Evidence map›Paper›PMID 34166700›Full record

ArticleJournal of neuroscience methods2021

Quantification of relative neurite tortuosity using Fourier transforms.

Benjamin Smith, Ananya Datta, Justin Lee, David Evans, Suzanne Fleiszig

Open access · hybridAbstract read
In one paragraph

Article in Journal of neuroscience methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% 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

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 2 institutions in 1 country.

Benjamin SmithSchool of Optometry, University of California, Berkeley, CA 94720, USA; Graduate Program in Vision Science, University of California, Berkeley, CA 94720, USA. Electronic address: benjamin.smith@berkeley.edu.
Ananya DattaSchool of Optometry, University of California, Berkeley, CA 94720, USA.
Justin LeeSchool of Optometry, University of California, Berkeley, CA 94720, USA.
David EvansSchool of Optometry, University of California, Berkeley, CA 94720, USA; College of Pharmacy, Touro University California, Vallejo, CA 94592, USA.
Suzanne FleiszigSchool of Optometry, University of California, Berkeley, CA 94720, USA; Graduate Program in Vision Science, University of California, Berkeley, CA 94720, USA.
University of California, Berkeley · USTouro University California · US

Funding

UC Berkeley Vision Science COREP30EY003176 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI RICHARD H KRAMER · 1985 to 2026
$16.4M
Transient Receptor Potential Ion Channels and Corneal Defense Against Bacterial AdhesionR01EY030350 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI Suzanne MJ FLEISZIG · 2019 to 2026
$3.0M
NEI NIH HHS P30 EY003176NEI NIH HHS R01 EY030350
6 · The paper itself

Abstract

backgroundThe tortuosity of nerve fibers has been shown to be important for identifying and monitoring clinically relevant manifestations resulting from of a variety of ocular and systemic disease pathologies and disorders. However, quantifying tortuosity in dense neurite networks can prove challenging, as existing methods require manual scoring and/or complete segmentation of the neurite network. NEW

methodWe measured neurite tortuosity by quantifying the degree of directional coherence in the Fourier transform of segmented neurite masks. This allowed for the analysis of neurite tortuosity without requiring complete segmentation of the neurite network. We were also able to adapt this method to measure tortuosity at different length and size scales.

resultsWith this novel method, neurite tortuosity was accurately quantified in simulated data sets at multiple length scales and scale variant and scale invariant tortuosity was accurately distinguished. Use of this method on images of murine corneal neurites correctly distinguished known differences between neurite tortuosity in the peripheral and central cornea. COMPARISON WITH EXISTING METHOD(S): Other methods require complete segmentation of neurites, which can be prohibitive in dense and/or sparsely labeled neurite networks such as in the cornea. Additionally, other methods require manual curation, manual scoring, or generation of a curated training set, while our novel method directly measures tortuosity as an intrinsic property of the image.

conclusionsWe report the use of Fourier transforms for quantification of neurite tortuosity at multiple length scales, and with an image input that contains incompletely segmented neurites. This new method does not require manual training or curation, allowing a direct and rapid measurement of neurite tortuosity, thereby enhancing the accuracy and utility of neurite tortuosity measurements for evaluation of ocular and systemic disease pathology.

Indexed as

Nerve FibersNeuritesAnimalsCorneaFourier AnalysisHumansImage Processing, Computer-AssistedMiceCorneaFluorescence microscopyFourier transformNeuriteSegmentationTortuosity

Identifiers

PMID34166700
PMCPMC10964090
OpenAlexW3173261366

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LicenceCC BY
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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.