Evidence map›Paper›PMID 36187237›Full record

ArticleBiomedical optics express2022

Comparison of contrast-to-noise ratios of different detection methods in ultrasound optical tomography.

Alexander Bengtsson, David Hill, Kevin Shortiss, Lars Rippe, Stefan Kröll

Registry-linked trialAbstract 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. It is linked to trial NCT07754500 (Measurement and Imaging Capability of a Novel Medical Imaging Method, Ultrasound Optical Tomography, Based on Ultrasound and Laser Light in Human Tissue), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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.

NCT07754500 narecruitingnot on this mapstarted 2025, after this paper: background citation

Measurement and Imaging Capability of a Novel Medical Imaging Method, Ultrasound Optical Tomography, Based on Ultrasound and Laser Light in Human Tissue

TypeinterventionalSponsorLund UniversityRan2025 to 2027Enrolled60ConditionsHealthy Tissue, Muscles, Extremity, BreastArmsMk1
3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. 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.

Alexander BengtssonLund University, Atomic Physics Division, Department of Physics, Professorsgatan 1, Lund, 22363, Sweden.ORCID https://orcid.org/0000-0003-2736-9281
David HillLund University, Atomic Physics Division, Department of Physics, Professorsgatan 1, Lund, 22363, Sweden.
Kevin ShortissLund University, Atomic Physics Division, Department of Physics, Professorsgatan 1, Lund, 22363, Sweden.ORCID https://orcid.org/0000-0002-5249-7034
Lars RippeLund University, Atomic Physics Division, Department of Physics, Professorsgatan 1, Lund, 22363, Sweden.
Stefan KröllLund University, Atomic Physics Division, Department of Physics, Professorsgatan 1, Lund, 22363, Sweden.ORCID https://orcid.org/0000-0002-4988-1481

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound optical tomography (UOT) is a hybrid imaging modality based on interaction between ultrasound and light, with a potential to extend optical imaging capabilities in biological tissues to depths of several centimeters. Several methods have been developed to detect the UOT signal. To better understand their potential for deep tissue imaging, we present a theoretical contrast-to-noise comparison between the spectral hole burning, single-shot off-axis holography, speckle contrast, and photorefractive detection methods for UOT. Our results indicate that spectral hole burning filters have the potential to reach the largest imaging depths. We find that digital off-axis holography and photorefractive detection can have good contrast-to-noise ratio at significant depths. The speckle contrast method has a smaller penetration depth comparatively.

Identifiers

PMID36187237
PMCPMC9484419

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Registered trials

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.