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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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Wooliscroft L, Salter A, Adusumilli G, Levasseur VA, Sun P, Lancia S, Perantie DC, Trinkaus K, Naismith RT, Song SK, Cross AH. Diffusion basis spectrum imaging and diffusion tensor imaging predict persistent black hole formation in multiple sclerosis. Mult Scler Relat Disord 2024; 84:105494. [PMID: 38359694 PMCID: PMC10978237 DOI: 10.1016/j.msard.2024.105494] [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: 09/20/2023] [Revised: 12/13/2023] [Accepted: 02/10/2024] [Indexed: 02/17/2024]
Abstract
BACKGROUND AND OBJECTIVES Diffusion basis spectrum imaging (DBSI) extracts multiple anisotropic and isotropic diffusion tensors, providing greater histopathologic specificity than diffusion tensor imaging (DTI). Persistent black holes (PBH) represent areas of severe tissue damage in multiple sclerosis (MS), and a high PBH burden is associated with worse MS disability. This study evaluated the ability of DBSI and DTI to predict which acute contrast-enhancing lesions (CELs) would persist as T1 hypointensities (i.e. PBHs) 12 months later. We expected that a higher radial diffusivity (RD), representing demyelination, and higher DBSI-derived isotropic non-restricted fraction, representing edema and increased extracellular space, of the acute CEL would increase the likelihood of future PBH development. METHODS In this prospective cohort study, relapsing MS patients with ≥1 CEL(s) underwent monthly MRI scans for 4 to 6 months until gadolinium resolution. DBSI and DTI metrics were quantified when the CEL was most conspicuous during the monthly scans. To determine whether the CEL became a PBH, a follow-up MRI was performed at least 12 months after the final monthly scan. RESULTS The cohort included 20 MS participants (median age 33 years; 13 women) with 164 CELs. Of these, 59 (36 %) CELs evolved into PBHs. At Gd-max, DTI RD and AD of all CELs increased, and both metrics were significantly elevated for CELs which became PBHs, as compared to non-black holes (NBHs). DTI RD above 0.74 conferred an odds ratio (OR) of 7.76 (CI 3.77-15.98) for a CEL becoming a PBH (AUC 0.80, CI 0.73-0.87); DTI axial diffusivity (AD) above 1.22 conferred an OR of 7.32 (CI 3.38-15.86) for becoming a PBH (AUC 0.75, CI 0.66-0.83). DBSI RD and AD did not predict PBH development in a multivariable model. At Gd-max, DBSI restricted fraction decreased and DBSI non-restricted fraction increased in all CELs, and both metrics were significantly different for CELs which became PBHs, as compared to NBHs. A CEL with a DBSI non-restricted fraction above 0.45 had an OR of 4.77 (CI 2.35-9.66) for becoming a PBH (AUC 0.74, CI 0.66-0.81); a CEL with a DBSI restricted fraction below 0.07 had an OR of 9.58 (CI 4.59-20.02) for becoming a PBH (AUC 0.80, 0.72-0.87). CONCLUSION Our findings suggest that greater degree of edema/extracellular space in a CEL is a predictor of tissue destruction, as evidenced by PBH evolution.
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Affiliation(s)
- Lindsey Wooliscroft
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA; Department of Neurology, VA Portland Health Care System, Portland, OR, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Amber Salter
- Department of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA; Department of Biostatistics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gautam Adusumilli
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Victoria A Levasseur
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Minneapolis Clinic of Neurology, Coon Rapids, MN, USA
| | - Peng Sun
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Samantha Lancia
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA; Department of Biostatistics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Dana C Perantie
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Kathryn Trinkaus
- Biostatistics Shared Resource, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Robert T Naismith
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne H Cross
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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Alan N, Zenkin S, Lavadi RS, Legarreta AD, Hudson JS, Fields DP, Agarwal N, Mamindla P, Ak M, Peddagangireddy V, Puccio L, Buell TJ, Hamilton DK, Kanter AS, Okonkwo DO, Zinn PO, Colen RR. Associating T1-Weighted and T2-Weighted Magnetic Resonance Imaging Radiomic Signatures With Preoperative Symptom Severity in Patients With Cervical Spondylotic Myelopathy. World Neurosurg 2024; 184:e137-e143. [PMID: 38253177 DOI: 10.1016/j.wneu.2024.01.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 01/14/2024] [Indexed: 01/24/2024]
Abstract
BACKGROUND Preoperative symptom severity in cervical spondylotic myelopathy (CSM) can be variable. Radiomic signatures could provide an imaging biomarker for symptom severity in CSM. This study utilizes radiomic signatures of T1-weighted and T2-weighted magnetic resonance imaging images to correlate with preoperative symptom severity based on modified Japanese Orthopaedic Association (mJOA) scores for patients with CSM. METHODS Sixty-two patients with CSM were identified. Preoperative T1-weighted and T2-weighted magnetic resonance imaging images for each patient were segmented from C2-C7. A total of 205 texture features were extracted from each volume of interest. After feature normalization, each second-order feature was further subdivided to yield a total of 400 features from each volume of interest for analysis. Supervised machine learning was used to build radiomic models. RESULTS The patient cohort had a median mJOA preoperative score of 13; of which, 30 patients had a score of >13 (low severity) and 32 patients had a score of ≤13 (high severity). Radiomic analysis of T2-weighted imaging resulted in 4 radiomic signatures that correlated with preoperative mJOA with a sensitivity, specificity, and accuracy of 78%, 89%, and 83%, respectively (P < 0.004). The area under the curve value for the ROC curves were 0.69, 0.70, and 0.77 for models generated by independent T1 texture features, T1 and T2 texture features in combination, and independent T2 texture features, respectively. CONCLUSIONS Radiomic models correlate with preoperative mJOA scores using T2 texture features in patients with CSM. This may serve as a surrogate, objective imaging biomarker to measure the preoperative functional status of patients.
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Affiliation(s)
- Nima Alan
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California.
| | - Serafettin Zenkin
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Raj Swaroop Lavadi
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Andrew D Legarreta
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Joseph S Hudson
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Daryl P Fields
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Nitin Agarwal
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Priyadarshini Mamindla
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Murat Ak
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Vishal Peddagangireddy
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Lauren Puccio
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Thomas J Buell
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - D Kojo Hamilton
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Adam S Kanter
- Department of Neurosurgery, Hoag Neurosciences Institute, Newport Beach, California
| | - David O Okonkwo
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Pascal O Zinn
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Rivka R Colen
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
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Zhang W, Gorelik AJ, Wang Q, Norton SA, Hershey T, Agrawal A, Bijsterbosch JD, Bogdan R. Associations between COVID-19 and putative markers of neuroinflammation: A diffusion basis spectrum imaging study. Brain Behav Immun Health 2024; 36:100722. [PMID: 38298902 PMCID: PMC10825665 DOI: 10.1016/j.bbih.2023.100722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 12/27/2023] [Accepted: 12/27/2023] [Indexed: 02/02/2024] Open
Abstract
COVID-19 remains a significant international public health concern. Yet, the mechanisms through which symptomatology emerges remain poorly understood. While SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal UK Biobank neuroimaging data acquired prior to and following COVID-19 testing (N = 416 including n = 224 COVID-19 cases; Mage = 58.6). Putative neuroinflammation was assessed in gray matter structures and white matter tracts using non-invasive Diffusion Basis Spectrum Imaging (DBSI), which estimates inflammation-related cellularity (DBSI-restricted fraction; DBSI-RF) and vasogenic edema (DBSI-hindered fraction; DBSI-HF). We hypothesized that COVID-19 case status would be associated with increases in DBSI markers after accounting for potential confound (age, sex, race, body mass index, smoking frequency, and data acquisition interval) and multiple testing. COVID-19 case status was not significantly associated with DBSI-RF (|β|'s < 0.28, pFDR >0.05), but with greater DBSI-HF in left pre- and post-central gyri and right middle frontal gyrus (β's > 0.3, all pFDR = 0.03). Intriguingly, the brain areas exhibiting increased putative vasogenic edema had previously been linked to COVID-19-related functional and structural alterations, whereas brain regions displaying subtle differences in cellularity between COVID-19 cases and controls included regions within or functionally connected to the olfactory network, which has been implicated in COVID-19 psychopathology. Nevertheless, our study might not have captured acute and transitory neuroinflammatory effects linked to SARS-CoV-2 infection, possibly due to symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with COVID-19.
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Affiliation(s)
- Wei Zhang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Aaron J. Gorelik
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
| | - Qing Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Sara A. Norton
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
| | - Tamara Hershey
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Janine D. Bijsterbosch
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
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Zhang W, Gorelik AJ, Wang Q, Norton SA, Hershey T, Agrawal A, Bijsterbosch JD, Bogdan R. Associations between COVID-19 and putative markers of neuroinflammation: A diffusion basis spectrum imaging study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.20.549891. [PMID: 37502886 PMCID: PMC10370178 DOI: 10.1101/2023.07.20.549891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
COVID-19 remains a significant international public health concern. Yet, the mechanisms through which symptomatology emerges remain poorly understood. While SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal UK Biobank neuroimaging data acquired prior to and following COVID-19 testing (N=416 including n=224 COVID-19 cases; Mage=58.6). Putative neuroinflammation was assessed in gray matter structures and white matter tracts using non-invasive Diffusion Basis Spectrum Imaging (DBSI), which estimates inflammation-related cellularity (DBSI-restricted fraction; DBSI-RF) and vasogenic edema (DBSI-hindered fraction; DBSI-HF).We hypothesized that COVID-19 case status would be associated with increases in DBSI markers after accounting for potential confound (age, sex, race, body mass index, smoking frequency, and data acquisition interval) and multiple testing. COVID-19 case status was not significantly associated with DBSI-RF (|β|'s<0.28, pFDR >0.05), but with greater DBSI-HF in left pre- and post-central gyri and right middle frontal gyrus (β's>0.3, all pFDR=0.03). Intriguingly, the brain areas exhibiting increased putative vasogenic edema had previously been linked to COVID-19-related functional and structural alterations, whereas brain regions displaying subtle differences in cellularity between COVID-19 cases and controls included regions within or functionally connected to the olfactory network, which has been implicated in COVID-19 psychopathology. Nevertheless, our study might not have captured acute and transitory neuroinflammatory effects linked to SARS-CoV-2 infection, possibly due to symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with COVID-19.
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Affiliation(s)
- Wei Zhang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Aaron J Gorelik
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
| | - Qing Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Sara A Norton
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
| | - Tamara Hershey
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Janine D Bijsterbosch
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
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Hu Z, Sun P, George A, Zeng X, Li M, Lin TH, Ye Z, Wei X, Jiang X, Song SK, Yang R. Diffusion basis spectrum imaging detects pathological alterations in substantia nigra and white matter tracts with early-stage Parkinson's disease. Eur Radiol 2023; 33:9109-9119. [PMID: 37438642 DOI: 10.1007/s00330-023-09780-0] [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: 08/31/2022] [Revised: 03/13/2023] [Accepted: 03/30/2023] [Indexed: 07/14/2023]
Abstract
OBJECTIVES Using diffusion basis spectrum imaging (DBSI) to examine the microstructural changes in the substantia nigra (SN) and global white matter (WM) tracts of patients with early-stage PD. METHODS Thirty-seven age- and sex-matched patients with early-stage PD and 22 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessments and diffusion-weighted MRI scans, analyzed by diffusion tensor imaging (DTI) and DBSI to assess the pathologies of PD in SN and global WM tracts. RESULTS The lower DTI fraction anisotropy (FA) was seen in SN of PD patients (PD: 0.316 ± 0.034 vs HCs: 0.331 ± 0.019, p = 0.015). The putative cells marker-DBSI-restricted fraction (PD: 0.132 ± 0.051 vs HCs: 0.105 ± 0.039, p = 0.031) and the edema/extracellular space marker-DBSI non-restricted-fraction (PD: 0.150 ± 0.052 vs HCs: 0.122 ± 0.052, p = 0.020) were both significantly higher and the density of axons/dendrites marker-DBSI fiber-fraction (PD: 0.718 ± 0.073 vs HCs: 0.773 ± 0.071, p = 0.003) was significantly lower in SN of PD patients. DBSI-restricted fraction in SN was negatively correlated with HAMA scores (r = - 0.501, p = 0.005), whereas DTI-FA was not correlated with any clinical scales. In WM tracts, only higher DTI axial diffusivity (AD) among DTI metrics was found in multiple WM regions in PD, while lower DBSI fiber-fraction and higher DBSI non-restricted-fraction were detected in multiple WM regions. DBSI non-restricted-fraction in both left fornix (cres)/stria terminalis (r = -0.472, p = 0.004) and right posterior thalamic radiation (r = - 0.467, p = 0.005) was negatively correlated with MMSE scores. CONCLUSION DBSI could potentially detect and quantify the extent of inflammatory cell infiltration, fiber/dendrite loss, and edema in both SN and WM tracts in patients with early-stage PD, a finding remains to be further investigated through more extensive longitudinal DBSI analysis. CLINICAL RELEVANCE STATEMENT Our study shows that DBSI indexes can potentially detect early-stage PD's pathological changes, with a notable ability to distinguish between inflammation and edema. This implies that DBSI has the potential to be an imaging biomarker for early PD diagnosis. KEY POINTS • Diffusion basis spectrum imaging detected higher restricted-fraction in Parkinson's disease, potentially reflecting inflammatory cell infiltration. • Diffusion basis spectrum imaging detected higher non-restricted-fraction and lower fiber-fraction in Parkinson's disease, indicating the presence of edema and/or dopaminergic neuronal/dendritic loss. • Diffusion basis spectrum imaging metrics correlated with non-motor symptoms, suggesting its potential diagnostic role to detect early-stage PD dysfunctions.
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Affiliation(s)
- Zexuan Hu
- Department of Radiology, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangdong, 510310, Guangzhou, China
| | - Peng Sun
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, Room 2313, 4525 Scott Ave, Campus Box 8227, St. Louis, MO, 63110-1093, USA
| | - Ajit George
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, Room 2313, 4525 Scott Ave, Campus Box 8227, St. Louis, MO, 63110-1093, USA
| | - Xiangling Zeng
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, #1 Panfu Road, Yuexiu District, Guangdong, 510180, Guangzhou, China
| | - Mengyan Li
- Department of Neurology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, #1 Panfu Road, Yuexiu District, Guangdong, 510180, Guangzhou, China
| | - Tsen-Hsuan Lin
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, Room 2313, 4525 Scott Ave, Campus Box 8227, St. Louis, MO, 63110-1093, USA
| | - Zezhong Ye
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, Room 2313, 4525 Scott Ave, Campus Box 8227, St. Louis, MO, 63110-1093, USA
| | - Xinhua Wei
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, #1 Panfu Road, Yuexiu District, Guangdong, 510180, Guangzhou, China
| | - Xinqing Jiang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, #1 Panfu Road, Yuexiu District, Guangdong, 510180, Guangzhou, China
| | - Sheng-Kwei Song
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, Room 2313, 4525 Scott Ave, Campus Box 8227, St. Louis, MO, 63110-1093, USA.
| | - Ruimeng Yang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, #1 Panfu Road, Yuexiu District, Guangdong, 510180, Guangzhou, China.
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Alghamdi AJ. The Value of Various Post-Processing Modalities of Diffusion Weighted Imaging in the Detection of Multiple Sclerosis. Brain Sci 2023; 13:brainsci13040622. [PMID: 37190587 DOI: 10.3390/brainsci13040622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 03/31/2023] [Accepted: 04/04/2023] [Indexed: 04/08/2023] Open
Abstract
Diffusion tensor imaging (DTI) showed its adequacy in evaluating the normal-appearing white matter (NAWM) and lesions in the brain that are difficult to evaluate with routine clinical magnetic resonance imaging (MRI) in multiple sclerosis (MS). Recently, MRI systems have been developed with regard to software and hardware, leading to different proposed diffusion analysis methods such as diffusion tensor imaging, q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and axonal diameter measurement. These methods have the ability to better detect in vivo microstructural changes in the brain than DTI. These different analysis modalities could provide supplementary inputs for MS disease characterization and help in monitoring the disease’s progression as well as treatment efficacy. This paper reviews some of the recent diffusion MRI methods used for the assessment of MS in vivo.
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Affiliation(s)
- Ahmad Joman Alghamdi
- Radiological Sciences Department, College of Applied Medical Sciences, Taif University, Taif 21944, Saudi Arabia
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Gilli F, Ceccarelli A. Magnetic resonance imaging approaches for studying mouse models of multiple sclerosis: A mini review. J Neurosci Res 2023. [DOI: 10.1002/jnr.25193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 01/30/2023] [Accepted: 03/10/2023] [Indexed: 04/03/2023]
Affiliation(s)
- Francesca Gilli
- Department of Neurology, Dartmouth Hitchcock Medical Center Geisel School of Medicine at Dartmouth Lebanon New Hampshire USA
| | - Antonia Ceccarelli
- Department of Neurology EpiCURA Centre Hospitalier Ath Belgium
- Hearthrhythmanagement, UZB Brussels Belgium
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Rahmani F, Ghezzi L, Tosti V, Liu J, Song SK, Wu AT, Rajamanickam J, Obert KA, Benzinger TL, Mittendorfer B, Piccio L, Raji CA. Twelve Weeks of Intermittent Caloric Restriction Diet Mitigates Neuroinflammation in Midlife Individuals with Multiple Sclerosis: A Pilot Study with Implications for Prevention of Alzheimer's Disease. J Alzheimers Dis 2023; 93:263-273. [PMID: 37005885 PMCID: PMC10460547 DOI: 10.3233/jad-221007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is a prototype neuroinflammatory disorder with increasingly recognized role for neurodegeneration. Most first-line treatments cannot prevent the progression of neurodegeneration and the resultant disability. Interventions can improve symptoms of MS and might provide insights into the underlying pathology. OBJECTIVE To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS. METHODS We randomized ten participants with relapsing remitting MS to either a 12-week intermittent calorie restriction (iCR) diet (n = 5) or control (n = 5). Cortical thickness and volumes were measured through FreeSurfer, cortical perfusion was measured by arterial spin labeling and neuroinflammation through diffusion basis spectrum imaging. RESULTS After 12 weeks of iCR, brain volume increased in the left superior and inferior parietal gyri (p: 0.050 and 0.049, respectively) and the banks of the superior temporal sulcus (p: 0.01). Similarly in the iCR group, cortical thickness improved in the bilateral medial orbitofrontal gyri (p: 0.04 and 0.05 in right and left, respectively), the left superior temporal gyrus (p: 0.03), and the frontal pole (p: 0.008) among others. Cerebral perfusion decreased in the bilateral fusiform gyri (p: 0.047 and 0.02 in right and left, respectively) and increased in the bilateral deep anterior white matter (p: 0.03 and 0.013 in right and left, respectively). Neuroinflammation, demonstrated through hindered and restricted water fractions (HF and RF), decreased in the left optic tract (HF p: 0.02), and the right extreme capsule (RF p: 0.007 and HF p: 0.003). CONCLUSION These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.
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Affiliation(s)
- Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Laura Ghezzi
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Valeria Tosti
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Jingxia Liu
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Surgery, Division of Public Health Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Sheng-Kwei Song
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Anthony T. Wu
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Jayashree Rajamanickam
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Kathleen A. Obert
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St Louis, St. Louis, MO, USA
| | - Bettina Mittendorfer
- Department of Medicine, Division of Geriatrics and Nutritional Science, Washington University in St. Louis, St. Louis, MO, USA
| | - Laura Piccio
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
- Brain and Mind Centre, School of Medical Sciences, The University of Sydney, NSW, Australia
- Charles Perkin Centre, The University of Sydney NSW, Australia
| | - Cyrus A. Raji
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St Louis, St. Louis, MO, USA
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10
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Zhang JK, Sun P, Jayasekera D, Greenberg JK, Javeed S, Dibble CF, Blum J, Song C, Song SK, Ray WZ. Utility of Diffusion Basis Spectrum Imaging in Quantifying Baseline Disease Severity and Prognosis of Cervical Spondylotic Myelopathy. Spine (Phila Pa 1976) 2022; 47:1687-1693. [PMID: 35969006 PMCID: PMC9712150 DOI: 10.1097/brs.0000000000004456] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 07/20/2022] [Indexed: 02/01/2023]
Abstract
STUDY DESIGN Prospective cohort study. OBJECTIVE The aim was to assess the association between diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI) measures and cervical spondylotic myelopathy (CSM) clinical assessments at baseline and two-year follow-up. SUMMARY OF BACKGROUND DATA Despite advancements in diffusion-weighted imaging, few studies have examined associations between diffusion magnetic resonance imaging (MRI) markers and CSM-specific clinical domains at baseline and long-term follow-up. MATERIALS AND METHODS A single-center prospective cohort study enrolled 50 CSM patients who underwent surgical decompression and 20 controls from 2018 to 2020. At initial evaluation, all patients underwent diffusion-weighted MRI acquisition, followed by DTI and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. To improve estimations of intra-axonal anisotropic diffusion, DBSI measures intra-/extra-axonal fraction and intra-axonal axial diffusivity. DBSI also evaluates extra-axonal isotropic diffusion by restricted and nonrestricted fraction. Clinical assessments were performed at baseline and two-year follow-up and included the modified Japanese Orthopedic Association (mJOA); 36-Item Short Form Survey physical component summary (SF-36 PCS); SF-36 mental component summary; neck disability index; myelopathy disability index; and disability of the arm, shoulder, and hand. Pearson correlation coefficients were computed to compare associations between DTI/DBSI and clinical measures. A False Discovery Rate correction was applied for multiple comparisons testing. RESULTS At baseline presentation, of 36 correlations analyzed between DTI metrics and CSM clinical measures, only DTI fractional anisotropy showed a positive correlation with SF-36 PCS ( r =0.36, P =0.02). In comparison, there were 30/81 (37%) significant correlations among DBSI and clinical measures. Increased DBSI axial diffusivity, intra-axonal axial diffusivity, intra-axonal fraction, restricted fraction, and extra-axonal anisotropic fraction were associated with worse clinical presentation (decreased mJOA; SF-36 PCS/mental component summary; and increased neck disability index; myelopathy disability index; disability of the arm, shoulder, and hand). At latest follow-up, increased preoperative DBSI intra-axonal axial diffusivity and extra-axonal anisotropic fraction were significantly correlated with improved mJOA. CONCLUSIONS This findings demonstrate that DBSI measures may reflect baseline disease burden and long-term prognosis of CSM as compared with DTI. With further validation, DBSI may serve as a noninvasive biomarker following decompressive surgery. LEVEL OF EVIDENCE 3.
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Affiliation(s)
- Justin K. Zhang
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Peng Sun
- Department of Imaging Physics, UT MD Anderson Cancer Center, Houston, Texas, 77030, USA
| | - Dinal Jayasekera
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, Saint Louis, Missouri, 63130, USA
| | - Jacob K. Greenberg
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Saad Javeed
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Christopher F. Dibble
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Chunyu Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Wilson Z. Ray
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
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11
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Salminen LE, Tubi MA, Bright J, Thomopoulos SI, Wieand A, Thompson PM. Sex is a defining feature of neuroimaging phenotypes in major brain disorders. Hum Brain Mapp 2022; 43:500-542. [PMID: 33949018 PMCID: PMC8805690 DOI: 10.1002/hbm.25438] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.
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Affiliation(s)
- Lauren E. Salminen
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Meral A. Tubi
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Joanna Bright
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Alyssa Wieand
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
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12
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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13
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Yang R, Lin TH, Zhan J, Lai S, Song C, Sun P, Ye Z, Wallendorf M, George A, Cross AH, Song SK. Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis. NEUROIMAGE-CLINICAL 2021; 31:102732. [PMID: 34166868 PMCID: PMC8240023 DOI: 10.1016/j.nicl.2021.102732] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/12/2021] [Accepted: 06/14/2021] [Indexed: 10/30/2022]
Abstract
OBJECTIVE To prospectively determine whether diffusion basis spectrum imaging (DBSI) detects, differentiates and quantitates coexisting inflammation, demyelination, axonal injury and axon loss in mice with optic neuritis (ON) due to experimental autoimmune encephalomyelitis (EAE), and to determine if DBSI accurately measures effects of fingolimod on underlying pathology. METHODS EAE was induced in 7-week-old C57BL/6 female mice. Visual acuity (VA) was assessed daily to detect onset of ON after which daily oral-treatment with either fingolimod (1 mg/kg) or saline was given for ten weeks. In vivo DBSI scans of optic nerves were performed at baseline, 2-, 6- and 10-weeks post treatment. DBSI-derived metrics including restricted isotropic diffusion tensor fraction (putatively reflecting cellularity), non-restricted isotropic diffusion tensor fraction (putatively reflecting vasogenic edema), DBSI-derived axonal volume, axial diffusivity, λ∥ (putatively reflecting axonal integrity), and increased radial diffusivity, λ⊥ (putatively reflecting demyelination). Mice were killed immediately after the last DBSI scan for immunohistochemical assessment. RESULTS Optic nerves of fingolimod-treated mice exhibited significantly better (p < 0.05) VA than saline-treated group at each time point. During ten-week of treatment, DBSI-derived non-restricted and restricted-isotropic-diffusion-tensor fractions, and axonal volumes were not significantly different (p > 0.05) from the baseline values in fingolimod-treated mice. Transient DBSI-λ∥ decrease and DBSI-λ⊥ increase were detected during Fingolimod treatment. DBSI-derived metrics assessed in vivo significantly correlated (p < 0.05) with the corresponding histological markers. CONCLUSION DBSI was used to assess changes of the underlying optic nerve pathologies in EAE mice with ON, exhibiting great potential as a noninvasive outcome measure for monitoring disease progression and therapeutic efficacy for MS.
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Affiliation(s)
- Ruimeng Yang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510640, China; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tsen-Hsuan Lin
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jie Zhan
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Shengsheng Lai
- Department of Medical Equipment, Guangdong Food and Drug Vocational College, Guangzhou, Guangdong 510520, China
| | - Chunyu Song
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Zezhong Ye
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Michael Wallendorf
- Department of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ajit George
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anne H Cross
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA.
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14
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Vavasour IM, Sun P, Graf C, Yik JT, Kolind SH, Li DK, Tam R, Sayao AL, Schabas A, Devonshire V, Carruthers R, Traboulsee A, Moore GW, Song SK, Laule C. Characterization of multiple sclerosis neuroinflammation and neurodegeneration with relaxation and diffusion basis spectrum imaging. Mult Scler 2021; 28:418-428. [PMID: 34132126 DOI: 10.1177/13524585211023345] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Advanced magnetic resonance imaging (MRI) methods can provide more specific information about various microstructural tissue changes in multiple sclerosis (MS) brain. Quantitative measurement of T1 and T2 relaxation, and diffusion basis spectrum imaging (DBSI) yield metrics related to the pathology of neuroinflammation and neurodegeneration that occurs across the spectrum of MS. OBJECTIVE To use relaxation and DBSI MRI metrics to describe measures of neuroinflammation, myelin and axons in different MS subtypes. METHODS 103 participants (20 clinically isolated syndrome (CIS), 33 relapsing-remitting MS (RRMS), 30 secondary progressive MS and 20 primary progressive MS) underwent quantitative T1, T2, DBSI and conventional 3T MRI. Whole brain, normal-appearing white matter, lesion and corpus callosum MRI metrics were compared across MS subtypes. RESULTS A gradation of MRI metric values was seen from CIS to RRMS to progressive MS. RRMS demonstrated large oedema-related differences, while progressive MS had the most extensive abnormalities in myelin and axonal measures. CONCLUSION Relaxation and DBSI-derived MRI measures show differences between MS subtypes related to the severity and composition of underlying tissue damage. RRMS showed oedema, demyelination and axonal loss compared with CIS. Progressive MS had even more evidence of increased oedema, demyelination and axonal loss compared with CIS and RRMS.
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Affiliation(s)
- Irene M Vavasour
- Department of Radiology, The University of British Columbia, UBC Hospital, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada
| | - Peng Sun
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Carina Graf
- Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Jackie T Yik
- Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Shannon H Kolind
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada/Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada/Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - David Kb Li
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Roger Tam
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - Ana-Luiza Sayao
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alice Schabas
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Virginia Devonshire
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Robert Carruthers
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Gr Wayne Moore
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada/Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Sheng-Kwei Song
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Cornelia Laule
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada/Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada/Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
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15
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Demyelination and remyelination detected in an alternative cuprizone mouse model of multiple sclerosis with 7.0 T multiparameter magnetic resonance imaging. Sci Rep 2021; 11:11060. [PMID: 34040141 PMCID: PMC8155133 DOI: 10.1038/s41598-021-90597-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 05/11/2021] [Indexed: 02/07/2023] Open
Abstract
The aim of this study was to investigate the mechanisms underlying demyelination and remyelination with 7.0 T multiparameter magnetic resonance imaging (MRI) in an alternative cuprizone (CPZ) mouse model of multiple sclerosis (MS). Sixty mice were divided into six groups (n = 10, each), and these groups were imaged with 7.0 T multiparameter MRI and treated with an alternative CPZ administration schedule. T2-weighted imaging (T2WI), susceptibility-weighted imaging (SWI), and diffusion tensor imaging (DTI) were used to compare the splenium of the corpus callosum (sCC) among the groups. Prussian blue and Luxol fast blue staining were performed to assess pathology. The correlations of the mean grayscale value (mGSV) of the pathology results and the MRI metrics were analyzed to evaluate the multiparameter MRI results. One-way ANOVA and post hoc comparison showed that the normalized T2WI (T2-nor), fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) values were significantly different among the six groups, while the mean phase (Φ) value of SWI was not significantly different among the groups. Correlation analysis showed that the correlation between the T2-nor and mGSV was higher than that among the other values. The correlations among the FA, RD, MD, and mGSV remained instructive. In conclusion, ultrahigh-field multiparameter MRI can reflect the pathological changes associated with and the underlying mechanisms of demyelination and remyelination in MS after the successful establishment of an acute CPZ-induced model.
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16
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Kassa RM, Sechi E, Flanagan EP, Kaufmann TJ, Kantarci OH, Weinshenker BG, Mandrekar J, Schmalstieg WF, Paz Soldan MM, Keegan BM. Onset of progressive motor impairment in patients with critical central nervous system demyelinating lesions. Mult Scler 2020; 27:895-902. [PMID: 32667237 DOI: 10.1177/1352458520940983] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To compare progressive motor impairment onset attributable to a "critical" central nervous system (CNS) demyelinating lesion in patients with highly restricted versus unlimited magnetic resonance imaging (MRI) lesion burden. METHODS We identified 135 patients with progressive motor impairment for ⩾1 year attributable to a "critical" demyelinating lesion with: MRI burden of 1 lesion ("progressive solitary sclerosis"), 2-5 lesions ("progressive paucisclerosis"), or unrestricted (>5) lesions and "progressive unilateral hemiparesis." Neuroradiology review of brain and spinal cord MRI documented unequivocally demyelinating lesions. RESULTS A total of 33 (24.4%) patients had progressive solitary sclerosis; 56 (41.5%) patients had progressive paucisclerosis; and 46 (34.1%) patients had progressive unilateral hemiparesis. Median age at onset of progressive motor impairment was younger in progressive solitary sclerosis (49 years; range 24-73) and progressive paucisclerosis (50 years; range 30-64) than in progressive unilateral hemiparesis (54 years; range 39-77; p = 0.02 and p = 0.003, respectively). Within progressive unilateral hemiparesis, motor-progression onset was similar between those with 4-10, 11-20, or >20 brain lesions (55, 54, 53 years of age, respectively; p = 0.44). CONCLUSION Motor-progression age is similar, but paradoxically earlier, in cohorts with highly restricted CNS lesion burden than in those with unrestricted lesion burden with progressive unilateral hemiparetic MS. The "critical" demyelinating lesion rather than total brain MRI lesion burden is the major contributor to motor-progression onset in these cohorts.
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Affiliation(s)
- Roman M Kassa
- Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN, USA/Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Elia Sechi
- Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eoin P Flanagan
- Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Orhun H Kantarci
- Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Brian G Weinshenker
- Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Jay Mandrekar
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | | | | | - B Mark Keegan
- Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN, USA
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Lakhani DA, Schilling KG, Xu J, Bagnato F. Advanced Multicompartment Diffusion MRI Models and Their Application in Multiple Sclerosis. AJNR Am J Neuroradiol 2020; 41:751-757. [PMID: 32354707 DOI: 10.3174/ajnr.a6484] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Accepted: 02/03/2020] [Indexed: 01/22/2023]
Abstract
Conventional MR imaging techniques are sensitive to pathologic changes of the brain and spinal cord seen in MS, but they lack specificity for underlying axonal and myelin integrity. By isolating the signal contribution from different tissue compartments, newly developed advanced multicompartment diffusion MR imaging models have the potential to detect specific tissue subtypes and associated injuries with increased pathologic specificity. These models include neurite orientation dispersion and density imaging, diffusion basis spectrum imaging, multicompartment microscopic diffusion MR imaging with the spherical mean technique, and models enabled through high-gradient diffusion MR imaging. In this review, we provide an appraisal of the current literature on the physics principles, histopathologic validation, and clinical applications of each of these techniques in both brains and spinal cords of patients with MS. We discuss limitations of each of the methods and directions that future research could take to provide additional validation of their roles as biomarkers of axonal and myelin injury in MS.
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Affiliation(s)
- D A Lakhani
- From the Neuroimaging Unit (D.A.L., F.B.), Neuroimmunology Division, Department of Neurology
- Division of Internal Medicine (D.A.L.)
- Department of Radiology (D.A.L.), West Virginia University, Morgantown, West Virginia
| | - K G Schilling
- Department of Radiology and Radiological Sciences (K.G.S., J.X.), Vanderbilt University Institute of Imaging Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - J Xu
- Department of Radiology and Radiological Sciences (K.G.S., J.X.), Vanderbilt University Institute of Imaging Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - F Bagnato
- From the Neuroimaging Unit (D.A.L., F.B.), Neuroimmunology Division, Department of Neurology
- Department of Neurology (F.B.), VA Tennessee Valley Healthcare System, Nashville, Tennessee
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