Written By Yumna Fatima Dar
1.1 Introduction
In the intricate tapestry of the human experience, the brain stands as the orchestrator of our thoughts, emotions, and actions. Yet, within its intricate folds also lie the shadows of neurological diseases and disorders that can disrupt the harmony of our lives. The pursuit of understanding, diagnosing, and monitoring these conditions has given rise to an era of scientific innovation that peers deep into the enigmatic realms of the brain.
1.2 Article Structure at a Glance
This article embarks on a journey into the forefront of neurological science, exploring the remarkable strides made in unraveling the complexities of diagnosing and monitoring neurological diseases. This article will discuss various neuroimaging techniques, explore the concept of biomarkers, detail how advances in genetic sequencing are illuminating the genetic basis of disorders, highlight the emergence of neuroinformatics, address the ethical challenges associated with the diagnosis of neurological diseases and discuss the potential future advancements in this field.
2.1 Neuroimaging: Peering into the Brain’s inner workings
The central (CNS) and peripheral (PNS) nervous systems' micro- and macro-components can be represented visually in imaging studies of neurosciences with the goal of examining their morphology and function, providing a diagnosis and prognosis for neurological diseases, and tracking treatment outcomes. Ex vivo microscopic viewing of single-neuron morphology or gene/protein expression in nervous system tissues is included, in addition to a wide range of in vivo methods including the common Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET). With the development of novel diagnostic methods and biomarkers as well as deeper neuroanatomical inquiry, the relationship between genetic changes and disease consequences, and other critical scientific concerns, neuroimaging applications have advanced quickly in recent years.(1)Traditional methods like magnetic resonance imaging (MRI) and computed tomography (CT) scans provide detailed anatomical information, but newer technologies like functional MRI (fMRI), positron emission tomography (PET), and diffusion tensor imaging (DTI) offer insights into brain activity, metabolism, and connectivity.(1)
Fig-1: Neuroimaging techniques in the diagnosis of Alzheimer’s Disease. (2)
2.2 Biomarkers: The Clues Hidden within Body Fluids
Biomarkers are molecules found in blood, cerebrospinal fluid, or other bodily fluids that can indicate the presence or progression of a disease. The identification and analysis of neurological disease biomarkers are transforming diagnostics. A variety of pathological illnesses can be accurately diagnosed using biomarkers, which are biological indicators of damage or disease. (1) Several proteins produced by neurons or astroglial cells have been suggested as possible biomarkers for Traumatic Brain Injury. These proteins include S100B, glial fibrilary acidic protein (GFAP), myelin basic protein (MBP), neuron-specific enolase (NSE), and the BB isozyme of creatine kinase (CK-BB, which predominates in the brain). These biomarkers may be useful as substitute indicators in clinical studies due to their presence in the cerebrospinal fluid and serum of patients with moderate-to-severe Traumatic Brain Injury and their connection with outcome. Additionally, several of these markers have been discovered to be sensitive indications of damage, therefore they may have the potential to diagnose persons with mild Traumatic Brain Injury.(3) The creation of blood-based biomarkers has been a significant advancement in the field of neurology. Due to the physical limitations imposed by the blood brain barrier, peripheral markers initially caused skepticism. However, recent technology advancements have made it feasible to monitor analytes in various biofluids at extremely low concentrations. The majority of the new equipment are based on mass spectrometry or SIMOA, which offer the best analytical sensitivity. The ability to measure neurofilaments in blood as a marker of neuronal damage in a variety of neurological conditions, including neurodegenerative diseases, multiple sclerosis, traumatic brain injury, peripheral neuropathies, and COVID-19 neurological-associated damage, represents a significant advancement in the field. Promising research is being done in the new discipline of liquid biopsy, which examines circulating biomarkers. Researchers are working to create sensitive techniques to detect disease-specific molecules in blood samples, potentially allowing for non-invasive and early diagnosis of conditions like Parkinson's and Huntington's diseases.(4)
Fig-2: Biomarkers for Neurodegenerative and Neurological Diseases. (5)
2.3 Neurogenetics: Decoding the Genetic Basis of Neurological Disorders
Clinical neurogenetics focuses on the diagnosis, management, and follow-up of people and families who have (monogenic or genomic) genetic conditions with primary symptoms that are developmental delay-related, secondary to central or peripheral nervous system degeneration or dysfunction, or both.(6) Unprecedented insights into the genetic alterations and expression patterns linked to diseases like ALS, muscular dystrophy, and hereditary neuropathies are being made possible by technologies like whole-genome sequencing and single-cell RNA sequencing. In addition, the creation of gene-editing technologies like CRISPR-Cas9 holds the promise of correcting defective genes, providing a ground-breaking method of treating hereditary neurological illnesses. Although these methods are still in their infancy, they hold promise for developing tailored treatments that might deal with the underlying causes of many disorders. (7)
2.4 Neuroinformatics: Data-Driven Insights
It has been estimated that day-to-day error rates and discrepancies in radiology are greater than 3%–5%. (8) As more computational power has been available and the medical data quality increased, the interest in employing advanced algorithms in the diagnosis of neurological diseases has increased. Hence, the use of Artificial Intelligence (AI) techniques has received growing interest in the field of brain imaging and computational neurosciences over the last decade. The influx of data from neuroimaging, genetics, and biomarker studies has led to the emergence of neuroinformatics, a field that combines neuroscience with data science. (9) Advanced algorithms and machine learning models are being developed to mine this vast data trove, enabling researchers to identify patterns, make predictions, and even develop personalized treatment strategies. In the realm of neurological diseases, these techniques are being used to create predictive models that can forecast disease progression, aiding in treatment decisions and patient management. Additionally, neuroinformatics plays a pivotal role in uncovering subtle biomarker signatures that might otherwise go unnoticed.
Fig-3: The Working of Neuroinformatics. (10)
2.5 Telemedicine and Wearable Technology: Monitoring in Real Time
Telemedicine and Wearable Technology have emerged as transformative tools in the monitoring of neurological diseases and disorders, revolutionizing the landscape of patient care and management. According to a study published in the "Journal of Telemedicine and Telecare," telemedicine has shown remarkable potential in enhancing access to specialized neurological care, particularly for individuals residing in remote or underserved areas. (10) Through secure video consultations, neurologists can remotely assess patients' symptoms, provide guidance, and adjust treatment plans, eliminating the barriers of geographical distance. Complementing this approach, wearable technology has gained momentum as an invaluable asset. Statistics from the "Journal of Medical Internet Research" reveal that the global market for wearable medical devices is projected to reach $18.2 billion by 2025. These wearables, ranging from smartwatches to EEG headsets, collect real-time data on various physiological parameters, movement patterns, and even brain activity. For instance, in the realm of neurological disorders such as epilepsy, wearable EEG devices can record and transmit data on seizure activity, enabling accurate diagnosis and timely intervention. Additionally, wearables equipped with motion sensors aid in monitoring the motor fluctuations of Parkinson's disease patients, facilitating personalized medication adjustments. This integration of telemedicine and wearable technology not only empowers patients with continuous monitoring but also provides healthcare providers with comprehensive insights for informed decision-making. As these technologies continue to evolve, the synergy between telemedicine and wearables holds the promise of improved patient outcomes and a more proactive approach to managing neurological conditions. (11)
Fig-4: Telemedicine and Wearable Technology for monitoring Neurological Conditions. (12)
3.1 Conclusion
In conclusion, the field of diagnosis and monitoring of neurological diseases and disorders stands at the threshold of a remarkable transformation. The strides made in neuroimaging technologies, biomarker discovery, genetics, data-driven insights, and wearable technology have paved the way for a new era of personalized and proactive healthcare. As we journey through the intricate landscapes of the brain, we find ourselves armed with an arsenal of innovative tools that empower us to detect, understand, and manage these conditions in ways previously unimaginable.
References
Biomarkers in neurological disorders: a fast-growing market Brain Communications, Volume 3, Issue 2, 2021, Oxford Academic.
Biomarkers for neurodegenerative diseases www.nature.com
Imaging Techniques in Alzheimer’s Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring. International Journal of Molecular Sciences International Journal of Molecular Sciences
Neuroimaging Applications for Diagnosis and Therapy of Pathologies in the Central and Peripheral Nervous System https://www.ncbi.nlm.nih.gov/
Neuroimaging and early diagnosis of Alzheimer disease: a look to the future JR Petrella, RE Coleman, PM Doraiswamy - Radiology, 2003 - pubs.rsna.org
https://www.frontiersin.org/journals/neuroinformatics
Artificial intelligence for brain diseases: A systematic review https://www.ncbi.nlm.nih.gov/
The future: Biomarkers, biosensors, neuroinformatics, and e-neuropsychiatry CR Lowe - International Review of Neurobiology, 2011 - Elsevier
Diagnostic reasoning in neurogenetics: a general approach https://www.ncbi.nlm.nih.gov/
Bringing together data-and knowledge-driven solutions for a better understanding and effective diagnostics of neurological disorders nih.gov
Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases https://www.mdpi.com/
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