Evidence map›Paper›PMID 40423003›Full record

ArticleJournal of imaging2025

Quantitative Ultrasound Texture Analysis of Breast Tumors: A Comparison of a Cart-Based and a Wireless Ultrasound Scanner.

David Alberico, Lakshmanan Sannachi, Maria Lourdes Anzola Pena, Joyce Yip, Laurentius O Osapoetra, Schontal Halstead, Daniel DiCenzo, Sonal Gandhi, Frances Wright, Michael Oelze and 1 more

Abstract read
In one paragraph

Article in Journal of imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

David AlbericoPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.
Lakshmanan SannachiPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.
Maria Lourdes Anzola PenaPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.ORCID 0009-0000-5588-9730
Joyce YipPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.
Laurentius O OsapoetraPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.
Schontal HalsteadPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.
Daniel DiCenzoPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.ORCID 0000-0003-4721-9627
Sonal GandhiDivision of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON M4N 0A4, Canada.ORCID 0000-0001-8993-1327
Frances WrightDepartment of Surgical Oncology, Department of Surgery, Sunnybrook Health Sciences Centre, Toronto, ON M4N 0A4, Canada.
Michael OelzeDepartment of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Champaign, IL 61801, USA.ORCID 0000-0002-3099-7425
Gregory J CzarnotaPhysical Sciences, Sunnybrook Research Institute, Toronto, ON M4N 0A4, Canada.

Funding

Developing a quantitative ultrasound breast scanner for identifying early response of breast cancer to chemotherapyR01CA273700 · NCI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Gregory Jan Czarnota, Michael L. Oelze · 2022 to 2026
$2.5M
Use of Radiological Clips for Improving Quantitative Ultrasound ImagingR01CA251939 · NCI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI OELZE, MICHAEL L. · 2020 to 2024
$2.0M
National Institute of Health 1R01CA273700-01NCI NIH HHS R01 CA251939NCI NIH HHS R01 CA273700
6 · The paper itself

Abstract

Previous work has demonstrated quantitative ultrasound (QUS) analysis techniques for extracting features and texture features from ultrasound radiofrequency data which can be used to distinguish between benign and malignant breast masses. It is desirable that there be good agreement between estimates of such features acquired using different ultrasound devices. Handheld ultrasound imaging systems are of particular interest as they are compact, relatively inexpensive, and highly portable. This study investigated the agreement between QUS parameters and texture features estimated from clinical ultrasound images of breast tumors acquired using two different ultrasound scanners: a traditional cart-based system and a wireless handheld ultrasound system. The 28 patients who participated were divided into two groups (benign and malignant). The reference phantom technique was used to produce functional estimates of the normalized power spectra and backscatter coefficient for each image. Root mean square differences of feature estimates were calculated for each cohort to quantify the level of feature variation attributable to tissue heterogeneity and differences in system imaging parameters. Cross-system statistical testing using the Mann-Whitney U test was performed on benign and malignant patient cohorts to assess the level of feature estimate agreement between systems, and the Bland-Altman method was employed to assess feature sets for systematic bias introduced by differences in imaging method. The range of

Indexed as

breast cancerquantitative ultrasoundtexture analysiswireless ultrasound

Identifiers

PMID40423003
PMCPMC12112010

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Registered trials

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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.