Evidence map›Paper›PMID 42595593›Full record

Observational studyUltrasound in medicine & biology2026

Volumetric Quantification of Breast Tissue Composition Using Transmission Ultrasound: A Validation Study Against MRI.

Bilal Malik, Jeon-Hor Chen, Min-Ying Su, James Wiskin, Elaine Iuanow

Registry-linked trialAbstract readComparative StudyMulticenter StudyObservational Study
In one paragraph

Observational study in Ultrasound in medicine & biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03052166 (A Prospective Multi-center Case Collection Study of Breast Imaging Examinations From Women to Evaluate the Non-inferiority of QT Ultrasound Compared to Digital Mammography-Digital Breast Tomography), which is not on this map. Not yet cited in PubMed.

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

NCT03052166 completednot on this map

A Prospective Multi-center Case Collection Study of Breast Imaging Examinations From Women to Evaluate the Non-inferiority of QT Ultrasound Compared to Digital Mammography-Digital Breast Tomography (DM-DBT)

TypeobservationalSponsorQT Ultrasound LLCRan2017 to 2020Enrolled755ConditionsBreastArmsQT Ultrasound scan
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Bilal MalikQT Imaging Holdings, Inc., Three Hamilton Landing, Novato, CA, USA. Electronic address: bilal.malik@qtimaging.com.
Jeon-Hor ChenDepartment of Radiological Sciences, Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine, CA, USA; Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung, Taiwan.
Min-Ying SuDepartment of Radiological Sciences, Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine, CA, USA.
James WiskinQT Imaging Holdings, Inc., Three Hamilton Landing, Novato, CA, USA.
Elaine IuanowQT Imaging Holdings, Inc., Three Hamilton Landing, Novato, CA, USA.

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Melanie Funes · 1994 to 2026
$57.9M
NCI NIH HHS P30 CA062203
6 · The paper itself

Abstract

RATIONALE AND

objectivesAccurate quantification of fibroglandular tissue volume (FGV) and the fibroglandular ratio which is the ratio of FGV to the total breast volume (TBV) (FGR = FGV/TBV) is critical for assessment of a patient's lifetime breast cancer risk and personalized screening strategies. Magnetic resonance imaging (MRI) is considered the research standard for volumetric breast composition analysis but is limited by cost, availability, and contraindications. This study evaluates the capability of quantitative transmission (QT) imaging technology to measure FGV and FGR and compares these results with MRI-derived metrics, establishing quantitative equivalence between the two modalities. MATERIALS AND

methodsA retrospective analysis included 53 breasts from 29 women imaged using QT scan and MRI within 30 days as part of the ACCRUE Study (ClinicalTrials.gov NCT03052166). QT data were acquired with the QT Scanner 2000 Model A and reconstructed into 3D speed-of-sound maps and respective reflection maps via a full-wave inverse scattering algorithm. FGV and FGR were computed using a fuzzy c-means segmentation as applied to the quantitative tissue maps. MRI datasets were segmented using a validated template-based method. Statistical comparisons included Pearson correlation (r), intraclass correlation coefficient (ICC), and Bland-Altman analysis.

resultsQT and MRI measurements demonstrated strong correlations for both FGV (r = 0.893) and FGR (r = 0.915, p < 0.0001). Mean biases were -13.2 cm³ for FGV and +12.7% for FGR. Regression slopes were 0.63 and 1.35, respectively, with significant proportional bias for both (p < 0.0001). Systematic differences were consistent with modality-specific contrast mechanisms and field-of-view definitions; the strong correlation and stable, predictable bias support quantitative concordance between the modalities.

conclusionQT technology provides accurate, reproducible, and volumetric quantification of breast fibroglandular tissue, demonstrating strong concordance with MRI. These results supported FDA clearance of the QT FGR feature, establishing it as a validated quantitative imaging biomarker for clinical breast density assessment.

Indexed as

BreastMagnetic Resonance ImagingUltrasonography, MammaryAdultAgedBreast NeoplasmsFemaleHumansMiddle AgedOrgan SizeReproducibility of ResultsRetrospective StudiesBreast densityBreast MRI comparisonFibroglandular tissueQuantitative imagingTransmission ultrasound

Identifiers

PMID42595593
PMCPMC13614700

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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.