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Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study
V. Ravano, M. Andelova, MJ. Fartaria, MFA. Mahdi, B. Maréchal, R. Meuli, T. Uher, J. Krasensky, M. Vaneckova, D. Horakova, T. Kober, J. Richiardi
Jazyk angličtina Země Nizozemsko
Typ dokumentu časopisecké články, multicentrická studie, práce podpořená grantem
NLK
Directory of Open Access Journals
od 2012
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od 2012
PubMed Central
od 2012
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od 2012
- MeSH
- algoritmy MeSH
- lidé MeSH
- mozek diagnostické zobrazování MeSH
- retrospektivní studie MeSH
- roztroušená skleróza * diagnostické zobrazování MeSH
- zobrazování difuzních tenzorů MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
The translational potential of MR-based connectivity modelling is limited by the need for advanced diffusion imaging, which is not part of clinical protocols for many diseases. In addition, where diffusion data is available, brain connectivity analyses rely on tractography algorithms which imply two major limitations. First, tracking algorithms are known to be sensitive to the presence of white matter lesions and therefore leading to interpretation pitfalls and poor inter-subject comparability in clinical applications such as multiple sclerosis. Second, tractography quality is highly dependent on the acquisition parameters of diffusion sequences, leading to a trade-off between acquisition time and tractography precision. Here, we propose an atlas-based approach to study the interplay between structural disconnectivity and lesions without requiring individual diffusion imaging. In a multi-centric setting involving three distinct multiple sclerosis datasets (containing both 1.5 T and 3 T data), we compare our atlas-based structural disconnectome computation pipeline to disconnectomes extracted from individual tractography and explore its clinical utility for reducing the gap between radiological findings and clinical symptoms in multiple sclerosis. Results using topological graph properties showed that overall, our atlas-based disconnectomes were suitable approximations of individual disconnectomes from diffusion imaging. Small-worldness was found to decrease for larger total lesion volumes thereby suggesting a loss of efficiency in brain connectivity of MS patients. Finally, the global efficiency of the created brain graph, combined with total lesion volume, allowed to stratify patients into subgroups with different clinical scores in all three cohorts.
Advanced Clinical Imaging Technology Siemens Healthcare AG Lausanne Switzerland
Department of Radiology Lausanne University Hospital and University of Lausanne Lausanne Switzerland
LTS5 École Polytechnique Fédérale de Lausanne Lausanne Switzerland
Citace poskytuje Crossref.org
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- $a Ravano, Veronica $u Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. Electronic address: veronica.ravano@epfl.ch
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