Evidence map›Paper›PMID 32991467›Full record

Observational studyMedicine2020

Evaluation of automated volumetric breast density software in comparison with visual assessments in an Asian population: A retrospective observational study.

Kartini Rahmat, Nazimah Ab Mumin, Marlina Tanty Ramli Hamid, Farhana Fadzli, Wei Lin Ng, Nadia Fareeda Muhammad Gowdh

Abstract readComparative StudyObservational Study
In one paragraph

Observational study in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

6 authors.

Kartini RahmatDepartment of Biomedical Imaging, University of Malaya Research Imaging Centre, Kuala Lumpur.
Nazimah Ab MuminDepartment of Biomedical Imaging, University of Malaya Research Imaging Centre, Kuala Lumpur.ORCID 0000-0001-8720-5700
Marlina Tanty Ramli HamidDepartment of Biomedical Imaging, University of Malaya Research Imaging Centre, Kuala Lumpur.
Farhana FadzliDepartment of Biomedical Imaging, University of Malaya Research Imaging Centre, Kuala Lumpur.
Wei Lin NgDepartment of Biomedical Imaging, University of Malaya Research Imaging Centre, Kuala Lumpur.
Nadia Fareeda Muhammad GowdhDepartment of Biomedical Imaging, University of Malaya Research Imaging Centre, Kuala Lumpur.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to compare Quantra, as an automated volumetric breast density (Vbd) tool, with visual assessment according to ACR BI-RADS density categories and to determine its potential usage in clinical practice.Five hundred randomly selected screening and diagnostic mammograms were included in this retrospective study. Three radiologists independently assigned qualitative ACR BI-RADS density categories to the mammograms. Quantra automatically calculates the volumetric density data into the system. The readers were blinded to the Quantra and other readers assessment. Inter-reader agreement and agreement between Quantra and each reader were tested. Region under the curve (ROC) analysis was performed to obtain the cut-off value to separate dense from a non-dense breast. Results with P value <.05 was taken as significant.There were 40.4% Chinese, 27% Malays, 19% Indian and 3.6% represent other ethnicities. The mean age of the patients was 57. 15%, 45.6%, 30.4%, and 9% of patients fall under BI-RADS A, B, C and D density category respectively. Fair agreement with Kappa (κ) value: 0.49, 0.38, and 0.30 were seen for Reader 1, 2 and 3 versus Quantra. Moderate agreement with κ value: 0.63, 0.64, 0.51 was seen when the data were dichotomized (density A and B to "non-dense", C and D to "dense"). The cut-off Vbd value was 13.5% to stratify dense from non-dense breasts with a sensitivity of 86.2% and specificity of 83.1% (AUC 91.4%; confidence interval: 88.8, 94.1).Quantra showed moderate agreement with radiologists visual assessment. Hence, this study adds to the available evidence to support the potential use of Quantra as an adjunct tool for breast density assessment in routine clinical practice in the Asian population. We found 13.5% is the best cut-off value to stratify dense to non-dense breasts in our study population. Its application will provide an objective, consistent and reproducible results as well as aiding clinical decision-making on the need for supplementary breast ultrasound in our screening population.

Indexed as

Breast DensitySoftwareAdultAgedAged, 80 and overAsian PeopleBreastFemaleHumansMammographyMiddle AgedRetrospective Studies

Identifiers

PMID32991467
PMCPMC7523847

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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.