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Christidi F, Kleinerova J, Tan EL, Delaney S, Tacheva A, Hengeveld JC, Doherty MA, McLaughlin RL, Hardiman O, Siah WF, Chang KM, Lope J, Bede P. Limbic Network and Papez Circuit Involvement in ALS: Imaging and Clinical Profiles in GGGGCC Hexanucleotide Carriers in C9orf72 and C9orf72-Negative Patients. BIOLOGY 2024; 13:504. [PMID: 39056697 PMCID: PMC11273537 DOI: 10.3390/biology13070504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 06/26/2024] [Accepted: 07/05/2024] [Indexed: 07/28/2024]
Abstract
Background: While frontotemporal involvement is increasingly recognized in Amyotrophic lateral sclerosis (ALS), the degeneration of limbic networks remains poorly characterized, despite growing evidence of amnestic deficits, impaired emotional processing and deficits in social cognition. Methods: A prospective neuroimaging study was conducted with 204 individuals with ALS and 111 healthy controls. Patients were stratified for hexanucleotide expansion status in C9orf72. A deep-learning-based segmentation approach was implemented to segment the nucleus accumbens, hypothalamus, fornix, mammillary body, basal forebrain and septal nuclei. The cortical, subcortical and white matter components of the Papez circuit were also systematically evaluated. Results: Hexanucleotide repeat expansion carriers exhibited bilateral amygdala, hypothalamus and nucleus accumbens atrophy, and C9orf72 negative patients showed bilateral basal forebrain volume reductions compared to controls. Both patient groups showed left rostral anterior cingulate atrophy, left entorhinal cortex thinning and cingulum and fornix alterations, irrespective of the genotype. Fornix, cingulum, posterior cingulate, nucleus accumbens, amygdala and hypothalamus degeneration was more marked in C9orf72-positive ALS patients. Conclusions: Our results highlighted that mesial temporal and parasagittal subcortical degeneration is not unique to C9orf72 carriers. Our radiological findings were consistent with neuropsychological observations and highlighted the importance of comprehensive neuropsychological testing in ALS, irrespective of the underlying genotype.
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Affiliation(s)
- Foteini Christidi
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Jana Kleinerova
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Siobhan Delaney
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
| | - Asya Tacheva
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
| | | | - Mark A. Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
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2
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Sun W, Liu SH, Wei XJ, Sun H, Ma ZW, Yu XF. Potential of neuroimaging as a biomarker in amyotrophic lateral sclerosis: from structure to metabolism. J Neurol 2024; 271:2238-2257. [PMID: 38367047 DOI: 10.1007/s00415-024-12201-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 01/14/2024] [Accepted: 01/16/2024] [Indexed: 02/19/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by motor neuron degeneration. The development of ALS involves metabolite alterations leading to tissue lesions in the nervous system. Recent advances in neuroimaging have significantly improved our understanding of the underlying pathophysiology of ALS, with findings supporting the corticoefferent axonal disease progression theory. Current studies on neuroimaging in ALS have demonstrated inconsistencies, which may be due to small sample sizes, insufficient statistical power, overinterpretation of findings, and the inherent heterogeneity of ALS. Deriving meaningful conclusions solely from individual imaging metrics in ALS studies remains challenging, and integrating multimodal imaging techniques shows promise for detecting valuable ALS biomarkers. In addition to giving an overview of the principles and techniques of different neuroimaging modalities, this review describes the potential of neuroimaging biomarkers in the diagnosis and prognostication of ALS. We provide an insight into the underlying pathology, highlighting the need for standardized protocols and multicenter collaborations to advance ALS research.
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Affiliation(s)
- Wei Sun
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, 130021, China
| | - Si-Han Liu
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Xiao-Jing Wei
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, 130021, China
| | - Hui Sun
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, 130021, China
| | - Zhen-Wei Ma
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, 130021, China
| | - Xue-Fan Yu
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, 130021, China.
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3
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Müller HP, Kassubek J. Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing. Front Hum Neurosci 2024; 18:1378896. [PMID: 38628970 PMCID: PMC11018884 DOI: 10.3389/fnhum.2024.1378896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 02/26/2024] [Indexed: 04/19/2024] Open
Abstract
Neuroimaging biomarkers have shown high potential to map the disease processes in the application to neurodegenerative diseases (NDD), e.g., diffusion tensor imaging (DTI). For DTI, the implementation of a standardized scanning and analysis cascade in clinical trials has potential to be further optimized. Over the last few years, various approaches to improve DTI applications to NDD have been developed. The core issue of this review was to address considerations and limitations of DTI in NDD: we discuss suggestions for improvements of DTI applications to NDD. Based on this technical approach, a set of recommendations was proposed for a standardized DTI scan protocol and an analysis cascade of DTI data pre-and postprocessing and statistical analysis. In summary, considering advantages and limitations of the DTI in NDD we suggest improvements for a standardized framework for a DTI-based protocol to be applied to future imaging studies in NDD, towards the goal to proceed to establish DTI as a biomarker in clinical trials in neurodegeneration.
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Irwin KE, Sheth U, Wong PC, Gendron TF. Fluid biomarkers for amyotrophic lateral sclerosis: a review. Mol Neurodegener 2024; 19:9. [PMID: 38267984 PMCID: PMC10809579 DOI: 10.1186/s13024-023-00685-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 11/21/2023] [Indexed: 01/26/2024] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the loss of upper and lower motor neurons. Presently, three FDA-approved drugs are available to help slow functional decline for patients with ALS, but no cure yet exists. With an average life expectancy of only two to five years after diagnosis, there is a clear need for biomarkers to improve the care of patients with ALS and to expedite ALS treatment development. Here, we provide a review of the efforts made towards identifying diagnostic, prognostic, susceptibility/risk, and response fluid biomarkers with the intent to facilitate a more rapid and accurate ALS diagnosis, to better predict prognosis, to improve clinical trial design, and to inform interpretation of clinical trial results. Over the course of 20 + years, several promising fluid biomarker candidates for ALS have emerged. These will be discussed, as will the exciting new strategies being explored for ALS biomarker discovery and development.
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Affiliation(s)
- Katherine E Irwin
- Department of Pathology, Johns Hopkins Medicine, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins Medicine, Baltimore, MD, 21205, USA
| | - Udit Sheth
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Philip C Wong
- Department of Pathology, Johns Hopkins Medicine, Baltimore, MD, 21205, USA.
- Department of Neuroscience, Johns Hopkins Medicine, Baltimore, MD, 21205, USA.
| | - Tania F Gendron
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA.
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL, 32224, USA.
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Singh RK, Nayak NP, Behl T, Arora R, Anwer MK, Gulati M, Bungau SG, Brisc MC. Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences. Diagnostics (Basel) 2024; 14:139. [PMID: 38248016 PMCID: PMC11154438 DOI: 10.3390/diagnostics14020139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth's subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.
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Affiliation(s)
- Rahul Kumar Singh
- Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India; (R.K.S.); (N.P.N.)
| | - Nirlipta Priyadarshini Nayak
- Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India; (R.K.S.); (N.P.N.)
| | - Tapan Behl
- Amity School of Pharmaceutical Sciences, Amity University, Mohali 140306, Punjab, India
| | - Rashmi Arora
- Chitkara College of Pharmacy, Chitkara University, Rajpura 140401, Punjab, India;
| | - Md. Khalid Anwer
- Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia;
| | - Monica Gulati
- School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 1444411, Punjab, India;
- Australian Research Centre in Complementary and Integrative Medicine, Faculty of Health, University of Technology Sydney, Ultimo, NSW 20227, Australia
| | - Simona Gabriela Bungau
- Department of Pharmacy, Faculty of Medicine and Pharmacy, University of Oradea, 410028 Oradea, Romania
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania
| | - Mihaela Cristina Brisc
- Department of Medical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania;
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6
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Ghaderi S, Fatehi F, Kalra S, Batouli SAH. MRI biomarkers for memory-related impairment in amyotrophic lateral sclerosis: a systematic review. Amyotroph Lateral Scler Frontotemporal Degener 2023:1-17. [PMID: 37469125 DOI: 10.1080/21678421.2023.2236651] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/06/2023] [Accepted: 06/30/2023] [Indexed: 07/21/2023]
Abstract
Introduction: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder associated with cognitive and behavioral impairments and motor symptoms. Magnetic resonance imaging (MRI) biomarkers have been investigated as potential tools for detecting and monitoring memory-related impairment in ALS. Our objective was to examine the importance of identifying MRI biomarkers for memory-related impairment in ALS, motor neuron disease (MND), and ALS frontotemporal dementia (FTD) (ALS-FTD) patients. Methods: PubMed and Scopus databases were searched. Keywords covering magnetic resonance imaging, ALS, MND, and memory impairments were searched. There were a total of 25 studies included in our work here. Results: The structural MRI (sMRI) studies reported gray matter (GM) atrophy in the regions associated with memory processing, such as the hippocampus and parahippocampal gyrus (PhG), in ALS patients. The diffusion tensor imaging (DTI) studies showed white matter (WM) alterations in the corticospinal tract (CST) and other tracts that are related to motor and extra-motor functions, and these alterations were associated with memory and executive function impairments in ALS. The functional MRI (fMRI) studies also demonstrated an altered activation in the prefrontal cortex, limbic system, and other brain regions involved in memory and emotional processing in ALS patients. Conclusion: MRI biomarkers show promise in uncovering the neural mechanisms of memory-related impairment in ALS. Nonetheless, addressing challenges such as sample sizes, imaging protocols, and longitudinal studies is crucial for future research. Ultimately, MRI biomarkers have the potential to be a tool for detecting and monitoring memory-related impairments in ALS.
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Affiliation(s)
- Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Neurology Department, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzad Fatehi
- Neurology Department, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Seyed Amir Hossein Batouli
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Moresi V. Amyotrophic Lateral Sclerosis as a Systemic Disease. Int J Mol Sci 2023; 24:ijms24087083. [PMID: 37108243 PMCID: PMC10138754 DOI: 10.3390/ijms24087083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 04/29/2023] Open
Abstract
The goal of this Special Issue is to report new research progress and reviews concerning amyotrophic lateral sclerosis (ALS) [...].
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Affiliation(s)
- Viviana Moresi
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), Sapienza University of Rome, 00185 Rome, Italy
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