field.[49.1] The history of neuropathology at Massachusetts General Hospital (MGH) can be divided into four partially overlapping eras, beginning with the period before 1927, when a formal neuropathology unit was established. During this initial phase, surgical neuropathology was conducted by anatomical pathologists, while research and autopsy neuropathology were performed by pathologists and neurologists.[45.1] The field of neuropathology underwent significant development with the First International Congress of Neuropathology in 1952, which was initiated by Dr. Armando Ferraro, then at the Psychiatric Institute in New York. This congress highlighted the necessity for new experimental methods and encouraged a chemical approach to neuropathological problems, reflecting the evolving methodologies within the discipline.[50.1]Key Figures and Contributions
Key figures and contributions to the field of neuropathology have significantly shaped its development, particularly through collaborations and advancements in related disciplines. The German Society for Neuropathology and Neuroanatomy has played a pivotal role in this evolution, facilitating research that bridges basic and clinical neurosciences. Their focus on understanding the mechanisms of neurological diseases has been instrumental in advancing the field, as evidenced by their commitment to research that combines molecular and cellular biology with disease models and human studies.[62.1] The collaboration between neurologists and neurosurgeons, particularly during the latter half of the 19th century, marked a significant turning point in neuropathology. Notable figures such as Sir Victor Horsley, Harvey Cushing, and Percival Bailey contributed to this interdisciplinary approach, which enriched the field with innovative investigative methods derived from anatomic pathology. This synergy not only enhanced the understanding of neuropathological morphology but also laid the groundwork for future research and clinical practices.[63.1] Moreover, the annual meetings organized by the German Society of Neuropathology and Neuroanatomy, such as the 65th Annual Meeting held virtually in 2021, exemplify the ongoing commitment to fostering collaboration among basic and clinical researchers, physicians, and junior scientists. These gatherings serve as platforms for sharing knowledge and advancing research in the brain and nerve microenvironment in health and disease, further solidifying the society's influence in the field.[64.1]Methodology
Techniques in Neuropathological Examination
The techniques employed in neuropathological examination have undergone significant evolution over the past few decades. Historically, pathologists relied on gross examination and various histochemical techniques to assess tissue samples, utilizing chemical compounds to visualize cells and cellular structures.[83.1] However, advancements in technology have introduced more sophisticated methodologies, such as microarray platforms and next-generation sequencing (NGS), which have become integral to neuropathology research and diagnostics. Microarray platforms have significantly advanced neuropathology research by enabling the discovery of gene expression and gene silencing combinations relevant to the classification of neurological disorders.[82.1] In recent years, single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a transformative technology, enhancing our understanding of complex neurological conditions by providing insights into cellular heterogeneity and gene expression profiles at an unprecedented resolution.[97.1] This methodology has been particularly impactful in studying brain tumors, where it has revealed cancer heterogeneity, and in cerebrovascular diseases, such as stroke, by identifying specific genes and cell-specific expression patterns that may inform potential therapeutic interventions.[97.1] Furthermore, scRNA-seq has facilitated the identification of transcriptional changes associated with diseases like Alzheimer’s and amyotrophic lateral sclerosis, highlighting alterations in gene expression within specific cell types involved in neuronal function and immune response.[97.1] Overall, these advanced techniques have contributed to a deeper understanding of the molecular complexities underlying neurological disorders, although the mechanisms of these diseases remain incompletely understood and therapeutic options are still limited.[96.1] The advent of next-generation sequencing (NGS) has revolutionized routine neuropathology diagnostics by enabling the simultaneous sequencing of numerous genomic regions, which allows for detailed interrogation of DNA and RNA from tissue samples.[91.1] This technology has generated vast amounts of data that can significantly support patient management.[93.1] Since its introduction in 2005, the cost of NGS has decreased markedly, and its relatively fast turnaround time has made its routine application in surgical neuropathology increasingly common.[91.1] As the number of prognostic and predictive genetic markers in neuro-oncology continues to rise, the demand for comprehensive molecular analysis of neuropathological samples has grown substantially.[92.1] In response to this need, customized enrichment/hybrid-capture-based NGS gene panels have been developed, which encompass the entire coding and selected intronic and promoter regions of 130 genes.[92.1] This high-throughput approach is anticipated to become increasingly valuable for treatment decision-making as more therapeutic targets emerge and genetic information becomes integral to the classification of brain tumors.[90.1] The integration of visual aids and interactive tools in neuropathological education significantly enhances the learning experience for students and professionals. The interactive nature of whole slide imaging (WSI), particularly when combined with internet-based programs, allows multiple individuals from different locations to view the same slide simultaneously, resembling a multiheaded microscope session.[86.1] Literature reviews have shown that the use of audiovisual aids during the educational process leads to improved information retention and increased satisfaction among learners.[88.1] Furthermore, visual learning tools provide distinct advantages for neurodivergent learners by breaking down complex information into manageable parts, encouraging active engagement through visuals and interactive interfaces, and enhancing memory retention by appealing to both cognitive and emotional responses.[89.1]Role of Imaging Technologies
Imaging technologies play a crucial role in the field of neuropathology, significantly enhancing the diagnosis and management of neurological disorders. Neuroimaging tools, such as magnetic resonance imaging (MRI), positron emission tomography (PET), and computerized tomography (CT), serve as important biomarkers for the identification, tracking, diagnosis, and treatment monitoring of various neurologic diseases, including neurodegenerative disorders like Alzheimer’s disease (AD), frontotemporal lobar degeneration (FTLD), and Parkinson’s disease (PD).[101.1] These imaging modalities provide critical insights into the underlying biology of these conditions, aiding in diagnostic classification and treatment response evaluation.[117.1] The integration of neuroimaging with artificial intelligence (AI) technologies has further advanced the field, enabling early diagnosis and the development of personalized treatment plans. AI-powered algorithms analyze diverse patient data, including imaging results and genetic profiles, to identify subtle markers of neurological disorders that may be overlooked by human observation.[102.1] This synergy between neuroimaging and AI not only enhances the quality and effectiveness of treatment plans but also drives transformative changes in patient care and our understanding of neurological disorders.[102.1] Moreover, the evolution of quantitative neuroimaging methods allows for systematic image analysis and statistical modeling, which are essential for evaluating the brain as an integrated structural and functional network.[99.1] These approaches are critical for deciphering brain circuitry and understanding the dysfunction of brain network connectivity that occurs during the progression of neurological and psychiatric disorders.[99.1] As neuroimaging continues to evolve, it is expected to cultivate opportunities for understanding brain development and neuropathology in varied settings, thereby improving clinical care.[98.1] The integration of neuroimaging findings with traditional histopathological assessments is also anticipated to enhance diagnostic accuracy in complex neurological disorders. This integration can provide valuable insights into brain barrier integrity and immune responses, which are crucial for understanding the pathology of neurological diseases.[120.1] Furthermore, the combination of neuroimaging, neuropathology, and biomarkers into clinical practice holds the potential to significantly improve the management and treatment of neurological diseases, leading to better outcomes for affected individuals and their families.[119.1]In this section:
Cellular StructuresTechnologyNext-generation SequencingGene ExpressionCerebrovascular Diseases
Recent Advancements
Innovations in Diagnostic Platforms
Recent advancements in neuropathology have led to significant innovations in diagnostic platforms, particularly through the integration of machine learning (ML) and artificial intelligence (AI) technologies. These innovations are transforming the analysis and understanding of neurodegenerative diseases by utilizing whole slide images (WSIs) and advanced computational techniques. For instance, ML/AI technologies have automated disease staging, identified novel morphological biomarkers, and uncovered new clinical insights via multi-modal AI approaches, thereby enhancing the capabilities of image-based medical fields, including anatomic pathology.[135.1] In the realm of neuroimaging, AI-enhanced analysis of MRI and CT scans has facilitated the early detection of neurodegenerative diseases, improving diagnostic accuracy and enabling pre-operative predictions of tumor biology.[137.1] Additionally, deep learning (DL) models applied to digital pathology have proven effective in distinguishing between various tumor grades and identifying rare pathologies, ensuring early and accurate diagnoses.[137.1] The incorporation of molecular features into the World Health Organization (WHO) grading of gliomas, alongside the growing availability of individualized tumor genetic data, further exemplifies how AI serves as a valuable tool for pathologists in interpreting complex datasets.[137.1] Moreover, the development of cerebrospinal fluid (CSF), imaging, and blood-based biomarkers for neurodegenerative diseases has been a focal point of recent research. These biomarkers are crucial for early diagnosis and have been discussed extensively in literature, highlighting their utility and limitations in clinical practice.[134.1] For example, positron emission tomography (PET) methods detecting amyloid-β and tau pathology in Alzheimer's disease are increasingly utilized to enhance the design of clinical trials and observational studies, thereby improving the clinical characterization of cognitive decline.[136.1]Emerging Therapeutic Approaches
Recent advancements in single-cell RNA sequencing (scRNA-seq) have significantly enhanced our understanding of cellular diversity within the brain, which has important implications for identifying potential therapeutic targets in neuropathological conditions. This technology allows for the analysis of transcriptomes from individual cells, thereby addressing the complexity and dynamics of the central nervous system. For instance, scRNA-seq has been applied to study the molecular taxonomy of the brain, revealing extensive cell type diversity across various regions, including both mouse and human brains.[141.1] Moreover, scRNA-seq has provided insights into the molecular complexities of cerebrovascular diseases, such as stroke, by elucidating specific genes and cell-specific expression patterns that could inform therapeutic interventions.[140.1] In the context of neurodegenerative diseases, scRNA-seq has identified transcriptional changes associated with conditions like Alzheimer's disease (AD) and amyotrophic lateral sclerosis (ALS), highlighting alterations in gene expression within specific cell types that are crucial for neuronal function and immune response.[140.1] This capability to pinpoint disease-associated cell types facilitates the development of targeted therapeutic strategies for these debilitating conditions. Emerging therapeutic approaches in the context of neuroinflammation are increasingly informed by advancements in single-cell RNA sequencing (scRNA-seq). A recent study utilizing a mouse model of multiple sclerosis applied scRNA-seq to determine how immune cells in the central nervous system (CNS) respond during inflammation, thereby highlighting novel insights into the mechanisms of neuroinflammation.[152.1] This technique has also provided unique insights into the transcriptomic changes occurring in the brains of patients with multiple sclerosis and Alzheimer’s disease.[153.1] Neurological diseases represent a significant global burden, and while the mechanisms underlying their development are not fully understood, many are associated with neuroinflammatory mediators. Current therapeutic options to address these conditions remain quite limited.[154.1] The construction of comprehensive immune cell atlases through scRNA-seq has revealed the transcriptional landscape and functional heterogeneity of immune cells, particularly neutrophils, and their interactions within the neuroinflammatory processes.[155.1] These insights not only deepen our understanding of the immune response in the CNS but also suggest potential avenues for novel therapeutic strategies aimed at modulating neuroinflammation.In this section:
Neurological Disorders
Alzheimer’s Disease
Alzheimer's disease (AD) is characterized by a range of neuropsychiatric symptoms (NPS) including depression, apathy, aggression, and psychosis, which are now recognized as core features of the condition. Research indicates that greater severity of these symptoms is predictive of faster cognitive decline, loss of independence, and even shorter survival rates among patients.[186.1] The psychological effects of Alzheimer's disease significantly influence the overall treatment plan, necessitating the integration of mental health support into patient care. Current strategies for addressing these psychological difficulties include cognitive behavioral therapy (CBT), which has been shown to be effective in treating depression and anxiety in individuals with neurological disorders.[200.1] CBT not only addresses the mental and emotional aspects of these conditions but also improves overall mental well-being, thereby enhancing the quality of life for patients.[200.1] The care provided to individuals with neurological disorders, such as Alzheimer's and Parkinson's disease, is often characterized as fragmented, leading to delays and a suboptimal experience for both patients and caregivers.[182.1] While foundations and professional societies have significantly contributed to raising awareness of mental healthcare needs, their initiatives have predominantly focused on disciplines outside of mental health, such as physical, occupational, and speech therapy.[183.1] The Parkinson's Foundation has initiated several educational programs that could be adapted to support the development of integrated care programs specifically aimed at enhancing mental health and psychological well-being.[181.1] This underscores the critical need for incorporating mental health strategies into the overall treatment plans for patients with Alzheimer's and similar conditions. Furthermore, the implementation of multidisciplinary palliative care programs has demonstrated improvements in quality of life for patients with moderate palliative care needs, underscoring the necessity of training professionals to address these psychological aspects effectively.[184.1] As the understanding of Alzheimer's disease evolves, it becomes increasingly clear that addressing the psychological needs of patients is essential for comprehensive care and improved outcomes.Interdisciplinary Connections
Relationship with Neurology and Neurosurgery
Interdisciplinary connections in neuropathology play a crucial role in enhancing the understanding and treatment of neurological disorders, particularly through the integration of various scientific disciplines. The 6th Mediterranean Neuroscience Society Meeting in 2017 served as a significant forum for discussing modern experimental and interdisciplinary approaches that have yielded important insights into the pathogenesis and treatment of diseases affecting the human central and peripheral nervous systems.[219.1] Notable studies have underscored the importance of interdisciplinary approaches in understanding neurological disorders such as Autism Spectrum Disorders and Parkinson's disease, emphasizing that collaboration across different fields can lead to more effective interventions.[205.1] For instance, the combined use of neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), alongside genetic analyses and cognitive testing, has advanced the development of interventions for schizophrenia.[220.1] This multifaceted approach not only enhances diagnostic accuracy but also paves the way for personalized treatment strategies that address the complexities of these disorders.[216.1] The integration of interdisciplinary approaches is crucial for advancing our understanding of complex mental disorders, particularly schizophrenia. This editorial emphasizes the importance of combining insights from various scientific disciplines, including neuropathology and psychology, to enhance treatment strategies for patients with schizophrenia spectrum illnesses.[217.1] Emerging intervention presentations highlight the need for empiricism in these collaborations, suggesting that evidence-based approaches can significantly improve symptom management.[215.1] By fostering such interdisciplinary collaborations, researchers can develop innovative strategies that address the multifaceted nature of psychiatric disorders, ultimately benefiting individuals affected by these conditions.[217.1] The role of environmental factors in the development of schizophrenia, as evidenced by studies on monozygotic twins, further illustrates the necessity of interdisciplinary research in understanding the multifactorial nature of neurological disorders.[218.1] By fostering collaborations among various scientific disciplines, researchers can better address the complexities of these conditions and develop more effective treatment modalities.In this section:
Challenges And Future Directions
Limitations in Current Diagnostic Methods
Current diagnostic methods in neuropathology face significant limitations, primarily due to regulatory challenges and the evolving nature of technology. One major issue is the neuropathological-clinical efficacy gap, which suggests that coordinated drug studies involving sequential clinical trials over many years will be necessary to demonstrate clinical efficacy relevant to Alzheimer's disease (AD).[251.1] This gap highlights the need for regulators to consider the implications of neuropathology on clinical efficacy, which can hinder advancements in diagnostic accuracy and patient care. As technology progresses, regulatory guidelines must be updated to reflect best practices; however, these updates can also introduce challenges for neurodiagnostic practitioners.[252.1] The complexity of new technologies, such as brain-computer interfaces (BCIs), raises ethical, legal, and safety concerns that existing regulatory frameworks may not adequately address. Regulators are tasked with balancing the potential medical benefits of these innovations against associated risks, ensuring proper oversight of experimental procedures, and addressing privacy concerns related to brain data collection.[253.1] Furthermore, the Coalition for Effective Diagnostics has advocated for comprehensive diagnostic testing reform to tailor the U.S. Food and Drug Administration's (FDA) regulatory oversight of laboratory-developed tests (LDTs).[254.1] This call for reform underscores the necessity of adapting regulatory approaches to improve diagnostic accuracy and enhance patient care in the field of neuropathology.Potential Areas for Research and Development
Neuropathology faces several challenges that necessitate ongoing research and development to enhance its efficacy and relevance in clinical practice. One significant area of focus is the increasing demand for pathology services, driven by a rise in the number of biopsies and the need to adhere to cancer case reporting guidelines and specimen handling recommendations.[241.1] This demand underscores the necessity for improved turnaround times in diagnostic processes, which are critical for effective clinical management.[241.1] Advancements in digital neuropathology and machine learning (ML) present promising avenues for addressing these challenges. Computational neurodegenerative neuropathology, which utilizes whole slide images (WSIs) and advanced ML techniques, has the potential to transform the analysis and understanding of neurodegenerative diseases.[244.1] These technologies can automate disease staging, identify novel morphologic biomarkers, and provide new clinical insights, thereby significantly advancing the field.[249.1] For instance, deep learning models applied to digital pathology can distinguish between various tumor grades and identify rare pathologies, ensuring early and accurate diagnoses.[250.1] Moreover, the integration of neuroimaging tools, such as magnetic resonance imaging (MRI) and positron emission tomography (PET), plays a crucial role in identifying, tracking, and monitoring treatment responses in neurodegenerative disorders.[247.1] The incorporation of molecular features into diagnostic criteria, such as the WHO grading of gliomas, further exemplifies how AI can assist pathologists in interpreting complex data sets.[250.1] Future research directions in neuropathology should also focus on innovative technologies that enhance diagnostic efficiency and accuracy. For example, the development of platforms like "AI Neuropathologist," which utilizes convolutional neural networks (CNNs) for unbiased histological diagnosis, demonstrates the potential for automation in pathology.[248.1] Such innovations could significantly alleviate the pressures faced by neuropathologists and improve patient outcomes.In this section:
References
[2] Neuropathology Simplified: A Guide for Clinicians and Neuroscientists — This updated second edition provides a practical and succinct overview of basic neuropathology. Key concepts and basic principles are covered and discussed with particular focus on recent advances, classification, and genetics. Practical points are included to detail how to best use the
[3] Neuropathology | A Simplified Psychology Guide — Neuropathology Neuropathology is a branch of medicine that deals with the study of diseases and disorders affecting the nervous system, particularly the brain and spinal cord. It involves the examination of tissue samples obtained from autopsies, surgeries, or biopsies to diagnose and understand the underlying causes of neurological conditions and to develop treatment strategies. Key Areas of
[4] Neuropathology Overview | University of Pennsylvania | Pathology and ... — Neuropathology Overview. The Division of Neuropathology provides clinical services, trains the next generation of leading academic neuropathologists, teaches medical students and residents, and carries out basic biomedical research. Each of these missions focuses on the nervous system. Clinical services include both autopsy and surgical
[5] Neuropathology Review - SpringerLink — The objectives are twofold: 1) to provide an overview of neuropathology for those initially encountering the discipline and, 2) to provide a framework for review for those preparing for in-service and board examinations in the disciplines of neurology, neurosurgery, and pathology, which require some knowledge of neuropathology.
[6] Neuropathology today: expertise, advancements and future considerations — Integrating pathological findings with clinical findings, including new imaging modalities, genetic tests and in vivo biomarkers in body fluids, Forrest and Kovacs 6 discuss the concept of future multidisciplinary meetings to provide optimal benefit for patient diagnosis and discussion of prognosis.
[7] The emerging role of artificial intelligence in neuropathology: Where ... — The integration of artificial intelligence (AI) into neuropathology represents a significant advancement, promising to enhance diagnostic accuracy, streamline workflows, and personalize treatment strategies . AI algorithms have demonstrated remarkable capabilities in analyzing histopathological images with high precision .
[9] Revolutionizing Neurology: The Role of Artificial Intelligence in ... — Keywords: ai algorithms, brain signals, neuroimaging, brain-computer interfaces, precision medicine, neurological disorders, artificial intelligence Integrating AI technologies into neurology has yielded many benefits, including early diagnosis, personalized treatment plans, neuroimaging analysis, treatment optimization, and groundbreaking research endeavors . AI-powered algorithms analyze diverse patient data - medical history, imaging results, genetic profiles - to identify subtle markers of neurological disorders that might evade human observation . AI can significantly enhance the quality and effectiveness of treatment plans for neurological disorders by leveraging data-driven insights and personalizing care for individual patients. From early diagnosis and personalized treatment to BCIs and drug discovery, AI drives transformative changes that enhance patient care and our understanding of neurological disorders.
[11] The emerging role of artificial intelligence in neuropathology: Where ... — Advances in understanding the molecular mechanisms of brain tumors led to the inclusion of molecular diagnostic criteria in the 2016 WHO Classification of Central Nervous System (CNS) Tumors . For instance, research by Parsons et al. and Yan et al. showed that diffuse gliomas with IDH1 and/or IDH2 (IDH1/2) mutations tend to have a less
[13] How Genetics Impact Neurological Conditions — Genetic mutations and variations play a pivotal role in the onset and progression of several neurological conditions, such as Alzheimer’s disease and Parkinson’s disease. The continuous exploration of genetic markers not only deepens our understanding of complex neurological conditions but also guides the development of precision medicine approaches tailored to individual patterns of genetic risk. Understanding the distinction between inherited and sporadic neurological conditions is essential for comprehending the genetic and environmental influences on these disorders. Family history provides a critical foundation for assessing genetic risks in neurological conditions, serving as a key tool to guide early diagnosis and proactive management. Early Detection and Prevention: A strong family history of neurological conditions, such as Parkinson’s disease or Huntington’s disease, can highlight at-risk individuals, allowing for early intervention.
[19] Neurology Tomorrow: Emerging Trends and Future Directions — Trends and Innovations in Neurology. 1. Gene Therapy for Neurological Disorders Gene therapy, which involves modifying or replacing defective genes to treat or prevent diseases, is a promising avenue for addressing neurological disorders with a genetic component. Recent breakthroughs in gene editing technologies, such as CRISPR-Cas9, offer new
[21] Revolutionizing Neurology: The Role of Artificial Intelligence in ... — Keywords: ai algorithms, brain signals, neuroimaging, brain-computer interfaces, precision medicine, neurological disorders, artificial intelligence Integrating AI technologies into neurology has yielded many benefits, including early diagnosis, personalized treatment plans, neuroimaging analysis, treatment optimization, and groundbreaking research endeavors . AI-powered algorithms analyze diverse patient data - medical history, imaging results, genetic profiles - to identify subtle markers of neurological disorders that might evade human observation . AI can significantly enhance the quality and effectiveness of treatment plans for neurological disorders by leveraging data-driven insights and personalizing care for individual patients. From early diagnosis and personalized treatment to BCIs and drug discovery, AI drives transformative changes that enhance patient care and our understanding of neurological disorders.
[44] A history of forensic neuropathology - ScienceDirect — Forensic neuropathology is now a well-established subspecialty of neuropathology and forensic pathology. It has a long history with ancient roots, as disorders and trauma of the head have been recorded in the literature back to the Edwin Smith papyrus around 1600 bce. Surgeons, particularly military surgeons, advanced our knowledge of trauma of
[45] PDF — Th e history of neuropathology at MGH can be divided into four partially overlapping eras: 1. Before 1927, when a formal neuropathol-ogy unit was established. During this period surgical neuropathology was performed by the anatomical pathologists and research and autopsy neuropathology by the pathologists and neurologists 2.
[49] A brief history of neuropathology - Edumed — Strong influences regarding direction and contents of neuropathology came fromthe blossoming field of neurosurgery which developed in the second half of the 19th century, in particular through the collaboration of neurologists and the neurosurgeon Sir Victor Horsley, as well as through Harvey Cushing and Percival Bailey in the United States,psychiatry, which was - thanks to Emil Kraepelin - heavily based on neuropathological morphology, and the foundation of the German Research Institute for Psychiatry in Munich,progress in anatomic pathology which has always provided the field of neuropathology with some of its investigative methodsThis kind of development was encountered - with regional differences as to its direction - in several European countries and the United States.
[50] THE PRACTICE OF NEUROPATHOLOGY: Past, Present, and Future — This rule was quickly relaxed because the First International Congress of Neuropathology in 1952, which we owe to the initiative of Dr. Armando Ferraro, then at the Psychiatrical Insti- tute, New York, stressed the need for new experimental methods and for encouraging the chemical approach to problems of neuropathology-a view which, curiously
[52] A brief history of neuropathology - Edumed — Strong influences regarding direction and contents of neuropathology came fromthe blossoming field of neurosurgery which developed in the second half of the 19th century, in particular through the collaboration of neurologists and the neurosurgeon Sir Victor Horsley, as well as through Harvey Cushing and Percival Bailey in the United States,psychiatry, which was - thanks to Emil Kraepelin - heavily based on neuropathological morphology, and the foundation of the German Research Institute for Psychiatry in Munich,progress in anatomic pathology which has always provided the field of neuropathology with some of its investigative methodsThis kind of development was encountered - with regional differences as to its direction - in several European countries and the United States.
[54] Introduction to Neuropathology | Principles And Practice Of ... — Neuropathology emerged as a distinct discipline during the latter half of the nineteenth century. Stimulated by the possibility of a clearer understanding of human behavior, European neuroscientists, particularly in Germany and France, conducted systematic morphologic studies of the diseased human brain.
[62] Neuropathology - UKE — Reference Center by appointment of the German Society for Neuropathology and Neuroanatomy. Research With our research, we gain novel insights into the mechanisms of neurological diseases. Neuropathology is at the hinge between basic and clinical neurosciences and our research combines molecular and cellular biology with disease models and human
[63] A brief history of neuropathology - Edumed — Strong influences regarding direction and contents of neuropathology came fromthe blossoming field of neurosurgery which developed in the second half of the 19th century, in particular through the collaboration of neurologists and the neurosurgeon Sir Victor Horsley, as well as through Harvey Cushing and Percival Bailey in the United States,psychiatry, which was - thanks to Emil Kraepelin - heavily based on neuropathological morphology, and the foundation of the German Research Institute for Psychiatry in Munich,progress in anatomic pathology which has always provided the field of neuropathology with some of its investigative methodsThis kind of development was encountered - with regional differences as to its direction - in several European countries and the United States.
[64] 65th Annual Meeting of the German Society of Neuropathology and ... — Dear participants, dear colleagues, It is our great pleasure to welcome you to the 65th Annual Meeting of the German Society of Neuropathology and Neuroanatomy - the brain and nerve microenvironment in health and disease - which will be held as a virtual meeting from September 1-3, 2021.. The meeting will bring together basic and clinical researchers, physicians as well as junior scientists
[82] "Current Pathology Techniques" Symposium Review: Advances and Issues in ... — This latter technology will likely see increased use in neuropathology research as automated analytical techniques and reliable commercially available arrays become more prevalent. Microarray platforms have led to the discovery of combinations of gene expression or gene silencing, which are related to neuropathology classification and
[83] Techniques in neuropathology - ScienceDirect — The techniques used by pathologists and neuropathologists have evolved dramatically over the last 20-30 years. For many years we assessed the tissue of interest with the naked eye, i.e., gross examination, and investigated the tissue applying various histochemical techniques, methods where, applying different chemical compounds tissue, cells and cell structures are visualized.
[86] Internet and World Wide Web‐Based Tools for Neuropathology Practice and ... — The interactive nature of WSI is particularly powerful in education and training when combined with internet‐based programs. This setup allows several individuals from different parts of the world to simultaneously view the same slide, akin to a multiheaded microscope session.
[88] The Use of Audiovisual Aids for Patient Education in the Interventional ... — The results of the literature review revealed positive outcomes in the use of visual aids during the education process. Individual studies showed improved information retention and increased patient satisfaction when audiovisual aids were used. Further study is needed to broaden the scope of research in the use of audiovisual aids during
[89] Visual Learning Tools: A Lifeline for Neurodivergent Minds — The Benefits of Visual Learning Tools. Visual learning tools offer multiple advantages for neurodivergent learners. They: Break down complex information into manageable parts.; Encourage active engagement through visuals and interactive interfaces.; Enhance memory retention by appealing to both cognitive and emotional responses.; For instance, mind maps and infographics simplify topics, while
[90] Next-generation sequencing in routine brain tumor diagnostics enables ... — In conclusion, we present the settings for high-throughput, adaptive next-generation sequencing in routine neuropathology diagnostics. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.
[91] Is Next-Generation Sequencing Alone Sufficient to Reliably Diagnose ... — Next-generation sequencing (NGS) involves the simultaneous sequencing of numerous genomic regions. Because NGS cost has dropped markedly since its advent in 2005, and has relatively fast turnaround time, its routine use in surgical neuropathology has become commonplace . As a result, some clinicians (and pathologists) wonder if it could
[92] Next-generation sequencing in routine brain tumor ... - Springer — With the number of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We therefore developed a customized enrichment/hybrid-capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes
[93] Next-Generation Sequencing in Diagnostic Pathology - PubMed — Recent developments in sequencing technology mean that DNA and RNA from tissue samples can now be interrogated in great detail. These new technologies, collectively known as next-generation sequencing (NGS), generate huge amounts of data which can be used to support patient management. In order to maximize the utility of tissue interrogation
[96] Advancements in Single-Cell RNA Sequencing Research for Neurological ... — Neurological diseases are a major cause of the global burden of disease. Although the mechanisms of the occurrence and development of neurological diseases are not fully clear, most of them are associated with cells mediating neuroinflammation. Yet medications and other therapeutic options to improve treatment are still very limited. Single-cell RNA sequencing (scRNA-seq), as a delightfully
[97] The molecular landscape of neurological disorders: insights from single ... — Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a particularly powerful tool, enabling the understanding of cellular heterogeneity and gene expression profiles at an unprecedented resolution . ScRNA-seq single-cell RNA sequencing, DAM disease associated microglia, SPP1 secreted phosphoprotein 1, IGF1 insulin-like growth factor 1 , for instance, used scRNA-seq to identify transcriptional changes associated with Alzheimer’s disease (AD), revealing alterations in gene expression within specific cell types involved in neuronal function and immune response. employed scRNA-seq to identify disease-associated cell types in amyotrophic lateral sclerosis (ALS), facilitating the development of potential therapeutic targets for this devastating disease.
[98] Future of Neurology & Technology: Neuroimaging Made Accessible Using ... — Increasing neuroimaging in these areas will also cultivate opportunities for understanding brain development and neuropathology in varied settings. 15 pMRI is currently commercially available in countries including the United States, Australia, and Pakistan and has been deployed in other areas including Germany and Malawi. e4 One group has
[99] The vast potential and bright future of neuroimaging - PMC — Quantitative neuroimaging is well-suited for statistical modeling and systematic image analysis approaches that utilize canonical templates or brain atlases to measure changes in specific regions of interest.7 Quantitative methods are beginning to evaluate the brain as an integrated structural and functional network.8 These new approaches might be critical not only for deciphering brain circuitry but also for understanding the dysfunction of brain network connectivity that occurs during the progression of many neurological and psychiatric disorders.
[101] Neuroimaging Advances in Neurologic and Neurodegenerative Diseases — Neuroimaging Advances in Neurologic and Neurodegenerative Diseases - PMC Neuroimaging tools, including magnetic resonance imaging (MRI), positron emission tomography (PET), and others (computerized tomography (CT), single-photon emission computerized tomography (SPECT), etc.) can be important biomarkers for identification, tracking, diagnosis, and treatment monitoring of neurologic diseases. Widely used in neurodegenerative disorders like Alzheimer’s disease (AD), frontotemporal lobar degeneration (FTLD), and Parkinson’s disease (PD) and associated disorders, neuroimaging methods are also applied to many other neurologic diseases to uncover important information about underlying biology, diagnostic classification, and treatment response. Finally, Brooks (2020) provides a comprehensive review of neuroimaging in PD and related disorders (such as LBD), focusing on MRI, SPECT (i.e., DATScan), and PET findings (primarily dopamine-focused and other neurotransmitter-focused tracers) .
[102] Revolutionizing Neurology: The Role of Artificial Intelligence in ... — Keywords: ai algorithms, brain signals, neuroimaging, brain-computer interfaces, precision medicine, neurological disorders, artificial intelligence Integrating AI technologies into neurology has yielded many benefits, including early diagnosis, personalized treatment plans, neuroimaging analysis, treatment optimization, and groundbreaking research endeavors . AI-powered algorithms analyze diverse patient data - medical history, imaging results, genetic profiles - to identify subtle markers of neurological disorders that might evade human observation . AI can significantly enhance the quality and effectiveness of treatment plans for neurological disorders by leveraging data-driven insights and personalizing care for individual patients. From early diagnosis and personalized treatment to BCIs and drug discovery, AI drives transformative changes that enhance patient care and our understanding of neurological disorders.
[117] Neuroimaging Advances in Neurologic and Neurodegenerative Diseases — Neuroimaging Advances in Neurologic and Neurodegenerative Diseases - PMC Neuroimaging tools, including magnetic resonance imaging (MRI), positron emission tomography (PET), and others (computerized tomography (CT), single-photon emission computerized tomography (SPECT), etc.) can be important biomarkers for identification, tracking, diagnosis, and treatment monitoring of neurologic diseases. Widely used in neurodegenerative disorders like Alzheimer’s disease (AD), frontotemporal lobar degeneration (FTLD), and Parkinson’s disease (PD) and associated disorders, neuroimaging methods are also applied to many other neurologic diseases to uncover important information about underlying biology, diagnostic classification, and treatment response. Finally, Brooks (2020) provides a comprehensive review of neuroimaging in PD and related disorders (such as LBD), focusing on MRI, SPECT (i.e., DATScan), and PET findings (primarily dopamine-focused and other neurotransmitter-focused tracers) .
[119] Neuropathology, Neuroimaging and Biomarkers in Neurological Disease - MDPI — Improved patient outcomes: The integration of neuropathology, neuroimaging, and biomarkers into clinical practice has the potential to greatly improve the management and treatment of neurological diseases, leading to better outcomes for the affected individuals and their families.
[120] Imaging of brain barrier inflammation and brain fluid drainage in human ... — This review explores the integration of neuroimaging data with immunopathological findings, providing valuable insights into brain barrier integrity and immune responses in neurological diseases.
[134] Editorial: Trends in biomarkers for neurodegenerative diseases: Current ... — Major advancements have been made in the development of cerebrospinal fluid (CSF), imaging, and blood-based biomarkers for several neurodegenerative diseases (Ashton et al., 2020; Kaipainen et al., 2020; Dutta et al., 2021; Taha et al., 2022), which are proof of concept for the possibilities of early diagnosis. This Research Topic is a collection of research articles and reviews from diverse groups around the globe discussing recent developments and insights in the field of biomarkers for neurodegenerative diseases, their utility and limitations, and future directions toward implementation of advanced biomarkers in regular clinical practice. Overall, this Research Topic highlights recent development and innovation in the field of biomarkers for neurodegenerative diseases, including AD, PD, HD, ALS, and others.
[135] Current Advancements in Digital Neuropathology and Machine Learning for ... — Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases - ScienceDirect Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases Computational neurodegenerative neuropathology represents a transformative approach in the analysis and understanding of neurodegenerative diseases through utilization of whole slide images (WSIs) and advanced machine learning/artificial intelligence (ML/AI) techniques. Recent advancements in ML/AI technologies have significantly affected image-based medical fields, including anatomic pathology, by automating disease staging, identifying novel morphologic biomarkers, and uncovering new clinical insights via multi-modal AI approaches. By addressing these challenges and leveraging cutting-edge AI techniques, computational neurodegenerative neuropathology has the potential to revolutionize the field and significantly advance our understanding of disease. For all open access content, the relevant licensing terms apply.
[136] Biomarkers for neurodegenerative diseases | Nature Medicine — Positron emission tomography methods detecting amyloid-β and tau pathology in Alzheimer’s disease have been increasingly used to improve the design of clinical trials and observational studies. Alzheimer’s disease biomarkers and their current use in clinical research and practice Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Plasma p-tau181 accurately predicts Alzheimer’s disease pathology at least 8 years prior to post-mortem and improves the clinical characterisation of cognitive decline. Comparison of [11C]UCB-J and [18F]FDG PET in Alzheimer’s disease: a tracer kinetic modeling study. Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures. Alzheimer’s disease biomarkers and their current use in clinical research and practice
[137] The emerging role of artificial intelligence in neuropathology: Where ... — For instance, DL models applied to digital pathology can help distinguish between various tumor grades and identify rare pathologies, ensuring early and accurate diagnoses .In the field of neuroimaging, AI-enhanced analysis of MRI and CT scans facilitates the early detection of neurodegenerative diseases and the pre-operative prediction of tumor biology of meningiomas . The incorporation of molecular features such as IDH mutation and 1p/19q co-deletion status into the WHO grading of gliomas, along with the growing availability of individualized tumor genetic data, makes AI a helpful tool for pathologists in interpreting large, multiparametric data sets to establish diagnoses 42, 43, 44, 46. Rowe, K.M. Kurian, J.A.R. Nicoll, C. MacDonald, L.H. Peng, M.B. Amin, A.J. Evans, A.R. Sangoi, C.H. Mermel, J.D. Hipp, M.C. Stumpe
[140] The molecular landscape of neurological disorders: insights from single ... — Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a particularly powerful tool, enabling the understanding of cellular heterogeneity and gene expression profiles at an unprecedented resolution . ScRNA-seq single-cell RNA sequencing, DAM disease associated microglia, SPP1 secreted phosphoprotein 1, IGF1 insulin-like growth factor 1 , for instance, used scRNA-seq to identify transcriptional changes associated with Alzheimer’s disease (AD), revealing alterations in gene expression within specific cell types involved in neuronal function and immune response. employed scRNA-seq to identify disease-associated cell types in amyotrophic lateral sclerosis (ALS), facilitating the development of potential therapeutic targets for this devastating disease.
[141] Transcriptomic diversity of cell types across the adult human brain - AAAS — Single-cell sequencing has revealed extensive cell type diversity in the entire mouse brain, as well as regions of the human brain (1-5). We performed single-nucleus RNA sequencing on tissue from across three entire human brains from male donors (Fig. 1A and Materials and methods). We aimed to sample 100 anatomically distinct locations
[152] The complexity of neuroinflammation at single-cell resolution — A new study, using a mouse model of multiple sclerosis, applied single-cell RNA sequencing to determine how immune cells in the CNS respond during inflammation. In addition to highlighting novel
[153] Neuroinflammation and neurodegeneration in human brain at single-cell ... — Single-cell and single-nucleus RNA sequencing has provided unique insight into the transcriptomic changes that occur in the brains of patients with multiple sclerosis and Alzheimer disease.
[154] Advancements in Single-Cell RNA Sequencing Research for ... - Springer — Neurological diseases are a major cause of the global burden of disease. Although the mechanisms of the occurrence and development of neurological diseases are not fully clear, most of them are associated with cells mediating neuroinflammation. Yet medications and other therapeutic options to improve treatment are still very limited. Single-cell RNA sequencing (scRNA-seq), as a delightfully
[155] Single-Cell RNA Sequencing Reveals Transcriptional Landscape of ... — Applying single-cell RNA sequencing (scRNA-seq), we constructed a comprehensive immune cell atlas of CLNs during development of EAE. Through this atlas, we concentrated on and uncovered the transcriptional landscape, phenotypic and functional heterogeneity of neutrophils, and their crosstalk with immune cells within CLNs in the neuroinflammatory processes in EAE.
[181] Integration and Extension of Specialty Mental Healthcare Services to ... — To date, the Parkinson's Foundation has led several educational initiatives that could be extended to provide the training required to support the development of integrated care programs focused on mental health and psychological well-being in PD.
[182] PDF — care that people with Parkinson's receive is often 'fragmented' resulting in delays and a suboptimal experience for patients and carers. This paper highlights the benefits of integrated working between Parkinson's clinics and Memory and Mental Health services through a 'virtual' multidisciplinary team meeting (MDT).
[183] Integration and Extension of Specialty Mental Healthcare ... - PubMed — Foundations and professional societies have played an important role in raising awareness of mental healthcare needs in PD; however, their initiatives to promote integrated or multidisciplinary care have traditionally focused on disciplines outside of mental health such as physical, occupational, and speech therapy.
[184] Integrated and patient-centred management of Parkinson's disease: a ... — People with Parkinson's disease can have moderate palliative care needs, 86 but palliation is presently unavailable for most patients.50, 51 One study showed that a 1-year multidisciplinary palliative care programme improved quality of life for patients with moderate palliative care needs, 87 emphasising the importance of training professionals
[186] Behavioral and Psychological Symptoms in Alzheimer's Disease — Abstract. Neuropsychiatric symptoms (NPS) such as depression, apathy, aggression, and psychosis are now recognized as core features of Alzheimer's disease (AD), and there is a general consensus that greater symptom severity is predictive of faster cognitive decline, loss of independence, and even shorter survival.
[200] Cognitive Behavioral Therapy for Neurological Disorders — CBT offers a tailored approach to managing the dual challenges of neurological illnesses. Using CBT for Anxiety Management in Neurological Disorders CBT is a highly effective tool for anxiety management in individuals with neurological illnesses. CBT helps patients address the mental and emotional aspects of anxiety. CBT also helps to improve their overall mental well-being. CBT is a powerful tool for depression in individuals with neurological illnesses. CBT helps individuals make lasting changes to their health by tapping into neuroplasticity. Why CBT Is a Game-Changer for Neurological and Mental Health CBT offers profound benefits for individuals with neurological illnesses. CBT also helps to manage the emotional aspects of these conditions. CBT improves the quality of life of those with neurological illnesses.
[205] (PDF) Interdisciplinary approaches for neuropathology — Notable studies investigating neurological disorders such as Autism Spectrum Disorders and Parkinson's disease are emphasized, pointing out the importance of interdisciplinary approaches in understanding and potentially intervening in neuropathological conditions.
[215] 31. Empirical Support for Interdisciplinary Interventions in ... — These emerging intervention presentations will emphasize empiricism in the context of interdisciplinary collaborations beyond psychology and psychiatry. We will conclude with a discussion on suggestions to improve and dissemination these evidence-based, yet emerging approaches to symptom management in schizophrenia spectrum illness.
[216] PDF — This interdisciplinary approach bridges basic neuroscience and clinical practice, paving the way for effective, personalized treatments and of-fering renewed hope for individuals with psychiatric disorders. Keywords: Anxiety; Depression; Schizophrenia; Neuroimaging and neurostimulation; Neural circuits; Neurotransmitter;
[217] Interdisciplinary Approaches in Psychiatric Research: From Neural ... — This editorial explores the dynamic psychiatric research field by focusing on interdisciplinary approaches to understand the complexity of mental disorders by placing particular emphasis on schizophrenia. It highlights the need to integrate findings from diverse scientific disciplines, such as neuro …
[218] Interdisciplinary Factors of Neuropathology in Schizophrenia — The role of the environmental factors in the development of schizophrenia is highlighted by studies which have been conducted on monozygotic patients affected by schizophrenia. While their genetic code is 100% similar, that is to say, entirely identical, one of the pair can be diagnosed as schizophrenic, while the other of the monozygotic pair
[219] Interdisciplinary approaches for neuropathology - Di Giovanni - 2018 ... — The 6th Mediterranean Neuroscience Society Meeting MNS 2017 MALTA was a forum to discuss modern experimental and interdisciplinary approaches that have led to important new insights on the pathogenesis and treatment of diseases of the human central and peripheral nervous systems and explore new avenues for understanding the brain.
[220] The Potential of Interdisciplinary Research to Solve Problems in the ... — For example, the combined use of such neuroimaging techniques as positron emission tomography (PET) to look at blood flow and magnetic resonance imaging to look at structures, genetic analyses, cognitive testing, and clinical trials of pharmaceutical agents to evaluate patients with schizophrenia is allowing progress toward the development of interventions for the disease.4 Continued interdisciplinary efforts in schizophrenia research—including epidemiology, genetics, structural brain abnormalities, development, behavior, and virology—should advance the understanding and treatment of the disease.
[241] Trends and Challenges in Pathology Practice - PubMed Central (PMC) — Among these are: 1) increased demand for pathology services;1 in diagnostic surgical pathology this has not only been in order to deal with the increased number of biopsies, but also to comply with guidelines for cancer case reporting2,3 and with the various recommendations of specimen handling and additional testing;4 2) the need to improve turnaround time as a critical element in clinical management;5 3) the need to comply with the statutory requirements of the various laboratory accreditation and quality assurance regulatory bodies; 4) the rising trend of subspecialisation within the clinical specialities;6 5) the introduction of the principle of multidisciplinary team meetings for the management of cancer patients;7 6) the decline in the number of autopsies; 7) the explosion in the number of rapidly evolving new techniques, and 8) advances in information technology and digital imaging.8,9
[244] Current Advancements in Digital Neuropathology and Machine Learning for ... — Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases - ScienceDirect Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases Computational neurodegenerative neuropathology represents a transformative approach in the analysis and understanding of neurodegenerative diseases through utilization of whole slide images (WSIs) and advanced machine learning/artificial intelligence (ML/AI) techniques. Recent advancements in ML/AI technologies have significantly affected image-based medical fields, including anatomic pathology, by automating disease staging, identifying novel morphologic biomarkers, and uncovering new clinical insights via multi-modal AI approaches. By addressing these challenges and leveraging cutting-edge AI techniques, computational neurodegenerative neuropathology has the potential to revolutionize the field and significantly advance our understanding of disease. For all open access content, the relevant licensing terms apply.
[247] Neuroimaging Advances in Neurologic and Neurodegenerative Diseases - PMC — Neuroimaging Advances in Neurologic and Neurodegenerative Diseases - PMC Neuroimaging tools, including magnetic resonance imaging (MRI), positron emission tomography (PET), and others (computerized tomography (CT), single-photon emission computerized tomography (SPECT), etc.) can be important biomarkers for identification, tracking, diagnosis, and treatment monitoring of neurologic diseases. Widely used in neurodegenerative disorders like Alzheimer’s disease (AD), frontotemporal lobar degeneration (FTLD), and Parkinson’s disease (PD) and associated disorders, neuroimaging methods are also applied to many other neurologic diseases to uncover important information about underlying biology, diagnostic classification, and treatment response. Finally, Brooks (2020) provides a comprehensive review of neuroimaging in PD and related disorders (such as LBD), focusing on MRI, SPECT (i.e., DATScan), and PET findings (primarily dopamine-focused and other neurotransmitter-focused tracers) .
[248] AI Neuropathologist: an innovative technology enabling a faultless ... — In this issue of Neuro-Oncology, using CNNs, Jin et al developed a quick and automatic platform named "AI Neuropathologist," which can provide an unbiased histological diagnosis on whole-slide images of hematoxylin and eosin (H&E)-stained sections. 6 This platform successfully demonstrated a patch-level accuracy of 86.5% and a patient
[249] Current Advancements in Digital Neuropathology and Machine Learning for ... — Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases - ScienceDirect Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases Computational neurodegenerative neuropathology represents a transformative approach in the analysis and understanding of neurodegenerative diseases through utilization of whole slide images (WSIs) and advanced machine learning/artificial intelligence (ML/AI) techniques. Recent advancements in ML/AI technologies have significantly affected image-based medical fields, including anatomic pathology, by automating disease staging, identifying novel morphologic biomarkers, and uncovering new clinical insights via multi-modal AI approaches. By addressing these challenges and leveraging cutting-edge AI techniques, computational neurodegenerative neuropathology has the potential to revolutionize the field and significantly advance our understanding of disease. For all open access content, the relevant licensing terms apply.
[250] The emerging role of artificial intelligence in neuropathology: Where ... — For instance, DL models applied to digital pathology can help distinguish between various tumor grades and identify rare pathologies, ensuring early and accurate diagnoses .In the field of neuroimaging, AI-enhanced analysis of MRI and CT scans facilitates the early detection of neurodegenerative diseases and the pre-operative prediction of tumor biology of meningiomas . The incorporation of molecular features such as IDH mutation and 1p/19q co-deletion status into the WHO grading of gliomas, along with the growing availability of individualized tumor genetic data, makes AI a helpful tool for pathologists in interpreting large, multiparametric data sets to establish diagnoses 42, 43, 44, 46. Rowe, K.M. Kurian, J.A.R. Nicoll, C. MacDonald, L.H. Peng, M.B. Amin, A.J. Evans, A.R. Sangoi, C.H. Mermel, J.D. Hipp, M.C. Stumpe
[251] A New Regulatory Road-Map for Alzheimer's Disease Drug Development — Given current evidence of the neuropathological-clinical efficacy gap in the emergence of AD, we expect that coordinated drug studies involving sequential clinical trials over many years will be needed for AD relevant clinical efficacy to be evidenced. We encourage regulators to consider the neuropathology-clinical efficacy gap implications.
[252] Latest Legal and Regulatory Updates in Neurodiagnostics — As technology evolves and new discoveries emerge, regulatory guidelines are updated to reflect the current best practices and improve patient care. ... Navigating Legal and Regulatory Challenges in Neurodiagnostics. While legal and regulatory updates bring valuable improvements, they can also present challenges for neurodiagnostic practitioners
[253] The challenges of regulating Neuralink and similar technologies — These devices, which aim to connect human brains directly with computers, raise complex ethical, legal, and safety concerns that existing regulatory frameworks may struggle to address adequately. Regulators must grapple with balancing potential medical benefits against risks, ensuring proper oversight of experimental procedures, and addressing privacy concerns related to brain data collection. The FDA must develop new regulatory approaches for BCIs. Current medical device regulations may not fully address the unique risks and ethical considerations of brain implants. Brain-computer interfaces (BCIs) are at the forefront of these advancements, with potential applications ranging from limb movement restoration to sensory augmentation. Responsible innovation in brain-computer interfaces requires balancing technological progress with ethical considerations. Keep Austin Well Austin on it
[254] Coalition for Effective Diagnostics Lobbies for LDT Reform Bill — WASHINGTON - The Coalition for Effective Diagnostics has called on House and Senate leaders to enact a comprehensive diagnostic testing reform package to tailor the US Food and Drug Administration (FDA) regulatory oversight of laboratory-developed tests (LDTs). The new coalition that includes the College of American Pathologists (CAP