All Articles

ZhiGang Cao^*, Mi Yang

Department of Neurology, Sichuan Taikang Hospital, Chengdu, Sichuan, China

Objective: This meta-analysis of randomized controlled trials (RCTs) examines the effects of repetitive transcranial magnetic stimulation (rTMS) on cognitive function in elderly patients (aged 55 or older) and identifies potential influencing factors.

Methods: Searches of Embase, Web of Science, Cochrane Library, PubMed, CNKI, and Wanfang identified RCT studies evaluating the Impact of rTMS on cognition in older adults. The search spanned the period from the database's inception to 15 December 2024. Following the study identification and data extraction by two independent reviewers, the risk of bias was assessed with the Cochrane RoB tool. Data synthesis and subgroup analysis were performed via SMD, WMD, and 95% CIs to evaluate the effects of rTMS and its influencing factors. The review protocol was prospectively registered in PROSPERO (CRD42020187336)

Results: A total of 13 studies, including 14 trials with 655 patients, were analyzed. Compared to the control group, real rTMS significantly improved cognition in elderly patients (Global Cognitive Function: SMD, 0.56;95% CI 0.33,0.79; p<0.0001; MMSE: WMD,2.04;95% CI 1.54,2.53; p<0.0001; ADAS-Cog: WMD, -2.59;95% CI -3.63, -1.54; p<0.0001; MoCA: WMD,2.46; 95% CI 1.47, 3.45; p<0.0001). Subgroup analysis revealed that participants receiving rTMS combined with cognitive training demonstrated more significant improvements than those receiving rTMS alone (WMD: 0.51; 95% CI: 0.26,0.76; p < 0.0001). Additionally, other subgroup analyses—including rTMS stimulating sites (multiple vs. single sites), education years (≥10 vs. <10 years), and rTMS frequency (5/10/20 Hz vs. iTBS (intermittent theta-burst stimulation)—showed no significant differences (p > 0.05).

Conclusion: Both standalone rTMS and rTMS combined with cognitive training—which varied across studies and included both computerized paradigms (face-name associative memory training, mirror neuron system therapy, VR interactions) and individualized one-on-one training—demonstrated significant efficacy in improving global cognitive function in elderly patients with mild to moderate symptoms. As a safe and well-tolerated intervention, rTMS demonstrates considerable potential for reliable clinical application.

Aditi Mohan^*, Kalam Singh Butola

Veer Chandra Singh Garhwali Government Institute of Medical Sciences and Research, Uttarakhand, India

Scrub typhus is an infectious rickettsial disease caused by the bacterium Orientia tsutsugamushi, transmitted through the bite of chigger mites. This illness can manifest in various ways, ranging from a simple tropical fever to complex multi-organ dysfunction, encompassing acute liver failure, renal failure, acute respiratory distress syndrome, myocarditis, septic cardiomyopathies, secondary hemophagocytic lymphohistiocytosis (HLH), and disseminated intravascular coagulation (DIC) among others. While neurological complications can arise in scrub typhus, the exact frequency remains uncertain. One rarely reported neurological complication associated with this condition is cerebellitis.

In this specific case report, we detail the clinical experience of a 25-year-old woman who presented with fever and substantial cerebellar dysfunction and was diagnosed with scrub typhus based on serological test ,specifically an IgM enzyme-linked immunosorbent assay (ELISA) blood test. Notably, her MRI scan and blood investigations revealed no abnormalities, and she responded well to antimicrobial and steroid therapy, ultimately experiencing a full recovery without any complications.

Danica F. Patton-Parfyonov, Thomas J. Kelley^*

Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA

New therapies in cystic fibrosis (CF) have made a significant impact on the overall health of people with CF (pwCF). Because of the success of these therapies, it is anticipated that lifespans of pwCF will significantly increase. For the first time, the impacts of aging with CF need to be considered. Until now, relatively little has been done to evaluate neurological health in pwCF. In this review, we consider evidence for a potential prevalence of neurodegenerative disease in CF including our recent study examining tauopathy in an aged CF mouse model.

Betelhem Molla Dumessa^1*, Tsion Haile Woldemariam^2*, Mohammed Kedir Shukri¹, Mihiret Legese Nadew¹, Kalkidan Molla Tegegne², Mahlet Minwuyelet Dagne², Asonya Abera Akuma², Melat Teklegiorgis Biru¹

¹Saint Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia

²Arba Minch University College of Medicine and Health Sciences, Arba Minch, Ethiopia

Background: Ischemic stroke is a major global cause of morbidity and mortality, disproportionately affecting low- and middle-income countries. Hemorrhagic transformation (HT) is a frequent and serious complication of acute ischemic stroke, occurring in 3.2% to 43.3% of patients and associated with increased mortality. Identifying predictors of HT is essential to improving patient outcomes.

Objective: To determine clinical and demographic predictors of hemorrhagic transformation in acute ischemic stroke patients admitted to three major hospitals in Addis Ababa, Ethiopia.

Methods: A retrospective case-control study was conducted on 270 adult inpatients with acute ischemic stroke at Saint Paul Hospital Millennium Medical College, Zewditu Memorial Hospital, and Tikur Anbessa Specialized Hospital between June 2019 and July 2022. Data were analyzed using SPSS version 26.0. Bivariate and multivariate logistic regression analyses identified associations between HT and potential predictors. Statistical significance was set at p < 0.05.

Results: The mean age was 61.2 years, with 37.8% aged 61–70 years. History of diabetes mellitus increased the risk of HT by 5.4 times (AOR=5.4, 95% CI: 2.35–12.31, p<0.001), and stress hyperglycemia increased risk by 12.2 times (AOR=12.2, 95% CI: 2.30–65.12, p=0.003). Previous stroke or transient ischemic attack raised risk 3.7-fold (AOR=3.7, 95% CI: 1.57–8.86, p=0.003). Warfarin therapy was associated with a 13.1-fold increased risk (AOR=13.1, 95% CI: 6.91–131.62, p<0.001), and concurrent use of multiple anticoagulants increased risk 3.8-fold (AOR=3.8, 95% CI: 1.55–9.57, p=0.004).

Conclusion: Anticoagulant therapy, stress hyperglycemia, prior stroke, and diabetes mellitus are significant independent predictors of hemorrhagic transformation in acute ischemic stroke. Emphasizing guideline-based management and addressing modifiable risk factors may reduce HT incidence and improve outcomes.

Tapasi Roy^1*, Snehasikta Swarnakar²

¹Acharya Jagadish Chandra Bose College, Kolkata, West Bengal, India

²CSIR-Indian Institute of Chemical Biology, Infectious Diseases and Immunology Division, Kolkata, West Bengal, India

Parkinson’s disease (PD) is a frequently occurring neurodegenerative condition. The onset of the disease is due to selective loss of dopaminergic neurons, causing increased dopamine (DA) in the neuronal microenvironment. Neurotoxicity due to such increased DA is the outcome of reactive oxygen species (ROS) and oxidative products of DA. Proteins like alpha-synuclein, ubiquitin carboxyl-terminal hydrolase L1 (UCHL1), Cofilin and matrix metalloproteinases 9 (MMP9) are few known key regulators in PD. The impact of elevated DA on these protein-protein interactions plays a crucial role in disease progression. Further, DA toxicity leads to alteration of protein-protein interactions and degrades neuronal cytoskeleton, leading to cell death. This review suggests a novel arena in PD treatment by targeting DA altered protein-protein interactions.

Alireza Hedayatfar

Eye Research Center, The Five Senses Institute, Rassoul Akram Hospital, Iran University of Medical Sciences, Tehran, Iran

Diana Fishbein

Frank Porter Graham Child Development Institute, University of North Carolina-Chapel Hill, NC, USA

This commentary by a patient describes a syndrome that often develops residual to chemotherapy and yet escapes timely detection and effective treatment: chemo-induced peripheral neuropathy (CIPN). Physicians and their patients who suffer from CIPN, particularly those with unremitting small fiber neuropathy (SFN), may benefit from the evidence-based guidance provided. The author also calls for deeper listening by the medical community, interdisciplinary collaboration and patient self-advocacy.

Gunjan Jindal^1,2, Poonam Bharti³, Amit Shrivastava^4*, Shiva Kumar³, Sopan Ganeshrao Dod⁴, Preeti Garg⁵

¹Department of Radiology, MMIMSR, Mullana, India

²University of Calgary, Alberta, Canada

³Department of Psychiatry, MMIMSR, Mullana, India

⁴Department of Radiology, MMIMSR, Mullana, India

⁵Department of oral medicine and radiology, MM college of dental sciences, Mullana, India

Background: Diffusion Tensor Imaging (DTI) is a novel MRI technique developed for measuring the integrity of white matter and its structural connectivity within the brain. DTI captures the movement of water molecules along the neural pathways, providing valuable information on the micro-structural changes that are associated with particular neurological disorders.

Methods: This paper examines some of the concepts related to DTI and its particular indices such as fractional anisotropy (FA) and mean diffusivity (MD). DTI scanning protocols and post-processing modifications are evaluated in the context of white matter tracts abnormalities detection.

Results: The results show how DTI can reveal changes in white matter lesions which could not be perceived using routine MRI techniques. Changing values of FA and MD are associated with the level of disease progression and cognitive deficit.

Conclusion: DTI is a powerful tool for investigating white matter integrity and diagnosing neurological disorders. While it offers significant advantages in neuroimaging, further advancements in imaging acquisition and analysis techniques are needed to improve reliability and clinical utility.

Abdullah Emre Taçyıldız¹*, Melih Üçer²

¹Department of Neurosurgery, Karabük University Faculty of Medicine, Karabük, Turkey

²Department of Neurosurgery, Biruni University Faculty of Medicine, Istanbul, Turkey

Objective: This study aims to analyze the limitations of human visual perception, compare them with the visual adaptations of other species, and explore how technological advancements—such as artificial intelligence, medical imaging, and augmented reality—have improved medical diagnostics and surgical precision.

Methods: A structured literature review was conducted, incorporating comparative analyses of visual perception across species, including frogs, dragonflies, and humans. The study evaluated the role of advanced imaging technologies, artificial intelligence-based diagnostics, and digital image processing tools in overcoming the limitations of biological vision. Selection criteria for species comparisons were based on functional adaptations and their relevance to medical imaging applications.

Results: Findings indicate that species-specific visual adaptations are optimized for survival rather than accuracy. Human vision, while advanced, is inherently constrained by physiological and neurological limitations. However, medical imaging technologies, including fluorescence-guided surgery, histology, and AI-assisted diagnostics, have significantly enhanced the precision of visual interpretation in clinical settings. The integration of computational tools, such as Adobe Photoshop for forensic and radiological analysis, further refines image accuracy and medical decision-making.

Conclusion: The interplay between biological vision and technological advancements underscores the necessity of integrating artificial intelligence and advanced imaging in medical practice. Future research should focus on optimizing these technologies to further enhance diagnostic accuracy, surgical precision, and clinical outcomes, ultimately pushing the boundaries of human visual perception.

Ilya Adamchic

Department of Radiology, Vivantes Hospital im Friedrichshain, Berlin, Germany

Intracranial aneurysms (IAs) pose a significant public health challenge due to their potential for rupture and associated morbidity and mortality. Despite advancements in imaging technologies such as magnetic resonance angiography (MRA) and computed tomography angiography (CTA), detecting small, incidental IAs remains challenging, particularly amid increasing global imaging volumes and resource constraints. Artificial intelligence (AI) has emerged as a transformative tool in medical imaging, demonstrating potential to enhance diagnostic accuracy and efficiency. Deep learning models, particularly convolutional neural networks (CNNs), have shown near-expert accuracy in detecting subtle aneurysmal features, enabling early diagnosis and improving clinical workflows. AI-driven approaches extend beyond detection to include rupture risk assessment, predictive diagnostics, and treatment planning, thereby improving patient-specific care and reducing unnecessary interventions.

However, challenges such as false-positive rates, ethical considerations, and the need for robust validation studies hinder AI adoption in clinical practice. This review contextualizes recent advancements and the findings of Adamchic et al. (2024), within the broader landscape of AI applications in IA diagnostics. It discusses AI’s role in addressing diagnostic variability, mitigating radiologist workloads, and enhancing reproducibility, particularly for junior clinicians. The article also explores barriers to widespread implementation, including data safety, algorithm transparency, and financial constraints, while emphasizing the need for collaborative efforts to refine AI models and integrate them seamlessly into radiology workflows. By addressing these challenges, AI has the potential to revolutionize intracranial aneurysm management, improving patient outcomes and transforming modern radiology practices.

Huma Ikram

Neurochemistry and Biochemical Neuropharmacology Research Unit, Department of Biochemistry, University of Karachi, Karachi, Pakistan

Nanomedicine is going to be a novel and different avenue of therapy for the neurological patients, overcoming blood-brain barrier difficulties while also addressing the unique complexity of neurological diseases. With applications of nanoparticles, including liposomes, dendrimers, exosomes, and polymeric nanoparticles, effective drug delivery will be possible via targeted and controlled release and reduced adverse effects. These technological breakthroughs are going to be of great help in the treatment of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's, and in conditions like multiple sclerosis. Because of this, nanomedicine has a great promise in the field of neuroinflammatory conditions as well. In addition, nanomedicine is going to play a significant role in precision medicine, where therapies can be planned according to the genetic, molecular, and biological makeup of the patients. However, precision in diagnosis and monitoring will also provide a personalized treatment regimen as nanotechnology can be integrated with other advanced diagnostic technologies like MRI, PET, and biomarker detection. Although it has a lot of promise, clinical translation has not avoided the same problems that have proved to be highly disconcerting for so many developments in nanomedicine, including issues of biocompatibility, safety, and, in the case of some products, regulatory approval. Addressing these factors will prove critical for the successful embedding of nanomedicine into the routine neurological care system. This review touches on the current status of nanomedicine in neurology, the promise that it holds for precision treatments, and the barriers that apply to its ability to effect real clinical practice portrayals, thereby providing an insight into the future of personalized therapy in neurology.

Vivian S. Nguyen^1*, Griffin J. Young², Adil Javed¹, Timothy J. Carroll²

¹Department of Neurology, The University of Chicago, Chicago, IL, USA

²Department of Radiology, The University of Chicago, Chicago, IL, USA

MRI has long been a critical tool for diagnosing and monitoring Multiple Sclerosis (MS). Conventional MRI employed in clinical practice is non-parametric, which disallows quantitative measures of tissue damage. This creates an unmet need to develop a post-acquisition image processing algorithm that can convert a qualitative image into a corresponding quantitative map. We present a methodology that can convert a clinically routine T1-weighted MPRAGE image into a parametric T1 map with high accuracy and precision in relation to a commonly used T1 mapping reference standard. We evaluate the methodology’s performance in Multiple Sclerosis for the purpose of quantifying tissue damage primarily in lesions and secondarily in white matter and gray matter regions.

Liping Wu, Tao Lv^*

The People’s Hospital of Deyang, North Taishan Road, Deyang, Sichuan, China

As of now, there are increasing cases related to oculogyric crisis (OGC), mainly focusing on clinical manifestations. The pathogenesis of OGC is still uncertain, and there is no unified treatment protocol. This review aims to explore the treatment and management strategies for OGC based on existing cases, hoping to provide references for clinicians in identifying and treating OGC in practice.

Andressa Gonçalves Rodrigues-Fândhrs¹, Bruna Kulmann-Leal¹, José Artur Bogo Chies^2*

¹Postgraduate Program in Genetics and Molecular Biology (PPGBM), Universidade Federal do Rio Grande do Sul – UFRGS, Porto Alegre, Brazil

²Laboratory of Immunobiology and Immunogenetics, Department of Genetics, Federal University of Rio Grande do Sul – UFRGS, Porto Alegre, Brazil

Huitong Ding^1,2*, Sanskruti Madan¹, Rhoda Au^1,2,3,4,5,6, P. Murali Doraiswamy⁷, Chunyu Liu^2,8

¹Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

²The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

³Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA

⁴Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

⁵Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

⁶Departments of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

⁷Neurocognitive Disorders Program, Departments of Psychiatry and Medicine, and the Duke Institute for Brain Sciences, Duke University School of Medicine, Durham, NC, USA

⁸Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

Accumulating evidence suggests that reproductive markers, such as age at menarche, are associated with cognitive function and the risk of developing Alzheimer's disease (AD). These reproductive markers offer promising potential for predicting the risk of AD, underscoring the necessity for sex-specific considerations in understanding and managing this neurodegenerative disorder. This review first discusses recent findings on reproductive markers in AD progression, and further points out the direction for future research to unravel the complex interplay between reproductive health and cognitive health. We advocate for the incorporation of sex heterogeneity into AD precision medicine to tailor sex-specific diagnostic and intervention approaches.

Hirotaka Nomiya¹, Masami Yamada^1,2*

¹Department of Cell Biology and Biochemistry, Division of Medicine, Faculty of Medical Sciences, University of Fukui, Matsuoka Shimoaizuki, Eiheiji-cho, Yoshida-gun, Fukui, Japan

²Life Science Innovation Center, University of Fukui, Bunkyo, Fukui-City, Fukui, Japan

The interactions between genetic and environmental factors (G x E interactions) play a crucial role in the pathogenesis of schizophrenia. The administration of phencyclidine, a psychotropic drug, to Kpna1-deficient mice induces behavioral abnormalities resembling schizophrenia. In the nucleus accumbens of these mice, the expressions of dopamine receptors, an RNA editing enzyme, and cytoplasmic dynein demonstrate gene-environment interaction-dependent alterations. Kpna1-deficient mice may be useful as a gene-environment interaction model for schizophrenia and provide insights into its pathogenesis. Further, changes in gene expression in the nucleus accumbens may be involved in the development of schizophrenia.

Dr. Robert W Baumhefner

Neurology Service, Veterans Administration West, Los Angeles Healthcare Center, Los Angeles, CA, USA;

Sarah Kawtharani¹, Elias Horanieh², Bader Ali³, Mohammad Housheimy¹, Houssein Darwish^1*

¹Department of Neurosurgery, American University of Beirut Medical Center, Beirut, Lebanon

²Department of Surgery, University of Balamand, Beirut, Lebanon

³Medical Student, University of Balamand, Beirut, Lebanon

Background: Contrast Induced Encephalopathy is a known but rare complication of endovascular procedures. Patients show neurologic symptoms mimicking a stroke and include visual disturbances, motor or sensory deficits, headache, seizures, memory loss, confusion, aphasia, and coma. Irreversible neurological symptoms are rare and fatal encephalopathy is even more so.

Case Report: In this article we present a case of a 75-year-old female patient who showed neurological symptoms mimicking a stroke post cerebral Digital Subtraction Angiography that was done with Iohexol as a contrast agent, as a diagnostic work up to rule out a ruptured aneurysm. Further investigations showed no arterial spasms nor dissection. Symptoms reappeared after the second contrast administration but completely resolved after the administration of steroids and fluids.

Conclusion: Contrast Induced Encephalopathy should be further investigated with imaging to rule out other thromboembolic or hemorrhagic causes. Treatment via the administration of steroids and fluids have shown to be effective with complete remission of symptoms.

Fumiaki Iwane^1*, Brian Johnson², Leonardo G Cohen¹

¹Human Cortical Physiology and Neurorehabilitation Section, NINDS, NIH, Bethesda, MD, USA

²Department of Occupational Therapy, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA

Itzhak Kurek^*, Jean-Christophe Quillet, Michael Siani-Rose

Cannformatics, Inc., San Francisco, CA, USA

Autism spectrum disorder (ASD) is a group of lifelong heterogeneous neurodevelopmental conditions with a wide range of severity levels that affect social communication and social interaction. Diagnosis of ASD relies on subjective observation of these clinical phenotypes. The growing body of big data generated by subjective methods and more recently by objective high-throughput technologies such as omics for the detection of biomolecules, is being successfully applied to a rapidly-growing number of machine learning (ML) algorithms to inform research for diagnostics and interventions for patients with ASD. While most reviews in this area are focused on the ML approaches, we highlight the impact of the database on the expected outcomes in ML-based ASD research studies.

Martina von der Bey^1,2, Ebru Ercan-Herbst^1*

¹BioMed X Institute, Im Neuenheimer Feld, Heidelberg, Germany

²Molecular and Translational Neuroscience, Department of Neurology, Ulm University, Albert-Einstein-Allee, Ulm, Germany

One of the biggest challenges in the field of neurological disorders is the limited availability of freshly dissected human brain tissue. Therefore, the use of human induced pluripotent stem cells (hiPSCs) is important to develop human brain-like models to study the interaction of different brain cell types in health and disease. For physiologically relevant disease modeling, three-dimensional (3D) cell culture systems are of great importance because they provide a more representative in vivo-like micro-environment to the cells. The field of 3D cell culture systems using diverse hiPSC-derived cells is growing and gets steadily advanced. However, to this day, there is no cell culture model available that includes all brain cell types. Here, we review the latest improvements of 3D hiPSC-based cell culture systems in the field of neuroscience. We focus on innovations for the generation of neurons, astrocytes, oligodendrocytes, microglia as well as endothelial cells and pericytes.

Robert B. Slocum

Narrative Medicine Program Coordinator, University of Kentucky HealthCare, Lexington, Kentucky, USA

Neda Jafri¹, Savanna Dasgupta¹, James E. Siegler^1,2*

¹Cooper Neurological Institute, Cooper University Health Care, Camden, NJ, USA

²Cooper Medical School of Rowan University, Camden, NJ, USA

Endovascular thrombectomy (EVT) revolutionized the treatment for acute ischemic stroke due to large vessel occlusion (LVO). Current guidelines published by multiple academic societies recommend EVT for eligible patients who present within 24 hours of the time last seen well. However, more recent data suggests that extending this window past 24 hours produces more favorable outcomes in specific patients presenting with anterior circulation LVO. More specifically, recent observational data indicates a higher probability of functional independence, functional improvement, and long-term survival with EVT when compared to best medical management. Based on the available data, there is unclear equipoise in randomizing all patients with acute ischemic stroke due to LVO to EVT or medical management. However, for those patients with large established infarction, distal occlusions, or well beyond the 24-hour window, randomized clinical trials are called upon to determine whether there is benefit of EVT in these patient groups. In this narrative review, we will summarize the most recent data on EVT in the ultra extended window (>24 hours after time last seen normal) and discuss further considerations of this treatment.

Christopher Nardone^1,2, Xin Gu³, Stephen J. Elledge^1,2*

¹Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women’s Hospital, Boston, MA, USA

²Department of Genetics, Harvard Medical School, Boston, MA, USA

³Department of Neurobiology, Harvard Medical School, Boston, MA, USA

The MiT/TFE proteins (MITF, TFE3, TFEB, and TFEC) constitute a family of transcription factors that maintain cellular homeostasis by controlling the transcription of genes involved in lysosomal biogenesis, autophagy, oxidative metabolism, and pigmentation. While significant effort has been placed in understanding the downstream function of this family, the upstream regulation has only recently become clearer. It was appreciated that the nutrient-sensing Rag GTPases-mTORC1 pathway attenuates the activity of this family, but how this occurs mechanistically remained unclear. The physiological role of the MiT/TFE family is underscored by the fact that numerous human diseases are caused by their misregulation. The goal of this minireview is to provide a summary of recent findings that have elucidated how this family is regulated upstream and, hence, the molecular basis of a rare kidney cancer and neurodevelopmental syndrome caused by mutations in TFE3. The information presented here may serve as a framework for future studies.

Sai Krishna Vallamchetla

All India Institute of Medical Sciences, Bhopal, India

The ketogenic diet (KD) has emerged as a promising therapeutic strategy for a variety of neurological disorders, including epilepsy, Alzheimer's disease, Parkinson's disease, multiple sclerosis, and autism spectrum disorder. The potential benefits of the KD are attributed to its capacity to modulate neurotransmission, reduce inflammation, improve mitochondrial function, and enhance synaptic plasticity. Despite the growing body of evidence supporting the KD's therapeutic potential, there remain challenges in its implementation, such as potential side effects, nutrient deficiencies, and the need for careful monitoring by healthcare professionals. Factors affecting the success of the KD include patient adherence, individual metabolic response, and appropriate diet customization. This review summarizes the current evidence supporting the KD's role in the management of neurological disorders, discusses the underlying mechanisms of action, highlights the challenges and considerations associated with its use, and addresses the factors that can influence treatment success. Further research is needed to optimize the KD for different patient populations, elucidate the specific therapeutic mechanisms, and identify potential biomarkers to predict treatment response, ultimately enhancing the quality of life and overall well-being of individuals affected by neurological disorders.