Evidence map›Paper›PMID 31453005›Full record

ArticleBiomedical optics express2019

Analysis of low-scattering regions in optical coherence tomography: applications to neurography and lymphangiography.

Valentin Demidov, Lev A Matveev, Olga Demidova, Alexander L Matveyev, Vladimir Y Zaitsev, Costel Flueraru, I Alex Vitkin

Abstract read
In one paragraph

Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
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  10. Biomedical optics express · 2020
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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

7 authors.

Valentin DemidovDepartment of Medical Biophysics, University of Toronto, 101 College St., Toronto, M5G 1L7, Canada.
Lev A MatveevInstitute of Applied Physics Russian Academy of Sciences, 46 Ulyanov Street, Nizhniy Novgorod, 603950, Russia.
Olga DemidovaDepartment of Arts and Science, Seneca College, 1750 Finch Avenue East, Toronto, M2J 2X5, Canada.
Alexander L MatveyevInstitute of Applied Physics Russian Academy of Sciences, 46 Ulyanov Street, Nizhniy Novgorod, 603950, Russia.
Vladimir Y ZaitsevInstitute of Applied Physics Russian Academy of Sciences, 46 Ulyanov Street, Nizhniy Novgorod, 603950, Russia.
Costel FlueraruNational Research Council Canada, Information Communication Technology, 1200 Montreal Rd, Ottawa, K1A0R6, Canada.
I Alex VitkinDepartment of Medical Biophysics, University of Toronto, 101 College St., Toronto, M5G 1L7, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analysis of semi-transparent low scattering biological structures in optical coherence tomography (OCT) has been actively pursued in the context of lymphatic imaging, with most approaches relying on the relative absence of signal as a means of detection. Here we present an alternate methodology based on spatial speckle statistics, utilizing the similarity of a distribution of given voxel intensities to the power distribution function of pure noise, to visualize the low-scattering biological structures of interest. In a human tumor xenograft murine model, we show that these correspond to lymphatic vessels and nerves; extensive histopathologic validation studies are reported to unequivocally establish this correspondence. The emerging possibility of OCT lymphangiography and neurography is novel and potentially impactful (especially the latter), although further methodology refinement is needed to distinguish between the visualized lymphatics and nerves.

Identifiers

PMID31453005
PMCPMC6701530

What OpenQuestion holds

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Registered trials

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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.