Evidence map›Paper›PMID 30625429›Full record

ArticlePhysics in medicine and biology2019

Synthesizing mammogram from digital breast tomosynthesis.

Jun Wei, Heang-Ping Chan, Mark A Helvie, Marilyn A Roubidoux, Colleen H Neal, Yao Lu, Lubomir M Hadjiiski, Chuan Zhou

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

8 authors.

Jun WeiDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Heang-Ping ChanDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Mark A HelvieDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Marilyn A RoubidouxDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Colleen H NealDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Yao LuDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Lubomir M HadjiiskiDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.
Chuan ZhouDepartment of Radiology, University of Michigan, Ann Arbor, MI, United States of America.

Funding

Improvement of microcalcification detection in digital breast tomosynthesisR01CA151443 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHAN, HEANG-PING · 2011 to 2015
$3.0M
Advanced breast tomosynthesis reconstruction for improved cancer diagnosisR01CA214981 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHAN, HEANG-PING, FESSLER, JEFFREY A · 2018 to 2022
$2.3M
Quantitative Parenchyma Descriptor as an Imaging Biomarker of Breast Cancer RiskU01CA195599 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WEI, JUN · 2015 to 2019
$1.8M
NCI NIH HHS R01 CA151443NCI NIH HHS R01 CA214981NCI NIH HHS U01 CA195599
6 · The paper itself

Abstract

The purpose of this study is to develop a new method for generating synthesized mammogram (SM) from digital breast tomosynthesis (DBT) and to assess its potential as an adjunct to DBT. We first applied multiscale bilateral filtering to the reconstructed DBT slices to enhance the high-frequency features and reduce noise. A maximum intensity projection (MIP) image was then obtained from the high-frequency components of the DBT slices. A multiscale image fusion method was designed to combine the MIP image and the central DBT projection view into an SM and further enhance the high-frequency features. We conducted a pilot reader study to visually assess the image quality of SM in comparison to full field digital mammograms (FFDM). For each DBT craniocaudal or mediolateral view, a clinical FFDM of the corresponding view was retrospectively collected. Three MQSA radiologists, blinded to the pathological and other clinical information, independently interpreted the SM and the corresponding FFDM side by side marked with the lesion locations. The differences in the BI-RADS assessments of both MCs and masses between SM and FFDM did not achieve statistical significance for all three readers. The conspicuity of MCs on SM was superior to that on FFDM and the BI-RADS assessments of MCs were comparable while the conspicuity of masses on SM was degraded and interpretation on SM was less accurate than that on FFDM. The SM may be useful for efficient prescreening of MCs in DBT but the DBT should be used for detection and characterization of masses.

Indexed as

Breast NeoplasmsFemaleHumansMammographyRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedRetrospective Studies

Identifiers

PMID30625429
PMCPMC6438841

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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.