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Friesen E, Hari K, Sheft M, Thiessen JD, Martin M. Magnetic resonance metrics for identification of cuprizone-induced demyelination in the mouse model of neurodegeneration: a review. MAGMA 2024:10.1007/s10334-024-01160-z. [PMID: 38635150 DOI: 10.1007/s10334-024-01160-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 03/17/2024] [Accepted: 03/26/2024] [Indexed: 04/19/2024]
Abstract
Neurodegenerative disorders, including Multiple Sclerosis (MS), are heterogenous disorders which affect the myelin sheath of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) provides a non-invasive method for studying, diagnosing, and monitoring disease progression. As an emerging research area, many studies have attempted to connect MR metrics to underlying pathophysiological presentations of heterogenous neurodegeneration. Most commonly, small animal models are used, including Experimental Autoimmune Encephalomyelitis (EAE), Theiler's Murine Encephalomyelitis (TMEV), and toxin models including cuprizone (CPZ), lysolecithin, and ethidium bromide (EtBr). A contrast and comparison of these models is presented, with focus on the cuprizone model, followed by a review of literature studying neurodegeneration using MRI and the cuprizone model. Conventional MRI methods including T1 Weighted (T1W) and T2 Weighted (T2W) Imaging are mentioned. Quantitative MRI methods which are sensitive to diffusion, magnetization transfer, susceptibility, relaxation, and chemical composition are discussed in relation to studying the CPZ model. Overall, additional studies are needed to improve both the sensitivity and specificity of MRI metrics for underlying pathophysiology of neurodegeneration and the relationships in attempts to clear the clinico-radiological paradox. We therefore propose a multiparametric approach for the investigation of MR metrics for underlying pathophysiology.
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Affiliation(s)
- Emma Friesen
- Chemistry, University of Winnipeg, Winnipeg, Canada.
| | - Kamya Hari
- Physics, University of Winnipeg, Winnipeg, Canada
- Electronics and Communication Engineering, SSN College of Engineering, Chennai, India
| | - Maxina Sheft
- Physics, University of Winnipeg, Winnipeg, Canada
- Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, USA
| | - Jonathan D Thiessen
- Imaging Program, Lawson Health Research Institute, London, Canada
- Medical Biophysics, Western University, London, Canada
- Medical Imaging, Western University, London, Canada
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Lee HH, Tian Q, Sheft M, Coronado-Leija R, Ramos-Llorden G, Abdollahzadeh A, Fieremans E, Novikov DS, Huang SY. The effects of axonal beading and undulation on axonal diameter estimation from diffusion MRI: Insights from simulations in human axons segmented from three-dimensional electron microscopy. NMR Biomed 2024; 37:e5087. [PMID: 38168082 PMCID: PMC10942763 DOI: 10.1002/nbm.5087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/19/2023] [Accepted: 11/21/2023] [Indexed: 01/05/2024]
Abstract
The increasing availability of high-performance gradient systems in human MRI scanners has generated great interest in diffusion microstructural imaging applications such as axonal diameter mapping. Practically, sensitivity to axon diameter in diffusion MRI is attained at strong diffusion weightings b , where the deviation from the expected 1 / b scaling in white matter yields a finite transverse diffusivity, which is then translated into an axon diameter estimate. While axons are usually modeled as perfectly straight, impermeable cylinders, local variations in diameter (caliber variation or beading) and direction (undulation) are known to influence axonal diameter estimates and have been observed in microscopy data of human axons. In this study, we performed Monte Carlo simulations of diffusion in axons reconstructed from three-dimensional electron microscopy of a human temporal lobe specimen using simulated sequence parameters matched to the maximal gradient strength of the next-generation Connectome 2.0 human MRI scanner ( ≲ 500 mT/m). We show that axon diameter estimation is accurate for nonbeaded, nonundulating fibers; however, in fibers with caliber variations and undulations, the axon diameter is heavily underestimated due to caliber variations, and this effect overshadows the known overestimation of the axon diameter due to undulations. This unexpected underestimation may originate from variations in the coarse-grained axial diffusivity due to caliber variations. Given that increased axonal beading and undulations have been observed in pathological tissues, such as traumatic brain injury and ischemia, the interpretation of axon diameter alterations in pathology may be significantly confounded.
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Affiliation(s)
- Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Maxina Sheft
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard–MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
| | - Ricardo Coronado-Leija
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Gabriel Ramos-Llorden
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Ali Abdollahzadeh
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Dmitry S. Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Susie Y. Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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Chitalia Y, Sarma A, Brumfiel TA, Deaton NJ, Sheft M, Desai JP. Model-based Design of the COAST Guidewire Robot for Large Deflection. IEEE Robot Autom Lett 2023; 8:5345-5352. [PMID: 37614723 PMCID: PMC10443931 DOI: 10.1109/lra.2023.3286125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
Minimally invasive endovascular procedures involve the manual placement of a guidewire, which is made difficult by vascular tortuosity and the lack of precise tip control. Steerable guidewire systems have been developed with tendon-driven, magnetic, and concentric tube actuation strategies to enable precise tip control, however, selecting machining parameters for such robots does not have a strict procedure. In this paper, we develop a systematic design procedure for selecting the tube pairs of the COaxially Aligned STeerable (COAST) guidewire robot. This includes the introduction of a mechanical model that accounts for micromachining-induced pre-curvatures with the goal of determining design parameters that reduce combined distal tip pre-curvature and minimize abrupt changes in actuated tip position for the COAST guidewire robot through selection of the best flexural rigidity between the tube pairs. We present adjustments in the kinematics modeling of COAST robot tip bending motion, and use these to characterize the bending behavior of the COAST robot for varying geometries of the micromachined tubes, with an average RMSE value for the tip position error of 0.816 mm in the validation study.
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Affiliation(s)
- Yash Chitalia
- Healthcare Robotics and Telesurgery (HeaRT) Laboratory, Department of Mechanical Engineering, University of Louisville, KY, USA. He contributed to the work presented in this paper when he was a graduate student in the RoboMed Laboratory at the Georgia Institute of Technology, GA, USA
| | - Achraj Sarma
- contributed to the work presented in this paper when he was a graduate student in the RoboMed Laboratory at the Georgia Institute of Technology, GA, USA
| | - Timothy A Brumfiel
- Medical Robotics and Automation (RoboMed) Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Nancy J Deaton
- Medical Robotics and Automation (RoboMed) Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Maxina Sheft
- contributed to the work presented in this paper when she was an undergraduate student at the Georgia Institute of Technology
| | - Jaydev P Desai
- Medical Robotics and Automation (RoboMed) Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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Lee HH, Tian Q, Sheft M, Coronado-Leija R, Ramos-Llorden G, Abdollahzadeh A, Fieremans E, Novikov DS, Huang SY. The influence of axonal beading and undulation on axonal diameter mapping. bioRxiv 2023:2023.04.19.537494. [PMID: 37131702 PMCID: PMC10153226 DOI: 10.1101/2023.04.19.537494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We consider the effect of non-cylindrical axonal shape on axonal diameter mapping with diffusion MRI. Practical sensitivity to axon diameter is attained at strong diffusion weightings b , where the deviation from the 1 / b scaling yields the finite transverse diffusivity, which is then translated into axon diameter. While axons are usually modeled as perfectly straight, impermeable cylinders, the local variations in diameter (caliber variation or beading) and direction (undulation) have been observed in microscopy data of human axons. Here we quantify the influence of cellular-level features such as caliber variation and undulation on axon diameter estimation. For that, we simulate the diffusion MRI signal in realistic axons segmented from 3-dimensional electron microscopy of a human brain sample. We then create artificial fibers with the same features and tune the amplitude of their caliber variations and undulations. Numerical simulations of diffusion in fibers with such tunable features show that caliber variations and undulations result in under- and over-estimation of axon diameters, correspondingly; this bias can be as large as 100%. Given that increased axonal beading and undulations have been observed in pathological tissues, such as traumatic brain injury and ischemia, the interpretation of axon diameter alterations in pathology may be significantly confounded.
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Affiliation(s)
- Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129,USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129,USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Maxina Sheft
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129,USA
- Harvard-MIT Health Sciences and Technology, Cambridge, MA 02139, USA
| | - Ricardo Coronado-Leija
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY 10016, USA
| | - Gabriel Ramos-Llorden
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129,USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Ali Abdollahzadeh
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY 10016, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY 10016, USA
| | - Dmitry S. Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY 10016, USA
| | - Susie Y. Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129,USA
- Harvard Medical School, Boston, MA 02115, USA
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Herrera SL, Sheft M, Mercredi ME, Buist R, Matsuda KM, Martin M. Axon diameter inferences in the human corpus callosum using oscillating gradient spin echo sequences. Magn Reson Imaging 2021; 85:64-70. [PMID: 34662703 DOI: 10.1016/j.mri.2021.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 08/30/2021] [Accepted: 10/12/2021] [Indexed: 10/20/2022]
Abstract
Previous methods used to infer axon diameter distributions using magnetic resonance imaging (MRI) primarily use single diffusion encoding sequences such as pulsed gradient spin echo (PGSE) and are thus sensitive to axons of diameters >5 μm. We applied oscillating gradient spin echo (OGSE) sequences to study human axons in the 1-2 μm range in the corpus callosum, which include the majority of axons constituting cortical connections. The ActiveAx model was applied to calculate the fitted mean effective diameter for axons (AxD) and was compared with values found using histology. Axon diameters from histological data were calculated using three different datasets; true diameters (minimum diameter), a combination of minimum and maximum diameters, and diameters measured across a consistent diffusion direction. The AxD estimates from MRI were 1.8 ± 0.1 μm to 2.34 ± 0.04 μm with an average of 2.0 ± 0.2 μm for the ActiveAx model. The histology AxD values were 1.43 ± 0.02 μm when using the true minimum axon diameters, 5.52 ± 0.02 μm when using the combination of minimum and maximum axon diameters, and 2.20 ± 0.02 μm when collecting measurements across a consistent diffusion direction. This experiment demonstrates the first known usage of OGSE to calculate axon diameters in the human corpus callosum on a 1-2 μm scale. The importance for the model to account for axonal orientation dispersion is indicated by histological results which more closely match the MRI model results depending on the direction of axon diameter measurements. These initial steps using this non-invasive imaging method can be applied to future methodology to develop in vivo axon diameter measurements in human brain tissue.
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Affiliation(s)
| | - Maxina Sheft
- Physics, University of Winnipeg, Canada; Biomedical Engineering, Georgia Institute of Technology, United States of America.
| | | | | | - Kant M Matsuda
- Pathology, Robert Wood Johnson (RWJ) Medical School, Rutgers University, United States of America
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