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Rimkus CDM, Otsuka FS, Nunes DM, Chaim KT, Otaduy MCG. Central Vein Sign and Paramagnetic Rim Lesions: Susceptibility Changes in Brain Tissues and Their Implications for the Study of Multiple Sclerosis Pathology. Diagnostics (Basel) 2024; 14:1362. [PMID: 39001252 PMCID: PMC11240827 DOI: 10.3390/diagnostics14131362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 05/29/2024] [Accepted: 06/03/2024] [Indexed: 07/16/2024] Open
Abstract
Multiple sclerosis (MS) is the most common acquired inflammatory and demyelinating disease in adults. The conventional diagnostic of MS and the follow-up of inflammatory activity is based on the detection of hyperintense foci in T2 and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and lesions with brain-blood barrier (BBB) disruption in the central nervous system (CNS) parenchyma. However, T2/FLAIR hyperintense lesions are not specific to MS and the MS pathology and inflammatory processes go far beyond focal lesions and can be independent of BBB disruption. MRI techniques based on the magnetic susceptibility properties of the tissue, such as T2*, susceptibility-weighted images (SWI), and quantitative susceptibility mapping (QSM) offer tools for advanced MS diagnostic, follow-up, and the assessment of more detailed features of MS dynamic pathology. Susceptibility-weighted techniques are sensitive to the paramagnetic components of biological tissues, such as deoxyhemoglobin. This capability enables the visualization of brain parenchymal veins. Consequently, it presents an opportunity to identify veins within the core of multiple sclerosis (MS) lesions, thereby affirming their venocentric characteristics. This advancement significantly enhances the accuracy of the differential diagnostic process. Another important paramagnetic component in biological tissues is iron. In MS, the dynamic trafficking of iron between different cells, such as oligodendrocytes, astrocytes, and microglia, enables the study of different stages of demyelination and remyelination. Furthermore, the accumulation of iron in activated microglia serves as an indicator of latent inflammatory activity in chronic MS lesions, termed paramagnetic rim lesions (PRLs). PRLs have been correlated with disease progression and degenerative processes, underscoring their significance in MS pathology. This review will elucidate the underlying physical principles of magnetic susceptibility and their implications for the formation and interpretation of T2*, SWI, and QSM sequences. Additionally, it will explore their applications in multiple sclerosis (MS), particularly in detecting the central vein sign (CVS) and PRLs, and assessing iron metabolism. Furthermore, the review will discuss their role in advancing early and precise MS diagnosis and prognostic evaluation, as well as their utility in studying chronic active inflammation and degenerative processes.
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Affiliation(s)
- Carolina de Medeiros Rimkus
- Department of Radiology and Oncology, Hospital das Clínicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Sao Paulo 05403-010, SP, Brazil
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HV Amsterdam, The Netherlands
- Instituto D'Or de Ensino e Pesquisa (IDOR), Sao Paulo 01401-002, SP, Brazil
| | - Fábio Seiji Otsuka
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
| | - Douglas Mendes Nunes
- Department of Radiology and Oncology, Hospital das Clínicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Sao Paulo 05403-010, SP, Brazil
- Grupo Fleury, Sao Paulo 04701-200, SP, Brazil
| | - Khallil Taverna Chaim
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
| | - Maria Concepción Garcia Otaduy
- Department of Radiology and Oncology, Hospital das Clínicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Sao Paulo 05403-010, SP, Brazil
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
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2
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Belov SE, Boyko AN, Dolgushin MB. [The central vein sign in the differential diagnosis of multiple sclerosis]. Zh Nevrol Psikhiatr Im S S Korsakova 2024; 124:58-65. [PMID: 39175241 DOI: 10.17116/jnevro202412407258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2024]
Abstract
OBJECTIVE To carry out a clinical and radiological assessment of the central vein sign (CVS) as a diagnostic marker for multiple sclerosis (MS) and other demyelinating and non-demyelinating diseases with focal brain damage, using clinical and laboratory examination data, as well as MRI. MATERIAL AND METHODS The results of clinical and neuroradiological examination of 107 patients diagnosed with MS or with other diseases accompanied by focal brain damage according to MRI data were analyzed. RESULTS CVS is a sensitive but low-specific diagnostic marker of MS. According to our data, the sensitivity and specificity of 40 and 50% of the threshold of perivenular lesions in the diagnosis of MS are the same and amount to 100% and 39.4%, respectively. Neither the type of MS course, nor the severity of the course, nor the intake of DMT (disease modifying treatment), affect the proportion of foci with CVS. The spread of the proportion of foci with CVS in patients with MS was 60-100%. The proportion of foci with CVS is below 40 and 50% of the threshold in patients with demyelinating and non-demyelinating diseases (NMOSD, migraine, systemic lupus erythematosus, Susak disease, CLIPPERS), which allows for differential diagnosis with MS. The proportion of foci with CVS comparable to MS in patients with acute disseminated encephalomyelitis, small vessel disease, as well as in patients with radiologically isolated syndrome does not allow using this symptom in the differential diagnosis of these conditions. CONCLUSION The use of CVS as a diagnostic marker of MS is possible only in combination with the already existing diagnostic criteria of MS.
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Affiliation(s)
- S E Belov
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - A N Boyko
- Pirogov Russian National Research Medical University, Moscow, Russia
- Federal Center for Brain Research and Neurotechnology, Moscow, Russia
| | - M B Dolgushin
- Federal Center for Brain Research and Neurotechnology, Moscow, Russia
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3
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Gill AJ, Schorr EM, Gadani SP, Calabresi PA. Emerging imaging and liquid biomarkers in multiple sclerosis. Eur J Immunol 2023; 53:e2250228. [PMID: 37194443 PMCID: PMC10524168 DOI: 10.1002/eji.202250228] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/10/2023] [Accepted: 05/12/2023] [Indexed: 05/18/2023]
Abstract
The advent of highly effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins, such as neurofilament light chain and glial fibrillary acidic protein, show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers, including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes, are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies.
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Affiliation(s)
- Alexander J. Gill
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Emily M. Schorr
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Sachin P. Gadani
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Peter A. Calabresi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
- Department of Neuroscience, Baltimore, MD, US
- Department of Ophthalmology, Baltimore, MD, US
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4
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Statsenko Y, Smetanina D, Arora T, Östlundh L, Habuza T, Simiyu GL, Meribout S, Talako T, King FC, Makhnevych I, Gelovani JG, Das KM, Gorkom KNV, Almansoori TM, Al Zahmi F, Szólics M, Ismail F, Ljubisavljevic M. Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis. BMJ Open 2023; 13:e068608. [PMID: 37451729 PMCID: PMC10351237 DOI: 10.1136/bmjopen-2022-068608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/03/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND The number of patients diagnosed with multiple sclerosis (MS) has increased significantly over the last decade. The challenge is to identify the transition from relapsing-remitting to secondary progressive MS. Since available methods to examine patients with MS are limited, both the diagnostics and prognostication of disease progression would benefit from the multimodal approach. The latter combines the evidence obtained from disparate radiologic modalities, neurophysiological evaluation, cognitive assessment and molecular diagnostics. In this systematic review we will analyse the advantages of multimodal studies in predicting the risk of conversion to secondary progressive MS. METHODS AND ANALYSIS We will use peer-reviewed publications available in Web of Science, Medline/PubMed, Scopus, Embase and CINAHL databases. In vivo studies reporting the predictive value of diagnostic methods will be considered. Selected publications will be processed through Covidence software for automatic deduplication and blind screening. Two reviewers will use a predefined template to extract the data from eligible studies. We will analyse the performance metrics (1) for the classification models reflecting the risk of secondary progression: sensitivity, specificity, accuracy, area under the receiver operating characteristic curve, positive and negative predictive values; (2) for the regression models forecasting disability scores: the ratio of mean absolute error to the range of values. Then, we will create ranking charts representing performance of the algorithms for calculating disability level and MS progression. Finally, we will compare the predictive power of radiological and radiomical correlates of clinical disability and cognitive impairment in patients with MS. ETHICS AND DISSEMINATION The study does not require ethical approval because we will analyse publicly available literature. The project results will be published in a peer-review journal and presented at scientific conferences. PROSPERO REGISTRATION NUMBER CRD42022354179.
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Affiliation(s)
- Yauhen Statsenko
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
- Big Data Analytics Center, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
| | - Darya Smetanina
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
| | - Teresa Arora
- Psychology Department, College of Natural and Health Sciences, Zayed University, Abu Dhabi, Abu Dhabi Emirate, UAE
| | - Linda Östlundh
- National Medical Library, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
- Library, Örebro University, Örebro, Sweden
| | - Tetiana Habuza
- Big Data Analytics Center, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
- Department of Computer Science, College of Information Technology, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
| | - Gillian Lylian Simiyu
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
| | - Sarah Meribout
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
- Internal Medicine Department, Maimonides Medical Center, New York, New York, USA
| | - Tatsiana Talako
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Department of Oncohematology, Minsk Scientific and Practical Center for Surgery, Transplantology and Hematology, Minsk, Belarus
| | - Fransina Christina King
- Physiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Neuroscience Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
| | - Iryna Makhnevych
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Juri George Gelovani
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Biomedical Engineering Department, Wayne State University, College of Engineering, Detroit, Michigan, USA
- Radiology Department, Siriraj Hospital, Faculty of Medicine, Mahidol University, Bangkok, Thailand
- Provost Office, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
| | - Karuna M Das
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Klaus Neidl-Van Gorkom
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Taleb M Almansoori
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Fatmah Al Zahmi
- Neurology Department, Mediclinic Parkview Hospital, Dubai, Dubai Emirate, UAE
- Neurology Department, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, Dubai Emirate, UAE
| | - Miklós Szólics
- Internal Medicine Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Division of Neurology, Department of Medicine, Tawam Hospital, Al Ain, Abu Dhabi Emirate, UAE
| | - Fatima Ismail
- Pediatrics Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi, UAE
| | - Milos Ljubisavljevic
- Physiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Neuroscience Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
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Lapucci C, Tazza F, Rebella S, Boffa G, Sbragia E, Bruschi N, Mancuso E, Mavilio N, Signori A, Roccatagliata L, Cellerino M, Schiavi S, Inglese M. Central vein sign and diffusion MRI differentiate microstructural features within white matter lesions of multiple sclerosis patients with comorbidities. Front Neurol 2023; 14:1084661. [PMID: 36970546 PMCID: PMC10030505 DOI: 10.3389/fneur.2023.1084661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 01/30/2023] [Indexed: 03/29/2023] Open
Abstract
Introduction The Central Vein Sign (CVS) has been suggested as a potential biomarker to improve diagnostic specificity in multiple sclerosis (MS). Nevertheless, the impact of comorbidities on CVS performance has been poorly investigated so far. Despite the similar features shared by MS, migraine and Small Vessel Disease (SVD) at T2-weighted conventional MRI sequences, ex-vivo studies demonstrated their heterogeneous histopathological substrates. If in MS, inflammation, primitive demyelination and axonal loss coexist, in SVD demyelination is secondary to ischemic microangiopathy, while the contemporary presence of inflammatory and ischemic processes has been suggested in migraine. The aims of this study were to investigate the impact of comorbidities (risk factors for SVD and migraine) on the global and subregional assessment of the CVS in a large cohort of MS patients and to apply the Spherical Mean Technique (SMT) diffusion model to evaluate whether perivenular and non-perivenular lesions show distinctive microstructural features. Methods 120 MS patients stratified into 4 Age Groups performed 3T brain MRI. WM lesions were classified in "perivenular" and "non-perivenular" by visual inspection of FLAIR* images; mean values of SMT metrics, indirect estimators of inflammation, demyelination and fiber disruption (EXTRAMD: extraneurite mean diffusivity, EXTRATRANS: extraneurite transverse diffusivity and INTRA: intraneurite signal fraction, respectively) were extracted. Results Of the 5303 lesions selected for the CVS assessment, 68.7% were perivenular. Significant differences were found between perivenular and non-perivenular lesion volume in the whole brain (p < 0.001) and between perivenular and non-perivenular lesion volume and number in all the four subregions (p < 0.001 for all). The percentage of perivenular lesions decreased from youngest to oldest patients (79.7%-57.7%), with the deep/subcortical WM of oldest patients as the only subregion where the number of non-perivenular was higher than the number of perivenular lesions. Older age and migraine were independent predictors of a higher percentage of non-perivenular lesions (p < 0.001 and p = 0.013 respectively). Whole brain perivenular lesions showed higher inflammation, demyelination and fiber disruption than non perivenular lesions (p = 0.001, p = 0.001 and p = 0.02 for EXTRAMD, EXTRATRANS and INTRA respectively). Similar findings were found in the deep/subcortical WM (p = 0.001 for all). Compared to non-perivenular lesions, (i) perivenular lesions located in periventricular areas showed a more severe fiber disruption (p = 0.001), (ii) perivenular lesions located in juxtacortical and infratentorial regions exhibited a higher degree of inflammation (p = 0.01 and p = 0.05 respectively) and (iii) perivenular lesions located in infratentorial areas showed a higher degree of demyelination (p = 0.04). Discussion Age and migraine have a relevant impact in reducing the percentage of perivenular lesions, particularly in the deep/subcortical WM. SMT may differentiate perivenular lesions, characterized by higher inflammation, demyelination and fiber disruption, from non perivenular lesions, where these pathological processes seemed to be less pronounced. The development of new non-perivenular lesions, especially in the deep/subcortical WM of older patients, should be considered a "red flag" for a different -other than MS- pathophysiology.
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Affiliation(s)
- Caterina Lapucci
- HNSR, IRRCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Francesco Tazza
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | | | - Giacomo Boffa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Elvira Sbragia
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Nicolò Bruschi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Elisabetta Mancuso
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Nicola Mavilio
- Department of Neuroradiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Alessio Signori
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Luca Roccatagliata
- Department of Neuroradiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Maria Cellerino
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino IRCCS, Genoa, Italy
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6
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Daboul L, O'Donnell CM, Cao Q, Amin M, Rodrigues P, Derbyshire J, Azevedo C, Bar-Or A, Caverzasi E, Calabresi P, Cree BAC, Freeman L, Henry RG, Longbrake EE, Nakamura K, Oh J, Papinutto N, Pelletier D, Samudralwar RD, Suthiphosuwan S, Schindler MK, Sotirchos ES, Sicotte NL, Solomon AJ, Shinohara RT, Reich DS, Ontaneda D, Sati P. Effect of GBCA Use on Detection and Diagnostic Performance of the Central Vein Sign: Evaluation Using a 3-T FLAIR* Sequence in Patients With Suspected Multiple Sclerosis. AJR Am J Roentgenol 2023; 220:115-125. [PMID: 35975888 PMCID: PMC10016223 DOI: 10.2214/ajr.22.27731] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND. The central vein sign (CVS) is a proposed MRI biomarker of multiple sclerosis (MS). The impact of gadolinium-based contrast agent (GBCA) administration on CVS evaluation remains poorly investigated. OBJECTIVE. The purpose of this study was to assess the effect of GBCA use on CVS detection and on the diagnostic performance of the CVS for MS using a 3-T FLAIR* sequence. METHODS. This study was a secondary analysis of data from the pilot study for the prospective multicenter Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS), which recruited adults with suspected MS from April 2018 to February 2020. Participants underwent 3-T brain MRI including FLAIR and precontrast and post-contrast echo-planar imaging T2*-weighted acquisitions. Postprocessing was used to generate combined FLAIR and T2*-weighted images (hereafter, FLAIR*). MS diagnoses were established using the 2017 McDonald criteria. Thirty participants (23 women, seven men; mean age, 45 years) were randomly selected from the CAVS-MS pilot study cohort. White matter lesions (WMLs) were marked using FLAIR* images. A single observer, blinded to clinical data and GBCA use, reviewed marked WMLs on FLAIR* images for the presence of the CVS. RESULTS. Thirteen of 30 participants had MS. Across participants, on precontrast FLAIR* imaging, 218 CVS-positive and 517 CVS-negative WMLs were identified; on post-contrast FLAIR* imaging, 269 CVS-positive and 459 CVS-negative WMLs were identified. The fraction of WMLs that were CVS-positive on precontrast and postcontrast images was 48% and 58% in participants with MS and 7% and 10% in participants without MS, respectively. The median patient-level CVS-positivity rate on precontrast and postcontrast images was 43% and 67% for participants with MS and 4% and 8% for participants without MS, respectively. In a binomial model adjusting for MS diagnoses, GBCA use was associated with an increased likelihood of at least one CVS-positive WML (odds ratio, 1.6; p < .001). At a 40% CVS-positivity threshold, the sensitivity of the CVS for MS increased from 62% on precontrast images to 92% on postcontrast images (p = .046). Specificity was not significantly different between precontrast (88%) and postcontrast (82%) images (p = .32). CONCLUSION. GBCA use increased CVS detection on FLAIR* images, thereby increasing the sensitivity of the CVS for MS diagnoses. CLINICAL IMPACT. The postcontrast FLAIR* sequence should be considered for CVS evaluation in future investigational trials and clinical practice.
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Affiliation(s)
- Lynn Daboul
- Department of Neurology, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Carly M O'Donnell
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Quy Cao
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Moein Amin
- Neurological Institute, Cleveland Clinic, Cleveland, OH
| | | | | | - Christina Azevedo
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eduardo Caverzasi
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Peter Calabresi
- Department of Neurology, Johns Hopkins University, Baltimore, MD
| | - Bruce A C Cree
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Roland G Henry
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
| | - Jiwon Oh
- Division of Neurology, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Nico Papinutto
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Rohini D Samudralwar
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX
| | - Suradech Suthiphosuwan
- Department of Medical Imaging, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Matthew K Schindler
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | | | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
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7
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La Rosa F, Wynen M, Al-Louzi O, Beck ES, Huelnhagen T, Maggi P, Thiran JP, Kober T, Shinohara RT, Sati P, Reich DS, Granziera C, Absinta M, Bach Cuadra M. Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues. Neuroimage Clin 2022; 36:103205. [PMID: 36201950 PMCID: PMC9668629 DOI: 10.1016/j.nicl.2022.103205] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.
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Key Words
- ms, multiple sclerosis
- mri, magnetic resonance imaging
- dl, deep learning
- ml, machine learning
- cl, cortical lesions
- prl, paramagnetic rim lesions
- cvs, central vein sign
- wml, white matter lesions
- flair, fluid-attenuated inversion recovery
- mprage, magnetization prepared rapid gradient-echo
- gm, gray matter
- wm, white matter
- psir, phase-sensitive inversion recovery
- dir, double inversion recovery
- mp2rage, magnetization-prepared 2 rapid gradient echoes
- sels, slowly evolving/expanding lesions
- cnn, convolutional neural network
- xai, explainable ai
- pv, partial volume
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Maxence Wynen
- CIBM Center for Biomedical Imaging, Switzerland; ICTeam, UCLouvain, Louvain-la-Neuve, Belgium; Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Till Huelnhagen
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Pietro Maggi
- Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Department of Neurology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, CHUV, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Switzerland; Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
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8
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Kolb H, Al-Louzi O, Beck ES, Sati P, Absinta M, Reich DS. From pathology to MRI and back: Clinically relevant biomarkers of multiple sclerosis lesions. Neuroimage Clin 2022; 36:103194. [PMID: 36170753 PMCID: PMC9668624 DOI: 10.1016/j.nicl.2022.103194] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 12/14/2022]
Abstract
Focal lesions in both white and gray matter are characteristic of multiple sclerosis (MS). Histopathological studies have helped define the main underlying pathological processes involved in lesion formation and evolution, serving as a gold standard for many years. However, histopathology suffers from an intrinsic bias resulting from over-reliance on tissue samples from late stages of the disease or atypical cases and is inadequate for routine patient assessment. Pathological-radiological correlative studies have established advanced MRI's sensitivity to several relevant MS-pathological substrates and its practicality for assessing dynamic changes and following lesions over time. This review focuses on novel imaging techniques that serve as biomarkers of critical pathological substrates of MS lesions: the central vein, chronic inflammation, remyelination and repair, and cortical lesions. For each pathological process, we address the correlative value of MRI to MS pathology, its contribution in elucidating MS pathology in vivo, and the clinical utility of the imaging biomarker.
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Affiliation(s)
- Hadar Kolb
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel,Corresponding author at: Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel.
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Institute of Experimental Neurology (INSPE), IRCSS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy,Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
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9
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Levasseur VA, Xiang B, Salter A, Yablonskiy DA, Cross AH. Stronger Microstructural Damage Revealed in Multiple Sclerosis Lesions With Central Vein Sign by Quantitative Gradient Echo MRI. J Cent Nerv Syst Dis 2022; 14:11795735221084842. [PMID: 35370433 PMCID: PMC8973074 DOI: 10.1177/11795735221084842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Background Multiple sclerosis (MS) lesions typically form around a central vein that can be visualized with FLAIR* MRI, creating the central vein sign (CVS) which may reflect lesion pathophysiology. Herein we used gradient echo plural contrast imaging (GEPCI) MRI to simultaneously visualize CVS and measure tissue damage in MS lesions. We examined CVS in relation to tissue integrity in white matter (WM) lesions and among MS subtypes. Objective We aimed to determine if CVS positive lesions were specific to MS subtype, if CVS can be detected consistently among readers using the GEPCI method, and if there were differences in tissue damage in lesions with vs without CVS. Subjects and Methods Thirty relapsing-remitting MS (RRMS) subjects and 38 primary and secondary progressive MS (PMS) subjects were scanned with GEPCI protocol at 3T. GEPCI T2*-SWI images were generated to visualize CVS. Two investigators independently evaluated WM lesions for CVS and measured lesion volumes. To estimate tissue damage severity, total lesion volume, and mean lesion volume, R2t*-based tissue damage score (TDS) of individual lesions and tissue damage load (TDL) were measured for CVS+, CVS-, and confluent lesions. Spearman correlations were made between MRI and clinical data. One-way ANCOVA with age and sex as covariates was used to compare measurements of CVS+ vs CVS- lesions in each individual. Results 398 of 548 lesions meeting inclusion criteria showed CVS. Most patients had ≥40% CVS+ lesions. CVS+ lesions were present in similar proportion among MS subtypes. Interobserver agreement was high for CVS detection. CVS+ and confluent lesions had higher average and total volumes vs CVS- lesions. CVS+ and confluent lesions had more tissue damage than CVS- lesions based on TDL and mean TDS. Conclusion CVS occurred in RRMS and PMS in similar proportions. CVS+ lesions had greater tissue damage and larger size than CVS- lesions.
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Affiliation(s)
- Victoria A. Levasseur
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Biao Xiang
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Amber Salter
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA, USA
| | - Dmitriy A. Yablonskiy
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Anne H. Cross
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
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10
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Chaaban L, Safwan N, Moussa H, El‐Sammak S, Khoury S, Hannoun S. Central vein sign: A putative diagnostic marker for multiple sclerosis. Acta Neurol Scand 2022; 145:279-287. [PMID: 34796472 DOI: 10.1111/ane.13553] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/04/2021] [Accepted: 11/03/2021] [Indexed: 11/29/2022]
Abstract
The presence of a "central vein sign" (CVS) has been introduced as a biomarker for the diagnosis of multiple sclerosis (MS) and shown to have the ability to accurately differentiate MS from other white matter diseases (MS mimics). Following the development of susceptibility-based magnetic resonance venography that allowed the in vivo detection of CVS, a standard CVS definition was established by introducing the "40% rule" that assesses the number of MS lesions with CVS as a fraction of the total number of lesions to differentiate MS lesions from other types of lesions. The "50% rule," the "three-lesion criteria," and the "six-lesion criteria" were later introduced and defined. Each of these rules had high levels of sensitivity, specificity, and accuracy in differentiating MS from other diseases, which has been recognized by the Magnetic Resonance Imaging in MS (MAGNIMS) group and the Consortium of MS Centers task force. The North American Imaging in Multiple Sclerosis Cooperative even provided statements and recommendations aiming to refine, standardize and evaluate the CVS in MS. Herein, we review the existing literature on CVS and evaluate its added value in the diagnosis of MS and usefulness in differentiating it from other vasculopathies. We also review the histopathology of CVS and identify available automated CVS assessment methods as well as define the role of vascular comorbidities in the diagnosis of MS.
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Affiliation(s)
- Lara Chaaban
- Department of Agriculture and Food Sciences American University of Beirut Beirut Lebanon
| | - Nancy Safwan
- Department of Agriculture and Food Sciences American University of Beirut Beirut Lebanon
| | - Hussein Moussa
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
| | - Sally El‐Sammak
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
| | - Samia J. Khoury
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
- Faculty of Medicine Abu‐Haidar Neuroscience Institute American University of Beirut Medical Center Beirut Lebanon
| | - Salem Hannoun
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
- Medical Imaging Sciences Program Division of Health Professions Faculty of Health Sciences American University of Beirut Beirut Lebanon
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11
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Gaitán MI, Paday Formenti ME, Calandri I, Ysrraelit MC, Yañez P, Correale J. The central vein sign is present in most infratentorial multiple sclerosis plaques. Mult Scler Relat Disord 2022; 58:103484. [PMID: 35007822 DOI: 10.1016/j.msard.2021.103484] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/27/2021] [Accepted: 12/31/2021] [Indexed: 01/02/2023]
Abstract
BACKGROUND AND PURPOSE There is growing evidence supporting the presence of the central vein sign (CVS) in the supratentorial brain as an imaging biomarker for multiple sclerosis (MS) diagnosis. Recently, using optimized susceptibility-weighted angiography (SWAN-venule), we detected CVS in 86% of supratentorial white matter lesions (WMLs) in the clinical setting on images obtained in a 3T MRI scanner. Despite the relevance of the infratentorial compartment, CVS prevalence in infratentorial MS plaques has not been investigated in detail. Our objective was to determine the proportion of MS infratentorial lesions showing CVS positivity. MATERIALS AND METHODS We included subjects with MS and other brain diseases showing at least one infratentorial lesion larger than 3 mm on 3D-FLAIR. Patients were scanned in a 3T MRI scanner (GE Medical Systems, discovery-MR750), applying a comprehensive protocol including post-contrast 3D-FLAIR and SWAN-venule sequences. CVS presence was confirmed by two trained raters. RESULTS Thirty MRIs of subjects with MS were analyzed. One hundred and one infratentorial lesions were detected on FLAIR, and 86% were centered by a vein. Fifteen MRIs from the non-MS group were analyzed, 19 lesions were visible ion FLAIR and 16% were positive for the CVS. CONCLUSIONS SWAN-venule detects infratentorial lesions and highlights the central vein in MS plaques at 3T MRI. As occurs in the supratentorial brain, most infratentorial lesions are perivenular.
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Affiliation(s)
- María Inés Gaitán
- Department of Neurology, FLENI. Buenos Aires, Argentina; María Inés Gaitán, Montañeses 2325, ZC, 1428, Buenos Aires City, Argentina.
| | | | | | | | - Paulina Yañez
- Department of Radiology, FLENI. Buenos Aires, Argentina
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12
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Belov S, Boyko A. A symptom of the central vein in various diseases and protocols of MRI examination. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:19-26. [DOI: 10.17116/jnevro202212207219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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13
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Abstract
PURPOSE OF REVIEW To summarize recent evidence from the application of susceptibility-based MRI sequences to investigate the 'central vein sign' (CVS) and 'iron rim' as biomarkers to improve the diagnostic work-up of multiple sclerosis (MS) and predict disease severity. RECENT FINDINGS The CVS is a specific biomarker for MS being detectable from the earliest phase of the disease. A threshold of 40% of lesions with the CVS can be optimal to distinguish MS from non-MS patients. Iron rim lesions, reflecting chronic active lesions, develop in relapsing-remitting MS patients and persist in progressive MS. They increase in size in the first few years after their formation and then stabilize. Iron rim lesions can distinguish MS from non-MS patients but not the different MS phenotypes. The presence of at least four iron rim lesions is associated with an earlier clinical disability, higher prevalence of clinically progressive MS and more severe brain atrophy. Automated methods for CVS and iron rim lesion detection are under development to facilitate their quantification. SUMMARY The assessment of the CVS and iron rim lesions is feasible in the clinical scenario and provides MRI measures specific to MS pathological substrates, improving diagnosis and prognosis of these patients.
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14
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Kaisey M, Solomon AJ, Guerrero BL, Renner B, Fan Z, Ayala N, Luu M, Diniz MA, Sati P, Sicotte NL. Preventing multiple sclerosis misdiagnosis using the "central vein sign": A real-world study. Mult Scler Relat Disord 2020; 48:102671. [PMID: 33444958 DOI: 10.1016/j.msard.2020.102671] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/15/2020] [Accepted: 11/30/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND Misdiagnosis of multiple sclerosis (MS) is common and often occurs due to misattribution of non-MS magnetic resonance imaging (MRI) lesions to MS demyelination. A recently developed MRI biomarker, the central vein sign (CVS), has demonstrated high specificity for MS lesions and may thus help prevent misdiagnosis. OBJECTIVE This study explores the potential "real world" diagnostic value of CVS by comparing CVS in patients with MS and patients previously misdiagnosed with MS. METHODS Fifteen patients with MS and 15 misdiagnosed with MS were prospectively recruited to undergo 3T brain MRI. T2-weighted fluid-attenuated inversion recovery (FLAIR) and T2*-weighted segmented echo-planar-imaging (T2*-EPI) were acquired. The generated FLAIR* images were analyzed by two independent raters. The percentage of lesions with CVS was calculated for each patient. RESULTS A CVS lesion threshold of 29% or higher resulted in high sensitivity (0.79) and specificity (0.88) for MS and correctly identified 87% of patients previously misdiagnosed with MS. Interrater reliability for CVS was high with a Cohen's kappa coefficient of 0.86. CONCLUSION This study demonstrates the ability of CVS to differentiate between patients with MS and patients with an MS misdiagnosis resulting from standard MRI and clinical evaluation. Clinical application of CVS may reduce MS misdiagnosis.
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Affiliation(s)
- Marwa Kaisey
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Andrew J Solomon
- Larner College of Medicine at the University of Vermont, Department of Neurological Sciences, 1 South Prospect Street, Arnold, Level 2, Burlington, Vermont 05401, USA.
| | - Brooke L Guerrero
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Brian Renner
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Zhaoyang Fan
- Cedars-Sinai Biomedical Imaging Research Institute, 116 N Robertson Blvd, Los Angeles, CA 90048, USA.
| | - Natalie Ayala
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Michael Luu
- Cedars-Sinai Biostatistics and Bioinformatics Research Center, 8700 Beverly Blvd North Tower, Los Angeles, CA 90048, USA.
| | - Marcio A Diniz
- Cedars-Sinai Biostatistics and Bioinformatics Research Center, 8700 Beverly Blvd North Tower, Los Angeles, CA 90048, USA.
| | - Pascal Sati
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Nancy L Sicotte
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
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15
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Etemadifar M, Ashourizadeh H, Nouri H, Kargaran PK, Salari M, Rayani M, Aghababaee A, Abhari AP. MRI signs of CNS demyelinating diseases. Mult Scler Relat Disord 2020; 47:102665. [PMID: 33310421 DOI: 10.1016/j.msard.2020.102665] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 11/25/2020] [Accepted: 11/28/2020] [Indexed: 11/27/2022]
Abstract
The differential diagnosis of the central nervous system (CNS) demyelinating diseases can be greatly facilitated by visualization and appreciation of pathognomonic radiological signs, visualized on magnetic resonance imaging (MRI) sequences. Given the distinct therapeutic approaches for each of these diseases, a decisive and reliable diagnosis in patients presenting with demyelination-associated symptoms is of crucial value. Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are major examples of such conditions, each possessing a number of MRI signs, closely associated with the disorder. This pictorial review aims to describe seventeen pathognomonic MRI signs associated with several CNS demyelinating disorders including MS, NMOSD, myelin oligodendrocyte glycoprotein-associated disease, Baló's concentric sclerosis, metachromatic leukodystrophy, progressive multifocal leukoencephalopathy, and neurosarcoidosis.
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Affiliation(s)
- Masoud Etemadifar
- Department of Neurosurgery, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Helia Ashourizadeh
- Functional Neurosurgery Research Center, Shohada Tajrish Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hosein Nouri
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran; Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Isfahan, Iran.
| | - Parisa K Kargaran
- Departments of Cardiovascular Medicine, Center for Regenerative Medicine, Mayo Clinic, Rochester, MN, USA
| | - Mehri Salari
- Department of Neurological Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Milad Rayani
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Ali Aghababaee
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Amir Parsa Abhari
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran; Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Isfahan, Iran
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16
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Castellaro M, Tamanti A, Pisani AI, Pizzini FB, Crescenzo F, Calabrese M. The Use of the Central Vein Sign in the Diagnosis of Multiple Sclerosis: A Systematic Review and Meta-analysis. Diagnostics (Basel) 2020; 10:diagnostics10121025. [PMID: 33260401 PMCID: PMC7760678 DOI: 10.3390/diagnostics10121025] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 11/26/2020] [Accepted: 11/26/2020] [Indexed: 02/01/2023] Open
Abstract
Background: The central vein sign (CVS) is a radiological feature proposed as a multiple sclerosis (MS) imaging biomarker able to accurately differentiate MS from other white matter diseases of the central nervous system. In this work, we evaluated the pooled proportion of the CVS in brain MS lesions and to estimate the diagnostic performance of CVS to perform a diagnosis of MS and propose an optimal cut-off value. Methods: A systematic search was performed on publicly available databases (PUBMED/MEDLINE and Web of Science) up to 24 August 2020. Analysis of the proportion of white matter MS lesions with a central vein was performed using bivariate random-effect models. A meta-regression analysis was performed and the impact of using particular sequences (such as 3D echo-planar imaging) and post-processing techniques (such as FLAIR*) was investigated. Pooled sensibility and specificity were estimated using bivariate models and meta-regression was performed to address heterogeneity. Inclusion and publication bias were assessed using asymmetry tests and a funnel plot. A hierarchical summary receiver operating curve (HSROC) was used to estimate the summary accuracy in diagnostic performance. The Youden index was employed to estimate the optimal cut-off value using individual patient data. Results: The pooled proportion of lesions showing a CVS in the MS population was 73%. The use of the CVS showed a remarkable diagnostic performance in MS cases, providing a pooled specificity of 92% and a sensitivity of 95%. The optimal cut-off value obtained from the individual patient data pooled together was 40% with excellent accuracy calculated by the area under the ROC (0.946). The 3D-EPI sequences showed both a higher pooled proportion compared to other sequences and explained heterogeneity in the meta-regression analysis of diagnostic performances. The 1.5 Tesla (T) scanners showed a lower (58%) proportion of MS lesions with a CVS compared to both 3T (74%) and 7T (82%). Conclusions: The meta-analysis we have performed shows that the use of the CVS in differentiating MS from other mimicking diseases is encouraged; moreover, the use of dedicated sequences such as 3D-EPI and the high MRI field is beneficial.
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Affiliation(s)
- Marco Castellaro
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
- Correspondence:
| | - Agnese Tamanti
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
| | - Anna Isabella Pisani
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
| | | | - Francesco Crescenzo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
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17
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Sinnecker T, Clarke MA, Meier D, Enzinger C, Calabrese M, De Stefano N, Pitiot A, Giorgio A, Schoonheim MM, Paul F, Pawlak MA, Schmidt R, Kappos L, Montalban X, Rovira À, Evangelou N, Wuerfel J. Evaluation of the Central Vein Sign as a Diagnostic Imaging Biomarker in Multiple Sclerosis. JAMA Neurol 2020; 76:1446-1456. [PMID: 31424490 DOI: 10.1001/jamaneurol.2019.2478] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Importance The central vein sign has been proposed as a specific imaging biomarker for distinguishing between multiple sclerosis (MS) and not MS, mainly based on findings from ultrahigh-field magnetic resonance imaging (MRI) studies. The diagnostic value of the central vein sign in a multicenter setting with a variety of clinical 3 tesla (T) MRI protocols, however, remains unknown. Objective To evaluate the sensitivity and specificity of various central vein sign lesion criteria for differentiating MS from non-MS conditions using 3T brain MRI with various commonly used pulse sequences. Design, Setting, and Participants This large multicenter, cross-sectional study enrolled participants (n = 648) of ongoing observational studies and patients included in neuroimaging research databases of 8 neuroimaging centers in Europe. Patient enrollment and MRI data collection were performed between January 1, 2010, and November 30, 2016. Data analysis was conducted between January 1, 2016, and April 30, 2018. Investigators were blinded to participant diagnosis by a novel blinding procedure. Main Outcomes and Measures Occurrence of central vein sign was detected on 3T T2*-weighted or susceptibility-weighted imaging. Sensitivity and specificity were assessed for these MRI sequences and for different central vein sign lesion criteria, which were defined by the proportion of lesions with central vein sign or by absolute numbers of lesions with central vein sign. Results A total of 606 participants were included in the study after exclusion of 42 participants. Among the 606 participants, 413 (68.2%) were women. Patients with clinically isolated syndrome and relapsing-remitting MS (RRMS) included 235 women (66.6%) and had a median (range) age of 37 (14.7-61.4) years, a median (range) disease duration of 2 (0-33) years, and a median (range) Expanded Disability Status Scale score of 1.5 (0-6.5). Patients without MS included 178 women (70.4%) and had a median (range) age of 54 (18-83) years. A total of 4447 lesions were analyzed in a total of 487 patients: 690 lesions in 98 participants with clinically isolated syndrome, 2815 lesions in 225 participants with RRMS, 54 lesions in 13 participants with neuromyelitis optica spectrum disorder, 54 lesions in 14 participants with systemic lupus erythematosus, 121 lesions in 29 participants with migraine or cluster headache, 240 lesions in 20 participants with diabetes, and 473 lesions in 88 participants with other types of small-vessel disease. The sensitivity was 68.1% and specificity was 82.9% for distinguishing MS from not MS using a 35% central vein sign proportion threshold. The 3 central vein sign lesion criteria had a sensitivity of 61.9% and specificity of 89.0%. Sensitivity was higher when an optimized T2*-weighted sequence was used. Conclusions and Relevance In this study, use of the central vein sign at 3T MRI yielded a high specificity and a moderate sensitivity in differentiating MS from not MS; international, multicenter studies may be needed to ascertain whether the central vein sign-based criteria can accurately detect MS.
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Affiliation(s)
- Tim Sinnecker
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland.,Medical Image Analysis Center, Basel, Switzerland.,Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Margareta A Clarke
- School of Psychology, University of Nottingham, Nottingham, United Kingdom.,Clinical Neurology, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - Dominik Meier
- Medical Image Analysis Center, Basel, Switzerland.,qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Christian Enzinger
- Division of Neuroradiology, Vascular and Interventional Radiology, Departments of Neurology and Radiology, Medical University of Graz, Graz, Austria
| | - Massimiliano Calabrese
- Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Alain Pitiot
- Laboratory of Image and Data Analysis, Ilixa Ltd, London, United Kingdom
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - 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.,Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health and Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Mikolaj A Pawlak
- Department of Neurology and Cerebrovascular Disorders, Poznan University of Medical Sciences, Poznan, Poland
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland
| | - Xavier Montalban
- Section of Neuroradiology, Department of Radiology (IDI), VHIR, Barcelona, Spain.,Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), VHIR, Barcelona, Spain
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, United Kingdom
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland.,Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health and Max Delbrück Center for Molecular Medicine, Berlin, Germany
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18
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Guisset F, Lolli V, Bugli C, Perrotta G, Absil J, Dachy B, Pot C, Théaudin M, Pasi M, van Pesch V, Maggi P. The central vein sign in multiple sclerosis patients with vascular comorbidities. Mult Scler 2020; 27:1057-1065. [DOI: 10.1177/1352458520943785] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: The central vein sign (CVS) is an imaging biomarker able to differentiate multiple sclerosis (MS) from other conditions causing similar appearance lesions on magnetic resonance imaging (MRI), including cerebral small vessel disease (CSVD). However, the impact of vascular risk factors (VRFs) for CSVD on the percentage of CVS positive (CVS+) lesions in MS has never been evaluated. Objective: To investigate the association between different VRFs and the percentage of CVS+ lesions in MS. Methods: In 50 MS patients, 3T brain MRIs (including high-resolution 3-dimensional T2*-weighted images) were analyzed for the presence of the CVS and MRI markers of CSVD. A backward stepwise regression model was used to predict the combined predictive effect of VRF (i.e. age, hypertension, diabetes, obesity, ever-smoking, and hypercholesterolemia) and MRI markers of CSVD on the CVS. Results: The median frequency of CVS+ lesions was 71% (range: 35%–100%). In univariate analysis, age ( p < 0.0001), hypertension ( p < 0.001), diabetes ( p < 0.01), obesity ( p < 0.01), smoking ( p < 0.05), and the presence of enlarged-perivascular-spaces on MRI ( p < 0.005) were all associated with a lower percentage of CVS+ lesions. The stepwise regression model showed that age and arterial hypertension were both associated with the percentage of CVS+ lesions in MS (adjusted R2 = 0.46; p < 0.0001 and p = 0.01, respectively). Conclusion: The proportion of CVS+ lesions significantly decreases in older and hypertensive MS patients. Although this study was conducted in patients with an already established MS diagnosis, the diagnostic yield of the previously proposed 35% CVS proportion-based diagnostic threshold appears to be not affected. Overall these results suggest that the presence of VRF for CSVD should be taken into account during the CVS assessment.
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Affiliation(s)
- François Guisset
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium/Department of Neurology, Hôpital Brugmann, Université Libre de Bruxelles, Brussels, Belgium
| | - Valentina Lolli
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Céline Bugli
- Plateforme technologique de Support en Méthodologie et Calcul Statistique, Université Catholique de Louvain, Brussels, Belgium
| | - Gaetano Perrotta
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Bernard Dachy
- Department of Neurology, Hôpital Brugmann, Université Libre de Bruxelles, Brussels, Belgium
| | - Caroline Pot
- Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marie Théaudin
- Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marco Pasi
- University of Lille, Inserm, CHU Lille, U1172—LilNCog—Lille Neuroscience & Cognition, Lille, France
| | - Vincent van Pesch
- Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pietro Maggi
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium/Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland/Department of Neurology, Cliniques universitaires Saint Luc, Université Catholique de Louvain, Brussels, Belgium
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19
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Wang H, Lin J, Zheng L, Zhao J, Song B, Dai Y. Texture analysis based on ADC maps and T2-FLAIR images for the assessment of the severity and prognosis of ischaemic stroke. Clin Imaging 2020; 67:152-159. [PMID: 32739735 DOI: 10.1016/j.clinimag.2020.06.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 05/12/2020] [Accepted: 06/07/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVES To explore the feasibility of texture analysis based on T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images and apparent diffusion coefficient (ADC) maps in the assessment of the severity and prognosis of ischaemic stroke using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin scale (mRS) scores, respectively. METHODS Overall, 116 patients diagnosed with subacute ischaemic stroke were included in this retrospective study. Based on T2-FLAIR images and ADC maps, 15 texture features were extracted from the ROIs of each patient using grey-level co-occurrence matrix (GLCM) and local binary pattern histogram Fourier (LBP-HF) methods. The correlations of NIHSS score on admission (NIHSSbaseline), NIHSS score 24 h after stroke onset (NIHSS24h) and mRS score with the texture features were evaluated using Spearman's partial correlations. The receiver operating characteristic (ROC) curve was used to compare the performance of the selected texture features in the evaluation of stroke severity and prognosis. RESULTS Texture features derived from the T2-FLAIR images and ADC maps were correlated with NIHSS score and mRS score. EntropyADC and 0.75QuantileT2-FLAIR showed the best diagnostic performance for assessing stroke severity. The combination of EntropyADC and 0.75QuantileT2-FLAIR achieved a better performance in the evaluation of stroke severity (AUC = 0.7, p = 0.01) than either feature alone. Only 0.05QuantileT2-FLAIR was found to be correlated with mRS score, and none of the texture features were predictive of mRS score. CONCLUSION Texture features derived from T2-FLAIR images and ADC maps might serve as biomarkers to evaluate stroke severity, but were insufficient to predict stroke prognosis.
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Affiliation(s)
- Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China
| | - Jixian Lin
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China; Department of Electronic Engineering, Fudan University, Shanghai, China
| | - Liyun Zheng
- Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Jing Zhao
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China.
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare, Shanghai, China
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20
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Clarke MA, Pareto D, Pessini-Ferreira L, Arrambide G, Alberich M, Crescenzo F, Cappelle S, Tintoré M, Sastre-Garriga J, Auger C, Montalban X, Evangelou N, Rovira À. Value of 3T Susceptibility-Weighted Imaging in the Diagnosis of Multiple Sclerosis. AJNR Am J Neuroradiol 2020; 41:1001-1008. [PMID: 32439639 DOI: 10.3174/ajnr.a6547] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 03/19/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Previous studies have suggested that the central vein sign and iron rims are specific features of MS lesions. Using 3T SWI, we aimed to compare the frequency of lesions with central veins and iron rims in patients with clinically isolated syndrome and MS-mimicking disorders and test their diagnostic value in predicting conversion from clinically isolated syndrome to MS. MATERIALS AND METHODS For each patient, we calculated the number of brain lesions with central veins and iron rims. We then identified a simple rule involving an absolute number of lesions with central veins and iron rims to predict conversion from clinically isolated syndrome to MS. Additionally, we tested the diagnostic performance of central veins and iron rims when combined with evidence of dissemination in space. RESULTS We included 112 patients with clinically isolated syndrome and 35 patients with MS-mimicking conditions. At follow-up, 94 patients with clinically isolated syndrome developed MS according to the 2017 McDonald criteria. Patients with clinically isolated syndrome had a median of 2 central veins (range, 0-19), while the non-MS group had a median of 1 central vein (range, 0-6). Fifty-six percent of patients who developed MS had ≥1 iron rim, and none of the patients without MS had iron rims. The sensitivity and specificity of finding ≥3 central veins and/or ≥1 iron rim were 70% and 86%, respectively. In combination with evidence of dissemination in space, the 2 imaging markers had higher specificity than dissemination in space and positive findings of oligoclonal bands currently used to support the diagnosis of MS. CONCLUSIONS A single 3T SWI scan offers valuable diagnostic information, which has the potential to prevent MS misdiagnosis.
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Affiliation(s)
- M A Clarke
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain
| | - D Pareto
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain.,Section of Neuroradiology, Department of Radiology (D.P., L.P.-F., C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - L Pessini-Ferreira
- Section of Neuroradiology, Department of Radiology (D.P., L.P.-F., C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - G Arrambide
- Department of Neurology-Neuroimmunology (G.A., M.T., J.S.-G., X.M.), Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - M Alberich
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain
| | - F Crescenzo
- Department of Neurosciences, Biomedicine and Movement Sciences (F.C.), University of Verona, Verona, Italy
| | - S Cappelle
- Division of Radiology (S.C.), University Hospital Leuven, Leuven, Belgium
| | - M Tintoré
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain.,Department of Neurology-Neuroimmunology (G.A., M.T., J.S.-G., X.M.), Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - J Sastre-Garriga
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain.,Department of Neurology-Neuroimmunology (G.A., M.T., J.S.-G., X.M.), Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - C Auger
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain.,Section of Neuroradiology, Department of Radiology (D.P., L.P.-F., C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - X Montalban
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain.,Department of Neurology-Neuroimmunology (G.A., M.T., J.S.-G., X.M.), Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain.,Division of Neurology (X.M.), St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - N Evangelou
- Division of Clinical Neuroscience (N.E.), University of Nottingham, Nottingham, UK
| | - À Rovira
- From the Vall d'Hebron Research Institute (M.A.C., D.P., M.A., M.T., J.S.-G., C.A., X.M., A.R.), Barcelona, Spain .,Section of Neuroradiology, Department of Radiology (D.P., L.P.-F., C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
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21
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Filippi M, Preziosa P, Banwell BL, Barkhof F, Ciccarelli O, De Stefano N, Geurts JJG, Paul F, Reich DS, Toosy AT, Traboulsee A, Wattjes MP, Yousry TA, Gass A, Lubetzki C, Weinshenker BG, Rocca MA. Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines. Brain 2020; 142:1858-1875. [PMID: 31209474 PMCID: PMC6598631 DOI: 10.1093/brain/awz144] [Citation(s) in RCA: 285] [Impact Index Per Article: 71.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/29/2019] [Accepted: 05/01/2019] [Indexed: 12/19/2022] Open
Abstract
MRI has improved the diagnostic work-up of multiple sclerosis, but inappropriate image interpretation and application of MRI diagnostic criteria contribute to misdiagnosis. Some diseases, now recognized as conditions distinct from multiple sclerosis, may satisfy the MRI criteria for multiple sclerosis (e.g. neuromyelitis optica spectrum disorders, Susac syndrome), thus making the diagnosis of multiple sclerosis more challenging, especially if biomarker testing (such as serum anti-AQP4 antibodies) is not informative. Improvements in MRI technology contribute and promise to better define the typical features of multiple sclerosis lesions (e.g. juxtacortical and periventricular location, cortical involvement). Greater understanding of some key aspects of multiple sclerosis pathobiology has allowed the identification of characteristics more specific to multiple sclerosis (e.g. central vein sign, subpial demyelination and lesional rims), which are not included in the current multiple sclerosis diagnostic criteria. In this review, we provide the clinicians and researchers with a practical guide to enhance the proper recognition of multiple sclerosis lesions, including a thorough definition and illustration of typical MRI features, as well as a discussion of red flags suggestive of alternative diagnoses. We also discuss the possible place of emerging qualitative features of lesions which may become important in the near future.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Brenda L Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, UK.,National Institute for Health Research University College London Hospitals Biomedical Research Center, National Institute for Health Research, London, UK
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité -Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ahmed T Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, UK
| | - Anthony Traboulsee
- MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada.,Faculty of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mike P Wattjes
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Tarek A Yousry
- Division of Neuroradiology and Neurophysics, UCL Institute of Neurology, London, UK.,Lysholm Department of Neuroradiology, London, UK
| | - Achim Gass
- Department of Neurology, Universitätsmedizin Mannheim, University of Heidelberg, Mannheim, Germany
| | - Catherine Lubetzki
- Sorbonne University, AP-HP Pitié-Salpétriére Hospital, Department of Neurology, 75013 Paris, France
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
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22
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Gaitán MI, Yañez P, Paday Formenti ME, Calandri I, Figueiredo E, Sati P, Correale J. SWAN-Venule: An Optimized MRI Technique to Detect the Central Vein Sign in MS Plaques. AJNR Am J Neuroradiol 2020; 41:456-460. [PMID: 32054616 DOI: 10.3174/ajnr.a6437] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 01/08/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND AND PURPOSE Multiple sclerosis lesions develop around small veins that are radiologically described as the so-called central vein sign. With 7T MR imaging and magnetic susceptibility-based sequences, the central vein sign has been observed in 80%-100% of MS lesions in patients' brains. However, a lower proportion ∼50% has been reported at 3T using susceptibility-weighted angiography (SWAN). Our aim was to assess a modified version of SWAN optimized at 3T for sensitive detection of the central vein sign. MATERIALS AND METHODS Thirty subjects with MS were scanned on a 3T clinical MR imaging system. 3D T2-weighted FLAIR and optimized 3D SWAN called SWAN-venule, were acquired after injection of a gadolinium-based contrast agent. Patients showing >3 focal white matter lesions were included. The central vein sign was recorded by 2 trained raters on SWAN-venule images in the supratentorial brain. RESULTS Twenty patients showing >3 white matter lesions were included. A total of 380 white matter lesions (135 periventricular, 144 deep white matter, and 101 juxtacortical) seen on both FLAIR and SWAN-venule images were analyzed. Overall, the central vein sign was detected in 86% of the white matter lesions (periventricular, 89%; deep white matter, 95%; and juxtacortical, 78%). CONCLUSIONS The SWAN-venule technique is an optimized MR imaging sequence for highly sensitive detection of the central vein sign in MS brain lesions. This work will facilitate the validation and integration of the central vein sign to increase the diagnostic certainty of MS and further prevent misdiagnosis in clinical practice.
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Affiliation(s)
- M I Gaitán
- From the Department of Neurology (M.I.G., J.C.), Neuroimmunolgy Section
| | - P Yañez
- Departments of Radiology (P.Y., M.E.P.F.)
| | | | - I Calandri
- Neurology (I.C.), FLENI, Buenos Aires, Argentina
| | | | - P Sati
- Translational Neuroradiology Section (P.S.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - J Correale
- From the Department of Neurology (M.I.G., J.C.), Neuroimmunolgy Section
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23
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Sartoretti E, Sartoretti T, Wyss M, Becker AS, Schwenk Á, van Smoorenburg L, Najafi A, Binkert C, Thoeny HC, Zhou J, Jiang S, Graf N, Czell D, Sartoretti-Schefer S, Reischauer C. Amide Proton Transfer Weighted Imaging Shows Differences in Multiple Sclerosis Lesions and White Matter Hyperintensities of Presumed Vascular Origin. Front Neurol 2019; 10:1307. [PMID: 31920930 PMCID: PMC6914856 DOI: 10.3389/fneur.2019.01307] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Accepted: 11/26/2019] [Indexed: 01/14/2023] Open
Abstract
Objectives: To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter (healthy WM) with APTw signal intensity of MSL and WHM. Materials and Methods: A total of 27 patients (16 female, 11 males, mean age 39.6 years) with multiple sclerosis, 35 patients (17 females, 18 males, mean age 66.6 years) with small vessel disease (SVD) and 20 healthy young volunteers (9 females, 11 males, mean age 29 years) were included in the MSL, the WMH, and the healthy WM group. MSL and WMH were segmented on fluid attenuated inversion recovery (FLAIR) images underlaid onto APTw images. Histogram parameters (mean, median, 10th, 25th, 75th, 90th percentile) were calculated. Mean APTw signal intensity values in healthy WM were defined by "Region of interest" (ROI) measurements. Wilcoxon rank sum tests and receiver operating characteristics (ROC) curve analyses of clustered data were applied. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018-p = 0.034). MSL presented with higher median values in all parameters. The histogram parameters offered only low diagnostic performance in discriminating between MSL and WMH. The 10th percentile yielded the highest diagnostic performance with an AUC of 0.6245 (95% CI: [0.532, 0.717]). Mean APTw signal intensity values of MSL were significantly higher than mean values of healthy WM (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Conclusions: We found significant differences in APTw signal intensity, based on straightforward magnetization transfer analysis, between MSL and WMH and between MSL and healthy WM. Low AUC values from ROC analyses, however, suggest that it may be challenging to determine type of lesion with APTw imaging. More advanced analysis of the APT CEST signal may be helpful for further differentiation of MSL and WMH.
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Affiliation(s)
| | - Thomas Sartoretti
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, Schwerzenbach, Switzerland
| | - Michael Wyss
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland.,Philips Healthsystems, Zurich, Switzerland
| | - Anton S Becker
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, Schwerzenbach, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Árpád Schwenk
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | | | - Arash Najafi
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Christoph Binkert
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Harriet C Thoeny
- Department of Medicine, University of Fribourg, Fribourg, Switzerland.,Department of Radiology, HFR Fribourg-Hôpital Cantonal, Fribourg, Switzerland
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | | | - David Czell
- Department of Neurology, Spital Linth, Uznach, Switzerland
| | | | - Carolin Reischauer
- Department of Medicine, University of Fribourg, Fribourg, Switzerland.,Department of Radiology, HFR Fribourg-Hôpital Cantonal, Fribourg, Switzerland
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24
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Suh CH, Kim SJ, Jung SC, Choi CG, Kim HS. The "Central Vein Sign" on T2*-weighted Images as a Diagnostic Tool in Multiple Sclerosis: A Systematic Review and Meta-analysis using Individual Patient Data. Sci Rep 2019; 9:18188. [PMID: 31796822 PMCID: PMC6890741 DOI: 10.1038/s41598-019-54583-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 11/14/2019] [Indexed: 12/15/2022] Open
Abstract
We aimed to evaluate the pooled incidence of central vein sign on T2*-weighted images from patients with multiple sclerosis (MS), and to determine the diagnostic performance of this central vein sign for differentiating MS from other white matter lesions and provide an optimal cut-off value. A computerized systematic search of the literature in PUBMED and EMBASE was conducted up to December 14, 2018. Original articles investigating central vein sign on T2*-weighted images of patients with MS were selected. The pooled incidence was obtained using random-effects model. The pooled sensitivity and specificity were obtained using a bivariate random-effects model. An optimal cut-off value for the proportion of lesions with a central vein sign was calculated from those studies providing individual patient data. Twenty-one eligible articles covering 501 patients with MS were included. The pooled incidence of central vein sign at the level of individual lesion in patients with MS was 74% (95% CI, 65-82%). The pooled sensitivity and pooled specificity for the diagnostic performance of the central vein sign were 98% (95% CI, 92-100%) and 97% (95% CI, 91-99%), respectively. The area under the HSROC curve was 1.00 (95% CI, 0.99-1.00). The optimal cut-off value for the proportion of lesions with a central vein sign was found to be 45%. Although various T2*-weighted images have been used across studies, the current evidence supports the use of the central vein sign on T2*-weighted images to differentiate MS from other white matter lesions.
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Affiliation(s)
- Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea.
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Choong Gon Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
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Haacke EM, Chen Y, Utriainen D, Wu B, Wang Y, Xia S, He N, Zhang C, Wang X, Lagana MM, Luo Y, Fatemi A, Liu S, Gharabaghi S, Wu D, Sethi SK, Huang F, Sun T, Qu F, Yadav BK, Ma X, Bai Y, Wang M, Cheng J, Yan F. STrategically Acquired Gradient Echo (STAGE) imaging, part III: Technical advances and clinical applications of a rapid multi-contrast multi-parametric brain imaging method. Magn Reson Imaging 2019; 65:15-26. [PMID: 31629075 DOI: 10.1016/j.mri.2019.09.006] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Revised: 09/11/2019] [Accepted: 09/15/2019] [Indexed: 12/15/2022]
Abstract
One major thrust in radiology today is image standardization with a focus on rapidly acquired quantitative multi-contrast information. This is critical for multi-center trials, for the collection of big data and for the use of artificial intelligence in evaluating the data. Strategically acquired gradient echo (STAGE) imaging is one such method that can provide 8 qualitative and 7 quantitative pieces of information in 5 min or less at 3 T. STAGE provides qualitative images in the form of proton density weighted images, T1 weighted images, T2* weighted images and simulated double inversion recovery (DIR) images. STAGE also provides quantitative data in the form of proton spin density, T1, T2* and susceptibility maps as well as segmentation of white matter, gray matter and cerebrospinal fluid. STAGE uses vendors' product gradient echo sequences. It can be applied from 0.35 T to 7 T across all manufacturers producing similar results in contrast and quantification of the data. In this paper, we discuss the strengths and weaknesses of STAGE, demonstrate its contrast-to-noise (CNR) behavior relative to a large clinical data set and introduce a few new image contrasts derived from STAGE, including DIR images and a new concept referred to as true susceptibility weighted imaging (tSWI) linked to fluid attenuated inversion recovery (FLAIR) or tSWI-FLAIR for the evaluation of multiple sclerosis lesions. The robustness of STAGE T1 mapping was tested using the NIST/NIH phantom, while the reproducibility was tested by scanning a given individual ten times in one session and the same subject scanned once a week over a 12-week period. Assessment of the CNR for the enhanced T1W image (T1WE) showed a significantly better contrast between gray matter and white matter than conventional T1W images in both patients with Parkinson's disease and healthy controls. We also present some clinical cases using STAGE imaging in patients with stroke, metastasis, multiple sclerosis and a fetus with ventriculomegaly. Overall, STAGE is a comprehensive protocol that provides the clinician with numerous qualitative and quantitative images.
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Affiliation(s)
- E Mark Haacke
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA; The MRI Institute for Biomedical Research, Bingham Farms, MI, USA; Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA.
| | - Yongsheng Chen
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA; Department of Neurology, Wayne State University School of Medicine, Detroit, MI, USA
| | - David Utriainen
- The MRI Institute for Biomedical Research, Bingham Farms, MI, USA; Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
| | - Bo Wu
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
| | - Yu Wang
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China; Neusoft Medical Systems Co., Ltd., Shanghai, China
| | - Shuang Xia
- Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunyan Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Yu Luo
- Department of Radiology, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China
| | - Ali Fatemi
- Departments of Radiology and Radiation Oncology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Saifeng Liu
- The MRI Institute for Biomedical Research, Bingham Farms, MI, USA
| | - Sara Gharabaghi
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Sean K Sethi
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA; The MRI Institute for Biomedical Research, Bingham Farms, MI, USA; Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA
| | - Feng Huang
- Neusoft Medical Systems Co., Ltd., Shanghai, China
| | - Taotao Sun
- Department of Radiology, International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feifei Qu
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Brijesh K Yadav
- Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Xiaoyue Ma
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China; Department of Radiology, Zhengzhou University People's Hospital, Zhengzhou, China
| | - Yan Bai
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China; Department of Radiology, Zhengzhou University People's Hospital, Zhengzhou, China
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China; Department of Radiology, Zhengzhou University People's Hospital, Zhengzhou, China.
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Cortese R, Collorone S, Ciccarelli O, Toosy AT. Advances in brain imaging in multiple sclerosis. Ther Adv Neurol Disord 2019; 12:1756286419859722. [PMID: 31275430 PMCID: PMC6598314 DOI: 10.1177/1756286419859722] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 05/21/2019] [Indexed: 12/31/2022] Open
Abstract
Brain imaging is increasingly used to support clinicians in diagnosing multiple sclerosis (MS) and monitoring its progression. However, the role of magnetic resonance imaging (MRI) in MS goes far beyond its clinical application. Indeed, advanced imaging techniques have helped to detect different components of MS pathogenesis in vivo, which is now considered a heterogeneous process characterized by widespread damage of the central nervous system, rather than multifocal demyelination of white matter. Recently, MRI biomarkers more sensitive to disease activity than clinical disability outcome measures, have been used to monitor response to anti-inflammatory agents in patients with relapsing-remitting MS. Similarly, MRI markers of neurodegeneration exhibit the potential as primary and secondary outcomes in clinical trials for progressive phenotypes. This review will summarize recent advances in brain neuroimaging in MS from the research setting to clinical applications.
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Affiliation(s)
- Rosa Cortese
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK
| | - Sara Collorone
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Russell Square, London WC1B 5EH, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK
- National Institute for Health Research, UCL Hospitals, Biomedical Research Centre, London, UK
| | - Ahmed T. Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK
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Hu XY, Rajendran L, Lapointe E, Tam R, Li D, Traboulsee A, Rauscher A. Three-dimensional MRI sequences in MS diagnosis and research. Mult Scler 2019; 25:1700-1709. [DOI: 10.1177/1352458519848100] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).
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Affiliation(s)
- Xun Yang Hu
- Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Luckshi Rajendran
- Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Emmanuelle Lapointe
- Department of Medicine, Division of Neurology, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Roger Tam
- Department of Radiology, School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - David Li
- Department of Radiology, UBC Hospital, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Division of Neurology, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alexander Rauscher
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
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Suthiphosuwan S, Sati P, Guenette M, Montalban X, Reich DS, Bharatha A, Oh J. The Central Vein Sign in Radiologically Isolated Syndrome. AJNR Am J Neuroradiol 2019; 40:776-783. [PMID: 31000526 DOI: 10.3174/ajnr.a6045] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 03/25/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Radiologically isolated syndrome describes asymptomatic individuals with incidental radiologic abnormalities suggestive of multiple sclerosis. Recent studies have demonstrated that >40% of white matter lesions in MS (and often substantially more) have visible central veins on MR imaging. This "central vein sign" reflects perivenous inflammatory demyelination and can assist in differentiating MS from other white matter disorders. We therefore hypothesized that >40% of white matter lesions in cases of radiologically isolated syndrome would show the central vein sign. MATERIALS AND METHODS We recruited 20 participants diagnosed with radiologically isolated syndrome after evaluation by a neurologist. We performed 3T MR imaging of the brain and cervical spinal cord. White matter lesions were analyzed for the central vein sign. RESULTS Of 391 total white matter lesions, 292 (75%) demonstrated the central vein sign (central vein sign+). The median proportion of central vein sign+ lesions per case was 87% (range, 29%-100%). When the "40% rule" that has been proposed to distinguish MS from other disorders was applied, of 20 participants, 18 cases of radiologically isolated syndrome (90%) had ≥40% central vein sign+ lesions (range, 55%-100%). Two participants (10%) had <40% central vein sign+ lesions (29% and 31%). When the simpler "rule of 6" was applied, 19 participants (95%) met these criteria. In multivariable models, the number of spinal cord and infratentorial lesions was associated with a higher proportion of central vein sign+ lesions (P = .002; P = .06, respectively). CONCLUSIONS Most cases of radiologically isolated syndrome had a high proportion of central vein sign+ lesions, suggesting that lesions in these individuals reflect perivenous inflammatory demyelination. Moreover, we found correlations between the proportion of central vein sign+ lesions and spinal cord lesions, a known risk factor for radiologically isolated syndrome progressing to MS. These findings raise the possibility, testable prospectively, that the central vein sign may have prognostic value in distinguishing patients with radiologically isolated syndrome at risk of developing clinical MS from those with white matter lesions of other etiologies.
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Affiliation(s)
- S Suthiphosuwan
- From the Division of Neuroradiology (S.S., A.B.)
- Division of Neurology (S.S., M.G., X.M., J.O.), Department of Medicine
| | - P Sati
- Translational Neuroradiology Section (P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - M Guenette
- Division of Neurology (S.S., M.G., X.M., J.O.), Department of Medicine
| | - X Montalban
- Division of Neurology (S.S., M.G., X.M., J.O.), Department of Medicine
| | - D S Reich
- Translational Neuroradiology Section (P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
- Department of Neurology (D.S.R., J.O.), Johns Hopkins University, Baltimore, Maryland
| | - A Bharatha
- From the Division of Neuroradiology (S.S., A.B.)
- Division of Neurosurgery (A.B.), Department of Surgery, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - J Oh
- Division of Neurology (S.S., M.G., X.M., J.O.), Department of Medicine
- Department of Neurology (D.S.R., J.O.), Johns Hopkins University, Baltimore, Maryland
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Miki Y. Magnetic resonance imaging diagnosis of demyelinating diseases: An update. ACTA ACUST UNITED AC 2019. [DOI: 10.1111/cen3.12501] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Yukio Miki
- Department of Diagnostic and Interventional Radiology Osaka City University Graduate School of Medicine Osaka Japan
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Abstract
PURPOSE OF REVIEW To summarize recent findings from the application of MRI in the diagnostic work-up of patients with suspected multiple sclerosis (MS), and to review the insights into disease pathophysiology and the utility of MRI for monitoring treatment response. RECENT FINDINGS New evidence from the application of MRI in patients with clinically isolated syndromes has guided the 2017 revision of the McDonald criteria for MS diagnosis, which has simplified their clinical use while preserving accuracy. Other MRI measures (e.g., cortical lesions and central vein signs) may improve diagnostic specificity, but their assessment still needs to be standardized, and their reliability confirmed. Novel MRI techniques are providing fundamental insights into the pathological substrates of the disease and are helping to give a better understanding of its clinical manifestations. Combined clinical-MRI measures of disease activity and progression, together with the use of clinically relevant MRI measures (e.g., brain atrophy) might improve treatment monitoring, but these are still not ready for the clinical setting. SUMMARY Advances in MRI technology are improving the diagnostic work-up and monitoring of MS, even in the earliest phases of the disease, and are providing MRI measures that are more specific and sensitive to disease pathological substrates.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Filippi M, Brück W, Chard D, Fazekas F, Geurts JJG, Enzinger C, Hametner S, Kuhlmann T, Preziosa P, Rovira À, Schmierer K, Stadelmann C, Rocca MA. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 2019; 18:198-210. [DOI: 10.1016/s1474-4422(18)30451-4] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 10/22/2018] [Accepted: 11/12/2018] [Indexed: 12/12/2022]
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Standardizing Magnetic Resonance Imaging Protocols, Requisitions, and Reports in Multiple Sclerosis: An Update for Radiologist Based on 2017 Magnetic Resonance Imaging in Multiple Sclerosis and 2018 Consortium of Multiple Sclerosis Centers Consensus Guidelines. J Comput Assist Tomogr 2019; 43:1-12. [PMID: 30015803 DOI: 10.1097/rct.0000000000000767] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The advent of magnetic resonance imaging has improved our understanding of the pathophysiology and natural course of multiple sclerosis (MS). The ability of magnetic resonance imaging to show the evolution of MS lesions on sequential scans has brought it to be one of the endpoints in clinical trials for disease-modifying therapies. Based on the most updated consensus guidelines from the American (Consortium of MS Centers) and European (Magnetic Resonance Imaging in MS) boards of experts in MS, this document shows the most relevant landmarks related to imaging findings, diagnostic criteria, indications to obtain a magnetic resonance, scan protocols and sequence options for patients with MS. Although incorporating the knowledge derived from the research arena into the daily clinical practice is always challenging, in this article, the authors provide useful recommendations to improve the information contained in the magnetic resonance report oriented to facilitate communication between radiologists and specialized medical teams involved in MS patients' multidisciplinary care.
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Ugga L, Cocozza S, Pontillo G, Russo C, Brescia Morra V, Lanzillo R, Riccio E, Pisani A, Brunetti A. Absence of infratentorial lesions in Fabry disease contributes to differential diagnosis with multiple sclerosis. Brain Behav 2018; 8:e01121. [PMID: 30277321 PMCID: PMC6236241 DOI: 10.1002/brb3.1121] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 08/12/2018] [Accepted: 08/17/2018] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND AND PURPOSE Multiple Sclerosis (MS) has been proposed as a possible differential diagnosis with Fabry Disease (FD). We evaluated the incidence of infratentorial lesions in FD patients, investigating whether their presence could help in differentiating these two conditions. We explored the diagnostic accuracy of this sign alone and in combination to the involvement of corpus callosum (CC). METHODS White Matter lesions were retrospectively evaluated on FLAIR images available from 136 MS and 144 FD patients. Infratentorial involvement was assessed considering the whole cerebellum, and the part of the brainstem included between the occipital foramen and the upper edge of the red nucleus. Furthermore, the presence of callosal lesions was also recorded, evaluating the portion of CC included between the two external walls of the lateral ventricles. RESULTS Infratentorial involvement was detectable in 119/136 (87.5%) MS patients, while it was present in only 17/144 (11.8%) FD patients. When the diagnostic performance of a positive infratentorial involvement was evaluated in combination with the presence of CC lesions, a specificity of 97%, with a positive predictive value of 96% was reached. CONCLUSIONS We concluded that the absence of infratentorial lesions, especially when combined to the evaluation of other typical imaging features, can help in the differential diagnosis between MS and FD.
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Affiliation(s)
- Lorenzo Ugga
- Department of Advanced Biomedical SciencesUniversity of Naples “Federico II”NaplesItaly
| | - Sirio Cocozza
- Department of Advanced Biomedical SciencesUniversity of Naples “Federico II”NaplesItaly
| | - Giuseppe Pontillo
- Department of Advanced Biomedical SciencesUniversity of Naples “Federico II”NaplesItaly
| | - Camilla Russo
- Department of Advanced Biomedical SciencesUniversity of Naples “Federico II”NaplesItaly
| | - Vincenzo Brescia Morra
- Department of Neurosciences and Reproductive and Odontostomatological SciencesUniversity of Naples “Federico II”NaplesItaly
| | - Roberta Lanzillo
- Department of Neurosciences and Reproductive and Odontostomatological SciencesUniversity of Naples “Federico II”NaplesItaly
| | - Eleonora Riccio
- Department of Public Health, Nephrology UnitUniversity of Naples “Federico II”NaplesItaly
| | - Antonio Pisani
- Department of Public Health, Nephrology UnitUniversity of Naples “Federico II”NaplesItaly
| | - Arturo Brunetti
- Department of Advanced Biomedical SciencesUniversity of Naples “Federico II”NaplesItaly
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Dworkin JD, Sati P, Solomon A, Pham DL, Watts R, Martin ML, Ontaneda D, Schindler MK, Reich DS, Shinohara RT. Automated Integration of Multimodal MRI for the Probabilistic Detection of the Central Vein Sign in White Matter Lesions. AJNR Am J Neuroradiol 2018; 39:1806-1813. [PMID: 30213803 DOI: 10.3174/ajnr.a5765] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 06/25/2018] [Indexed: 01/16/2023]
Abstract
BACKGROUND AND PURPOSE The central vein sign is a promising MR imaging diagnostic biomarker for multiple sclerosis. Recent studies have demonstrated that patients with MS have higher proportions of white matter lesions with the central vein sign compared with those with diseases that mimic MS on MR imaging. However, the clinical application of the central vein sign as a biomarker is limited by interrater differences in the adjudication of the central vein sign as well as the time burden required for the determination of the central vein sign for each lesion in a patient's full MR imaging scan. In this study, we present an automated technique for the detection of the central vein sign in white matter lesions. MATERIALS AND METHODS Using multimodal MR imaging, the proposed method derives a central vein sign probability, πij, for each lesion, as well as a patient-level central vein sign biomarker, ψi. The method is probabilistic in nature, allows site-specific lesion segmentation methods, and is potentially robust to intersite variability. The proposed algorithm was tested on imaging acquired at the University of Vermont in 16 participants who have MS and 15 participants who do not. RESULTS By means of the proposed automated technique, participants with MS were found to have significantly higher values of ψ than those without MS (ψMS = 0.55 ± 0.18; ψnon-MS = 0.31 ± 0.12; P < .001). The algorithm was also found to show strong discriminative ability between patients with and without MS, with an area under the curve of 0.88. CONCLUSIONS The current study presents the first fully automated method for detecting the central vein sign in white matter lesions and demonstrates promising performance in a sample of patients with and without MS.
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Affiliation(s)
- J D Dworkin
- From the Department of Biostatistics, Epidemiology, and Informatics (J.D.D., M.L.M., R.T.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - P Sati
- Translational Neuroradiology Section (P.S., M.K.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - A Solomon
- Departments of Neurological Sciences (A.S.)
| | - D L Pham
- Center for Neuroscience and Regenerative Medicine (D.L.P.), Henry M. Jackson Foundation, Bethesda, Maryland
| | - R Watts
- Radiology (R.W.), Larner College of Medicine at the University of Vermont, Burlington, Vermont
| | - M L Martin
- From the Department of Biostatistics, Epidemiology, and Informatics (J.D.D., M.L.M., R.T.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - D Ontaneda
- Mellen Center for Multiple Sclerosis Treatment and Research (D.O.), Cleveland Clinic, Cleveland, Ohio
| | - M K Schindler
- Translational Neuroradiology Section (P.S., M.K.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - D S Reich
- Translational Neuroradiology Section (P.S., M.K.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
- Department of Neurology (D.S.R.), Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - R T Shinohara
- From the Department of Biostatistics, Epidemiology, and Informatics (J.D.D., M.L.M., R.T.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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Absinta M, Sati P, Fechner A, Schindler MK, Nair G, Reich DS. Identification of Chronic Active Multiple Sclerosis Lesions on 3T MRI. AJNR Am J Neuroradiol 2018; 39:1233-1238. [PMID: 29724768 DOI: 10.3174/ajnr.a5660] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 03/13/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND PURPOSE MR imaging-pathologic studies have reported that paramagnetic rims on 7T susceptibility-based MR imaging identify, in vivo, the subset of MS lesions with compartmentalized inflammation at the lesion edge and associated remyelination failure. Here, we assessed the reliability of detecting these rims on high-resolution 3T phase images. MATERIALS AND METHODS High-resolution T2* and phase MR imaging was collected in 20 patients with MS at 3T (3D segmented EPI, 0.65 mm3) and 7T (2D gradient-echo, 0.2 × 0.2 × 1 mm) MR imaging. In each case, 5 discrete chronic (nonenhancing) MS lesions were selected on T2 FLAIR images for rim evaluation. Five raters experienced in MS imaging contributed to the rim assessment, of whom 3 worked independently on 3T data, and 2, on 7T data. Consensus agreement was reached for both 3T and 7T rim evaluations. Discrepancies between 3T and 7T were discussed, and consensus was reached. RESULTS Phase rims were seen in 34 lesions at 7T and in 36 lesions at 3T by consensus. Inter- and intrarater reliability were "substantial/good" both at 3T and 7T analysis (Cohen κ, >0.71). Based on consensus agreement, the reliability of rim visualization at 3T versus 7T was 0.78 (κ) with a pair-wise agreement of 90%. More lesions were judged to be false-positive or false-negative at 3T than at 7T. CONCLUSIONS Nearly all 7T paramagnetic rims can also be seen at 3T. Imaging at 3T opens the possibility of implementing paramagnetic rims as an outcome measure in multicenter, MR imaging-based clinical trials aimed at treating perilesional persistent inflammation and its potential effects on remyelination.
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Affiliation(s)
- M Absinta
- From the Translational Neuroradiology Section (M.A., P.S., A.F., M.K.S., G.N., D.S.R.), Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - P Sati
- From the Translational Neuroradiology Section (M.A., P.S., A.F., M.K.S., G.N., D.S.R.), Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - A Fechner
- From the Translational Neuroradiology Section (M.A., P.S., A.F., M.K.S., G.N., D.S.R.), Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.,Department of Radiology (A.F.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - M K Schindler
- From the Translational Neuroradiology Section (M.A., P.S., A.F., M.K.S., G.N., D.S.R.), Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - G Nair
- From the Translational Neuroradiology Section (M.A., P.S., A.F., M.K.S., G.N., D.S.R.), Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - D S Reich
- From the Translational Neuroradiology Section (M.A., P.S., A.F., M.K.S., G.N., D.S.R.), Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
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Sparacia G, Agnello F, Gambino A, Sciortino M, Midiri M. Multiple sclerosis: High prevalence of the 'central vein' sign in white matter lesions on susceptibility-weighted images. Neuroradiol J 2018; 31:356-361. [PMID: 29565219 DOI: 10.1177/1971400918763577] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Purpose The aim of this study was to determine the occurrence and distribution of the 'central vein' sign in white matter lesions on susceptibility-weighted magnetic resonance images in patients with multiple sclerosis (MS) and cerebral small vessel disease (CSVD). Materials and methods T2-weighted and fluid-attenuated inversion recovery magnetic resonance images of 19 MS patients and 19 patients affected by CSVD were analysed for the presence and localisation of focal hyperintense white matter lesions. Lesions were subdivided into periventricular or non-periventricular (juxtacortical, subcortical, deep white matter and cerebellar) distributed. The number and localisation of lesions presenting with the central vein sign were recorded and compared between MS and CSVD lesions. Results A total of 313 MS patients and 75 CSVD lesions were identified on T2-weighted and fluid-attenuated inversion recovery magnetic resonance images. The central vein sign was found in 128 MS lesions (40.9%), and the majority of them (71/128, 55.5%) had a periventricular distribution. The central vein sign was found in 22 out of 75 (29.3%) CSVD lesions, and periventricular distribution was seen in six out of 22 (27.2%) CSVD lesions. The difference in the proportion of white matter hyperintense lesions that presented with the central vein sign on susceptibility-weighted images in patients with MS and CSVD was statistically different, and a significantly higher number of MS patients presented with lesions with the central vein sign compared to CSVD patients. Conclusion The presence of the central vein sign on susceptibility-weighted images for MS lesions improves the understanding of the periventricular distribution of MS lesions and could contribute as adjunctive diagnostic criteria for MS disease.
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Affiliation(s)
| | - Francesco Agnello
- 1 DIBIMED - Sezione di Scienze Radiologiche, University of Palermo, Palermo, Italy
| | - Angelo Gambino
- 1 DIBIMED - Sezione di Scienze Radiologiche, University of Palermo, Palermo, Italy
| | | | - Massimo Midiri
- 1 DIBIMED - Sezione di Scienze Radiologiche, University of Palermo, Palermo, Italy
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Maggi P, Absinta M, Grammatico M, Vuolo L, Emmi G, Carlucci G, Spagni G, Barilaro A, Repice AM, Emmi L, Prisco D, Martinelli V, Scotti R, Sadeghi N, Perrotta G, Sati P, Dachy B, Reich DS, Filippi M, Massacesi L. Central vein sign differentiates Multiple Sclerosis from central nervous system inflammatory vasculopathies. Ann Neurol 2018; 83:283-294. [PMID: 29328521 PMCID: PMC5901412 DOI: 10.1002/ana.25146] [Citation(s) in RCA: 148] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Revised: 01/10/2018] [Accepted: 01/10/2018] [Indexed: 12/12/2022]
Abstract
Objectives In multiple sclerosis (MS), magnetic resonance imaging (MRI) is a sensitive tool for detecting white matter lesions, but its diagnostic specificity is still suboptimal; ambiguous cases are frequent in clinical practice. Detection of perivenular lesions in the brain (the “central vein sign”) improves the pathological specificity of MS diagnosis, but comprehensive evaluation of this MRI biomarker in MS‐mimicking inflammatory and/or autoimmune diseases, such as central nervous system (CNS) inflammatory vasculopathies, is lacking. In a multicenter study, we assessed the frequency of perivenular lesions in MS versus systemic autoimmune diseases with CNS involvement and primary angiitis of the CNS (PACNS). Methods In 31 patients with inflammatory CNS vasculopathies and 52 with relapsing–remitting MS, 3‐dimensional T2*‐weighted and T2–fluid‐attenuated inversion recovery images were obtained during a single MRI acquisition after gadolinium injection. For each lesion, the central vein sign was evaluated according to consensus guidelines. For each patient, lesion count, volume, and brain location, as well as fulfillment of dissemination in space MRI criteria, were assessed. Results MS showed higher frequency of perivenular lesions (median = 88%) than did inflammatory CNS vasculopathies (14%), without overlap between groups or differences between 3T and 1.5T MRI. Among inflammatory vasculopathies, Behçet disease showed the highest median frequency of perivenular lesions (34%), followed by PACNS (14%), antiphospholipid syndromes (12%), Sjögren syndrome (11%), and systemic lupus erythematosus (0%). When a threshold of 50% perivenular lesions was applied, central vein sign discriminated MS from inflammatory vasculopathies with a diagnostic accuracy of 100%. Interpretation The central vein sign differentiates inflammatory CNS vasculopathies from MS at standard clinical magnetic field strengths. Ann Neurol 2018;83:283–294
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Affiliation(s)
- Pietro Maggi
- Department of Neurology, Université Libre de Bruxelles, Brussels, Belgium.,Department of Neurology, Brugmann University Hospital, Université Libre de Bruxelles, Brussels, Belgium.,Department of Neurology, Lausanne University Hospital, Lausanne, Switzerland
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.,Department of Neurology, Vita-Salute San Raffaele University, Milan, Italy.,Neuroimaging Research Unit, Institute of Experimental Neurology, San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Matteo Grammatico
- Department of Neuroscience, Drug and Child Health, University of Florence, Florence, Italy
| | - Luisa Vuolo
- Department of Neuroscience, Drug and Child Health, University of Florence, Florence, Italy
| | - Giacomo Emmi
- Internal Interdisciplinary Medicine, Center for Rare Cardiovascular and Immunological Diseases Lupus Clinic, Careggi University Hospital, University of Florence, Florence, Italy
| | - Giovanna Carlucci
- Multiple Sclerosis Center, Department of Neurology 2, Careggi University Hospital, University of Florence, Florence, Italy
| | - Gregorio Spagni
- Department of Neuroscience, Drug and Child Health, University of Florence, Florence, Italy
| | - Alessandro Barilaro
- Multiple Sclerosis Center, Department of Neurology 2, Careggi University Hospital, University of Florence, Florence, Italy
| | - Anna Maria Repice
- Multiple Sclerosis Center, Department of Neurology 2, Careggi University Hospital, University of Florence, Florence, Italy
| | - Lorenzo Emmi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Domenico Prisco
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | | | - Roberta Scotti
- Department of Radiology, Vita-Salute San Raffaele University, Milan, Italy
| | - Niloufar Sadeghi
- Department of Radiology, Erasme University Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Gaetano Perrotta
- Department of Neurology, Université Libre de Bruxelles, Brussels, Belgium
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Bernard Dachy
- Department of Neurology, Brugmann University Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Massimo Filippi
- Department of Neurology, Vita-Salute San Raffaele University, Milan, Italy.,Neuroimaging Research Unit, Institute of Experimental Neurology, San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Luca Massacesi
- Department of Neuroscience, Drug and Child Health, University of Florence, Florence, Italy.,Multiple Sclerosis Center, Department of Neurology 2, Careggi University Hospital, University of Florence, Florence, Italy
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