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Elkady AM, Elliott C, Fetco D, Araujo D, Karimaghaloo Z, Ganzetti M, Clayton D, Craveiro L, Kazlauskaite A, Narayanan S, Arnold DL, Rudko DA. Longitudinal Multiparametric Quantitative MRI Evaluation of Acute and Chronic Multiple Sclerosis Paramagnetic Rim Lesions. J Magn Reson Imaging 2024. [PMID: 39239775 DOI: 10.1002/jmri.29583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 08/07/2024] [Accepted: 08/07/2024] [Indexed: 09/07/2024] Open
Abstract
BACKGROUND Multiple sclerosis (MS) paramagnetic rim lesions (PRLs) are markers of chronic active biology and exhibit complex iron and myelin changes that may complicate quantification when using conventional MRI approaches. PURPOSE To conduct a multiparametric MRI analysis of PRLs. STUDY TYPE Retrospective/longitudinal. SUBJECTS Ninety-five progressive MS subjects with at least one persistent PRL who were enrolled in the CONSONANCE trial. FIELD STRENGTH/SEQUENCE 3-T/Susceptibility-weighted, T1-weighted, T2-weighted, and fluid-attenuated inversion recovery. ASSESSMENT Acute/chronic PRLs and non-PRLs were measured at screening, 24, 48, and 96 weeks using quantitative magnetic susceptibility (QS), R2*, and standardized T1w/T2w ratio (sT1w/T2w). PRL analyses were performed for whole lesion, core, and rim. The correlations between PRL core and rim sT1w/T2w, QS, and R2* were assessed. STATISTICAL TESTS Linear mixed models. A P-value <0.05 was considered significant. RESULTS There was a significant decrease in sT1w/T2w (-0.24 ± -5.3 × 10-3) and R2* (-3.6 ± 2.2 Hz) but a significant increase in QS (+21 ± 1.3 ppb) using whole-lesion analysis of chronic PRLs compared to non-PRLs at screening. Tissue damage accumulated at the 96-week time point was more evident in acute/chronic PRLs compared to acute/chronic non-PRLs (ΔsT1w/T2w = -0.21/-0.24 ± 0.033/0.0053; ΔR2* = -4.4/-3.6 ± 1.4/2.2 Hz). New, acute PRL sT1w/T2w significantly increased in lesion core (+4.3 × 10-3 ± 1.2 × 10-4) and rim (+5.6 × 10-3 ± 1.2 × 10-4) 24 weeks post lesion inception, suggestive of partial recovery. Chronic PRLs, contrastingly, showed significant decreases in sT1w/T2w over the initial 24 weeks for both core (-2.1 × 10-4 ± 2.0 × 10-5) and rim (-2.4 × 10-4 ± 2.0 × 10-5), indicative of irreversible tissue damage. Significant positive correlations between PRL core and rim sT1w/T2w (R2 = 0.53), R2* (R2 = 0.69) and QS (R2 = 0.52) were observed. DATA CONCLUSION Multiparametric assessment of PRLs has the potential to be a valuable tool for assessing complex iron and myelin changes in chronic active PRLs of progressive MS patients. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Ahmed M Elkady
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- NeuroRx Research, Montreal, Quebec, Canada
| | | | - Dumitru Fetco
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- NeuroRx Research, Montreal, Quebec, Canada
| | - David Araujo
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- NeuroRx Research, Montreal, Quebec, Canada
| | | | | | | | | | | | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- NeuroRx Research, Montreal, Quebec, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- NeuroRx Research, Montreal, Quebec, Canada
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
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2
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Torgerson C, Ahmadi H, Choupan J, Fan CC, Blosnich JR, Herting MM. Sex, gender diversity, and brain structure in early adolescence. Hum Brain Mapp 2024; 45:e26671. [PMID: 38590252 PMCID: PMC11002534 DOI: 10.1002/hbm.26671] [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: 07/28/2023] [Revised: 02/27/2024] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.
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Affiliation(s)
- Carinna Torgerson
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Hedyeh Ahmadi
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Jeiran Choupan
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Chun Chieh Fan
- Center for Population Neuroscience and GeneticsLaureate Institute for Brain ResearchTulsaOklahomaUSA
- Department of Radiology, School of MedicineUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - John R. Blosnich
- Suzanne Dworak‐Peck School of Social WorkUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Megan M. Herting
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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3
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Hartung TJ, Cooper G, Jünger V, Komnenić D, Ryan L, Heine J, Chien C, Paul F, Prüss H, Finke C. The T1-weighted/T2-weighted ratio as a biomarker of anti-NMDA receptor encephalitis. J Neurol Neurosurg Psychiatry 2024; 95:366-373. [PMID: 37798094 PMCID: PMC10958321 DOI: 10.1136/jnnp-2023-332069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis rarely causes visible lesions in conventional MRI, yet advanced imaging detects extensive white matter damage. To improve prognostic capabilities, we evaluate the T1-weighted/T2-weighted (T1w/T2w) ratio, a measure of white matter integrity computable from clinical MRI sequences, in NMDAR encephalitis and examine its associations with cognitive impairment. METHODS T1-weighted and T2-weighted MRI were acquired cross-sectionally at 3 Tesla in 53 patients with NMDAR encephalitis (81% women, mean age 29 years) and 53 matched healthy controls. Quantitative and voxel-wise group differences in T1w/T2w ratios and associations with clinical and neuropsychological outcomes were assessed. P-values were false discovery rate (FDR) adjusted where multiple tests were conducted. RESULTS Patients with NMDAR encephalitis had significantly lower T1w/T2w ratios across normal appearing white matter (p=0.009, Hedges' g=-0.51), which was associated with worse verbal episodic memory performance (r=0.39, p=0.005, p(FDR)=0.026). White matter integrity loss was observed in the corticospinal tract, superior longitudinal fascicle, optic radiation and callosal body with medium to large effects (Cohen's d=[0.42-1.17]). In addition, patients showed decreased T1w/T2w ratios in the hippocampus (p=0.002, p(FDR)=0.005, Hedges' g=-0.62), amygdala (p=0.002, p(FDR)=0.005, Hedges' g=-0.63) and thalamus (p=0.010, p(FDR)=0.019, Hedges' g=-0.51). CONCLUSIONS The T1w/T2w ratio detects microstructural changes in grey and white matter of patients with NMDAR encephalitis that correlate with cognitive performance. Computable from conventional clinical MRI sequences, this measure shows promise in bridging the clinico-radiological dissociation in NMDAR encephalitis and could serve as an imaging outcome measure in clinical trials.
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Affiliation(s)
- Tim Julian Hartung
- Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Graham Cooper
- Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Valentin Jünger
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center (NCRC), Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Darko Komnenić
- Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Lara Ryan
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Josephine Heine
- Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center (NCRC), Charité - Universitätsmedizin Berlin, Berlin, Germany
- Medizinische Klinik m.S. Psychosomatik, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Harald Prüss
- Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany
| | - Carsten Finke
- Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
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4
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Wang J, Sugiyama A, Yokota H, Hirano S, Yamamoto T, Yamanaka Y, Araki N, Ito S, Paul F, Kuwabara S. Differentiation between Parkinson's Disease and the Parkinsonian Subtype of Multiple System Atrophy Using the Magnetic Resonance T1w/T2w Ratio in the Middle Cerebellar Peduncle. Diagnostics (Basel) 2024; 14:201. [PMID: 38248077 PMCID: PMC10814850 DOI: 10.3390/diagnostics14020201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/30/2023] [Accepted: 01/15/2024] [Indexed: 01/23/2024] Open
Abstract
Multiple system atrophy with predominant parkinsonism (MSA-P) can hardly be distinguished from Parkinson's disease (PD) clinically in the early stages. This study investigated whether a standardized T1-weighted/T2-weighted ratio (sT1w/T2w ratio) can effectively detect degenerative changes in the middle cerebellar peduncle (MCP) associated with MSA-P and PD and evaluated its potential to distinguish between these two diseases. We included 35 patients with MSA-P, 32 patients with PD, and 17 controls. T1w and T2w scans were acquired using a 1.5-T MR system. The MCP sT1w/T2w ratio was analyzed via SPM12 using a region-of-interest approach in a normalized space. The diagnostic performance of the MCP sT1w/T2w ratio was compared between the MSA-P, PD, and controls. Patients with MSA-P had significantly lower MCP sT1w/T2w ratios than patients with PD and controls. Furthermore, MCP sT1w/T2w ratios were lower in patients with PD than in the controls. The MCP sT1w/T2w ratio showed excellent or good accuracy for differentiating MSA-P or PD from the control (area under the curve (AUC) = 0.919 and 0.814, respectively) and substantial power for differentiating MSA-P from PD (AUC = 0.724). Therefore, the MCP sT1w/T2w ratio is sensitive in detecting degenerative changes in the MCP associated with MSA-P and PD and is useful in distinguishing MSA-P from PD.
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Affiliation(s)
- Jiaqi Wang
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
| | - Atsuhiko Sugiyama
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
| | - Hajime Yokota
- Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Shigeki Hirano
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
| | - Tatsuya Yamamoto
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
- Department of Rehabilitation, Division of Occupational Therapy, Chiba Prefectural University of Health Sciences, Chiba 261-0014, Japan
| | - Yoshitaka Yamanaka
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
- Urayasu Rehabilitation Education Center, Chiba University Hospital, Urayasu 279-0023, Japan
| | - Nobuyuki Araki
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
| | - Shoichi Ito
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
- Department of Medical Education, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Einstein Center for Neurosciences, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Department of Neurology, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Satoshi Kuwabara
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (J.W.); (T.Y.); (S.I.); (S.K.)
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5
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Torgerson C, Ahmadi H, Choupan J, Fan CC, Blosnich JR, Herting MM. Sex, gender diversity, and brain structure in children ages 9 to 11 years old. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.28.551036. [PMID: 37546960 PMCID: PMC10402171 DOI: 10.1101/2023.07.28.551036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.
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Affiliation(s)
- Carinna Torgerson
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
- Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Hedyeh Ahmadi
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Jeiran Choupan
- Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Chun Chieh Fan
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Radiology, School of Medicine, University of California, San Diego
| | - John R. Blosnich
- Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, USA
| | - Megan M. Herting
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
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6
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Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
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Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
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7
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Chen L, Wu Z, Zhao F, Wang Y, Lin W, Wang L, Li G. An attention-based context-informed deep framework for infant brain subcortical segmentation. Neuroimage 2023; 269:119931. [PMID: 36746299 PMCID: PMC10241225 DOI: 10.1016/j.neuroimage.2023.119931] [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: 11/05/2022] [Revised: 01/13/2023] [Accepted: 02/03/2023] [Indexed: 02/06/2023] Open
Abstract
Precise segmentation of subcortical structures from infant brain magnetic resonance (MR) images plays an essential role in studying early subcortical structural and functional developmental patterns and diagnosis of related brain disorders. However, due to the dynamic appearance changes, low tissue contrast, and tiny subcortical size in infant brain MR images, infant subcortical segmentation is a challenging task. In this paper, we propose a context-guided, attention-based, coarse-to-fine deep framework to precisely segment the infant subcortical structures. At the coarse stage, we aim to directly predict the signed distance maps (SDMs) from multi-modal intensity images, including T1w, T2w, and the ratio of T1w and T2w images, with an SDM-Unet, which can leverage the spatial context information, including the structural position information and the shape information of the target structure, to generate high-quality SDMs. At the fine stage, the predicted SDMs, which encode spatial-context information of each subcortical structure, are integrated with the multi-modal intensity images as the input to a multi-source and multi-path attention Unet (M2A-Unet) for achieving refined segmentation. Both the 3D spatial and channel attention blocks are added to guide the M2A-Unet to focus more on the important subregions and channels. We additionally incorporate the inner and outer subcortical boundaries as extra labels to help precisely estimate the ambiguous boundaries. We validate our method on an infant MR image dataset and on an unrelated neonatal MR image dataset. Compared to eleven state-of-the-art methods, the proposed framework consistently achieves higher segmentation accuracy in both qualitative and quantitative evaluations of infant MR images and also exhibits good generalizability in the neonatal dataset.
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Affiliation(s)
- Liangjun Chen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhengwang Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Fenqiang Zhao
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ya Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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8
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Sui YV, Masurkar AV, Rusinek H, Reisberg B, Lazar M. Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study. Neuroimage 2022; 264:119743. [PMID: 36368498 PMCID: PMC9904172 DOI: 10.1016/j.neuroimage.2022.119743] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/31/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
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Affiliation(s)
- Yu Veronica Sui
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Corresponding author. (Y.V. Sui)
| | - Arjun V. Masurkar
- Department of Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, USA,Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA,Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Barry Reisberg
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariana Lazar
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA
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9
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Wu Y, Ridwan AR, Niaz MR, Qi X, Zhang S, Alzheimer's Disease Neuroimaging Initiative, Bennett DA, Arfanakis K. Development of high quality T 1-weighted and diffusion tensor templates of the older adult brain in a common space. Neuroimage 2022; 260:119417. [PMID: 35793748 PMCID: PMC9437946 DOI: 10.1016/j.neuroimage.2022.119417] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/27/2022] [Accepted: 06/27/2022] [Indexed: 01/23/2023] Open
Abstract
High-quality T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates that are representative of the individuals under study enhance the accuracy of template-based neuroimaging investigations, and when they are also located in a common space they facilitate optimal integration of information on brain morphometry and diffusion characteristics. However, such multimodal templates have not been constructed for the brain of older adults. The purpose of this work was threefold: (A) to introduce an iterative method for construction of multimodal T1w and DTI templates that aims at maximizing the quality of each template separately as well as the spatial matching between templates, (B) to use this method to develop T1w and DTI templates of the older adult brain in a common space, and (C) to evaluate the performance of the method across iterations and compare it to the performance of state-of-the-art approaches based on multichannel registration. It was demonstrated that more iterations of the proposed method enhanced the characteristics and spatial matching of the resulting T1w and DTI templates. The templates of the older adult brain generated by the final iteration of the proposed method provided better delineation of brain structures, higher discriminability between tissues, and higher image sharpness near the cortex compared to templates generated with approaches employing multichannel registration. In addition, the spatial matching between the T1w and DTI templates constructed by the proposed method approximated the template alignment achieved with methods employing multichannel registration. Finally, when using the templates generated by the proposed method as references for spatial normalization of older adult T1w and DTI data, both the intra-modality inter-subject normalization precision and the inter-modality spatial matching were higher in most metrics than those achieved with templates constructed with other methods. Overall, the present work brought new insights into multimodal template construction, generated much-needed high quality T1w and DTI templates of the older adult brain in a common space, and conducted a thorough, quantitative evaluation of available multimodal template construction methods.
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Affiliation(s)
- Yingjuan Wu
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL USA
| | - Abdur Raquib Ridwan
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL USA
| | - Mohammad Rakeen Niaz
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL USA
| | - Xiaoxiao Qi
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL USA
| | - Shengwei Zhang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois USA
| | - Alzheimer's Disease Neuroimaging Initiative
- A portion of the data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois USA
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL USA; Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois USA.
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10
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Gd 2O 3-mesoporous silica/gold nanoshells: A potential dual T1/ T2 contrast agent for MRI-guided localized near-IR photothermal therapy. Proc Natl Acad Sci U S A 2022; 119:e2123527119. [PMID: 35858309 PMCID: PMC9303993 DOI: 10.1073/pnas.2123527119] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
A promising clinical trial utilizing gold-silica core-shell nanostructures coated with polyethylene glycol (PEG) has been reported for near-infrared (NIR) photothermal therapy (PTT) of prostate cancer. The next critical step for PTT is the visualization of therapeutically relevant nanoshell (NS) concentrations at the tumor site. Here we report the synthesis of PEGylated Gd2O3-mesoporous silica/gold core/shell NSs (Gd2O3-MS NSs) with NIR photothermal properties that also supply sufficient MRI contrast to be visualized at therapeutic doses (≥108 NSs per milliliter). The nanoparticles have r1 relaxivities more than three times larger than those of conventional T1 contrast agents, requiring less concentration of Gd3+ to observe an equivalent signal enhancement in T1-weighted MR images. Furthermore, Gd2O3-MS NS nanoparticles have r2 relaxivities comparable to those of existing T2 contrast agents, observed in agarose phantoms. This highly unusual combination of simultaneous T1 and T2 contrast allows for MRI enhancement through different approaches. As a rudimentary example, we demonstrate T1/T2 ratio MR images with sixfold contrast signal enhancement relative to its T1 MRI and induced temperature increases of 20 to 55 °C under clinical illumination conditions. These nanoparticles facilitate MRI-guided PTT while providing real-time temperature feedback through thermal MRI mapping.
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11
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Diagnostic efficacy of the magnetic resonance T1w/T2w ratio for the middle cerebellar peduncle in multiple system atrophy and spinocerebellar ataxia: A preliminary study. PLoS One 2022; 17:e0267024. [PMID: 35427382 PMCID: PMC9012356 DOI: 10.1371/journal.pone.0267024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 04/01/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The standardized T1-weighted/T2-weighted (sT1w/T2w) ratio for the middle cerebellar peduncle (MCP) has been reported to be sensitive for detecting degenerative changes in the cerebellar subtype of multiple system atrophy (MSA-C), even in the early stages. We aimed to investigate the diagnostic value of the MCP sT1w/T2w ratio for differentiating between MSA-C and spinocerebellar ataxia (SCA). METHODS We included 32 MSA-C, 8 SCA type 3 (SCA3), 16 SCA type 6 (SCA6) patients, and 17 controls, and the MCP sT1w/T2w ratio was analyzed using a region-of-interest approach. The diagnostic performance of the MCP sT1w/T2w ratio in discriminating among MSA-C, SCA3, and SCA6 was assessed and compared with diagnosis based on visual interpretation of MCP hyperintensities and the "hot cross bun" (HCB) sign. RESULTS MCP sT1w/T2w ratio values were markedly lower in patients with MSA-C than in those with SCA3, those with SCA6, and controls (p < 0.001). The MCP sT1w/T2w ratio showed high diagnostic accuracy for distinguishing MSA-C from SCA3 (area under curve = 0.934), SCA6 (area under curve = 0.965), and controls (area under curve = 0.980). The diagnostic accuracy of the MCP sT1w/T2w ratio for differentiating MSA-C from SCA3 or SCA6 (90.0% for MSA-C vs. SCA3, and 91.7% for MSA-C vs. SCA6) was comparable to or superior than that of visual interpretation of MCP hyperintensities (80.0-87.5% in MSA-C vs. SCA3 and 87.6-97.9% in MSA-C vs. SCA6) or the HCB sign (72.5-80.0% in MSA-C vs. SCA3 and 77.1-93.8% in MSA-C vs. SCA6). CONCLUSIONS The MCP sT1w/T2w ratio might be a sensitive imaging-based marker for detecting MSA-C-related changes and differentiating MSA-C from SCA3 or SCA6.
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12
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Preziosa P, Pagani E, Meani A, Moiola L, Rodegher M, Filippi M, Rocca MA. Slowly Expanding Lesions Predict 9-Year Multiple Sclerosis Disease Progression. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:9/2/e1139. [PMID: 35105685 PMCID: PMC8808355 DOI: 10.1212/nxi.0000000000001139] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 12/15/2021] [Indexed: 11/15/2022]
Abstract
Background and Objectives Chronic active lesions contribute to multiple sclerosis (MS) severity, but their association with long-term disease progression has not been evaluated yet. White matter (WM) lesions showing linear expansion over time on serial T1- and T2-weighted scans (i.e., slowly expanding lesions [SELs]) have been proposed as a marker of chronic inflammation. In this study, we assessed whether SEL burden and microstructural abnormalities were associated with Expanded Disability Status Scale (EDSS) score worsening and secondary progressive (SP) conversion at 9.1-year follow-up in patients with relapsing-remitting (RR) MS. Methods In 52 patients with RRMS, SELs were identified among WM lesions by linearly fitting the Jacobian of the nonlinear deformation field between time points obtained combining 3T brain T1- and T2-weighted scans acquired at baseline and months 6, 12, and 24. Logistic regression analysis was applied to investigate the associations of SEL number, volume, magnetization transfer ratio (MTR), and T1-weighted signal intensity with disability worsening (i.e., EDSS score increase) and SP conversion after a median follow-up of 9.1 years. Results At follow-up, 20/52 (38%) patients with MS showed EDSS score worsening; 13/52 (25%) showed SP conversion. A higher baseline EDSS score (for each point higher: OR = 3.15 [95% CI = 1.61; 8.38], p = 0.003), a higher proportion of SELs among baseline lesions (for each % increase: OR = 1.22 [1.04; 1.58], p = 0.04), and lower baseline MTR values of SELs (for each % higher: OR = 0.66 [0.41; 0.92], p = 0.033) were significant independent predictors of EDSS score worsening at follow-up (C-index = 0.892). A higher baseline EDSS score (for each point higher: OR = 6.37 [1.98; 20.53], p = 0.002) and lower baseline MTR values of SELs (for each % higher: OR = 0.48 [0.25; 0.89], p = 0.02) independently predicted SPMS conversion (C-index = 0.947). Discussion The proportion of SELs is associated with MS progression after 9 years. More severe SEL microstructural abnormalities independently predict EDSS score worsening and SPMS conversion. The quantification of SEL burden and damage using T1-, T2-weighted, and MTR sequences may identify patients with RRMS at a higher risk of long-term disability progression and SPMS conversion. Classification of Evidence This study provides Class III evidence that in patients with RRMS starting treatment with natalizumab or fingolimod, the proportion of SELs on brain MRI was associated with EDSS score worsening and SPMS conversion at 9-year follow-up.
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Affiliation(s)
- Paolo Preziosa
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy
| | - Alessandro Meani
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy
| | - Lucia Moiola
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy
| | - Mariaemma Rodegher
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy
| | - Massimo Filippi
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy
| | - Maria A Rocca
- From the Neuroimaging Research Unit (P.P., E.P., A.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (P.P., L.M., M.R., M.F., M.A.R.); Neurorehabilitation Unit (M.F.); Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (M.F., M.A.R.); Milan, Italy.
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13
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Albishri AA, Shah SJH, Kang SS, Lee Y. AM-UNet: automated mini 3D end-to-end U-net based network for brain claustrum segmentation. MULTIMEDIA TOOLS AND APPLICATIONS 2022; 81:36171-36194. [PMID: 35035265 PMCID: PMC8742670 DOI: 10.1007/s11042-021-11568-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 09/08/2021] [Accepted: 09/20/2021] [Indexed: 06/14/2023]
Abstract
Recent advances in deep learning (DL) have provided promising solutions to medical image segmentation. Among existing segmentation approaches, the U-Net-based methods have been used widely. However, very few U-Net-based studies have been conducted on automatic segmentation of the human brain claustrum (CL). The CL segmentation is challenging due to its thin, sheet-like structure, heterogeneity of its image modalities and formats, imperfect labels, and data imbalance. We propose an automatic optimized U-Net-based 3D segmentation model, called AM-UNet, designed as an end-to-end process of the pre and post-process techniques and a U-Net model for CL segmentation. It is a lightweight and scalable solution which has achieved the state-of-the-art accuracy for automatic CL segmentation on 3D magnetic resonance images (MRI). On the T1/T2 combined MRI CL dataset, AM-UNet has obtained excellent results, including Dice, Intersection over Union (IoU), and Intraclass Correlation Coefficient (ICC) scores of 82%, 70%, and 90%, respectively. We have conducted the comparative evaluation of AM-UNet with other pre-existing models for segmentation on the MRI CL dataset. As a result, medical experts confirmed the superiority of the proposed AM-UNet model for automatic CL segmentation. The source code and model of the AM-UNet project is publicly available on GitHub: https://github.com/AhmedAlbishri/AM-UNET.
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Affiliation(s)
- Ahmed Awad Albishri
- School of Computing and Engineering, University of Missouri-Kansas City, Kansas City, MO 64110 USA
- College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia
| | - Syed Jawad Hussain Shah
- School of Computing and Engineering, University of Missouri-Kansas City, Kansas City, MO 64110 USA
| | - Seung Suk Kang
- Department of Psychiatry Biomedical Sciences, School of Medicine, University of Missouri-Kansas City, Kansas City, MO 64110 USA
| | - Yugyung Lee
- School of Computing and Engineering, University of Missouri-Kansas City, Kansas City, MO 64110 USA
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Nerland S, Jørgensen KN, Nordhøy W, Maximov II, Bugge RAB, Westlye LT, Andreassen OA, Geier OM, Agartz I. Multisite reproducibility and test-retest reliability of the T1w/T2w-ratio: A comparison of processing methods. Neuroimage 2021; 245:118709. [PMID: 34848300 DOI: 10.1016/j.neuroimage.2021.118709] [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] [Received: 06/09/2021] [Revised: 10/29/2021] [Accepted: 11/02/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The ratio of T1-weighted (T1w) and T2-weighted (T2w) magnetic resonance imaging (MRI) images is often used as a proxy measure of cortical myelin. However, the T1w/T2w-ratio is based on signal intensities that are inherently non-quantitative and known to be affected by extrinsic factors. To account for this a variety of processing methods have been proposed, but a systematic evaluation of their efficacy is lacking. Given the dependence of the T1w/T2w-ratio on scanner hardware and T1w and T2w protocols, it is important to ensure that processing pipelines perform well also across different sites. METHODS We assessed a variety of processing methods for computing cortical T1w/T2w-ratio maps, including correction methods for nonlinear field inhomogeneities, local outliers, and partial volume effects as well as intensity normalisation. These were implemented in 33 processing pipelines which were applied to four test-retest datasets, with a total of 170 pairs of T1w and T2w images acquired on four different MRI scanners. We assessed processing pipelines across datasets in terms of their reproducibility of expected regional distributions of cortical myelin, lateral intensity biases, and test-retest reliability regionally and across the cortex. Regional distributions were compared both qualitatively with histology and quantitatively with two reference datasets, YA-BC and YA-B1+, from the Human Connectome Project. RESULTS Reproducibility of raw T1w/T2w-ratio distributions was overall high with the exception of one dataset. For this dataset, Spearman rank correlations increased from 0.27 to 0.70 after N3 bias correction relative to the YA-BC reference and from -0.04 to 0.66 after N4ITK bias correction relative to the YA-B1+ reference. Partial volume and outlier corrections had only marginal effects on the reproducibility of T1w/T2w-ratio maps and test-retest reliability. Before intensity normalisation, we found large coefficients of variation (CVs) and low intraclass correlation coefficients (ICCs), with total whole-cortex CV of 10.13% and whole-cortex ICC of 0.58 for the raw T1w/T2w-ratio. Intensity normalisation with WhiteStripe, RAVEL, and Z-Score improved total whole-cortex CVs to 5.91%, 5.68%, and 5.19% respectively, whereas Z-Score and Least Squares improved whole-cortex ICCs to 0.96 and 0.97 respectively. CONCLUSIONS In the presence of large intensity nonuniformities, bias field correction is necessary to achieve acceptable correspondence with known distributions of cortical myelin, but it can be detrimental in datasets with less intensity inhomogeneity. Intensity normalisation can improve test-retest reliability and inter-subject comparability. However, both bias field correction and intensity normalisation methods vary greatly in their efficacy and may affect the interpretation of results. The choice of T1w/T2w-ratio processing method must therefore be informed by both scanner and acquisition protocol as well as the given study objective. Our results highlight limitations of the T1w/T2w-ratio, but also suggest concrete ways to enhance its usefulness in future studies.
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Affiliation(s)
- Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo 0319, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Kjetil N Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo 0319, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wibeke Nordhøy
- Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ivan I Maximov
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Robin A B Bugge
- Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Oliver M Geier
- Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo 0319, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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15
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Moura FS, Beraldo RG, Ferreira LA, Siltanen S. Anatomical atlas of the upper part of the human head for electroencephalography and bioimpedance applications. Physiol Meas 2021; 42. [PMID: 34673557 DOI: 10.1088/1361-6579/ac3218] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/21/2021] [Indexed: 11/11/2022]
Abstract
Objective.The objective of this work is to develop a 4D (3D+T) statistical anatomical atlas of the electrical properties of the upper part of the human head for cerebral electrophysiology and bioimpedance applications.Approach.The atlas was constructed based on 3D magnetic resonance images (MRI) of 107 human individuals and comprises the electrical properties of the main internal structures and can be adjusted for specific electrical frequencies. T1w+T2w MRI images were used to segment the main structures of the head while angiography MRI was used to segment the main arteries. The proposed atlas also comprises a time-varying model of arterial brain circulation, based on the solution of the Navier-Stokes equation in the main arteries and their vascular territories.Main results.High-resolution, multi-frequency and time-varying anatomical atlases of resistivity, conductivity and relative permittivity were created and evaluated using a forward problem solver for EIT. The atlas was successfully used to simulate electrical impedance tomography measurements indicating the necessity of signal-to-noise between 100 and 125 dB to identify vascular changes due to the cardiac cycle, corroborating previous studies. The source code of the atlas and solver are freely available to download.Significance.Volume conductor problems in cerebral electrophysiology and bioimpedance do not have analytical solutions for nontrivial geometries and require a 3D model of the head and its electrical properties for solving the associated PDEs numerically. Ideally, the model should be made with patient-specific information. In clinical practice, this is not always the case and an average head model is often used. Also, the electrical properties of the tissues might not be completely known due to natural variability. Anatomical atlases are important tools forin silicostudies on cerebral circulation and electrophysiology that require statistically consistent data, e.g. machine learning, sensitivity analyses, and as a benchmark to test inverse problem solvers.
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Affiliation(s)
- Fernando S Moura
- Engineering, modelling and Applied Social Sciences Center, Federal University of ABC São Bernardo do Campo, São Paulo, Brazil.,Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Roberto G Beraldo
- Engineering, modelling and Applied Social Sciences Center, Federal University of ABC São Bernardo do Campo, São Paulo, Brazil
| | - Leonardo A Ferreira
- Engineering, modelling and Applied Social Sciences Center, Federal University of ABC São Bernardo do Campo, São Paulo, Brazil
| | - Samuli Siltanen
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
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16
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Sugiyama A, Cooper G, Hirano S, Yokota H, Mori M, Shimizu K, Yakiyama M, Finke C, Brandt AU, Paul F, Kuwabara S. Cognitive Impairment in Multiple System Atrophy Is Related to White Matter Damage Detected by the T1-Weighted/T2-Weighted Ratio. Eur Neurol 2021; 84:435-443. [PMID: 34284398 DOI: 10.1159/000517360] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 05/15/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION This study aimed to use a novel MRI contrast, the standardized T1-weighted/T2-weighted (sT1w/T2w) ratio, to assess damage of the white matter and gray matter in multiple system atrophy (MSA). Furthermore, this study investigated whether the sT1w/T2w ratio was associated with cognitive impairment in MSA. METHODS The white matter and gray matter sT1w/T2w ratio of 37 MSA patients and 19 healthy controls were measured. Correlation analyses were used to evaluate the relationship between sT1w/T2w ratio values and clinical variables, and a multivariate analysis was used to identify independent factors associated with cognitive impairment in MSA. RESULTS MSA patients showed a higher white matter sT1w/T2w ratio value than controls (p < 0.001), and the white matter sT1w/T2w ratio value was significantly correlated with the International Cooperative Ataxia Rating Scale score (r = 0.377, p = 0.021) and the Addenbrooke's cognitive examination III score (r = -0.438, p = 0.007). Cognitively impaired MSA patients had a significantly higher white matter sT1w/T2w ratio value than cognitively preserved MSA patients (p = 0.010), and the multiple logistic regression analysis revealed that the median white matter sT1w/T2w ratio value was independently associated with cognitive impairment in MSA. CONCLUSION The sT1w/T2w ratio is sensitive to degenerative changes in the white matter that is associated with cognitive ability in MSA patients.
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Affiliation(s)
- Atsuhiko Sugiyama
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Graham Cooper
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Department of Experimental Neurology and Center for Stroke Research, Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Shigeki Hirano
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan.,Medical Center for Dementia, Chiba University Hospital, Chiba, Japan
| | - Hajime Yokota
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Masahiro Mori
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Keisuke Shimizu
- Medical Center for Dementia, Chiba University Hospital, Chiba, Japan
| | | | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, University of California, Irvine, California, USA
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Satoshi Kuwabara
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan.,Medical Center for Dementia, Chiba University Hospital, Chiba, Japan
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Cooper G, Chien C, Zimmermann H, Bellmann-Strobl J, Ruprecht K, Kuchling J, Asseyer S, Brandt AU, Scheel M, Finke C, Paul F. Longitudinal analysis of T1w/T2w ratio in patients with multiple sclerosis from first clinical presentation. Mult Scler 2021; 27:2180-2190. [PMID: 33856249 PMCID: PMC8597181 DOI: 10.1177/13524585211003479] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background: Cross-sectional studies suggest normal appearing white matter (NAWM) integrity loss may lead to cortical atrophy in late-stage relapsing-remitting multiple sclerosis (MS). Objective: To investigate the relationship between NAWM integrity and cortical thickness from first clinical presentation longitudinally. Methods: NAWM integrity and cortical thickness were assessed with 3T magnetic resonance imaging (MRI) in 102 patients with clinically isolated syndrome or early MS (33.2 (20.1–60.1) years old, 68% female) from first clinical presentation over 2.8 ± 1.6 years. Fifty healthy controls (HCs) matched for age and sex were included. NAWM integrity was evaluated using the standardized T1w/T2w ratio (sT1w/T2w). The association between sT1w/T2w and cortical thickness was assessed using linear mixed models. The effect of disease activity was investigated using the No Evidence of Disease Activity (NEDA-3) criteria. Results: At baseline, sT1w/T2w (p = 0.152) and cortical thickness (p = 0.489) did not differ from HCs. Longitudinally, decreasing sT1w/T2w was associated with cortical thickness and increasing lesion burden (marginal R2 = 0.061). The association was modulated by failing NEDA-3 (marginal R2 = 0.097). Conclusion: sT1w/T2w may be a useful MRI biomarker for early MS, detecting relevant NAWM damage over time using conventional MRI scans, although with less sensitivity compared to quantitative measures.
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Affiliation(s)
- Graham Cooper
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/ Department of Experimental Neurology and Center for Stroke Research, Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany/ Einstein Center for Neurosciences, Berlin, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/ Department for Psychiatry and Psychotherapy-Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Hanna Zimmermann
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/ NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Judith Bellmann-Strobl
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/ NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Joseph Kuchling
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Susanna Asseyer
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/Department of Neurology, University of California, Irvine, California, USA
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/Department of Neuroradiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany/Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/ NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany/Einstein Center for Neurosciences, Berlin, Germany/Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
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18
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Sugiyama A, Yokota H, Hirano S, Cooper G, Mukai H, Koide K, Wang J, Ito S, Finke C, Brandt AU, Paul F, Kuwabara S. Magnetic resonance T1w/T2w ratio in the middle cerebellar peduncle might be a sensitive biomarker for multiple system atrophy. Eur Radiol 2020; 31:4277-4284. [PMID: 33241514 DOI: 10.1007/s00330-020-07521-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 10/10/2020] [Accepted: 11/13/2020] [Indexed: 12/26/2022]
Abstract
OBJECTIVE We aimed to investigate the use of a myelin-sensitive MRI contrast, the standardized T1-weighted/T2-weighted (sT1w/T2w) ratio, for detecting early changes in the middle cerebellar peduncle (MCP) in cerebellar subtype multiple system atrophy (MSA-C) patients. METHODS We included 28 MSA-C patients, including a subset of 17 MSA-C patients within 2 years of disease onset (early MSA-C), and 28 matched healthy controls. T1w and T2w scans were acquired using a 3-T MR system. The sT1w/T2w ratio in MCP was analyzed using SPM12 by utilizing a region-of-interest approach in normalized space. The diagnostic performance of the MCP sT1w/T2w ratio in discriminating MSA-C and the subgroup of early MSA-C from the matched controls was assessed. Correlation analyses were performed to evaluate the relationship between the MCP sT1w/T2w ratio and other clinical parameters including the International Cooperative Ataxia Scale (ICARS) score for quantifying cerebellar ataxia. RESULTS Compared to controls, the sT1w/T2w ratio in the MCP was markedly lower in all (p < 0.001) MSA-C patients and 17 early (p < 0.001) MSA-C patients. The MCP sT1w/T2w ratio had high sensitivity (96%) and specificity (100%) to distinguish MSA-C from controls (area under the curve = 0.99), even for the early MSA-C group (area under the curve = 0.99; sensitivity = 94%, specificity = 100%). The MCP sT1w/T2w ratio correlated with the ICARS score in early MSA-C. CONCLUSIONS The sT1w/T2w ratio can detect MSA-C-related changes in the MCP, even in the early stages of the disorder, and could be a sensitive biomarker for MSA-C. KEY POINTS • The sT1w/T2w ratio can detect MSA-C-related changes in the middle cerebellar peduncle, even in the early stages of the disorder. • The middle cerebellar peduncle sT1w/T2w ratio correlated with a cerebellar ataxia score in early MSA-C patients.
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Affiliation(s)
- Atsuhiko Sugiyama
- Department of Neurology, Graduate School of Medicine, Chiba University 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan.
| | - Hajime Yokota
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Shigeki Hirano
- Department of Neurology, Graduate School of Medicine, Chiba University 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan
| | - Graham Cooper
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Department of Experimental Neurology and Center for Stroke Research, Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Hiroki Mukai
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Kyosuke Koide
- Department of Neurology, Graduate School of Medicine, Chiba University 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan
| | - Jiaqi Wang
- Department of Neurology, Graduate School of Medicine, Chiba University 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan
| | - Shoichi Ito
- Department of Neurology, Graduate School of Medicine, Chiba University 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan.,Department of Medical Education, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, University of California, Irvine, CA, USA
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Satoshi Kuwabara
- Department of Neurology, Graduate School of Medicine, Chiba University 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan
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Preziosa P, Pagani E, Moiola L, Rodegher M, Filippi M, Rocca MA. Occurrence and microstructural features of slowly expanding lesions on fingolimod or natalizumab treatment in multiple sclerosis. Mult Scler 2020; 27:1520-1532. [DOI: 10.1177/1352458520969105] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background: In multiple sclerosis (MS), up to 57% of white matter lesions are chronically active. These slowly expanding lesions (SELs) contribute to disability progression. Objective: The aim of this study is to compare fingolimod and natalizumab effects on progressive linearly enlarging lesions (i.e. SELs), a putative biomarker of smouldering inflammation. Methods: Relapsing-remitting MS patients starting fingolimod ( n = 24) or natalizumab ( n = 28) underwent 3T brain magnetic resonance imaging (MRI) at baseline, months 6, 12 and 24. SELs were identified among baseline-visible lesions showing ⩾ 12.5% of annual increase, calculated by linearly fitting the Jacobian of the nonlinear deformation field between timepoints obtained combining T1- and T2-weighted scans. SEL burden, magnetization transfer ratio (MTR) and T1 signal intensity were compared using linear models. Results: The prevalences of fingolimod (75%) and natalizumab patients (46%) with ⩾ 1 SEL were not significantly different (adjusted- p = 0.08). Fingolimod group had higher SEL number and volume (adjusted- p ⩽ 0.047, not false discovery rate (FDR) survived). In both groups, SELs versus non-SELs showed lower MTR and T1 signal intensity (adjusted- p ⩽ 0.01, FDR-survived). Longitudinally, non-SEL MTR increased in both treatment groups (adjusted- p ⩽ 0.005, FDR-survived). T1 signal intensity decreased in SELs with both treatments (adjusted- p ⩽ 0.049, FDR-survived in fingolimod group) and increased in natalizumab non-SELs (adjusted- p = 0.03, FDR-survived). Conclusion: The effects of natalizumab and fingolimod on SEL occurrence seem modest, with natalizumab being slightly more effective. Both treatments may promote reparative mechanisms in stable or chronic inactive lesions.
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Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy/Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lucia Moiola
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy/Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy/Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy/Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy/Vita-Salute San Raffaele University, Milan, Italy
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20
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Sugiyama A, Cooper G, Hirano S, Yokota H, Mori M, Shimizu K, Yakiyama M, Finke C, Brandt AU, Paul F, Kuwabara S. WITHDRAWN: Cognitive impairment in multiple system atrophy is related to white matter damage detected by the T1w/T2w ratio. Parkinsonism Relat Disord 2020. [DOI: 10.1016/j.parkreldis.2020.05.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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21
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Feng ST, Huang M, Dong Z, Xu L, Li Y, Jia Y, Cai H, Shen B, Li ZP. MRI T2-Weighted Imaging and Fat-Suppressed T2-Weighted Imaging Image Fusion Technology Improves Image Discriminability for the Evaluation of Anal Fistulas. Korean J Radiol 2019; 20:429-437. [PMID: 30799574 PMCID: PMC6389820 DOI: 10.3348/kjr.2018.0260] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 11/02/2018] [Indexed: 12/16/2022] Open
Affiliation(s)
- Shi Ting Feng
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Mengqi Huang
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhi Dong
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ling Xu
- Faculty of Medicine and Dentistry, University of Western Australia, Perth, Australia
| | - Yin Li
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yingmei Jia
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Huasong Cai
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Bingqi Shen
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zi Ping Li
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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Li F, Wu D, Lui S, Gong Q, Sweeney JA. Clinical Strategies and Technical Challenges in Psychoradiology. Neuroimaging Clin N Am 2019; 30:1-13. [PMID: 31759566 DOI: 10.1016/j.nic.2019.09.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Psychoradiology is an emerging discipline at the intersection between radiology and psychiatry. It holds promise for playing a role in clinical diagnosis, evaluation of treatment response and prognosis, and illness risk prediction for patients with psychiatric disorders. Addressing complex issues, such as the biological heterogeneity of psychiatric syndromes and unclear neurobiological mechanisms underpinning radiological abnormalities, is a challenge that needs to be resolved. With the advance of multimodal imaging and more efforts in standardization of image acquisition and analysis, psychoradiology is becoming a promising tool for the future of clinical care for patients with psychiatric disorders.
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Affiliation(s)
- Fei Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China
| | - Dongsheng Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, No. 37 Guo Xue Lane, Chengdu 610041, China
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Suite 3200, 260 Stetson Street, Cincinnati, OH 45219, USA
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23
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Sepehrband F, Barisano G, Sheikh-Bahaei N, Cabeen RP, Choupan J, Law M, Toga AW. Image processing approaches to enhance perivascular space visibility and quantification using MRI. Sci Rep 2019; 9:12351. [PMID: 31451792 PMCID: PMC6710285 DOI: 10.1038/s41598-019-48910-x] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 08/15/2019] [Indexed: 02/03/2023] Open
Abstract
Imaging the perivascular spaces (PVS), also known as Virchow-Robin space, has significant clinical value, but there remains a need for neuroimaging techniques to improve mapping and quantification of the PVS. Current technique for PVS evaluation is a scoring system based on visual reading of visible PVS in regions of interest, and often limited to large caliber PVS. Enhancing the visibility of the PVS could support medical diagnosis and enable novel neuroscientific investigations. Increasing the MRI resolution is one approach to enhance the visibility of PVS but is limited by acquisition time and physical constraints. Alternatively, image processing approaches can be utilized to improve the contrast ratio between PVS and surrounding tissue. Here we combine T1- and T2-weighted images to enhance PVS contrast, intensifying the visibility of PVS. The Enhanced PVS Contrast (EPC) was achieved by combining T1- and T2-weighted images that were adaptively filtered to remove non-structured high-frequency spatial noise. EPC was evaluated on healthy young adults by presenting them to two expert readers and also through automated quantification. We found that EPC improves the conspicuity of the PVS and aid resolving a larger number of PVS. We also present a highly reliable automated PVS quantification approach, which was optimized using expert readings.
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Affiliation(s)
- Farshid Sepehrband
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Giuseppe Barisano
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Neuroscience graduate program, University of Southern California, Los Angeles, CA, USA
| | - Nasim Sheikh-Bahaei
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Radiology, Keck Hospital of USC, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jeiran Choupan
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Meng Law
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Radiology, Alfred Health, Melbourne, Australia
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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24
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Pagnozzi AM, Fripp J, Rose SE. Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies. Neuroimage 2019; 201:116018. [PMID: 31319182 DOI: 10.1016/j.neuroimage.2019.116018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 07/01/2019] [Accepted: 07/12/2019] [Indexed: 12/13/2022] Open
Abstract
The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.
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Affiliation(s)
- Alex M Pagnozzi
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia
| | - Stephen E Rose
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia
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25
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Kor D, Birkl C, Ropele S, Doucette J, Xu T, Wiggermann V, Hernández-Torres E, Hametner S, Rauscher A. The role of iron and myelin in orientation dependent R 2* of white matter. NMR IN BIOMEDICINE 2019; 32:e4092. [PMID: 31038240 DOI: 10.1002/nbm.4092] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 02/05/2019] [Accepted: 02/17/2019] [Indexed: 06/09/2023]
Abstract
Brain myelin and iron content are important parameters in neurodegenerative diseases such as multiple sclerosis (MS). Both myelin and iron content influence the brain's R2* relaxation rate. However, their quantification based on R2* maps requires a realistic tissue model that can be fitted to the measured data. In structures with low myelin content, such as deep gray matter, R2* shows a linear increase with increasing iron content. In white matter, R2* is not only affected by iron and myelin but also by the orientation of the myelinated axons with respect to the external magnetic field. Here, we propose a numerical model which incorporates iron and myelin, as well as fibre orientation, to simulate R2* decay in white matter. Applying our model to fibre orientation-dependent in vivo R2* data, we are able to determine a unique solution of myelin and iron content in global white matter. We determine an averaged myelin volume fraction of 16.02 ± 2.07% in non-lesional white matter of patients with MS, 17.32 ± 2.20% in matched healthy controls, and 18.19 ± 2.98% in healthy siblings of patients with MS. Averaged iron content was 35.6 ± 8.9 mg/kg tissue in patients, 43.1 ± 8.3 mg/kg in controls, and 47.8 ± 8.2 mg/kg in siblings. All differences in iron content between groups were significant, while the difference in myelin content between MS patients and the siblings of MS patients was significant. In conclusion, we demonstrate that a model that combines myelin-induced orientation-dependent and iron-induced orientation-independent components is able to fit in vivo R2* data.
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Affiliation(s)
- Daniel Kor
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Christoph Birkl
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Pediatrics (Division of Neurology), University of British Columbia, Vancouver, BC, Canada
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Jonathan Doucette
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Pediatrics (Division of Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Tianyou Xu
- Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK
| | - Vanessa Wiggermann
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Pediatrics (Division of Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Enedino Hernández-Torres
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Pediatrics (Division of Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Simon Hametner
- Institute of Neuropathology, University Medical Center Göttingen, Göttingen, Germany
| | - Alexander Rauscher
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Pediatrics (Division of Neurology), University of British Columbia, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
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26
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Senel LK, Kilic T, Gungor A, Kopanoglu E, Guven HE, Saritas EU, Koc A, Cukur T. Statistically Segregated k-Space Sampling for Accelerating Multiple-Acquisition MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:1701-1714. [PMID: 30640604 DOI: 10.1109/tmi.2019.2892378] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techniques can alleviate this limitation via randomly undersampled acquisitions. A frequent sampling strategy is to prescribe for each acquisition a different random pattern drawn from a common sampling density. However, naive random patterns often contain gaps or clusters across the acquisition dimension that, in turn, can degrade reconstruction quality or reduce scan efficiency. To address this problem, a statistically segregated sampling method is proposed for multiple-acquisition MRI. This method generates multiple patterns sequentially while adaptively modifying the sampling density to minimize k-space overlap across patterns. As a result, it improves incoherence across acquisitions while still maintaining similar sampling density across the radial dimension of k-space. Comprehensive simulations and in vivo results are presented for phase-cycled balanced steady-state free precession and multi-echo [Formula: see text]-weighted imaging. Segregated sampling achieves significantly improved quality in both Fourier and compressed-sensing reconstructions of multiple-acquisition datasets.
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27
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Cooper G, Finke C, Chien C, Brandt AU, Asseyer S, Ruprecht K, Bellmann-Strobl J, Paul F, Scheel M. Standardization of T1w/T2w Ratio Improves Detection of Tissue Damage in Multiple Sclerosis. Front Neurol 2019; 10:334. [PMID: 31024428 PMCID: PMC6465519 DOI: 10.3389/fneur.2019.00334] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 03/19/2019] [Indexed: 01/24/2023] Open
Abstract
Normal appearing white matter (NAWM) damage develops early in multiple sclerosis (MS) and continues in the absence of new lesions. The ratio of T1w and T2w (T1w/T2w ratio), a measure of white matter integrity, has previously shown reduced intensity values in MS NAWM. We evaluate the validity of a standardized T1w/T2w ratio (sT1w/T2w ratio) in MS and whether this method is sensitive in detecting MS-related differences in NAWM. T1w and T2w scans were acquired at 3 Tesla in 47 patients with relapsing-remitting MS and 47 matched controls (HC). T1w/T2w and sT1w/T2w ratios were then calculated. We compared between-group variability between T1w/T2w and sT1w/T2w ratio in HC and MS and assessed for group differences. We also evaluated the relationship between the T1w/T2w and sT1w/T2w ratios and clinically relevant variables. Compared to the classic T1w/T2w ratio, the between-subject variability in sT1w/T2w ratio showed a significant reduction in MS patients (p < 0.001) and HC (p < 0.001). However, only sT1w/T2w ratio values were reduced in patients compared to HC (p < 0.001). The sT1w/T2w ratio intensity values were significantly influenced by age, T2 lesion volume and group status (MS vs. HC) (adjusted R2 = 0.30, p < 0.001). We demonstrate the validity of the sT1w/T2w ratio in MS and that it is more sensitive to MS-related differences in NAWM compared to T1w/T2w ratio. The sT1w/T2w ratio shows promise as an easily-implemented measure of NAWM in MS using readily available scans and simple post-processing methods.
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Affiliation(s)
- Graham Cooper
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Claudia Chien
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Susanna Asseyer
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Judith Bellmann-Strobl
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
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28
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Viviani R, Pracht ED, Brenner D, Beschoner P, Stingl JC, Stöcker T. Multimodal MEMPRAGE, FLAIR, and [Formula: see text] Segmentation to Resolve Dura and Vessels from Cortical Gray Matter. Front Neurosci 2017; 11:258. [PMID: 28536501 PMCID: PMC5423271 DOI: 10.3389/fnins.2017.00258] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Accepted: 04/21/2017] [Indexed: 02/03/2023] Open
Abstract
While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast) with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.
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Affiliation(s)
- Roberto Viviani
- Institute of Psychology, University of InnsbruckInnsbruck, Austria.,Psychiatry and Psychotherapy Clinic III, University of UlmUlm, Germany
| | | | - Daniel Brenner
- German Center for Neurodegenerative Diseases (DZNE)Bonn, Germany
| | - Petra Beschoner
- Clinic for Psychosomatic Medicine and Psychotherapy, University of UlmUlm, Germany
| | - Julia C Stingl
- Research Division, Federal Institute for Drugs and Medical DevicesBonn, Germany.,Center for Translational Medicine, University of Bonn Medical SchoolBonn, Germany
| | - Tony Stöcker
- German Center for Neurodegenerative Diseases (DZNE)Bonn, Germany.,Department of Physics and Astronomy, University of BonnBonn, Germany
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29
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Hernández-Torres E, Kassner N, Forkert ND, Wei L, Wiggermann V, Daemen M, Machan L, Traboulsee A, Li D, Rauscher A. Anisotropic cerebral vascular architecture causes orientation dependency in cerebral blood flow and volume measured with dynamic susceptibility contrast magnetic resonance imaging. J Cereb Blood Flow Metab 2017; 37:1108-1119. [PMID: 27259344 PMCID: PMC5363485 DOI: 10.1177/0271678x16653134] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Measurements of cerebral perfusion using dynamic susceptibility contrast magnetic resonance imaging rely on the assumption of isotropic vascular architecture. However, a considerable fraction of vessels runs in parallel with white matter tracts. Here, we investigate the effects of tissue orientation on dynamic susceptibility contrast magnetic resonance imaging. Tissue orientation was measured using diffusion tensor imaging and dynamic susceptibility contrast was performed with gradient echo planar imaging. Perfusion parameters and the raw dynamic susceptibility contrast signals were correlated with tissue orientation. Additionally, numerical simulations were performed for a range of vascular volumes of both the isotropic vascular bed and anisotropic vessel components, as well as for a range of contrast agent concentrations. The effect of the contrast agent was much larger in white matter tissue perpendicular to the main magnetic field compared to white matter parallel to the main magnetic field. In addition, cerebral blood flow and cerebral blood volume were affected in the same way with angle-dependent variations of up to 130%. Mean transit time and time to maximum of the residual curve exhibited weak orientation dependency of 10%. Numerical simulations agreed with the measured data, showing that one-third of the white matter vascular volume is comprised of vessels running in parallel with the fibre tracts.
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Affiliation(s)
- Enedino Hernández-Torres
- 1 Department of Pediatrics, Division of Neurology, University of British Columbia, Vancouver, Canada.,2 UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
| | - Nora Kassner
- 3 Department of Physics, University of Heidelberg, Heidelberg, Germany
| | - Nils Daniel Forkert
- 4 Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Luxi Wei
- 2 UBC MRI Research Centre, University of British Columbia, Vancouver, Canada.,5 Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - Vanessa Wiggermann
- 1 Department of Pediatrics, Division of Neurology, University of British Columbia, Vancouver, Canada.,2 UBC MRI Research Centre, University of British Columbia, Vancouver, Canada.,5 Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - Madeleine Daemen
- 6 Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Lindsay Machan
- 7 Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Anthony Traboulsee
- 8 Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - David Li
- 2 UBC MRI Research Centre, University of British Columbia, Vancouver, Canada.,7 Department of Radiology, University of British Columbia, Vancouver, Canada.,8 Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Alexander Rauscher
- 1 Department of Pediatrics, Division of Neurology, University of British Columbia, Vancouver, Canada.,2 UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
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30
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Hernández-Torres E, Wiggermann V, Hametner S, Baumeister TR, Sadovnick AD, Zhao Y, Machan L, Li DKB, Traboulsee A, Rauscher A. Orientation Dependent MR Signal Decay Differentiates between People with MS, Their Asymptomatic Siblings and Unrelated Healthy Controls. PLoS One 2015; 10:e0140956. [PMID: 26489078 PMCID: PMC4619399 DOI: 10.1371/journal.pone.0140956] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Accepted: 10/02/2015] [Indexed: 11/19/2022] Open
Abstract
R2* relaxometry of the brain is a quantitative magnetic resonance technique which is influenced by iron and myelin content across different brain regions. Multiple sclerosis (MS) is a common inflammatory, demyelinating disease affecting both white and grey matter regions of the CNS. Using R2*, increased iron deposition has been described in deep gray matter of MS patients. Iron accumulation might promote oxidative stress in the brain, which can lead to cell death and neurodegeneration. However, recent histological work indicates that iron may be reduced within the normal appearing white matter (WM) in MS. In the present study we analyzed the R2* signal across the white matter in 39 patients with MS, 31 asymptomatic age matched siblings of patients and 30 age-matched controls. The measurement of R2* in white matter is affected by the signal's dependency on white matter fibre orientation with respect to the main magnetic field which can be accounted using diffusion tensor imaging. We observed a clear separation of the three study groups in R2*. The values in the MS group were significantly lower compared to the siblings and controls, while the siblings group presented with significantly higher R2* values than both unrelated healthy controls and patients. Furthermore, we found significantly decreased normal-appearing white matter R2* values in patients with more severe disease course. Angle resolved analysis of R2* improves the sensitivity for detecting subtle differences in WM R2* compared to standard histogram based analyses. Our findings suggest that the decreased R2* values in MS are due to diffuse tissue damage and decreased myelin in the normal appearing and diffusely abnormal WM. The increased R2* in unaffected siblings may identify a predisposition to increased iron and the potential for oxidative stress as a risk factor for developing MS.
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Affiliation(s)
- Enedino Hernández-Torres
- UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
| | - Vanessa Wiggermann
- UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - Simon Hametner
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Tobias R. Baumeister
- UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
- Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, Canada
| | - A. Dessa Sadovnick
- Department of Medicine (Neurology), University of British Columbia, Vancouver, Canada
- Centre for Brain Health, University of British Columbia, Vancouver, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Yinshan Zhao
- Department of Medicine (Neurology), University of British Columbia, Vancouver, Canada
| | - Lindsay Machan
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - David K. B. Li
- UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
- Department of Medicine (Neurology), University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Anthony Traboulsee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, Canada
- Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Alexander Rauscher
- UBC MRI Research Centre, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
- Centre for Brain Health, University of British Columbia, Vancouver, Canada
- Child and Family Research Institute, University of British Columbia, Vancouver, Canada
- * E-mail:
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