Magnetic resonance imaging (MRI) is a crucial tenet in the diagnostic criteria for multiple sclerosis (MS), requiring the presence of hyperintense lesions on T2-weighted or Fluid Attenuated Inversion Recovery (FLAIR) sequences and having a specific size, morphology, and location.1,2 Since the 1990s, incidentally uncovered T2 lesions suggestive of MS in asymptomatic patients have been described.3–6 In 2009, the radiologically isolated syndrome (RIS) criteria were defined to enhance the characterization of individuals with abnormal MRI studies.7 Analysis of a worldwide RIS cohort demonstrated that younger age, male sex, and the presence of spinal cord lesions were associated with a 5-year risk of conversion to a first clinical demyelinating event.8 After 10 years, age and spinal cord lesions were still associated with increased risk, as were cerebrospinal fluid (CSF) restricted oligoclonal bands (OCBs), infratentorial lesions, and gadolinium-enhancing lesions on the index scan.9,10
Recently, the RIS diagnostic criteria were revised to encompass subjects with fewer T2 lesions.11 While these updated criteria may enhance clinical practice, aligning more closely with the 2017 McDonald criteria for MS, the issue of misdiagnosing RIS in people with other white matter (WM) disorders remains a crucial concern.12–14 Given this, there is a need for specific biomarkers capable of accurately characterizing people with presymptomatic anomalies typical for MS on MRI compared to those with WM anomalies from other causes. The origin of lesions on MRI in the context of MS is due to activated immune cells crossing the blood–brain barrier to access the central nervous system (CNS) tissue, resulting in injury around perivenular structures.15 Therefore, interest in studying perivenular involvement in MS has increased over the last few decades.16–19 With the development of ultra-high-field (i.e., 7T) MRI, better visualization of venous structures has emerged, offering enhanced image resolution and improved susceptibility contrast of venous blood.17,20–24 These studies suggest that observing small veins in MS lesions could improve lesion specificity for autoimmune inflammatory demyelination. Such findings may have great applicability in identifying those with RIS. In 2013, the first studies on 3T MR scans used in clinical practice appeared,18,19,23,25–28 using susceptibility-weighted imaging (SWI). Based on existing literature, the central vein sign (CVS) seems to be associated with high sensitivity and specificity for MS compared to other WM lesion etiologies.26–29
Our study aims to evaluate the diagnostic performance of the CVS sign in people with RIS by comparing the proportion of CVS-positive (CVS+) lesions between subjects with RIS, patients with MS, and patients with non-MS WM lesions. The secondary objective was to evaluate the ideal CVS threshold for diagnosing RIS.
Methods EthicsAccording to French laws, participants received appropriate research information and non-opposing participation documentation. The study received approval from the Institutional Review Board of the Nice University Hospital, and the protocol was registered under the reference EI-529.
ParticipantsAll participants underwent a 3T brain MRI with SWI sequences from June 1, 2020, to January 1, 2023. All RIS subjects were recruited from the RIS database (NCT05388331) and fulfilled the 2009 RIS diagnostic criteria.7 Patients with non-MS were recruited prospectively from the CyBIRD cohort (NCT05056740), corresponding to patients referred to the MS tertiary center for the diagnostic work-up of white matter hyperintensities suggestive of underlying inflammatory demyelinating disease. MS patients were newly diagnosed and fulfilled the 2017 McDonald criteria. The non-MS subjects were separated into two subgroups depending on their diagnosis: (i) noninflammatory neurological disorders group (NIND) consisting of patients with small cerebral vessel disease, migraine, antiphospholipid syndrome and (ii) other inflammatory neurological disorders group (OIND) consisting of patients with a non-MS inflammatory CNS disorders or a cerebral vasculopathy associated with a systemic inflammatory disorder (e.g., myelitis, vasculitis, neuromyelitis optica spectrum disorder, and neuroborreliosis). MS and non-MS participants were sex- and age-matched (±5 years) with the RIS cohort to limit bias from comorbidities in the CVS evaluation (1:1:2 ratio). After a complete clinical assessment, a multidisciplinary group of neurologists (CLF, MC) and neuroradiologists (LM, AT) validated all final diagnoses.
All MR examinations were performed using a single 3T MRI system (Discovery MR750w, GE Healthcare, Milwaukee, WI, USA) using 32-channel head coils. The following sequences were obtained in all patients: 3D T1 sagittal IR-prepped Fast Spoiled Gradient Recalled imaging IR-FSPGR-BRAVO with TR/TI/TE of 7.3/450/2.7 ms and acquisition matrix of 1 × 1 × 1 mm; 3D axial T2 star weighted angiography (SWAN)-venule with TR/TE of 48/25 ms, section thickness 0.8 mm, flip angle = 8°; 3D sagittal CUBE FLAIR with TR/TI/TE of 7202/1981/124 ms; 3D sagittal CUBE T1 with TR/TE of 502/12.1 ms and acquisition matrix of 1.2 × 1.2 × 1.2 mm; SWAN-venule, FLAIR, and 3D CUBE T1. SWAN-venule sequence was immediately acquired after the intravenous administration of 0.1 mmol/kg of gadolinium-based contrast agent (gadoterate meglumine, Dotarem; Guerbet, Aulnay-sous-Bois, France).
Image processing and analysisSWAN-venule images were co-registered to FLAIR images using the Advantage Windows 4.7 Workstation GE Healthcare integrated registration software. According to the North American Imaging in Multiple Sclerosis Cooperative consensus statement (NAIMS),30 a lesion was considered vein-centered when the vein was visible in a minimum of two perpendicular planes. The vein was required to run partially or entirely through the lesion and be positioned in the approximate center of the lesion (e.g., Fig. 1). Small (<3 mm diameter) and confluent lesions were excluded from the analysis, along with lesions containing multiple distinct veins. Image interpretation was performed on XERO® viewer with no tool for lesion identification. Lesions were identified on the FLAIR images, and CVS assessment was performed on the SWAN-venule images in the three planes using the workstation's synchronization tool. The proportion of CVS+ WMLs was expressed as absolute values and percentage of the total WMLs.
The 3-lesion CVS+ threshold was positive if at least three candidate lesions with CVS were restricted to subcortical, deep white matter, and juxtacortical regions.31
The six-lesion CVS+ threshold was determined as positive if at minimum six candidate lesions with CVS in the whole brain.26
Cervical lesions and gadolinium enhancement were assessed on the sagittal CUBE FLAIR and sagittal 3D CUBE T1 postinjection.
Two independent evaluators (CLC and ML) analyzed all MRI studies and were blinded to baseline demographic information and group classification. Both evaluators, experienced in neuroimaging, underwent CVS assessment training before completing this study. In case of evaluators' disagreement, two independent neuroradiologists (LM and AT) were asked to adjudicate the CVS assessment, and the final decision was determined via consensus agreement.
Laboratory featuresBlood and cerebrospinal fluid (CSF) were collected and analyzed in the Nice University Hospital immunology laboratory. Blood and CSF IgG, albumin, and KFLC were measured by turbidimetry with the analyzer Optilite (The Binding Site, Birmingham, UK) using the serum-free light chain immunoassay Freelight (The Binding Site, Birmingham, UK), according to the manufacturer's instructions. Oligoclonal bands (OCB) were determined by isoelectric focusing on agarose gel using subsequent immunoblotting using IgG-specific antibody staining (Hydrasys platform; Sebia, Lisses, France). OCB patterns were evaluated by an experienced biologist and classified as positive (patterns II and III) or negative (other patterns). The determination of intrathecal synthesis of KFLC was evaluated by calculating the K-index using the formula: K-index = (CSF KFLC/serum KFLC)/(CSF albumin/serum albumin).32,33 A cutoff ≥2 CSF restricted bands or K-index ≥8.92 defined CSF positivity.
Statistical analysisStatistical analyses were performed using the online application EasyMedStat (version 3.22
The diagnostic performance of CVS characteristics (total number of CVS+ lesions, % of CVS+ lesions) in various brain locations (all locations, periventricular, deep white matter [DWM], cortical–juxtacortical, infratentorial) was analyzed using receiver operating characteristics (ROC) curves, calculating the area under the curves (AUC). According to DeLong's method, the best combination of CVS biomarkers and location in the RIS cohort was identified by comparing each AUC with their 95% confidence interval (CI). The optimal CVS+ threshold that best separated RIS from non-MS subjects was determined by maximizing the Youden index. Sensitivity, specificity, accuracy, and positive and negative predictive values were assessed using different CVS thresholds: (i) our optimized threshold, (ii) the “40% CVS+ threshold,” (iii) the “the 3-lesion CVS+ threshold”, and the “the 6-lesion CVS+ threshold”.25,26,29,31,34–36 RIS and MS participants with CVS+ lesions above the threshold were classified as true positives. Participants without MS with CVS+ lesions below the threshold were classified as true negatives. Finally, the diagnostic performances of CVS in RIS and MS were compared using independent AUC comparisons (DeLong's method) using ROC AUC and standard errors. A p-value less than 0.05 was considered statistically significant.
Results Clinical characteristicsOne hundred eighty participants were included: 45 with RIS, 45 with MS (39 with relapsing–remitting and 6 with primary progressive clinical courses), and 90 with non-MS (54 NIND and 36 OIND). Mean (±SD) age was 47.1 (±13.5), 43.8 (±12.7), 50.1 (±14.4), and 50.8 (±14.7) years in RIS, MS, NIND, and OIND groups, respectively (p = 0.076); and, 77.8%, 77.8%, 81.5%, and 69.4% of the included participants were females in the RIS, MS, NIND, and OIND groups, respectively (p = 0.613). People in the MS and RIS groups exhibited a higher frequency of positive OCB and positive Kappa index than non-MS (p < 0.001), but RIS and MS groups were comparable for OCB status (p = 0.17), Table 1.
Table 1 Demographic and clinical characteristics of the entire cohort.
Bold text indicates p values that reach statistical significance (p < 0.05).
CVS, central vein sign; DWM, deep white matter; Gd, Gadolinium; MS, multiple sclerosis; NIND, noninflammatory neurological disorder; OCBs, oligoclonal bands; OIND, other inflammatory neurological disorders; RIS, radiologically isolated syndrome; SD, standard deviation; WM, white matter.
*The association between variables and diagnosis was tested with the chi-squared test.
**The difference between age according to diagnosis was assessed with the ANOVA.
***The difference between variables according to diagnosis was assessed with the Kruskal–Wallis.
After excluding noneligible WMLs for CVS assessment, 4608 (87%) lesions (970 in RIS, 1378 in MS, 1722 in NIND, and 538 in OIND) were analyzed. The number of periventricular, juxtacortical, and infratentorial WMLs was higher in the RIS group than in non-MS groups (p < 0.05 for all pairwise comparisons). RIS and OIND groups were comparable according to the number of participants with T1-gadolinium-enhanced lesions (p = 0.232) and cervical spinal cord lesions (p = 0.612).
Of the 4608 analyzed WMLs, 1905 (41.5%) were vein-centered. The proportion of CVS+ WMLs was higher in MS (70.4%) and RIS (66.4%) than in non-MS (12.9%), p < 0.001 (Fig. 2). The mean proportion of CVS+ WMLs per patient was higher in both MS (70.7% ± 16.7) and RIS (73.6% ± 19.8) than in non-MS subjects (15.0% ± 15.8 in the NIND group and 20.0% ± 20.7 in the OIND group) (p < 0.001) (Table 1). The mean percentage of CVS+ WMLs per patient was not statistically different between RIS and MS (p = 0.626) (Fig. 2).
Most of the periventricular WMLs were CVS+, independent of group assignments. The mean proportion of periventricular CVS+ WMLs was 93.6%, 74.2%, 69.2%, and 62.9% in the RIS, MS, OIND, and NIND groups, respectively (p = 0.074) (Table 1). According to ROC analysis (OIND and NIND pooled as non-MS), the periventricular proportion of CVS+ lesions had poor diagnostic performance in separating RIS (AUC 0.608 [0.501; 0.714]) and MS (AUC 0.517 [0.403; 0.632]) from non-MS (Fig. 3).
The mean proportion of CVS+ WMLs was not different between RIS and MS for juxtacortical (p = 0.502), infratentorial (p = 0.986), and DWM (p = 0.480) brain locations. However, the proportion of CVS+ WMLs was higher in all brain locations in RIS compared to the non-MS group (<0.001 for all pairwise comparisons) (Table 1).
According to ROC analysis, the proportion of DWM CVS+ lesions, the proportion of all CVS+ excluding periventricular lesions, and the absolute number of CVS+ lesions performed well in separating RIS from non-MS; AUC of 0.950 [0.914; 0.985], 0.957 [0.924; 0.991], and 0.905 [0.857; 0.954], respectively (Fig. 3). The optimal threshold that best separated RIS from non-MS was 25% CVS+ lesions when considering only DWM locations, 40% CVS+ lesions when considering all of the brain, excluding periventricular areas, and 6-lesion CVS+ when considering the absolute number of eligible lesions. According to an independent ROC comparison (Table 2), the proportion of DMW CVS+ lesions had similar performances in separating RIS from non-MS (AUC 0.950) than MS from non-MS (AUC 0.975) (p = 0.255). Similarly, the proportion of all areas excluding periventricular CVS+ lesions had similar performances in separating RIS from non-MS (AUC 0.957) and MS from non-MS (AUC 0.969) (p = 0.837).
Table 2 Comparison of the diagnosis performance of the CVS between RIS and MS.
MS | RIS | MS vs. RIS comparison | ||||||
AUC | SE | AUC | SE | AUC difference | SE | z statistic | p-value | |
Proportion of positive CVS lesions (all brain locations except periventricular) | 0.969 | 0.0323 | 0.957 | 0.0362 | 0.011 | 0.0485 | 0.206 | 0.837 |
Proportion of positive CVS DWM lesions | 0.975 | 0.0127 | 0.950 | 0.0179 | 0.025 | 0.0219 | 1.139 | 0.255 |
AUC, area under the curve; CVS, central vein sign; DWM, deep white matter; MS, multiple sclerosis; RIS, radiologically isolated syndrome; SE, standard error.
Clinical application ofPerformances were calculated for different CVS thresholds: (i) our obtained 25% CVS+ proportion threshold, (ii) a 40% CVS+ proportion threshold, (iii) a ≥ 3 CVS+ lesion threshold, and (iv) a ≥ 6 CVS+ lesion threshold in both RIS and MS populations (Table 3).
Table 3 Diagnosis performance of different CVS thresholds in RIS and MS.
Thresholds | % | |||||||||
RIS vs. non-MS | MS vs. non-MS | |||||||||
Se | Sp | PPN | NPV | ACC | Se | Sp | PPN | NPV | ACC | |
Optimized threshold (25% CVS+) | ||||||||||
25% CVS+, including all areas | 98 | 76 | 67 | 99 | 83 | 100 | 76 | 67 | 100 | 84 |
25% CVS+ excluding PV | 93 | 80 | 70 | 96 | 85 | 100 | 80 | 72 | 100 | 87 |
25% CVS+ restricted to DWM | 98 | 82 | 73 | 99 | 88 | 100 | 82 | 74 | 100 | 88 |
40% CVS+ rule | ||||||||||
40% CVS+, including all areas | 96 | 88 | 80 | 98 | 90 | 96 | 88 | 80 | 98 | 90 |
40% CVS+ excluding PV | 84 | 90 | 81 | 92 | 88 | 93 | 90 | 83 | 96 | 91 |
40% CVS+ restricted to DWM | 80 | 90 | 80 | 90 | 87 | 93 | 90 | 83 | 96 | 91 |
≥3 central veins | ||||||||||
3-lesion CVS+ | 80 | 67 | 55 | 87 | 71 | 91 | 67 | 58 | 94 | 75 |
≥6 central veins | ||||||||||
6-lesion CVS+ | 95 | 83 | 74 | 97 | 87 | 98 | 83 | 76 | 98 | 88 |
ACC, accuracy; CVS, central vein sign; CVS+, positive central vein sign; DWM, deep white matter; MS, multiple sclerosis; NPV, negative predictive value; PPV, positive predictive value; PV, periventricular; RIS, radiologically isolated syndrome; Se, sensitivity; Sp, specificity.
The 40% CVS+ proportion threshold showed similar accuracy in diagnosing RIS and MS when considering assessments isolated to the DWM and all areas excluding periventricular locations. The 25% CVS+ threshold categorized RIS or MS with very high sensitivity (0.93 and 0.98 for RIS and 1.00 for MS, in both the DWM region and all areas excluding periventricular locations, respectively), but with a significant loss of specificity (0.80 and 0.82 instead of 0.90) when compared with the 40% CVS+ threshold. Overall, there was no statistical difference in using the 40% or the 25% CVS+ thresholds in separating RIS from non-MS (p = 0.623 when considering isolated DMW lesions and p = 0.713 when considering all excluding periventricular lesions for AUC comparisons). The 40% CVS+ threshold showed a slightly better accuracy, favoring a higher specificity, in diagnosing RIS and MS than the 25% CVS+ threshold (Table 3).
The 6-lesion CVS+ threshold categorized RIS or MS with very high sensitivity (0.95 for RIS and 0.98 for MS) but with a loss of specificity (0.83 instead of 0.90) when compared with the 40% CVS+ threshold. Nonetheless, the 6-lesion CVS+ threshold showed better accuracy in diagnosing RIS and MS than the 3-lesion CVS+ threshold (Table 3).
Adding OCBs or K-index positivity to the CVS biomarker increased the specificity (up to 100%) for RIS diagnosis but with lower sensitivity, supplementary data 1.
DiscussionOur results revealed that (i) the proportion of CVS+ WMLs is similar between RIS and MS subjects, (ii) the proportion of CVS+ WMLs effectively distinguishes subjects with RIS from non-MS patients with overall good performances, and (iii) the 6-lesion CVS+ is excellent tool to increase specificity for the T2 lesions suggestive of RIS or MS. There is currently no established biological or imaging biomarker for diagnosing MS and, by extension, RIS. Our findings reinforce the importance of CVS in identifying lesions related to CNS demyelination, even in the presymptomatic stage of the disease.17–19,23,24,27,29,34,35,37 The diagnosis of MS is enhanced by the presence of clinical symptoms (i.e., optic neuritis and myelitis), biological (i.e., CSF-restricted OCBs and kappa-free light chain), and MRI criteria.38–41 However, the diagnosis of RIS is primarily limited by lesion specificity, given the absence of clinical events.7,11 Therefore, MRI expertise remains a cornerstone in accurately classifying observed lesions on MRI. Imaging accuracy is even more critical for RIS than MS, especially with the completion of two clinical trials that confirm the efficacy of disease-modifying therapies used in RIS in delaying or preventing clinical conversion to symptomatic MS.42,43 In both MS and RIS, the latest diagnostic criteria require a reduced number of T2-weighted hyperintensities to establish the diagnosis.11,38 This modification allows for the earlier recognition of at-risk subjects with a higher sensitivity but lower specificity, increasing the risk of misdiagnosis.11,14,44–47 Our results suggest that the 3T MRI technique using SWI sequence as part of routine imaging of the CNS may improve diagnostic accuracy. Doing so may allow for more effective clinical counseling and care for those with RIS.42,43
Our results align with others and suggest that the CVS is not a discriminant biomarker capable of delineating between CNS disorders containing periventricular lesions.29 This may be explained by the high number of veins within the region, which may lead to a false positive interpretation. On the other hand, in our study, infratentorial and juxtacortical lesions from MS and RIS patients were mostly vein-centered (nearly 80% for infratentorial and 65% for juxtacortical), as opposed to non-MS (20% for infratentorial and 27% for juxtacortical) confirming previous observations.48,49
Thresholds of CVS+ are wide and mainly dependent on the number of included patients and the chosen control populations. For example, a 50% CVS+ threshold is reported to separate MS from inflammatory vasculopathy, and a 54% CVS+ is said to separate MS from NMOSD.28,50 A 45% CVS+ threshold is adopted to separate MS from small cerebral vessel disease.27 The more extensive series reported to date estimates a sensitivity of 100% and a specificity of 89% for a 35% CVS+ threshold to separate MS from nonselected controls according to optimized T2*-weighted imaging and highlights that the diagnostic performance of the CVS highly depends on magnetic susceptibility images, lower with standard SWI images and higher with 3D T2*-weighted sequences optimized.29 CVS should be evaluated on dedicated standardized MRI protocols51: MRI parameters are crucial, notably using one plane high-resolution, millimeter isotropic voxel to allow 3D reconstruction with good resolution and a clinically acceptable acquisition time. Also, using gadolinium agents is essential to increase the conspicuity of the veins.19 Limitations include the need for dedicated sequences accessibility (e.g., SWI, T2 FLAIR*, and SWAN), radiological expertise, standardized protocols for training, and a consensus on the CVS threshold.
CVS is not the only surrogate marker for MS and RIS lesions. MS lesions incur deformation and displacement on longitudinal 3D scans, transitioning both in shape and location within the CNS.52 Changes also influence the direction and magnitude of volume.53 These characteristics may explain why central vessels are only sometimes seen. These observations suggest that CVS would be more likely to be seen in a newer lesion that is stable in morphology.
Still, it is unclear how to apply such biomarkers in routine clinical practice. The inclusion of CVS in MS criteria is still an ongoing discussion. Dedicated prospective studies are needed to evaluate how to use such biomarkers in routine care. Also, an automated method that can make this more palatable as a clinical tool needs to be improved.
While some pivotal work in RIS previously focused on CVS, to our knowledge, our study is the first comparative study demonstrating that CVS shows high specificity in diagnosing RIS compared to other WMLs non-MS disorders.36 We found that a 40% CVS+ lesions threshold may correctly separate RIS and MS from non-MS groups, except for periventricular lesions, whether isolated to DWM or other lesion types. This threshold is concordant with what is proposed for MS in the literature.35,37,54 Using this threshold, RIS could be diagnosed with a sensitivity of 84% and a specificity of 90% compared to non-MS subjects. These results align with other studies on RIS subjects, finding that a 40% CVS+ threshold could correctly identify more than 90% of RIS.36,55
There is a need for consensus recommendations on using the CVS to determine WML etiologies in clinical practice. Some studies suggest applying the CVS detection to three random lesions suggestive of MS restricted to the subcortical or deep white matter (the “select-3” rule), and in the observation of at least two of three lesions are CVS+, a positive result is considered.31 Other studies suggest applying CVS detection in six suggestive MS lesions, including all areas. A positive result is considered if six or more morphologically characteristic MS lesions are identified.26 Eventually, some studies report thresholds based on a proportion of lesions that should be vein-centered to diagnose MS.44,45,48 Our results support that a ratio of CVS+ lesions seems more accurate than an absolute number of CVS+ lesions. However, using a ratio requires evaluating all white matter lesions, is time-consuming, faces many lesions, and appears difficult to apply in clinical practice where time is limited. Even if a proportion of CVS+ WMLs seems slightly more accurate, showing better specificity in diagnosing MS or RIS, using an absolute number of CVS+ lesions is more applicable in clinical practice with high values. Performances of the 6-lesion CVS+ demonstrate the major utility for differentiating MS lesions from mimics.
Some limitations to this study should be considered. First, the monocentric characteristic of the study may induce a center effect bias, justifying a multicentric evaluation of CVS in RIS. Nonetheless, multicentric CVS studies have established the efficiency of the CVS in MS, assuming, by extension, that the results should be similar in RIS. Second, MS and non-MS sample sizes are modest; however, sampling was done considering the number of patients with RIS identified. Considering the rarity of RIS, our results should be regarded as relevant.
Nonetheless, these results need to be confirmed in dedicated longitudinal studies evaluating the ability of the CVS to predict clinical CNS demyelination in presymptomatic patients. In addition, the proportion of analyzed lesions in the RIS group was lower than in other groups (75.4% vs 91.4% in MS and 90.7% in non-MS). Moreover, all evaluators involved in the CVS analysis had experience in MS MRI reading. Therefore, the diagnosis value of the CVS in RIS and MS may be overestimated because of an interpretation bias. Nonetheless, this bias could not have influenced the comparison between MS and RIS groups due to the same morphological characteristics.
This study shows evidence that CVS is an effective imaging biomarker in improving brain lesions associated with RIS in comparison to non-MS subjects with a 40% CVS+ threshold or a 6-lesion CVS+ threshold, allowing for greater accuracy in diagnosing subjects with RIS and patients with MS. As current scientific efforts aim to identify those at risk for MS earlier, such noninvasive tools may be essential in better-classifying lesions encountered in clinical practice that ultimately enhance the education provided to patients and the clinical care delivered. Nonetheless, these results need to be confirmed in dedicated longitudinal studies evaluating the ability of the CVS to predict clinical CNS demyelination in presymptomatic patients.
AcknowledgementsLandes-Chateau and Lebrun-Frenay elaborated the study protocol in collaboration with the Radiologically Isolated Syndrome Consortium (RISC) members.
RISConcortium members: Christine Lebrun-Frenay, Orhun Kantarci, Aksel Siva, Daniel Pelletier, Christina J. Azevedo, Naila Makhani, Darin T. Okuda.
This study did not receive any funding.
Author ContributionsConception and design: C.L.-C., C.L.-F, L.M., M.L., and O.H K. Acquisition and analysis of data: C.L.-C., C.L.-F, L.M., M.L., A.T., and M.C. Drafting and Editing: C.L.-C., C.L.-F, L.M., M.L., A.T., DTO, AS, OHK, DP, and M.C.
Conflict of InterestC.L.-C. has received a NeuroMod grant for her Ph.D. M.L., A.T., M.C., O.H K., D.P., L.M., and C.L.-F. declare no conflicts of interest. D.T.O. received personal compensation for consulting and advisory services from Alexion, Biogen, Celgene/Bristol Myers Squibb, EMD Serono, Genentech, Genzyme, Janssen Pharmaceuticals, Novartis, Osmotica Pharmaceuticals, RVL Pharmaceuticals, Inc., TG Therapeutics, Viela Bio, Inc., and research support from Biogen, EMD Serono/Merck, and Novartis. Dr. Okuda has issued national and international patents and pending patents related to other developed technologies. Dr. Okuda received royalties for intellectual property licensed by The Board of Regents of The University of Texas System. A.S. has no financial conflicts related to this work and has received research grants from The Turkish Multiple Sclerosis Society, The Scientific and Technological Research Council Of Turkey & Istanbul University-Cerrahpasa Research Support Funds. He has received consultancy fees from Roche Ltd, Merck-Serono, Biogen Idec/Gen Pharma of Turkey, Sanofi-Genzyme, Novartis, and Alexion and received honoraria for lectures from Sanofi-Genzyme, Novartis, Roche Ltd, and Teva—registration coverage for attending scientific congresses or symposia from Sanofi-Genzyme, and Alexion.
Data Availability StatementC.L.-C. and C.L.-F. had full access to all of the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Authors will share deidentified individual participant data and others with academic investigators following publication and approval of a data access agreement by the Nice University Hospital. All requests should be submitted to C.L.-C (
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Abstract
Objective
The radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS). Increasing evidence suggests that the central vein sign (CVS) enhances lesion specificity, allowing for greater MS diagnostic accuracy. This study evaluated the diagnostic performance of the CVS in RIS.
Methods
Patients were prospectively recruited in a single tertiary center for MS care. Participants with RIS were included and compared to a control group of sex and age-matched subjects. All participants underwent 3 Tesla magnetic resonance imaging, including postcontrast susceptibility-based sequences, and the presence of CVS was analyzed. Sensitivity and specificity were assessed for different CVS lesion criteria, defined by proportions of lesions positive for CVS (CVS+) or by the absolute number of CVS+ lesions.
Results
180 participants (45 RIS, 45 MS, 90 non-MS) were included, representing 5285 white matter lesions. Among them, 4608 were eligible for the CVS assessment (970 in RIS, 1378 in MS, and 2260 in non-MS). According to independent ROC comparisons, the proportion of CVS+ lesions performed similarly in diagnosing RIS from non-MS than MS from non-MS (
Interpretation
This study shows evidence that CVS is an effective imaging biomarker in differentiating RIS from non-MS, with similar performances to those in MS.
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1 Université Cote d'Azur, UMR2CA (URRIS), Nice, France
2 Université Cote d'Azur, UMR2CA (URRIS), Nice, France; Service de Médecine Interne, Centre Hospitalier Universitaire de Nice, Nice, France
3 The University of Texas Southwestern Medical Center, Dallas, Texas, USA
4 Service de Radiologie, Centre Hospitalier Universitaire de Nice, Nice, France
5 Université Cote d'Azur, UMR2CA (URRIS), Nice, France; Service de Neurologie, Centre de Ressource et de Compétence Sclérose en Plaques (CRC-SEP), Centre Hospitalier Universitaire de Nice, Nice, France
6 Mayo Clinic, Rochester, Minnesota, USA
7 Istanbul University, Cerrahpasa School of Medicine, Istanbul, Turkey
8 University of South California, San Francisco, California, USA
9 Université Cote d'Azur, UMR2CA (URRIS), Nice, France; Service de Radiologie, Centre Hospitalier Universitaire de Nice, Nice, France