Evidence map›Paper›PMID 36589566›Full record

ArticleBiomedical optics express2022

Model of dynamic speckle evolution for evaluating laser speckle contrast measurements of tissue dynamics.

Sharvari Zilpelwar, Edbert J Sie, Dmitry Postnov, Anderson Ichun Chen, Bernhard Zimmermann, Francesco Marsili, David A Boas, Xiaojun Cheng

Open access · goldAbstract read
In one paragraph

Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
5.2field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 49 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

8 authors at 3 institutions in 4 countries.

Sharvari ZilpelwarDepartment of Electrical and Computer Engineering, Boston University, MA 02215, USA.ORCID https://orcid.org/0000-0003-1051-6345
Edbert J SieReality Labs Research, Meta Platforms Inc., Menlo Park, CA 94025, USA.ORCID https://orcid.org/0000-0003-3477-6459
Dmitry PostnovDepartment of Clinical Medicine, Aarhus University, Aarhus 8000, Denmark.ORCID https://orcid.org/0000-0002-9708-8453
Anderson Ichun ChenNeurophotonics Center, Department of Biomedical Engineering, Boston University, MA 02215, USA.ORCID https://orcid.org/0000-0001-6110-5285
Bernhard ZimmermannNeurophotonics Center, Department of Biomedical Engineering, Boston University, MA 02215, USA.
Francesco MarsiliReality Labs Research, Meta Platforms Inc., Menlo Park, CA 94025, USA.
David A BoasDepartment of Electrical and Computer Engineering, Boston University, MA 02215, USA.
Xiaojun ChengNeurophotonics Center, Department of Biomedical Engineering, Boston University, MA 02215, USA.ORCID https://orcid.org/0000-0002-3568-0603
Boston University · USBC Platforms (Finland) · FIAarhus University · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce a dynamic speckle model (DSM) to simulate the temporal evolution of fully developed speckle patterns arising from the interference of scattered light reemitted from dynamic tissue. Using this numerical tool, the performance of laser speckle contrast imaging (LSCI) or speckle contrast optical spectroscopy (SCOS) systems which quantify tissue dynamics using the spatial contrast of the speckle patterns with a certain camera exposure time is evaluated. We have investigated noise sources arising from the fundamental speckle statistics due to the finite sampling of the speckle patterns as well as those induced by experimental measurement conditions including shot noise, camera dark and read noise, and calibrated the parameters of an analytical noise model initially developed in the fundamental or shot noise regime that quantifies the performance of SCOS systems using the number of independent observables (NIO). Our analysis is particularly focused on the low photon flux regime relevant for human brain measurements, where the impact of shot noise and camera read noise can become significant. Our numerical model is also validated experimentally using a novel fiber based SCOS (fb-SCOS) system for a dynamic sample. We have found that the signal-to-noise ratio (SNR) of fb-SCOS measurements plateaus at a camera exposure time, which marks the regime where shot and fundamental noise dominates over camera read noise. For a fixed total measurement time, there exists an optimized camera exposure time if temporal averaging is utilized to improve SNR. For a certain camera exposure time, photon flux value, and camera noise properties, there exists an optimized speckle-to-pixel size ratio (s/p) at which SNR is maximized. Our work provides the design principles for any LSCI or SCOS systems given the detected photon flux and properties of the instruments, which will guide the experimental development of a high-quality, low-cost fb-SCOS system that monitors human brain blood flow and functions.

Identifiers

PMID36589566
PMCPMC9774840
OpenAlexW4308797477

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.