OBJECTIVE: To examine the predictive value of central atrophy in early multiple sclerosis (MS) patients, for medium term clinical outcome. METHODS: In 54 patients with recently diagnosed MS, clinical and MRI parameters were obtained at baseline, and after 2 and 5.5 years of follow-up. In addition to conventional MRI parameters and the annualised percentage brain volume change (aPBVC), the annualised percentage ventricular volume change (aPVVC) was quantified. Main outcome measure was disease progression, defined by an increase in Expanded Disability Status Scale of ≥1 after 5.5 years. RESULTS: Disease progression occurred in 29 patients. aPVVC within the first two years was significantly higher in these progressing patients (median 4.76%; IQR 3.05-9.17) compared with stable patients (median 3.23%; IQR -0.1-6.02) (p=0.02). A logistic regression model selected aPVVC within the first 2 years as the only MRI marker predicting progression after 5.5 years (OR 1.17, 95% CI 1.02 to 1.35). When entering all MRI and clinical markers, again aPVVC within the first 2 years was the only MRI marker selected. While aPVVC was correlated between the two consecutive time intervals (ρ=0.41, p<0.01), aPBVC was not. Furthermore, baseline T2 lesion load and gadolinium enhancing lesion load were correlated with aPVVC in the second time interval (2-5.5 years) but not with aPBVC. CONCLUSION: The rate of ventricular enlargement seems to be even more strongly predictive of disease progression after medium term follow-up than whole brain atrophy rate, and also outperforms lesion measures. Central atrophy rate could therefore be an important prognostic marker, especially in the early stages of MS.
OBJECTIVE: To examine the predictive value of central atrophy in early multiple sclerosis (MS) patients, for medium term clinical outcome. METHODS: In 54 patients with recently diagnosed MS, clinical and MRI parameters were obtained at baseline, and after 2 and 5.5 years of follow-up. In addition to conventional MRI parameters and the annualised percentage brain volume change (aPBVC), the annualised percentage ventricular volume change (aPVVC) was quantified. Main outcome measure was disease progression, defined by an increase in Expanded Disability Status Scale of ≥1 after 5.5 years. RESULTS: Disease progression occurred in 29 patients. aPVVC within the first two years was significantly higher in these progressing patients (median 4.76%; IQR 3.05-9.17) compared with stable patients (median 3.23%; IQR -0.1-6.02) (p=0.02). A logistic regression model selected aPVVC within the first 2 years as the only MRI marker predicting progression after 5.5 years (OR 1.17, 95% CI 1.02 to 1.35). When entering all MRI and clinical markers, again aPVVC within the first 2 years was the only MRI marker selected. While aPVVC was correlated between the two consecutive time intervals (ρ=0.41, p<0.01), aPBVC was not. Furthermore, baseline T2 lesion load and gadolinium enhancing lesion load were correlated with aPVVC in the second time interval (2-5.5 years) but not with aPBVC. CONCLUSION: The rate of ventricular enlargement seems to be even more strongly predictive of disease progression after medium term follow-up than whole brain atrophy rate, and also outperforms lesion measures. Central atrophy rate could therefore be an important prognostic marker, especially in the early stages of MS.
Authors: Nicola De Stefano; Laura Airas; Nikolaos Grigoriadis; Heinrich P Mattle; Jonathan O'Riordan; Celia Oreja-Guevara; Finn Sellebjerg; Bruno Stankoff; Agata Walczak; Heinz Wiendl; Bernd C Kieseier Journal: CNS Drugs Date: 2014-02 Impact factor: 5.749
Authors: J Kuchling; T Sinnecker; I Bozin; J Dörr; V I Madai; J Sobesky; T Niendorf; F Paul; J Wuerfel Journal: Nervenarzt Date: 2014-04 Impact factor: 1.214
Authors: E Ghione; N Bergsland; M G Dwyer; J Hagemeier; D Jakimovski; D P Ramasamy; D Hojnacki; A A Lizarraga; C Kolb; S Eckert; B Weinstock-Guttman; R Zivadinov Journal: AJNR Am J Neuroradiol Date: 2020-08-06 Impact factor: 3.825
Authors: Hugo Vrenken; Eline K Vos; W M van der Flier; Ingrid C Sluimer; Keith S Cover; Dirk L Knol; Frederik Barkhof Journal: Hum Brain Mapp Date: 2013-01-30 Impact factor: 5.038