Evidence map›Paper›PMID 26046722›Full record

ArticleJournal of biomedical optics2015

Estimation and imaging of breast lesions using a two-layer tissue structure by ultrasound-guided optical tomography.

Yan Xu, Quing Zhu

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Yan XuUniversity of Connecticut, Electrical and Computer Engineering Department, 371 Fairfield Road, Unit 4157, Storrs, Connecticut 06269-4157, United States.
Quing ZhuUniversity of Connecticut, Electrical and Computer Engineering Department, 371 Fairfield Road, Unit 4157, Storrs, Connecticut 06269-4157, United StatesbUniversity of Connecticut, Biomedical Engineering Department, Storrs, Connecticut 06269, United States.

Funding

Near Infrared Diffused Light Imaging with Ultrasound Guidance: Predicting Neoadjuvant Chemotherapy ResponseR01EB002136 · NIBIB · WASHINGTON UNIVERSITY · PI ZHU, QUING · 2003 to 2016
$3.4M
NIBIB NIH HHS R01 EB002136NIBIB NIH HHS R01EB002136
6 · The paper itself

Abstract

A new two-step estimation and imaging method is developed for a two-layer breast tissue structure consisting of a breast tissue layer and a chest wall underneath. First, a smaller probe with shorter distance source-detector pairs was used to collect the reflected light mainly from the breast tissue layer. Then, a larger probe with 9×14 source-detector pairs and a centrally located ultrasound transducer was used to collect reflected light from the two-layer tissue structure. The data collected from the smaller probe were used to estimate breast tissue optical properties. With more accurate estimation of the average breast tissue properties, the second layer properties can be assessed from data obtained from the larger probe. Using this approach, the unknown variables have been reduced from four to two and the estimated bulk tissue optical properties are more accurate and robust. In addition, a two-step reconstruction using a genetic algorithm and conjugate gradient method is implemented to simultaneously reconstruct the absorption and reduced scattering maps of targets inside a two-layer tissue structure. Simulations and phantom experiments have been performed to validate the new reconstruction method, and a clinical example is given to demonstrate the feasibility of this approach.

Indexed as

BreastBreast NeoplasmsFemaleHumansImage Interpretation, Computer-AssistedTomography, OpticalUltrasonography, Mammary

Identifiers

PMID26046722
PMCPMC4457415

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.