Evidence map›Paper›PMID 33796383›Full record

ArticleBiomedical optics express2021

Analysis of sensitivity in quantitative micro-elastography.

Jiayue Li, Matt S Hepburn, Lixin Chin, Alireza Mowla, Brendan F Kennedy

Abstract read
In one paragraph

Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

  1. Phantoms for use in optical coherence elastography.Journal of biomedical optics · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Biomedical optics express · 2024
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Introduction to optical coherence elastography: tutorial.Journal of the Optical Society of America. A, Optics, image science, and vision · 2022
    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

5 authors.

Jiayue LiBRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Western Australia, 6009, Australia and Centre for Medical Research, The University of Western Australia, Crawley, Western Australia, 6009, Australia.
Matt S HepburnBRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Western Australia, 6009, Australia and Centre for Medical Research, The University of Western Australia, Crawley, Western Australia, 6009, Australia.ORCID https://orcid.org/0000-0001-5953-4478
Lixin ChinBRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Western Australia, 6009, Australia and Centre for Medical Research, The University of Western Australia, Crawley, Western Australia, 6009, Australia.
Alireza MowlaBRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Western Australia, 6009, Australia and Centre for Medical Research, The University of Western Australia, Crawley, Western Australia, 6009, Australia.
Brendan F KennedyBRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Western Australia, 6009, Australia and Centre for Medical Research, The University of Western Australia, Crawley, Western Australia, 6009, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative micro-elastography (QME), a variant of compression optical coherence elastography (OCE), is a technique to image tissue elasticity on the microscale. QME has been proposed for a range of applications, most notably tumor margin assessment in breast-conserving surgery. However, QME sensitivity, a key imaging metric, has yet to be systematically analyzed. Consequently, it is difficult to optimize imaging performance and to assess the potential of QME in new application areas. To address this, we present a framework for analyzing sensitivity that incorporates the three main steps in QME image formation: mechanical deformation, its detection using optical coherence tomography (OCT), and signal processing used to estimate elasticity. Firstly, we present an analytical model of QME sensitivity, validated by experimental data, and demonstrate that sub-kPa elasticity sensitivity can be achieved in QME. Using silicone phantoms, we demonstrate that sensitivity is dependent on friction, OCT focus depth, and averaging methods in signal processing. For the first time, we show that whilst lubrication of layer improves accuracy by reducing surface friction, it reduces sensitivity due to the time-dependent effect of lubricant exudation from the layer boundaries resulting in increased friction. Furthermore, we demonstrate how signal processing in QME provides a trade-off between sensitivity and resolution that can be used to optimize imaging performance. We believe that our framework to analyze sensitivity can help to sustain the development of QME and, also, that it can be readily adapted to other OCE techniques.

Identifiers

PMID33796383
PMCPMC7984799

What OpenQuestion holds

Textmetadata
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.