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Mendeley readers
Attention Score in Context
| Title |
A Fully Automated Pipeline for Normative Atrophy in Patients with Neurodegenerative Disease
|
|---|---|
| Published in |
Frontiers in Neurology, January 2018
|
| DOI | 10.3389/fneur.2017.00727 |
| Pubmed ID | |
| Authors |
Christian Rummel, Fabian Aschwanden, Richard McKinley, Franca Wagner, Anke Salmen, Andrew Chan, Roland Wiest |
| Abstract |
Volumetric image analysis to detect progressive brain tissue loss in patients with multiple sclerosis (MS) has recently been suggested as a promising marker for "no evidence of disease activity." Software packages for longitudinal whole-brain volume analysis in individual patients are already in clinical use; however, most of these methods have omitted region-based analysis. Here, we suggest a fully automatic analysis pipeline based on the free software packages FSL and FreeSurfer. Fifty-five T1-weighted magnetic resonance imaging (MRI) datasets of five patients with confirmed relapsing-remitting MS and mild to moderate disability were longitudinally analyzed compared to a morphometric reference database of 323 healthy controls (HCs). After lesion filling, the volumes of brain segmentations and morphometric parameters of cortical parcellations were automatically screened for global and regional abnormalities. Error margins and artifact probabilities of regional morphometric parameters were estimated. Linear models were fitted to the series of follow-up MRIs and checked for consistency with cross-sectional aging in HCs. As compared to leave-one-out cross-validation in a subset of the control dataset, anomaly detection rates were highly elevated in MRIs of two patients. We detected progressive volume changes that were stronger than expected compared to normal aging in 4/5 patients. In individual patients, we also identified stronger than expected regional decreases of subcortical gray matter, of cortical thickness, and areas of reducing gray-white contrast over time. Statistical comparison with a large normative database may provide complementary and rater independent quantitative information about regional morphological changes related to disease progression or drug-related disease modification in individual patients. Regional volume loss may also be detected in clinically stable patients. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 2 | 40% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 16% |
| Student > Bachelor | 6 | 12% |
| Student > Ph. D. Student | 6 | 12% |
| Student > Master | 6 | 12% |
| Professor | 5 | 10% |
| Other | 8 | 16% |
| Unknown | 11 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 14 | 28% |
| Medicine and Dentistry | 9 | 18% |
| Computer Science | 3 | 6% |
| Engineering | 3 | 6% |
| Psychology | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 15 | 30% |
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 11 April 2018.
All research outputs
#7,487,474
of 23,018,998 outputs
Outputs from Frontiers in Neurology
#4,639
of 11,914 outputs
Outputs of similar age
#153,941
of 441,261 outputs
Outputs of similar age from Frontiers in Neurology
#63
of 223 outputs
Altmetric has tracked 23,018,998 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 11,914 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 60% 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 441,261 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 64% of its contemporaries.
We're also able to compare this research output to 223 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.