Evidence map›Paper›PMID 28479655›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2016

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction.

S Mazdak Abulnaga, Zhen Yang, Aaron Carass, Kalyani Kansal, Bruno M Jedynak, Chiadi U Onyike, Sarah H Ying, Jerry L Prince

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

S Mazdak AbulnagaElectrical and Computer Engineering, The University of British Columbia, Vancouver, Canada.
Zhen YangElectrical and Computer Engineering, The Johns Hopkins University, Baltimore, USA.
Aaron CarassElectrical and Computer Engineering, The Johns Hopkins University, Baltimore, USA.
Kalyani KansalDepartment of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, USA.
Bruno M JedynakDepartment of Mathematics and Statistics, Portland State University, Portland, USA.
Chiadi U OnyikeDepartment of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, USA.
Sarah H YingRadiology, The Johns Hopkins School of Medicine, Baltimore, USA.
Jerry L PrinceElectrical and Computer Engineering, The Johns Hopkins University, Baltimore, USA.
Johns Hopkins Medicine · USJohns Hopkins University · USPortland State University · USUniversity of British Columbia · CA

Funding

Automatic Cerebellar MRI Labeling In Health and DiseaseR01NS056307 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PRINCE, JERRY L · 2006 to 2015
$3.0M
NINDS NIH HHS R01 NS056307
6 · The paper itself

Abstract

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

Indexed as

cerebellar ataxiacerebellumgraphical user interfacelinear discriminant analysisprincipal component analysisregression analysisshape analysisstructural changevisualization

Identifiers

PMID28479655
PMCPMC5417711
OpenAlexW2304618850

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.