Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Burggraaff, Jessica; Liu, Yao; Prieto, Juan Carlos; Simões, Jorge; Sitter, Alexandra de; Ruggieri, Serena; Brouwer, Iman; Lissenberg‐Witte, Birgit I.; Rocca, M. A.; Valsasina, Paola; Ropele, Stefan; Gasperini, Claudio; Gallo, Antonio; Pareto, Deborah; Sastre‐Garriga, Jaume; Enzinger, Christian; Filippi, Massimo; Stefano, Nicola De; Ciccarelli, Olga; Hulst, Hanneke E.; Wattjes, Mike P.; Barkhof, Frederik; Uitdehaag, Bernard M. J.; Vrenken, Hugo; Guttmann, Charles R.G.

doi:10.1016/j.nicl.2020.102549

Cited by 22 publications

(13 citation statements)

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“…However, a decrease of CCV in MS has not always been shown to proceed parallel to a gray matter volume loss [18,19]. Thus, based on previous observations, we can speculate that TV and CCV changes may progress independently during the course of MS [11,12].…”

Section: Discussionmentioning

confidence: 86%

“…The training dataset consisted of 2000 MRI studies from the OASIS-3 database [7] and 400 studies obtained as a part of the MRImmuno Project (see Funding). Brain structure segmentations, used as prediction labels in the CNN training set, were obtained using an automated pipeline of the FreeSurfer v6 software [8,9], as a well-established and widely tested brain MRI image processing and analyzing tool [10][11][12]. All FreeSurfer segmentations were executed with the default library settings (-all) and used as a CNN training set, without any manual correction.…”

Section: Mri Acquisition and Processingmentioning

confidence: 99%

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Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results

Rościszewska-Żukowska

Podyma²,

Stasiołek

et al. 2021

Brain Sciences

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Radiological activity in the post-partum period in MS patients is a well-known phenomenon, but there is no data concerning the influence of pregnancy on regional brain atrophy. The aim of this article was to investigate local brain atrophy in the peri-pregnancy period (PPP) in patients with MS. Thalamic volume (TV); corpus callosum volume (CCV) and classical MRI activity (new gadolinium enhancing lesions (Gd+), new T2 lesions, T1 lesions volume (T1LV) and T2 lesions volume (T2LV)) were analyzed in 12 clinically stable women with relapsing–remitting MS and with MRI performed in the PPP. We showed that there was a significant decrease in TV (p = 0.021) in the PPP. We also observed a significant increase in the T1 lesion volume (p = 0.028), new gadolinium-enhanced and new T2 lesions (in 46% and 77% of the scans, respectively) in the post-partum period. Our results suggest that the PPP in MS may be associated not only with classical MRI activity but, also, with regional brain atrophy.

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Section: Discussionmentioning

confidence: 86%

Section: Mri Acquisition and Processingmentioning

confidence: 99%

Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results

Rościszewska-Żukowska

Podyma²,

Stasiołek

et al. 2021

Brain Sciences

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“…For example, it may be possible to build the classification model with deep learning by virtually increasing the number of samples as in 50 . Liu et al 51 used convolutional neural networks (CNNs) to predict Alzheimer’s patients based on the fMRI images of their hippocampus, but we did not use them because the explanatory variables in our patient prediction model were gene expression levels, in which the similarities could not be assumed between elements close in location as in images. However, as mentioned above, the statistical relevance of the genes selected by PCAUFE is already guaranteed because we found the conventional machine learning models had sufficient prediction accuracies.…”

Section: Discussionmentioning

confidence: 99%

PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Fujisawa

Shimo

Taguchi

et al. 2021

Sci Rep

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Coronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

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“…Three-dimensional T1-weighted and T2-weighted FLAIR images with 1mm slice thickness were used in order to perform the analyses. First, all scans were evaluated for moving artifacts; then, we used the VolBrain TM platform [ 53 ] for the volumetric and lesion load analysis, as in Refs [ 54 , 55 , 56 ]. Lesion analysis with VolBrain TM was not conducted for cervical MRI, as this analysis is not available.…”

Section: Methodsmentioning

confidence: 99%

Ocrelizumab in Patients with Active Primary Progressive Multiple Sclerosis: Clinical Outcomes and Immune Markers of Treatment Response

Boziki

Bakirtzis

Sintila

et al. 2022

Cells

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Ocrelizumab is a B-cell-depleting monoclonal antibody approved for the treatment of relapsing-remitting multiple sclerosis (RRMS) and active primary progressive MS (aPPMS). This prospective, uncontrolled, open-label, observational study aimed to assess the efficacy of ocrelizumab in patients with aPPMS and to dissect the clinical, radiological and laboratory attributes of treatment response. In total, 22 patients with aPPMS followed for 24 months were included. The primary efficacy outcome was the proportion of patients with optimal response at 24 months, defined as patients free of relapses, free of confirmed disability accumulation (CDA) and free of T1 Gd-enhancing lesions and new/enlarging T2 lesions on the brain and cervical MRI. In total, 14 (63.6%) patients and 13 patients (59.1%) were classified as responders at 12 and 24 months, respectively. Time exhibited a significant effect on mean absolute and normalized gray matter cerebellar volume (F = 4.342, p = 0.23 and F = 4.279, p = 0.024, respectively). Responders at 24 months exhibited reduced peripheral blood ((%) of CD19+ cells) plasmablasts compared to non-responders at the 6-month point estimate (7.69 ± 4.4 vs. 22.66 ± 7.19, respectively, p = 0.043). Response to ocrelizumab was linked to lower total and gray matter cerebellar volume loss over time. Reduced plasmablast depletion was linked for the first time to sub-optimal response to ocrelizumab in aPPMS.

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Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Cited by 22 publications

References 50 publications

Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results

Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results

PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Ocrelizumab in Patients with Active Primary Progressive Multiple Sclerosis: Clinical Outcomes and Immune Markers of Treatment Response

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