Evidence map›Paper›PMID 35786546›Full record

ArticleIEEE transactions on bio-medical engineering2022

Direct Visualization and Quantitative Imaging of Small Airway Anatomy In Vivo Using Deep Learning Assisted Diffractive OCT.

Wu Yuan, Jeffrey Thiboutot, Hyeon-Cheol Park, Ang Li, Jeffrey Loube, Wayne Mitzner, Lonny Yarmus, Robert H Brown, Xingde Li

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.0field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Translating endobronchial optical coherence tomography to clinical practice.American journal of physiology. Lung cellular and molecular physiology · 2024
    Article
  11. Multimodal Diagnostics of Changes in Rat Lungs after Vaping.Diagnostics (Basel, Switzerland) · 2023
    Article
  12. Review
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

9 authors at 1 institution in 2 countries.

Wu Yuan
Jeffrey Thiboutot
Hyeon-Cheol Park
Ang Li
Jeffrey Loube
Wayne Mitzner
Lonny Yarmus
Robert H Brown
Xingde Li
Johns Hopkins University · US

Funding

MULTIDISCIPLINARY TRAINING PROGRAM IN LUNG DISEASEST32HL007534 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Nadia N Hansel, Larissa A. Shimoda · 1985 to 2026
$28.3M
Micro Coherence Imaging Technology for Assessing Obstructive Lung Disease in vivoR01HL121788 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI BROWN, ROBERT H, LI, XINGDE · 2014 to 2018
$3.7M
Nonlinear Optical Endomicroscopy for Optical Biopsy of Cancer in Internal OrgansR01CA153023 · NCI · JOHNS HOPKINS UNIVERSITY · PI LI, XINGDE · 2011 to 2015
$2.6M
Changes in Airway Wall Microstructures Following Bronchial Thermoplasty Detected by Optical Coherence TomographyF32HL144121 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI THIBOUTOT, JEFFREY · 2018 to 2018
$57k
NCI NIH HHS R01 CA153023NHLBI NIH HHS F32 HL144121NHLBI NIH HHS R01 HL121788NHLBI NIH HHS T32 HL007534
6 · The paper itself

Abstract

OBJECTIVE/

backgroundIn vivo imaging and quantification of the microstructures of small airways in three dimensions (3D) allows a better understanding and management of airway diseases, such as asthma and chronic obstructive pulmonary disease (COPD). At present, the resolution and contrast of the currently available conventional optical coherence tomography (OCT) imaging technologies operating at 1300 nm remain challenging to directly visualize the fine microstructures of small airways in vivo.

methodsWe developed an ultrahigh-resolution diffractive endoscopic OCT at 800 nm to afford a resolving power of 1.7 µm (in tissue) with an improved contrast and a custom deep residual learning based image segmentation framework to perform accurate and automated 3D quantification of airway anatomy.

resultsThe 800-nm diffractive OCT enabled the direct delineation of the structural components in the small airway wall in vivo. We further first demonstrated the 3D anatomic quantification of critical tissue compartments of small airways in sheep using the automated segmentation method.

conclusionThe deep learning assisted diffractive OCT provides a unique ability to access the small airways, directly visualize and quantify the important tissue compartments, such as airway smooth muscle, in the airway wall in vivo in 3D. SIGNIFICANCE: These pilot results suggest a potential technology for calculating volumetric measurements of small airways in patients in vivo.

Identifiers

PMID35786546
PMCPMC9842112
OpenAlexW4283826389

What OpenQuestion holds

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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.