Application of the 2017 McDonald diagnostic criteria for multiple sclerosis in Korean patients with clinically isolated syndrome

Multiple Sclerosis: Clinical Update and Clinically-Oriented Radiologic Reporting

Multiple sclerosis (MS) is a chronic inflammatory disease of the nervous system. MR imaging findings play an integral part in establishing diagnostic hallmarks of the disease during initial diagnosis and evaluating disease status. Multiple iterations of diagnostic criteria and consensus guidelines are put forth by various expert groups incorporating imaging of the brain and spine, and efforts have been made to standardize imaging protocols for MS. Emerging ancillary imaging findings have also attracted increasing interests and should be sought for on radiologic examination. In this paper, the authors review the clinical guidelines and approach to imaging of MS and related disorders, focusing on clinically impactful image interpretation and MR imaging reporting.

Time to involve the multiple sclerosis expert community at large when revising the McDonald diagnostic criteria

Prof. Kurtzke once said, "Multiple sclerosis is what a good clinician would call multiple sclerosis." Recent McDonald's diagnostic criteria revisions have allowed for earlier diagnoses over the past decades. Revisions often allowed increasing sensitivity but at the expense of lowering specificity. In this correspondence, I suggest that the multiple sclerosis expert community worldwide should be given the opportunity to comment and provide feedback on the proposed revisions of the diagnostic criteria before their publication via providing a duration where open commentaries are welcomed to allow for the expert panel to incorporate diverse feedback to improve the final product.

A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis

BACKGROUND

The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established.

OBJECTIVE

The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS.

METHODS

Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed.

RESULTS

Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*.

CONCLUSION

A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.

Real-life evaluation of the 2017 McDonald criteria for relapsing-remitting multiple sclerosis after a clinically isolated syndrome confirms a gain in time-to-diagnosis

BACKGROUND

Previous cohort studies evaluating the performances of the McDonald criteria suffered from bias regarding real-life conditions. We aimed to evaluate the probability of diagnosing relapsing-remitting multiple sclerosis (MS) at several timepoints from the first medical evaluation and the gain in time-to-diagnosis with the 2017 McDonald criteria compared with the 2001, 2005 and 2010 versions in real life.

METHODS

Patients with a first demyelinating event suggestive of MS between 2002 and 2020 were included in the ReLSEP, an exhaustive and prospectively incremented registry of MS patients in North-Eastern France. We estimated the probability of being positive at the first medical evaluation and at five timepoints according to the four versions of criteria using Kaplan-Meier estimators and Cox models.

RESULTS

A total of 2220 patients were followed up for a median of 7.1 years. At baseline, 31.7%, 32.1%, 36.6% and 54.0% of patients, respectively, fulfilled the 2001, 2005, 2010 and 2017 McDonald criteria. Using the 2017 criteria, the gain in time-to-diagnosis was 3.7 months compared with the 2010 criteria. The presence of intrathecal synthesis of immunoglobulin G in the McDonald 2017 criteria led to a 1.8-month reduction in median time-to-diagnosis compared to a version of McDonald 2017 without this criteria.

CONCLUSIONS

In real-life, the 2017 McDonald criteria revision undoubtedly shortened time-to-diagnosis.

Performance of McDonald 2017 multiple sclerosis diagnostic criteria and evaluation of genetic ancestry in patients with a first demyelinating event in Argentina

BACKGROUND

Information on performance of multiple sclerosis (MS) diagnostic criteria is scarce for populations from Latin America, Asia, or the Caribbean.

OBJECTIVE

To assess performance of revised 2017 McDonald criteria as well as evaluate genetic ancestry in a group of MS patients from Argentina experiencing a debut demyelinating event.

METHODS

Demographic and clinical characteristics, cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI) findings and new T2 lesions were recorded at baseline and during relapses. Diagnostic accuracy in predicting conversion to clinically defined MS (CDMS) based on initial imaging applying revised 2017 criteria was evaluated and genetic ancestry-informative markers analyzed.

RESULTS

Of 201 patients experiencing their first demyelinating event (median follow-up 60 months), CDMS was confirmed in 67. We found 2017 diagnostic criteria were more sensitive (84% vs 67%) and less specific (14% vs 33%) than 2010 criteria, especially in a group of patients revised separately, presenting positive oligoclonal bands (88% vs 8%). Genetic testing performed in 128 cases showed 72% of patients were of European ancestry and 27% presented genetic admixture.

CONCLUSION

2017 McDonald criteria showed higher sensitivity and lower specificity compared with 2010 criteria, shortening both time-to-diagnosis and time-to-treatment implementation.

Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective

In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.

Leistungsfähigkeit der McDonald-Kriterien von 2017

Hintergrund

Die schnelle und zuverlässige Diagnose einer Multiplen Sklerose (MS) ist entscheidend, um eine angepasste verlaufsmodifizierende Therapie zu beginnen. Die 2017-Revision der McDonald-Kriterien hat das Ziel, eine einfachere und frühzeitigere MS-Diagnose mit hoher diagnostischer Genauigkeit zu ermöglichen.

Ziel der Arbeit/Fragestellung

In der vorliegenden Arbeit wurden die publizierten Arbeiten, die die Anwendung der McDonald-Kriterien von 2017 und 2010 miteinander verglichen haben, ausgewertet und bezüglich der diagnostischen Leistungsfähigkeit analysiert.

Material und Methoden

Mittels Literaturrecherche in der PubMed-Datenbank (Suchbegriff: McDonald criteria 2010 and McDonald criteria 2017) wurden 20 Studien und ein Übersichtsartikel mit insgesamt 3006 auswertbaren Patienten identifiziert.

Ergebnisse

Bei Anwendung der McDonald-Kriterien von 2017 konnte die Diagnose einer MS bei mehr Patienten (2277/3006 Patienten, 76 %) und in einem früheren Stadium (3–10 Monate) verglichen mit der Revision von 2010 (1562/3006 Patienten, 52 %) gestellt werden. Von den zusätzlichen MS-Diagnosen sind 193/715 auf die Anpassung der bildgebenden Kriterien der zeitlichen Dissemination und 536/715 auf die Einführung der oligoklonalen Banden als diagnostisches Kriterium zurückführen.

Diskussion

Die revidierten McDonald-Kriterien von 2017 erlauben die Diagnosestellung einer MS bei einem höheren Anteil an Patienten beim ersten klinischen Ereignis.

The kappa free light chain index and oligoclonal bands have a similar role in the McDonald criteria

Intrathecal production of kappa free light chains (KFLC) occurs in multiple sclerosis and can be measured using the KFLC index. KFLC index values can be determined more easily than oligoclonal bands (OB) detection and seem more sensitive than the immunoglobulin (Ig)G index to diagnose multiple sclerosis. We assessed the value of OB, KFLC index cut-offs 5.9, 6.6, and 10.61, and IgG index to diagnose multiple sclerosis with prospectively acquired data from a clinically isolated syndrome (CIS) inception cohort. We selected patients with sufficient data to determine OB positivity, MRI dissemination in space (DIS) and time (DIT), IgG index, and sufficient quantities of paired CSF and blood samples to determine KFLC indexes (n = 214). We used Kendall´s Tau coefficient to estimate concordance; calculated the number of additional diagnoses when adding each positive index to DIS and positive OB; performed survival analyses for OB and each index with the outcomes second attack and 2017 MRI DIS and DIT; and estimated the diagnostic properties of OB and the different indexes for the abovementioned outcomes at five years. OB were positive in 138 patients (64.5%), KFLC-5.9 in 136 (63.6%), KFLC-6.6 in 135 (63.1%), KFLC-10.61 in 126 (58.9%) and IgG index in 101 (47.2%). The highest concordance was between OB and KFLC-6.6 (τ=0.727) followed by OB and KFLC-5.9 (τ=0.716). Combining DIS plus OB or KFLC-5.9 increased the number of diagnosed patients by 11 (5.1%), with KFLC-6.6 by 10 (4.7%), with KFLC-10.61 by 9 (4.2%), and with IgG index by 3 (1.4%). Patients with positive OB or indexes reached second attack and MRI DIS and DIT faster than patients with negative results (P < 0.0001 except IgG index in second attack: P = 0.016). In multivariable Cox models [aHR (95% CI)], the risk for second attack was very similar between KFLC-5.9 [2.0 (0.9-4.3), P = 0.068] and KFLC-6.6 [2.1 (1.1-4.2), P = 0.035]. The highest risk for MRI DIS and DIT was demonstrated with KFLC-5.9 [4.9 (2.5-9.6), P < 0.0001], followed by KFLC-6.6 [3.4 (1.9-6.3), P < 0.0001]. KFLC-5.9 and KFLC-6.6 had a slightly higher diagnostic accuracy than OB for second attack (70.5, 71.1, and 67.8) and MRI DIS and DIT (85.7, 85.1, and 81.0). KFLC indexes 5.9 and 6.6 performed slightly better than OB to assess multiple sclerosis risk and in terms of diagnostic accuracy. Given the concordance between OB and these indexes, we suggest using DIS plus positive OB or positive KFLC index as a modified criterion to diagnose multiple sclerosis.

Factors driving delayed time to multiple sclerosis diagnosis: Results from a population-based study

BACKGROUND

Multiple sclerosis (MS) is a highly complex chronic inflammatory disease, in which a diagnostic delay could reduce the available therapeutic options. Our aim was to identify factors contributing to diagnostic delay in a MS population living in the municipality of Biancavilla.

METHODS

This retrospective population-based study consecutively selected patients with MS diagnosed from 1992 to 2018 and resident in the city of Biancavilla. Socio-demographic and clinical data were collected through the iMed database. Date of final MS diagnosis was obtained and diagnostic delay was calculated.

RESULTS

A total of 70 patients (66.7% women) were found affected by MS according to the 2011 McDonald criteria in the municipality of Biancavilla in the period between 2005 and 2010. The mean diagnostic delay in the MS cohort of Biancavilla was 33.8 ± 56 months [median 19.5, range 1-315]. The multivariate logistic regression confirmed that age ≥ 40 years, lower educational level (1-5 years) and motor symptoms at onset were associated to longer diagnostic delay.

CONCLUSION

In this population-based study a mean delay of about 30 months occurred between initial symptoms and the MS diagnosis. Older age at onset, lower education level and motor symptoms at onset were associated to longer MS diagnostic delay.

Performance of the 2017 and 2010 Revised McDonald Criteria in Predicting MS Diagnosis After a Clinically Isolated Syndrome: A MAGNIMS Study

BACKGROUND AND OBJECTIVES

To compare the performance of the 2017 revisions to the McDonald criteria with the 2010 McDonald criteria in establishing MS diagnosis and predicting prognosis in patients with clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS).

METHODS

CSF examination, brain and spinal cord MRI obtained ≤5 months from CIS onset, and a follow-up brain MRI acquired within 15 months from CIS onset were evaluated in 785 CIS patients from 9 European centers. Date of second clinical attack and of reaching Expanded Disability Status Score (EDSS) ≥ 3.0, if they occurred, were also collected. Performance of the 2017 and 2010 McDonald criteria for dissemination in space (DIS), time (DIT) (including oligoclonal bands assessment) and DIS + DIT for predicting a second clinical attack (clinically definite [CD] MS) and EDSS ≥ 3.0 at follow-up was evaluated. Time to MS diagnosis for the different criteria was also estimated.

RESULTS

At follow-up (median = 69.1 months), 406/785 CIS patients developed CDMS. At 36 months, the 2017 DIS + DIT criteria had higher sensitivity (0.83 vs 0.66), lower specificity (0.39 vs 0.60) and similar area under the curve values (0.61 vs 0.63). Median time to MS diagnosis was shorter with the 2017 vs the 2010 or CDMS criteria (2017 revision = 3.2; 2010 revision = 13.0; CDMS = 58.5 months). The 2 sets of criteria similarly predicted EDSS ≥ 3.0 milestone. Three periventricular lesions improved specificity in patients ≥45 years.

DISCUSSION

The 2017 McDonald criteria showed higher sensitivity, lower specificity and similar accuracy in predicting CDMS compared to 2010 McDonald criteria, while shortening time to diagnosis of MS.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the 2017 McDonald Criteria more accurately distinguish CDMS in patients early after a CIS when compared to the 2010 McDonald criteria.

Time to diagnosis in multiple sclerosis: Epidemiological data from the German Multiple Sclerosis Registry

OBJECTIVE

To investigate the time to diagnosis in multiple sclerosis (MS) in Germany.

METHODS

Analysis of real-world registry data from the German Multiple Sclerosis Registry (GMSR) and performing a primary analysis in patients where month-specific registration of the dates of onset and diagnosis was available.

RESULTS

As of January 2020, data of a total of 28,658 patients with MS were extracted from the GMSR, with 9836 patients included in the primary analysis. The mean time to diagnosis was shorter following the introduction of the first magnetic resonance imaging (MRI)-based McDonald criteria in 2001. This effect was most pronounced in younger adults below the age of 40 years with relapsing onset multiple sclerosis (ROMS), with a decrease from 1.9 years in 2010 to 0.9 years in 2020, while unchanged in patients aged 40-50 years (1.4 years in 2010 and 1.3 years in 2020). In the limited number of paediatric onset MS patients, the time to diagnosis was longer and did not change (2.9 years).

CONCLUSION

The current sensitive MRI-based diagnostic criteria have likely contributed to an earlier diagnosis of MS in Germany in younger adults aged 18-39 years with ROMS. Whether this translated to earlier initiation of disease-modifying treatment or had a beneficial effect on patient outcomes remains to be demonstrated.

Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics

OBJECTIVES

The aims of this study were to present a deep learning approach for the automated classification of multiple sclerosis and its mimics and compare model performance with that of 2 expert neuroradiologists.

MATERIALS AND METHODS

A total of 268 T2-weighted and T1-weighted brain magnetic resonance imagin scans were retrospectively collected from patients with migraine (n = 56), multiple sclerosis (n = 70), neuromyelitis optica spectrum disorders (n = 91), and central nervous system vasculitis (n = 51). The neural network architecture, trained on 178 scans, was based on a cascade of 4 three-dimensional convolutional layers, followed by a fully dense layer after feature extraction. The ability of the final algorithm to correctly classify the diseases in an independent test set of 90 scans was compared with that of the neuroradiologists.

RESULTS

The interrater agreement was 84.9% (Cohen κ = 0.78, P < 0.001). In the test set, deep learning and expert raters reached the highest diagnostic accuracy in multiple sclerosis (98.8% vs 72.8%, P < 0.001, for rater 1; and 81.8%, P < 0.001, for rater 2) and the lowest in neuromyelitis optica spectrum disorders (88.6% vs 4.4%, P < 0.001, for both raters), whereas they achieved intermediate values for migraine (92.2% vs 53%, P = 0.03, for rater 1; and 64.8%, P = 0.01, for rater 2) and vasculitis (92.1% vs 54.6%, P = 0.3, for rater 1; and 45.5%, P = 0.2, for rater 2). The overall performance of the automated method exceeded that of expert raters, with the worst misdiagnosis when discriminating between neuromyelitis optica spectrum disorders and vasculitis or migraine.

CONCLUSIONS

A neural network performed better than expert raters in terms of accuracy in classifying white matter disorders from magnetic resonance imaging and may help in their diagnostic work-up.

MR Diffusion Properties of Cervical Spinal Cord as a Predictor of Progression to Multiple Sclerosis in Patients with Clinically Isolated Syndrome

BACKGROUND AND PURPOSE

This study's aim was to investigate diffusion properties of the cervical spinal cord in patients with clinically isolated syndrome (CIS) through analysis of diffusion tensor imaging (DTI) data and thereby to assess the capacity of this technique for predicting the progression of CIS to clinically definite multiple sclerosis (CDMS).

METHODS

The study groups were comprised of 47 patients with CIS (15 of them with progression to CDMS within 2 years of follow-up) and 57 asymptomatic controls. All patients and controls had undergone magnetic resonance imaging (MRI) of the cervical spine including DTI and brain MRI. Methodological approaches included histogram analysis of the cervical cord's diffusion parameters and evaluation of T2 hyperintense lesions of the spinal cord and brain. All parameters were compared between the study groups. Sensitivity and specificity calculations were then performed with a view to predicting conversion to CDMS.

RESULTS

The patient subgroups defined by progression to CDMS differed significantly in values of fractional anisotropy (FA) kurtosis measured within white matter (WM) and normal-appearing WM (NAWM). The same parameters also differed significantly when patients with progression to CDMS were compared to healthy controls. Receiver operating characteristic (ROC) analysis revealed sensitivity and specificity of FA kurtosis of WM and NAWM of 93% and 72%, respectively, in terms of predicting CIS to CDMS progression.

CONCLUSION

This study presents evidence that histogram analysis of diffusion parameters of the cervical spinal cord in patients with CIS may be helpful in predicting conversion to CDMS.

Evaluation of the Central Vein Sign as a Diagnostic Imaging Biomarker in Multiple Sclerosis

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.

IgG Index Revisited: Diagnostic Utility and Prognostic Value in Multiple Sclerosis

Objective: Early and accurate diagnosis of multiple sclerosis (MS) remains a clinical challenge. The main objective is to evaluate the diagnostic and prognostic value of the routinely performed immunoglobulin G (IgG) index for MS patients in the Asian population.

Methods: A retrospective study was conducted among a cohort of clinically isolated syndrome (CIS) patients in China with known oligoclonal band (OCB) status and IgG index at baseline. We first evaluated the predictive value of IgG index for OCB status. Secondly, the diagnostic utility and prognostic value of IgG index alone were tested. Lastly, we incorporated IgG index into the 2017 McDonald criteria by replacing OCB with either “IgG index or OCB” (modified criteria 1), “IgG index and OCB” (modified criteria 2), or “IgG index” (modified criteria 3). The diagnostic utility of different criteria was calculated and compared.

Results: In a CIS cohort in China (n = 105), IgG index > 0.7 forecasted OCB positivity (X² = 22.90, P < 0.001). An elevated IgG index was highly prognostic of more clinical relapses [1-year adjusted odds ratio [OR] = 1.32, P = 0.015; 2-years adjusted OR = 1.69, P = 0.013] and Expanded Disability Status Scale worsening (1-year adjusted OR = 1.76, P = 0.040; 2-years adjusted OR = 1.85, P = 0.032). Under the 2017 McDonald criteria (Positive Likelihood Ratio = 1.54, Negative Likelihood Ratio = 0.56), an IgG index > 0.7 in CIS patients increased the likelihood of developing MS within 2 years, either when OCB status was unknown (Positive Likelihood Ratio = 2.11) or with OCB positivity (Positive Likelihood Ratio = 2.11) at baseline; An IgG index ≤ 0.7, along with a negative OCB, helped rule out the MS diagnosis (Negative Likelihood Ratio = 0.53).

Conclusions: IgG index > 0.7 predicts OCB positivity at the initial attack of MS and is prognostic of early disease activity. IgG index serves as an easily-obtainable and accurate OCB surrogate for MS diagnosis in the Asian population.

Validity of the McDonald criteria in predicting second events in multiple sclerosis

BACKGROUND

The McDonald criteria are designed for predicting the second event in multiple sclerosis. With several revisions made to the McDonald criteria, the criteria get much easier to use, but what about the diagnostic validity? This research is conducted for evaluating the diagnostic validity of the McDonald criteria in multiple sclerosis.

METHODS

Pubmed, Web of Science, Cochrane Library were systematically searched with keywords of "Multiple sclerosis" and "McDonald criteria" from, January 1^st, 2010 to 27^th, February 2020. The methodological quality of each study is assessed by Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). All of the statistics are analyzed by software STATA 12.0 and Meta-Disc 1.4.

RESULTS

Twenty articles are finally included according to the inclusion and exclusion criteria. Both the 2010 and 2017 McDonald criteria have excellent performance in predicting second events in multiple sclerosis. The 2017 McDonald criteria have better performance compared to the 2010 McDonald criteria (AUC, 0.83 vs 0.77). It is increased in sensitivity but decreased in specificity.

CONCLUSION

The McDonald criteria are useful in predicting second events in multiple sclerosis. The 2017 McDonald criteria have better performance than the 2010 McDonald criteria with increased sensitivity but decreased specificity.

Value of 3T Susceptibility-Weighted Imaging in the Diagnosis of Multiple Sclerosis

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.

Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines

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.

Central vein sign for multiple sclerosis: A systematic review and meta-analysis

AIMS

To systematically review the diagnostic value of the central vein sign (CVS) in multiple sclerosis (MS) and to meta-analyse the proportion of positive lesions for CVS needed to distinguish MS from non-MS mimics.

MATERIALS AND METHODS

A literature review was performed and a proportion meta-analysis was performed to examine the proportion of the CVS in MS lesions. Studies reporting a threshold of the CVS containing lesions with 100% diagnostic accuracy were included in the meta-analysis. This was compared to MS mimics in order to establish the discriminative value of the CVS.

RESULTS

The CVS was found to be viable at lower field strengths (3 T and 1.5 T) and automated analysis is currently less accurate than manual counting. Five studies were included for the proportional meta-analysis. From the analysis, a proportion of 45% of lesions having the CVS was suggested given that the findings that the weighted proportion was 46.4% (95% confidence interval [CI]: of 40.3%-52.6%) with low heterogeneity (I² = 0.0%; p=0.5).

CONCLUSION

Although the CVS is a clinically relevant and viable sign, further work is needed to integrate this into the existing diagnostic criteria. As manual determination is a time-consuming process, the development of automated methods will be beneficial. With improvements in computational imaging techniques, the CVS will have an important role in the diagnosis and differentiation of MS.

Application of the 2017 McDonald criteria in a Chinese population with clinically isolated syndrome

Background:

Diagnostic criteria for multiple sclerosis have evolved over time, with the most recent being the 2017 McDonald criteria. Evidence is lacking regarding the validity of the 2017 McDonald criteria among the Asian population. Therefore, this study aims to evaluate the diagnostic performance of the 2017 McDonald criteria in Chinese patients with clinically isolated syndrome (CIS).

Methods:

A total of 93 patients with initial findings suggestive of CIS in a tertiary hospital in China from 2012 to 2017 were included in this retrospective study. Baseline and follow-up data were reviewed. Diagnostic performance (sensitivity, specificity, accuracy), was assessed and survival analysis was performed for the 2017 and 2010 McDonald criteria respectively.

Results:

Among the 93 Chinese patients with CIS, 57 were female (61.3%) and the median (interquartile range) age of onset was 37 (31.3–41.8) years. The 2017 McDonald criteria displayed a higher sensitivity (75.0% versus 14.6%, p < 0.0001), lower specificity (47.1% versus 100.0%, p < 0.05) but an overall higher accuracy (67.7% versus 36.9%, p < 0.0001) when compared with the 2010 iteration. The novel criteria allow for a better detection of MS at baseline (40.8% versus 9.9%, p < 0.0001).

Conclusion:

The 2017 McDonald criteria had a higher sensitivity but lower specificity than the 2010 iteration. Overall it facilitated an earlier and more accurate diagnosis of multiple sclerosis in Chinese patients with CIS.

Impact of the McDonald Criteria 2017 on Early Diagnosis of Relapsing-Remitting Multiple Sclerosis

Multiple sclerosis is a chronic immune mediated demyelinating disease leading to neurological disabilities that need to be diagnosed and treated early. Guidelines on multiple sclerosis diagnosis and monitoring experienced comprehensive changes over the last decades. The first McDonald criteria published in 2001 emphasized the importance of MR imaging but also recognized the role of cerebrospinal fluid diagnostics. The demonstration of an intrathecal immunoglobulin G synthesis is a well-established additional component and has a long tradition in the diagnosis of relapsing-remitting multiple sclerosis. However, the role of cerebrospinal fluid for diagnostic purposes was rather diminished in each revision of the McDonald criteria. In the latest revision of the McDonald criteria of 2017, the detection of an intrathecal immunoglobulin G synthesis as oligoclonal bands experienced a revival. Patients with the first clinical event suggesting multiple sclerosis who fulfill the criteria for dissemination in space can be diagnosed with relapsing-remitting multiple sclerosis when oligoclonal bands in cerebrospinal fluid are detected. The diagnostic sensitivity of these novel criteria with a focus on dissemination in time and oligoclonal bands as a substitute for dissemination in time was published in different cohorts in the last year and is of special interest in this review. Recently published data show that by applying the 2017 McDonald criteria, multiple sclerosis can be diagnosed more frequently at the time of first clinical event as compared to the 2010 McDonald criteria. The main effect was due to the implementation of oligoclonal bands as a substitute for dissemination in time. However, careful differential diagnosis is essential in patients with atypical clinical manifestations to avoid misdiagnoses.

2017 McDonald criteria for multiple sclerosis: Earlier diagnosis with reduced specificity?

BACKGROUND

McDonald criteria for multiple sclerosis (MS) diagnosis were revised in 2017.

OBJECTIVE

Aim of our study was to evaluate and compare the sensitivity and specificity of 2017 and 2010 McDonald criteria in patients presenting with an initial demyelinating event (IDE).

METHODS

We retrospectively identified patients with an IDE and collected clinical, MRI and CSF data in order to demonstrate fulfilment of 2010 and 2017 McDonald criteria.

RESULTS

2017 McDonald criteria showed 100% (86.8-100%) sensitivity and 13.8% (3.9-31.7%) specificity.

CONCLUSION

2017 McDonald criteria appear to have higher sensitivity but reduced specificity compared to 2010 McDonald criteria.