A search for new MRI criteria for dissemination in space in subjects with a clinically isolated syndrome.
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ABSTRACT:
SUBMITTER: Korteweg T
PROVIDER: S-EPMC2719077 | biostudies-other | 2009 Sep
REPOSITORIES: biostudies-other
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Project description:ObjectivesTo investigate whether inclusion of lesions in the symptomatic region influences the performance of dissemination in space (DIS) criteria for a diagnosis of clinically definite multiple sclerosis (CDMS) in patients with a clinically isolated syndrome (CIS).MethodsWe studied 30 patients with CIS with brainstem/cerebellar and spinal cord syndromes who had MRI scans at the time of CIS and were followed up for the development of CDMS. We retrospectively applied the McDonald 2010 DIS criteria (excluding all lesions in the symptomatic region) to baseline MRI scans and 2 modified DIS criteria: (1) the inclusion of asymptomatic lesions in the symptomatic region in DIS, and (2) the inclusion of any lesion in the symptomatic region in DIS. The performance of the McDonald 2010 DIS criteria and the 2 modified criteria for the development of CDMS was compared.ResultsThe sensitivity, specificity, and accuracy of the DIS criteria was, respectively, 73%, 73%, and 73% for the McDonald 2010 criteria, 80%, 73%, and 77% when asymptomatic lesions in the symptomatic region were included, and 87%, 73%, and 80% when any lesion in the symptomatic region was included in DIS.ConclusionsIncluding lesions in the symptomatic region in DIS increases the sensitivity of MRI criteria for diagnosing multiple sclerosis without compromising specificity. These findings may help inform future revisions of the diagnostic criteria for multiple sclerosis.Classification of evidenceThis study provides Class II evidence that for patients with CIS, including lesions in the symptomatic region as part of the criteria for DIS does not significantly increase the accuracy for predicting the development of CDMS. The study lacks the precision to detect an important change in accuracy.
| S-EPMC4999167 | biostudies-literature
Project description:Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). To determine whether pattern classification using SVMs facilitates predicting conversion to clinically definite multiple sclerosis (CDMS) from clinically isolated syndrome (CIS). We used baseline MRI data from 364 patients with CIS, randomised to interferon beta-1b or placebo. Non-linear SVMs and 10-fold cross-validation were applied to predict converters/non-converters (175/189) at two years follow-up based on clinical and demographic data, lesion-specific quantitative geometric features and grey-matter-to-whole-brain volume ratios. We applied linear SVM analysis and leave-one-out cross-validation to subgroups of converters (n = 25) and non-converters (n = 44) based on cortical grey matter segmentations. Highest prediction accuracies of 70.4% (p = 8e-5) were reached with a combination of lesion-specific geometric (image-based) and demographic/clinical features. Cortical grey matter was informative for the placebo group (acc.: 64.6%, p = 0.002) but not for the interferon group. Classification based on demographic/clinical covariates only resulted in an accuracy of 56% (p = 0.05). Overall, lesion geometry was more informative in the interferon group, EDSS and sex were more important for the placebo cohort. Alongside standard demographic and clinical measures, both lesion geometry and grey matter based information can aid prediction of conversion to CDMS.
| S-EPMC6733701 | biostudies-literature
Project description:Importance:In 2017, the International Panel on Diagnosis of Multiple Sclerosis revised the McDonald 2010 criteria for the diagnosis of multiple sclerosis (MS). The new criteria are easier to apply and could lead to more and earlier diagnoses. It is important to validate these criteria globally for their accuracy in clinical practice. Objective:To evaluate the diagnostic accuracy of the 2017 criteria vs the 2010 criteria in prediction of clinically definite MS in patients with a typical clinically isolated syndrome (CIS). Design, Setting and Patients:A total of 251 patients at Erasmus MC, Rotterdam, the Netherlands, in collaboration with several regional hospitals, fulfilled the inclusion criteria. Thirteen patients received another diagnosis early in the diagnostic process and therefore were excluded from the analyses. Nine patients with CIS declined to participate in the study. This left 229 patients who were included between March 2006 and August 2016 in this prospective CIS cohort. Patients underwent a baseline magnetic resonance imaging scan within 3 months after onset of symptoms and, if clinically required, a lumbar puncture was performed. Data were analyzed between December 2017 and January 2018. Main Outcomes and Measures:Sensitivity, specificity, accuracy, and positive and negative predictive value were calculated after 1, 3, and 5 years for the 2017 vs the 2010 criteria. Results:Among the 229 patients with CIS, 167 were women (73%), and the mean (SD) age was 33.5 (8.2) years. One hundred thirteen patients (49%) were diagnosed as having CDMS during a mean (SD) follow-up time of 65.3 (30.9) months. Sensitivity for the 2017 criteria was higher than for the 2010 criteria (68%; 95% CI, 57%-77% vs 36%; 95% CI, 27%-47%; P?<?.001), but specificity was lower (61%; 95% CI, 50%-71% vs 85%; 95% CI, 76%-92%; P?<?.001). Using the 2017 criteria, more MS diagnoses could be made at baseline (n?=?97 [54%]; 95% CI, 47%-61% vs n?=?46 [26%]; 95% CI, 20%-32%; P?<?.001). In the group with at least 5 years of follow-up, 33% of patients who were diagnosed as having MS using the 2017 criteria did not experience a second attack during follow-up vs 23% when using the 2010 criteria. Conclusions and Relevance:The 2017 revised McDonald criteria are associated with greater sensitivity but less specificity for a second attack than the previous 2010 criteria. The tradeoff is that it leads to a higher number of MS diagnoses in patients with a less active disease course.
| S-EPMC6248116 | biostudies-literature
Project description:BACKGROUND:Compared to 1.5 T, 3 T magnetic resonance imaging (MRI) increases signal-to-noise ratio leading to improved image quality. However, its clinical relevance in clinically isolated syndrome suggestive of multiple sclerosis remains uncertain. OBJECTIVES:The purpose of this study was to investigate how 3 T MRI affects the agreement between raters on lesion detection and diagnosis. METHODS:We selected 30 patients and 10 healthy controls from our ongoing prospective multicentre cohort. All subjects received baseline 1.5 and 3 T brain and spinal cord MRI. Patients also received follow-up brain MRI at 3-6 months. Four experienced neuroradiologists and four less-experienced raters scored the number of lesions per anatomical region and determined dissemination in space and time (McDonald 2010). RESULTS:In controls, the mean number of lesions per rater was 0.16 at 1.5 T and 0.38 at 3 T ( p = 0.005). For patients, this was 4.18 and 4.40, respectively ( p = 0.657). Inter-rater agreement on involvement per anatomical region and dissemination in space and time was moderate to good for both field strengths. 3 T slightly improved agreement between experienced raters, but slightly decreased agreement between less-experienced raters. CONCLUSION:Overall, the interobserver agreement was moderate to good. 3 T appears to improve the reading for experienced readers, underlining the benefit of additional training.
| S-EPMC6393953 | biostudies-literature
Project description:BackgroundSteps towards the development of diagnostic criteria are needed for children with the radiologically isolated syndrome to identify children at risk of clinical demyelination.ObjectivesTo evaluate the 2005 and 2016 MAGNIMS magnetic resonance imaging criteria for dissemination in space for multiple sclerosis, both alone and with oligoclonal bands in cerebrospinal fluid added, as predictors of a first clinical event consistent with central nervous system demyelination in children with radiologically isolated syndrome.MethodsWe analysed an international historical cohort of 61 children with radiologically isolated syndrome (≤18 years), defined using the 2010 magnetic resonance imaging dissemination in space criteria (Ped-RIS) who were followed longitudinally (mean 4.2 ± 4.7 years). All index scans also met the 2017 magnetic resonance imaging dissemination in space criteria.ResultsDiagnostic indices (95% confidence intervals) for the 2005 dissemination in space criteria, with and without oligoclonal bands, were: sensitivity 66.7% (38.4-88.2%) versus 72.7% (49.8-89.3%); specificity 83.3% (58.6-96.4%) versus 53.9% (37.2-69.9%). For the 2016 MAGNIMS dissemination in space criteria diagnostic indices were: sensitivity 76.5% (50.1-93.2%) versus 100% (84.6-100%); specificity 72.7% (49.8-89.3%) versus 25.6% (13.0-42.1%).ConclusionsOligoclonal bands increased the specificity of magnetic resonance imaging criteria in children with Ped-RIS. Clinicians should consider testing cerebrospinal fluid to improve diagnostic certainty. There is rationale to include cerebrospinal fluid analysis for biomarkers including oligoclonal bands in planned prospective studies to develop optimal diagnostic criteria for radiologically isolated syndrome in children.
| S-EPMC6429663 | biostudies-literature
Project description:To diagnose multiple sclerosis (MS), evidence for dissemination in space and time is required. There is no clear definition on how symptoms and signs of a patient indicate clinical dissemination in space. To provide a uniform approach on this subject, a clinical classification system was described recently differentiating patients with mono- and multifocal clinical presentation. Here we assess the predictive value of clinically defined dissemination in space at first presentation for time to clinically definite MS (CDMS).Four hundred and sixty-eight patients with a first episode suggestive of MS were classified as clinically mono- or multifocal by two neurologists blinded to magnetic resonance imaging (MRI) results. These patients were part of the BENEFIT study in which 292 patients were randomized to interferon beta-1b (IFNB-1b) and 176 to placebo. By using Kaplan-Meier statistics the risk for CDMS was studied in mono- and multifocal patients of the placebo group, both with and without taking into account MRI measures of potential prognostic relevance.Time to CDMS was similar in monofocal and multifocal patients. In monofocal patients, the risk for CDMS over 2 years was significantly higher when >or= 9 T2 lesions or at least one Gd-enhancing lesion were present at the first event or 3 or 6 months after the first event. In patients with multifocal presentation, these MRI measures had no significant added value in predicting time to CDMS.These data indicate that a carefully performed neurological assessment of symptoms and signs, combined with lesions on MRI, is important for defining the risk of conversion to CDMS.The Benefit trial has been registered under NCT00185211 http://www.clinicaltrials.gov.
| S-EPMC2702360 | biostudies-literature
Project description:BackgroundThe incidence of multiple sclerosis (MS) is rising in women.ObjectiveTo determine whether the use of combined oral contraceptives (COCs) are associated with MS risk and whether this varies by progestin content.MethodsWe conducted a nested case-control study of females ages 14-48 years with incident MS or clinically isolated syndrome (CIS) 2008-2011 from the membership of Kaiser Permanente Southern California. Controls were matched on age, race/ethnicity and membership characteristics. COC use up to ten years prior to symptom onset was obtained from the complete electronic health record.ResultsWe identified 400 women with incident MS/CIS and 3904 matched controls. Forty- percent of cases and 32% of controls had used COCs prior to symptom onset. The use of COCs was associated with a slightly increased risk of MS/CIS (adjusted OR = 1.52, 95%CI = 1.21-1.91; p<0.001). This risk did not vary by duration of COC use. The association varied by progestin content being more pronounced for levenorgestrol (adjusted OR = 1.75, 95%CI = 1.29-2.37; p<0.001) than norethindrone (adjusted OR = 1.57, 95%CI = 1.16-2.12; p = 0.003) and absent for the newest progestin, drospirenone (p = 0.95).ConclusionsOur findings should be interpreted cautiously. While the use of some combination oral contraceptives may contribute to the rising incidence of MS in women, an unmeasured confounder associated with the modern woman's lifestyle is a more likely explanation for this weak association.
| S-EPMC4780760 | biostudies-literature
Project description:We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clinically isolated syndrome (CIS), on the basis of single patient's lesion features and clinical/demographic characteristics. Seventy-four patients at onset of CIS were scanned and clinically reviewed after one and three years. CDMS was used as the gold standard against which SVM classification accuracy was tested. Radiological features related to lesional characteristics on conventional MRI were defined a priori and used in combination with clinical/demographic features in an SVM. Forward recursive feature elimination with 100 bootstraps and a leave-one-out cross-validation was used to find the most predictive feature combinations. 30 % and 44 % of patients developed CDMS within one and three years, respectively. The SVMs correctly predicted the presence (or the absence) of CDMS in 71.4 % of patients (sensitivity/specificity: 77 %/66 %) at 1 year, and in 68 % (60 %/76 %) at 3 years on average over all bootstraps. Combinations of features consistently gave a higher accuracy in predicting outcome than any single feature. Machine-learning-based classifications can be used to provide an "individualised" prediction of conversion to MS from subjects' baseline scans and clinical characteristics, with potential to be incorporated into routine clinical practice.
| S-EPMC4297887 | biostudies-literature
Project description:ImportanceMultiple sclerosis (MS) is usually diagnosed in women during their childbearing years. Currently, no consensus exists on whether pregnancy can delay the first episode of demyelination or clinically isolated syndrome (CIS).ObjectiveTo investigate the association of pregnancy with time to CIS onset.Design, setting, and participantsThis multicenter cohort study collected reproductive history (duration of each pregnancy, date of delivery, length of breastfeeding) on all participants between September 1, 2016, and June 25, 2019. Adult women being treated at the MS outpatient clinics of 4 tertiary hospitals in 2 countries (Charles University and General University Hospital in Prague, Czech Republic; Royal Melbourne Hospital in Melbourne, Australia; Alfred Hospital in Melbourne, Australia; and John Hunter Hospital in Newcastle, Australia) were recruited to participate in the study. Preexisting data (date of CIS onset, date of birth, sex, date of clinical onset, and Expanded Disability Status Scale result) were collected from MSBase, an international registry of long-term prospectively collected data on patients with MS. Data analyses were performed from June 1, 2019, to February 3, 2020.ExposuresGravida (defined as any pregnancy, including pregnancy that ended in miscarriage and induced abortion) and parity (defined as childbirth after gestational age of more than 20 weeks, including livebirth and stillbirth) before CIS onset.Main outcomes and measuresTime to CIS onset. The following were assessed: (1) whether women with previous pregnancies and childbirths had a delayed onset of CIS compared with those who had never been pregnant and those who had never given birth, and (2) whether a dose response existed, whereby a higher number of gravidity and parity was associated with a later onset of CIS.ResultsOf the 2557 women included in the study, the mean (SD) age at CIS onset was 31.5 (9.7) years. Of these women, before CIS onset, 1188 (46%) had at least 1 pregnancy and 1100 (43%) had at least 1 childbirth. The mean (SD) age at first pregnancy was 23.3 (4.5) years and at first childbirth was 23.8 (4.5) years. Women with previous pregnancies and childbirths had a later onset of CIS compared with those who had never been pregnant (HR, 0.68; 95% CI, 0.62-0.75; P < .001), with a median delay of 3.3 (95% CI, 2.5-4.1) years. Women who had given birth also had a later CIS onset compared with women who had never given birth (HR 0.68; 95% CI, 0.61-0.75; P < .001), with a similar median delay of 3.4 (95% CI, 1.6-5.2) years. A higher gravidity and parity number was not associated with delay in CIS onset.Conclusions and relevanceThis study suggests an association between previous pregnancies and childbirths and timing of CIS onset, but having more pregnancies or childbirths did not appear to be associated with a later CIS onset. Further studies are needed to help explain the mechanisms behind the associations between pregnancy and onset of multiple sclerosis.
| S-EPMC7490748 | biostudies-literature
Project description:In magnetic resonance imaging based brain morphometry, Gaussian smoothing is often applied to increase the signal-to-noise ratio and to increase the detection power of statistical parametric maps. However, most existing studies used a single smoothing filter without adequately justifying their choices. In this article, we want to determine the extent for which performing a morphometry analysis using multiple smoothing filters, namely conducting a scale space search, improves or decreases the detection power. We first compared scale space search with single-filter analysis through a simulated population study. The multiple comparisons in our four-dimensional scale space searches were corrected for using a unified P-value approach. Our results illustrate that, compared with a single-filter analysis, a scale space search analysis can properly capture the variations in analysis results caused by variations in smoothing, and more importantly, it can obviously increase the sensitivity for detecting brain morphometric changes. We also show that the cost of an increased critical threshold for conducting a scale space search is very small. In the second experiment, we investigated age and gender effects on cortical volume, thickness, and surface area in 104 normal subjects using scale space search. The obtained results provide a perspective of scale space theory on the morphological changes with age and gender. These results suggest that, in exploratory studies of aging, gender, and disease, conducting a scale space search is essential, if we are to produce a complete description of the structural changes or abnormalities associated with these dimensions.
| S-EPMC6870203 | biostudies-literature