2D linear measures of ventricular enlargement may be relevant markers of brain atrophy and long-term disability progression in multiple sclerosis

Pontillo, Giuseppe; Cocozza, Sirio; Stasi, Martina Di; Carotenuto, Antonio; Paolella, Chiara; Cipullo, Maria Brunella; Perillo, Teresa; Vola, Elena Augusta; Russo, Camilla; Masullo, Massimiliano; Moccia, Marcello; Lanzillo, Roberta; Tedeschi, Enrico; Elefante, Andrea; Morra, Vincenzo Brescia; Brunetti, Arturo; Quarantelli, Mario; Petracca, Maria

doi:10.1007/s00330-020-06738-4

Cited by 19 publications

(29 citation statements)

References 39 publications

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“…Among all of the imaging biomarkers, more than half of the NRs identified the central vein sign as a promising and useful marker for MS diagnosis, in line with research studies suggesting its application to increase diagnostic sensitivity and specificity [37][38][39][40], followed by a quantitative assessment of cerebral atrophy. As per this latter biomarker, although measures of brain atrophy are valuable markers of ongoing neurodegeneration in MS [41,42], and an atrophy cut-off able to differentiate pathological from physiological atrophy accrual has been identified [43], we must not forget that the determination of meaningful atrophy in the single-subject is still beyond our reach. Interestingly, less confidence in diagnostic sensitivity and specificity was reserved to other neuroradiological biomarkers such as the "slow-expanding lesions", probably due to methodological concerns.…”

Section: Discussionmentioning

confidence: 99%

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis

et al. 2021

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(1) Although guidelines about the use of MRI sequences for Multiple Sclerosis (MS) diagnosis and follow-up are available, variability in acquisition protocols is not uncommon in everyday clinical practice. The aim of this study was to evaluate the real-world application of MS imaging guidelines in different settings to clarify the level of adherence to these guidelines. (2) Via an on-line anonymous survey, neuroradiologists (NR) were asked about MRI protocols and parameters routinely acquired when MS patients are evaluated in their center, both at diagnosis and follow-up. Furthermore, data about report content and personal opinions about emerging neuroimaging markers were also retrieved. (3) A total of 46 participants were included, mostly working in a hospital or university hospital (80.4%) and with more than 10 years of experience (47.9%). We found a relatively good adherence to the suggested MRI protocols regarding the use of T2-weighted sequences, although almost 10% of the participants routinely acquired 2D sequences with a slice thickness superior to 3 mm. On the other hand, a wider degree of heterogeneity was found regarding gadolinium administration, almost routinely performed at follow-up examination (87.0% of cases) in contrast with the current guidelines, as well as a low use of a standardized reporting system (17.4% of cases). (4) Although the MS community is getting closer to a standardization of MRI protocols, there is still a relatively wide heterogeneity among NR, with particular reference to contrast administration, which must be overcome to guarantee an adequate quality of patients’ care in MS.

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Section: Discussionmentioning

confidence: 99%

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis

et al. 2021

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“…Of these 163 subjects, at baseline 122 patients had a relapsing-remitting form of MS, while the remaining 41 patients had a progressive form. Patients showed a disease duration of 9.90 ± 8.06 years, range [0.00-37.00], with a time between visits that was 3.93 ± 0.95 years, range [2][3][4][5][6]. At the follow-up examination, disease progression was observed in 58 over 163 patients (35.6% of the sample), whose EDSS distributions at baseline and at follow-up were respectively 3.5 [0.0-7.0] and 4.5 [1.5-7.0], while in the remaining 105 patients the EDSS remained stable at 3.0 [0.0-7.5].…”

Section: Sample Selectionmentioning

confidence: 99%

“…Neuroimaging techniques are powerful tools to investigate MS [ 4 ] and Magnetic Resonance Imaging (MRI) findings are considered good predictors of conversion from clinically isolated syndrome (CIS) to clinically definite MS [ 5 ], as well as of long-term disability [ 6 , 7 ]. Several MRI studies have highlighted various aspects of tissue damage in MS [ 8 ] demonstrating a prognostic role of T2-hyperintense lesions, global and cortical atrophy [ 9 ], as well as that of damage to some key structures, such as thalamus [ 10 ] and cerebellum [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis

et al. 2021

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Objectives To evaluate the accuracy of a data-driven approach, such as machine learning classification, in predicting disability progression in MS. Methods We analyzed structural brain images of 163 subjects diagnosed with MS acquired at two different sites. Participants were followed up for 2–6 years, with disability progression defined according to the expanded disability status scale (EDSS) increment at follow-up. T2-weighted lesion load (T2LL), thalamic and cerebellar gray matter (GM) volumes, fractional anisotropy of the normal appearing white matter were calculated at baseline and included in supervised machine learning classifiers. Age, sex, phenotype, EDSS at baseline, therapy and time to follow-up period were also included. Classes were labeled as stable or progressed disability. Participants were randomly chosen from both sites to build a sample including 50% patients showing disability progression and 50% patients being stable. One-thousand machine learning classifiers were applied to the resulting sample, and after testing for overfitting, classifier confusion matrix, relative metrics and feature importance were evaluated. Results At follow-up, 36% of participants showed disability progression. The classifier with the highest resulting metrics had accuracy of 0.79, area under the true positive versus false positive rates curve of 0.81, sensitivity of 0.90 and specificity of 0.71. T2LL, thalamic volume, disability at baseline and administered therapy were identified as important features in predicting disability progression. Classifiers built on radiological features had higher accuracy than those built on clinical features. Conclusions Disability progression in MS may be predicted via machine learning classifiers, mostly evaluating neuroradiological features.

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“…Third ventricular width (TVW) is an established technique, [13] and correlates with long-term disability progression in MS [14]. TVW was measured as the width of the third ventricle at the midpoint of a line running parallel to the long axis of the ventricle on axially acquired PD/T2-weighted MR scans at baseline, one, five, 10, 14 and 20 years, and T2 weighted images at 30 years.…”

Section: Image Analysismentioning

confidence: 99%

Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up

Haider

Chung

Birch

et al. 2021

J Neurol Neurosurg Psychiatry

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ObjectiveTo determine 30-year brain atrophy rates following clinically isolated syndromes and the relationship of atrophy in the first 5 years and clinical outcomes 25 years later.MethodsA cohort of 132 people who presented with a clinically isolated syndrome suggestive of multiple sclerosis (MS) were recruited between 1984–1987. Clinical and MRI data were collected prospectively over 30 years. Widths of the third ventricle and the medulla oblongata were used as linear atrophy measures.ResultsAt 30 years, 27 participants remained classified as having had a clinically isolated syndrome, 34 converted to relapsing remitting MS, 26 to secondary progressive MS and 16 had died due to MS. The mean age at baseline was 31.7 years (SD 7.5) and the mean disease duration was 30.8 years (SD 0.9). Change in medullary and third ventricular width within the first 5 years, allowing for white matter lesion accrual and Expanded Disability Status Scale increases over the same period, predicted clinical outcome measures at 30 years. 1 mm of medullary atrophy within the first 5 years increased the risk for secondary progressive MS or MS related death by 30 years by 583% (OR 5.83, 95% CI 1.74 to 19.61, p<0.005), using logistic regression.ConclusionsOur findings show that brain regional atrophy within 5 years of a clinically isolated syndrome predicts progressive MS or a related death, and disability 25 years later.

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2D linear measures of ventricular enlargement may be relevant markers of brain atrophy and long-term disability progression in multiple sclerosis

Cited by 19 publications

References 39 publications

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis

Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis

Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up

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