Evidence map›Paper›PMID 29183348›Full record

ArticleBreast cancer research : BCR2017

Influence of breast compression pressure on the performance of population-based mammography screening.

Katharina Holland, Ioannis Sechopoulos, Ritse M Mann, Gerard J den Heeten, Carla H van Gils, Nico Karssemeijer

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In one paragraph

Article in Breast cancer research : BCR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  15. Flat-panel conebeam CT in the clinic: history and current state.Journal of medical imaging (Bellingham, Wash.) · 2021
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  18. Characterization of the imaging settings in screening mammography using a tracking and reporting system: A multi-center and multi-vendor analysis.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2020
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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

6 authors.

Katharina HollandDepartment of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands. KHolland.rad@gmail.com.
Ioannis SechopoulosDepartment of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
Ritse M MannDepartment of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
Gerard J den HeetenDepartment of Radiology/Biomedical Engineering and Physics, Academic Medical Center Amsterdam, PO Box 22660, 1100 DD, Amsterdam, The Netherlands.
Carla H van GilsJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
Nico KarssemeijerDepartment of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.

Funding

European Union's Seventh Framework Programme FP7 306088
6 · The paper itself

Abstract

backgroundIn mammography, breast compression is applied to reduce the thickness of the breast. While it is widely accepted that firm breast compression is needed to ensure acceptable image quality, guidelines remain vague about how much compression should be applied during mammogram acquisition. A quantitative parameter indicating the desirable amount of compression is not available. Consequently, little is known about the relationship between the amount of breast compression and breast cancer detectability. The purpose of this study is to determine the effect of breast compression pressure in mammography on breast cancer screening outcomes.

methodsWe used digital image analysis methods to determine breast volume, percent dense volume, and pressure from 132,776 examinations of 57,179 women participating in the Dutch population-based biennial breast cancer screening program. Pressure was estimated by dividing the compression force by the area of the contact surface between breast and compression paddle. The data was subdivided into quintiles of pressure and the number of screen-detected cancers, interval cancers, false positives, and true negatives were determined for each group. Generalized estimating equations were used to account for correlation between examinations of the same woman and for the effect of breast density and volume when estimating sensitivity, specificity, and other performance measures. Sensitivity was computed using interval cancers occurring between two screening rounds and using interval cancers within 12 months after screening. Pair-wise testing for significant differences was performed.

resultsPercent dense volume increased with increasing pressure, while breast volume decreased. Sensitivity in quintiles with increasing pressure was 82.0%, 77.1%, 79.8%, 71.1%, and 70.8%. Sensitivity based on interval cancers within 12 months was significantly lower in the highest pressure quintile compared to the third (84.3% vs 93.9%, p = 0.034). Specificity was lower in the lowest pressure quintile (98.0%) compared to the second, third, and fourth group (98.5%, p < 0.005). Specificity of the fifth quintile was 98.4%.

conclusionResults suggest that if too much pressure is applied during mammography this may reduce sensitivity. In contrast, if pressure is low this may decrease specificity.

Indexed as

AdultAgedBreast NeoplasmsEarly Detection of CancerFemaleHumansImage Processing, Computer-AssistedMammographyMass ScreeningMiddle AgedNetherlandsPopulation SurveillanceReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityBreast cancer screeningBreast compressionMammographyPerformance measures

Identifiers

PMID29183348
PMCPMC5706300

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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.