Evidence map›Paper›PMID 30261534›Full record

ArticleEndoscopy2019

Assessment of Barrett's esophagus and dysplasia with ultrahigh-speed volumetric en face and cross-sectional optical coherence tomography.

Osman O Ahsen, Kaicheng Liang, Hsiang-Chieh Lee, Michael G Giacomelli, Zhao Wang, Benjamin Potsaid, Marisa Figueiredo, Qin Huang, Vijaysekhar Jayaraman, James G Fujimoto and 1 more

Open access · greenAbstract read
In one paragraph

Article in Endoscopy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 14 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

Osman O AhsenDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Kaicheng LiangDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Hsiang-Chieh LeeDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Michael G GiacomelliDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Zhao WangDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Benjamin PotsaidDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Marisa FigueiredoVA Boston Healthcare System, Boston, Massachusetts, United States.
Qin HuangVA Boston Healthcare System, Boston, Massachusetts, United States.
Vijaysekhar JayaramanPraevium Research, Inc., Santa Barbara, California, United States.
James G FujimotoDepartment of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Hiroshi MashimoVA Boston Healthcare System, Boston, Massachusetts, United States.
Massachusetts Institute of Technology · USHarvard University · USPraevium Research (United States) · USVA Boston Healthcare System · US

Funding

Novel Optical Diagnostics with Optical Coherence TomographyR01EY011289 · NEI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI JAMES G FUJIMOTO · 1995 to 2026
$9.5M
OPTICAL BIOPSY USING OPTICAL COHERENCE TOMOGRAPHYR01CA075289 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI FUJIMOTO, JAMES G, MASHIMO, HIROSHI · 1997 to 2018
$4.8M
Intraoperative real time breast cancer margin assessment with nonlinear microscopR01CA178636 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI CONNOLLY, JAMES, FUJIMOTO, JAMES G · 2013 to 2018
$1.7M
NCI NIH HHS R01 CA075289NCI NIH HHS R01 CA178636NEI NIH HHS R01 EY011289
6 · The paper itself

Abstract

backgroundThis study aimed to evaluate the use of ultrahigh-speed volumetric en face and cross-sectional optical coherence tomography (OCT) with micromotor catheters for the in vivo assessment of Barrett's esophagus and dysplasia.

methods74 OCT datasets with correlated biopsy/endoscopic mucosal resection histology (49 nondysplastic Barrett's esophagus [NDBE], 25 neoplasia) were obtained from 14 patients with Barrett's esophagus and a history of dysplasia and 30 with NDBE. The associations between irregular mucosal patterns on en face OCT, absence of mucosal layering, surface signal > subsurface, and > 5 atypical glands on cross-sectional OCT vs. histology and treatment history were assessed by three blinded readers.

resultsAtypical glands under irregular mucosal patterns occurred in 75 % of neoplasia (96 % of treatment-naïve neoplasia) vs. 30 % of NDBE datasets (43 % of short- and 18 % of long-segment NDBE). Mucosal layering was absent in 35 % of neoplasia and 50 % of NDBE datasets, and surface signal > subsurface occurred in 29 % of neoplasia and 30 % of NDBE datasets.

conclusionsAtypical glands under irregular mucosal patterns are strongly associated with neoplasia, suggesting potential markers for dysplasia and a role in pathogenesis.

Indexed as

Barrett EsophagusEsophageal MucosaEsophageal NeoplasmsPrecancerous ConditionsBiopsyEsophagoscopyFemaleHumansMaleMiddle AgedReproducibility of ResultsTomography, Optical Coherence

Identifiers

PMID30261534
PMCPMC6674974
OpenAlexW2892524576

What OpenQuestion holds

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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.