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Diffusion tensor imaging for multilevel assessment of the visual pathway: possibilities for personalized outcome prediction in autoimmune disorders of the central nervous system

Overview of attention for article published in EPMA Journal, July 2017
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)

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Title
Diffusion tensor imaging for multilevel assessment of the visual pathway: possibilities for personalized outcome prediction in autoimmune disorders of the central nervous system
Published in
EPMA Journal, July 2017
DOI 10.1007/s13167-017-0102-x
Pubmed ID
Authors

Joseph Kuchling, Alexander U Brandt, Friedemann Paul, Michael Scheel

Abstract

The afferent visual pathway represents the most frequently affected white matter pathway in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD). Diffusion tensor imaging (DTI) can reveal microstructural or non-overt brain tissue damage and quantify pathological processes. DTI facilitates the reconstruction of major white matter fiber tracts allowing for the assessment of structure-function and damage-dysfunction relationships. In this review, we outline DTI studies investigating the afferent visual pathway in idiopathic optic neuritis (ON), NMOSD, and MS. Since MS damage patterns are believed to depend on multiple factors, i.e., ON (anterior visual pathway damage), inflammatory lesions (posterior visual pathway damage), and global diffuse inflammatory and neurodegenerative processes, comprehensive knowledge on different contributing factors using DTI in vivo may advance our understanding of MS disease pathology. Combination of DTI measures and visual outcome parameters yields the potential to improve routine clinical diagnostic procedures and may further the accuracy of individual prognosis with regard to visual function and personalized disease outcome. However, due to the inherent limitations of DTI acquisition and post-processing techniques and the so far heterogeneous and equivocal data of previous studies, evaluation of the true potential of DTI as a possible biomarker for afferent visual pathway dysfunction is still substantially limited. Further research efforts with larger longitudinal studies and standardized DTI acquisition and post-processing validation criteria are needed to overcome current DTI limitations. DTI evaluation at different levels of the visual pathway has the potential to provide markers for individual damage evaluation in the future. As an imaging biomarker, DTI may support individual outcome prediction during personalized treatment algorithms in MS and other neuroinflammatory diseases, hereby leveraging the concept of predictive, preventive, and personalized medicine in the field of clinical neuroimmunology.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 18%
Researcher 6 12%
Student > Ph. D. Student 6 12%
Student > Doctoral Student 4 8%
Other 4 8%
Other 5 10%
Unknown 16 32%
Readers by discipline Count As %
Medicine and Dentistry 12 24%
Neuroscience 8 16%
Nursing and Health Professions 6 12%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Earth and Planetary Sciences 1 2%
Other 3 6%
Unknown 19 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 April 2019.
All research outputs
#7,719,114
of 23,999,200 outputs
Outputs from EPMA Journal
#107
of 318 outputs
Outputs of similar age
#118,014
of 319,962 outputs
Outputs of similar age from EPMA Journal
#7
of 9 outputs
Altmetric has tracked 23,999,200 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 318 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 319,962 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.