Evidence map›Paper›PMID 41404593›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2025

Soft-tissue lesion and microcalcification detectability in cone-beam breast CT: cascaded system analysis.

Thomas Larsen, Hsin Wu Tseng, Jing-Tzyh Alan Chiang, Srinivasan Vedantham

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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

4 authors.

Thomas LarsenUniversity of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States.
Hsin Wu TsengUniversity of Arizona, Department of Radiology & Imaging Sciences, Tucson, Arizona, United States.
Jing-Tzyh Alan ChiangUniversity of Arizona, Department of Radiology & Imaging Sciences, Tucson, Arizona, United States.
Srinivasan VedanthamUniversity of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States.ORCID https://orcid.org/0000-0003-4123-8392

Funding

Towards screening with high-resolution, low-dose, dedicated breast CTR01CA199044 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SRINIVASAN VEDANTHAM · 2016 to 2026
$6.1M
Upright, Low-dose, High-resolution, 3D Breast CTR01CA241709 · NCI · UNIVERSITY OF ARIZONA · PI VEDANTHAM, SRINIVASAN · 2019 to 2023
$3.6M
NCI NIH HHS R01 CA199044NCI NIH HHS R01 CA241709
6 · The paper itself

Abstract

Purpose: We aim to investigate the performance of dedicated breast computed tomography (CT) for the detection of soft-tissue lesions and compare it to the detection of microcalcification clusters using cascaded systems analysis, with the intent of identifying which lesion type should be used for system optimization. Approach: Signal and noise were propagated through the imaging chain using a cascaded systems model to obtain the modulation transfer function and noise power spectrum. Two imaging tasks were considered: a soft-tissue mass lesion modeled as a disk of 4 mm diameter and a cluster of microcalcifications modeled as calcium carbonate spheres of Results: Detectability index trends are reversed between soft-tissue lesion and microcalcification cluster for the range of X-ray tube voltages and filtrations studied, indicating a potential need for compromise. However, for each of the 150 combinations studied (6 kV settings Conclusion: When the lesion type is unknown, such as during breast cancer screening, it is more appropriate to optimize the system parameters for the task of detecting a microcalcification cluster, as the detectability index for the soft-tissue lesion exceeded that for the microcalcification cluster for all conditions investigated.

Indexed as

breast cancerbreast CTcascaded systemsdetectability indexnumerical observers

Identifiers

PMID41404593
PMCPMC12704369

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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.