Transient enlargement of brain ventricles during relapsing-remitting multiple sclerosis and experimental autoimmune encephalomyelitis

Millward, Jason M.; Delgado, Paula Ramos; Smorodchenko, Alina; Boehmert, Laura; Periquito, Joao; Reimann, Henning Matthias; Prinz, Christian; Els, Antje; Scheel, Michael; Bellmann‐Strobl, Judith; Waiczies, Helmar; Wuerfel, Jens; Infante-Duarte, Carmen; Chien, Claudia; Kuchling, Joseph; Pohlmann, Andreas; Zipp, Frauke; Paul, Friedemann; Niendorf, Thoralf; Waiczies, Sonia

doi:10.1172/jci.insight.140040

Cited by 15 publications

(15 citation statements)

References 78 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 37 Importantly, it has been found that the pattern of neurodegeneration in MS is associated with the load of inflammatory infiltrates in the CSF, such as chemokines that are produced by the CP and then affecting the LV regions. 38 Thus, along with previous findings that the ventricular volume in early RRMS patients transiently fluctuate, 9 our findings using raw-MRI data even without contrast enhancement, support observations that disease activity may be related to changes in the CP and LV. Our results could lead to a more easily accessible clinical tool, whereby patient raw MRIs (i.e.…”

Section: Discussionsupporting

confidence: 89%

“…It has been shown that the lateral ventricles (LV) contract and expand over the course of early MS, whereas patients with higher ventricular CSF volume change had lower disability scores. 9 Also, areas around the ventricles were found to be most predictive in discriminating between MS patients and healthy participants using a deep learning algorithm. 10 Recently, the choroid plexus (CP) within the LV was shown to have significantly higher gadolinium-enhancing (Gd) intensities in MS patients versus healthy participants, thus this region could be related to disease activity.…”

Section: Introductionmentioning

confidence: 97%

See 1 more Smart Citation

Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity

Chien

Seiler²,

Eitel

et al. 2022

Multiple Sclerosis Journal - Experimental, Translational and Cl

Self Cite

View full text Add to dashboard Cite

Background Lack of easy-to-interpret disease activity prediction methods in early MS can lead to worse patient prognosis. Objectives Using machine learning (multiple kernel learning – MKL) models, we assessed the prognostic value of various clinical and MRI measures for disease activity. Methods Early MS patients ( n = 148) with at least two associated clinical and MRI visits were investigated. T2-weighted MRIs were cropped to contain mainly the lateral ventricles (LV). High disease activity was defined as surpassing NEDA-3 Criteria more than once per year. Clinical demographic, MRI-extracted image-derived phenotypes (IDP), and MRI data were used as inputs for separate kernels to predict future disease activity with MKL. Model performance was compared using bootstrapped effect size analysis of mean differences. Results A total of 681 visits were included, where 81 (55%) patients had high disease activity in a combined end point measure using all follow-up visits. MKL model discrimination performance was moderate (AUC ≥ 0.62); however, modelling with combined clinical and cropped LV kernels gave the highest prediction performance (AUC = 0.70). Conclusions MRIs contain valuable information on future disease activity, especially in and around the LV. MKL techniques for combining different data types can be used for the prediction of disease activity in a relatively small MS cohort.

show abstract

Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 97%

Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity

Chien

Seiler²,

Eitel

et al. 2022

Multiple Sclerosis Journal - Experimental, Translational and Cl

Self Cite

View full text Add to dashboard Cite

show abstract

“…The remaining variability of CBA can, at least partially, be attributed to transients fluctuation of ventricular size (+/-6%), reported recently in MS patients (Millward et al, 2020).…”

Section: Fig 3 Linear Regression Model Of Cba (A) and Total Brain Atr...mentioning

confidence: 67%

Mechanisms of central brain atrophy in multiple sclerosis

Klistorner

Barnett

Yiannikas

et al. 2022

Preprint

View full text Add to dashboard Cite

Background and objectives: The measurement of longitudinal change in ventricular volume has been suggested as an accurate and reliable surrogate of central brain atrophy (CBA), potentially applicable to the everyday management of patient with multiple sclerosis (MS). To better understand mechanisms underlying central brain atrophy in RRMS patients we investigated the contribution of inflammatory activity in different lesion compartments to the enlargement of ventricular CSF volume. In addition, we investigated the role of the severity of lesional tissue damage in CBA progression. Methods: Pre- and post-gadolinium 3D-T1, 3D fluid-attenuated inversion recovery (FLAIR) and diffusion tensor images were acquired from 50 patients with relapsing MS. Lesional activity between baseline and 48 months was analysed on FLAIR images using custom-build software, which independently segmented expanding part of the chronic lesions, new confluent lesions and new free-standing lesions. The degree of lesional tissue damage was assessed by change in Mean Diffusivity (MD). Volumetric change of lateral ventricles was used as a measure of central brain atrophy. Results: During follow-up ventricles expanded on average by 12.6+/-13.7%. There was significant increase of total lesion volume, 69.3% of which was due to expansion of chronic lesions and 30.7%-to new (confluent and free-standing) lesional activity. There was high degree of correlation between volume of combined lesional activity and CBA (r2=0.67), which became considerably stronger when lesion volume was adjusted by the degree of tissue damage severity (r2=0.81). Linear regression analysis explained 90% of CBA variability and revealed that chronic lesion expansion was by far the largest contributor to ventricular enlargement (Standardized Coefficient Beta 0.68 (p<0.001) for expansion of chronic lesions compared to 0.29 (p=<0.001) for confluent lesions and 0.23 (p=0.001) for free-standing new lesions). Age and baseline ventricular volume also provided significant input to the model. Discussion: Our data suggest that central brain atrophy is almost entirely explained by the combination of the volume and severity of lesional tissue activity. Furthermore, the expansion of chronic lesions plays a central role in this process.

show abstract

“…Pathological observations in animal models of disease are of little consequence if they do not reflect the human counterpart. Millward et al observed dynamic expansions and contractions of ventricle volumes in the mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis) by repeated MR measurements over a 2-month period [14]. In Multiple Sclerosis (MS) patients, short-term fluctuations in ventricle volumes were less striking than those in the animal model but they were clearly present.…”

Section: Contributions Of Preclinical Mri To the 3rsmentioning

confidence: 99%

Contribution of preclinical MRI to responsible animal research: living up to the 3R principle

Wachsmuth

Mensen

Barca

et al. 2021

Magn Reson Mater Phy

Self Cite

View full text Add to dashboard Cite

Transient enlargement of brain ventricles during relapsing-remitting multiple sclerosis and experimental autoimmune encephalomyelitis

Cited by 15 publications

References 78 publications

Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity

Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity

Mechanisms of central brain atrophy in multiple sclerosis

Contribution of preclinical MRI to responsible animal research: living up to the 3R principle

Contact Info

Product

Resources

About