Journal Article DZNE-2023-00604

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png
Brain Volume Changes after COVID-19 Compared to Healthy Controls by Artificial Intelligence-Based MRI Volumetry.

 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;

2023
MDPI Basel

Diagnostics 13(10), 1716 () [10.3390/diagnostics13101716] special issue: "Quantitative Imaging in COVID-19"

This record in other databases:    

Please use a persistent id in citations: doi:

Abstract: Cohort studies that quantify volumetric brain data among individuals with different levels of COVID-19 severity are presently limited. It is still uncertain whether there exists a potential correlation between disease severity and the effects of COVID-19 on brain integrity. Our objective was to assess the potential impact of COVID-19 on measured brain volume in patients with asymptomatic/mild and severe disease after recovery from infection, compared with healthy controls, using artificial intelligence (AI)-based MRI volumetry. A total of 155 participants were prospectively enrolled in this IRB-approved analysis of three cohorts with a mild course of COVID-19 (n = 51, MILD), a severe hospitalised course (n = 48, SEV), and healthy controls (n = 56, CTL) all undergoing a standardised MRI protocol of the brain. Automated AI-based determination of various brain volumes in mL and calculation of normalised percentiles of brain volume was performed with mdbrain software, using a 3D T1-weighted magnetisation-prepared rapid gradient echo (MPRAGE) sequence. The automatically measured brain volumes and percentiles were analysed for differences between groups. The estimated influence of COVID-19 and demographic/clinical variables on brain volume was determined using multivariate analysis. There were statistically significant differences in measured brain volumes and percentiles of various brain regions among groups, even after the exclusion of patients undergoing intensive care, with significant volume reductions in COVID-19 patients, which increased with disease severity (SEV > MILD > CTL) and mainly affected the supratentorial grey matter, frontal and parietal lobes, and right thalamus. Severe COVID-19 infection, in addition to established demographic parameters such as age and sex, was a significant predictor of brain volume loss upon multivariate analysis. In conclusion, neocortical brain degeneration was detected in patients who had recovered from SARS-CoV-2 infection compared to healthy controls, worsening with greater initial COVID-19 severity and mainly affecting the fronto-parietal brain and right thalamus, regardless of ICU treatment. This suggests a direct link between COVID-19 infection and subsequent brain atrophy, which may have major implications for clinical management and future cognitive rehabilitation strategies.

Keyword(s): COVID-19 ; SARS-CoV-2 ; artificial intelligence ; brain atrophy ; magnetic resonance imaging

Classification:

Contributing Institute(s):
  1. Clinical Neuroimaging (AG Radbruch)
  2. Interventional Trials and Biomarkers in Neurodegenerative Diseases (Biomarker)
  3. Clinical Research Platform (CRP) (Clinical Research Platform (CRP))
Research Program(s):
  1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

Appears in the scientific report 2023
Database coverage:
Medline ; Creative Commons Attribution CC BY (No Version) ; Creative Commons Attribution CC BY 4.0 ; DOAJ ; OpenAccess ; Article Processing Charges ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF < 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
Click to display QR Code for this record

The record appears in these collections:
Institute Collections > BN DZNE > BN DZNE-Clinical Research Platform (CRP)
Document types > Articles > Journal Article
Institute Collections > BN DZNE > BN DZNE-AG Radbruch
Institute Collections > BN DZNE > BN DZNE-Biomarker
Full Text Collection
Public records
Publications Database

 Record created 2023-06-13, last modified 2023-11-20