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Theme Issue:
Innovations in Neuroimaging
The field of neuroimaging is undergoing transformative growth, driven by rapid advances in imaging technologies, computational methods, and clinical applications. This theme issue highlights cutting-edge developments ranging from ultra-high-field MRI and advanced PET tracers to machine learning–enhanced image analysis.
Emerging approaches in multimodal imaging are offering unprecedented insights into brain connectivity, neurodegeneration, and functional dynamics. Contemporary challenges such as data standardization, integration of big data, and clinical translation are addressed through diverse perspectives that bridge neuroscience research and patient care.
Real-time imaging innovations are reshaping intraoperative guidance and treatment monitoring, while novel biomarkers are accelerating early detection of neurological disorders. Ethical considerations around data privacy, accessibility, and responsible AI use underscore the importance of patient-centered approaches in this evolving field.
Collectively, these contributions illustrate how the convergence of technology, computation, and clinical practice is redefining the landscape of modern neuroimaging.
This theme issue was organized in collaboration with the Neurodegenerative Disease Committee.
Contents
Research Article
Real-Time Alzheimer's Detection using Deep Vision Models
Alzheimer’s disease is a progressive neurodegenerative condition that leads to cognitive decline, memory loss, and ultimately loss of independence. Early detection of Alzheimer’s disease is essential for timely intervention, but traditional diagnostic tools often fall short due to their reliance on manual evaluation and limited sensitivity. This study introduces a novel application of the latest advancement in real-time object detection framework to detect and localize biomarkers of Alzheimer’s disease using structural brain magnetic resonance imaging data.
By Yashwanth Reddy Akkidi, Wisam Bukaita, PhD - Lawrence Technological University
Research Article
Deciphering Signals of Imaging Techniques based on an Old Paradigm of Energy Metabolism Could Lead to Misunderstanding of Brain Function
The sequence of the enzymatic reactions of glycolysis, the first biochemical pathway to be elucidated, was revealed in 1940. Today, eighty-five years later, this pathway is still displayed in textbooks, academic courses and online platforms unchanged from its original representation, despite major discoveries that question its accuracy. The dogmatic division of the pathway into aerobic and anaerobic glycolysis, each producing a different end-product, pyruvate or lactate, respectively, a concept that has been debunked, is continuing to be taught and used unchanged. As a result, the term “aerobic glycolysis” continues to imply an inefficient energy production that ends with lactate, despite the presence of oxygen.
By Avital Schurr - Department of Anesthesiology and Perioperative Medicine, University of Louisville School of Medicine, Louisville, KY 40202, USA
Research Article
Bridging Imaging and Molecular Biomarkers in Trigeminal Neuralgia: Toward Precision Diagnosis and Prognostication in Neuropathic Pain
Despite advances in imaging and clinical assessment, current diagnostic paradigms lack precision needed to subcategorize disease or predict therapeutic response with accuracy. This review proposes precision neuropathic pain diagnostics through the combination of artificial intelligence-guided imaging and molecular biomarker identification, using the use-case of Trigeminal neuralgia (TN), a refractory craniofacial pain disorder characterized by paroxysmal, one-sided facial pain and variable treatment response. We use trigeminal neuralgia as a case example to explore how deep learning, advanced imaging, and molecular profiling can work together to improve the diagnosis and treatment of neuropathic pain.
By Matthew Abikenari, M.S., Bhav Jain, B.S., Michael Lim, M.D.—Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA ; Risheng Xu, M.D, Ph.D., Christopher Jackson, M.D., Judy Huang, M.D., Chetan Bettegowda, M.D, Ph.D.—Department of Neurosurgery, John Hopkins University School of Medicine, Baltimore, Maryland, USA
Research Article
Diagnostic Accuracy of Phase Contrast MRI Technique in Detecting Cerebrospinal Fluid Flow
Phase contrast – Magnetic resonance imaging is a valuable tool for assessing cerebro-spinal fluid flow dynamics, providing critical insights into the pathophysiology of neurological conditions. The study highlights the importance of peak velocity as a reliable metric, suggesting its incorporation into routine clinical assessments to enhance diagnostic accuracy and patient outcomes.
By Dr. Sachin Khanduri, Dr. Danish Ansari, Dr. Kunal Dwari, Dr. Avani Kanojia, Dr. Vinima Jaiswal, Dr. Nida Yasrab, Dr. K. Prithvi Perumal, Dr. Sajida Ansari - Department of Radiodiagnosis, Era’s Lucknow Medical College & Hospital, Lucknow, India
Research Article
THE 3-D Pictorial Spirochetal Pathway to Alzheimer’s Disease
This perspective article features a visual depiction supporting a potential link between spirochetal infection and Alzheimer’s disease (AD). Two-dimensional (2D) images, alongside innovative three-dimensional (3D) imaging derived from 2D photomicrographs, provide the basis for a pathway through which spirochetes travel to the brain, with the hippocampus identified as their initial target. Upon arrival at this specific region, spirochetes can be found both extracellularly and intracellularly.
By Herbert B. Allen, MD - Department of Dermatology, Drexel University College of Medicine, Philadelphia, PA, USA Dermatology, Eastern Virginia Medical School, Norfolk, VA, USA Rowan School of Osteopathic Medicine Geriatrics and Gerontology, Stratford, NJ, USA; Judith Miklossy, MD, PhD - International Alzheimer Research Centre, Prevention Alzheimer International Foundation Martigny-Croix, Switzerland
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