Evidence map›Paper›PMID 33452822›Full record

ArticleMedical physics2021

Fibroglandular tissue distribution in the breast during mammography and tomosynthesis based on breast CT data: A patient-based characterization of the breast parenchyma.

Christian Fedon, Marco Caballo, Eloy García, Oliver Diaz, John M Boone, David R Dance, Ioannis Sechopoulos

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Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Christian FedonDepartment of Medical Imaging, Radboud University Medical Center, 6500 HB Geert Grooteplein-Zuid, Nijmegen, The Netherlands.
Marco CaballoDepartment of Medical Imaging, Radboud University Medical Center, 6500 HB Geert Grooteplein-Zuid, Nijmegen, The Netherlands.
Eloy GarcíaVall d' Hebron Institute of Oncology (VHIO), Barcelona, Spain.
Oliver DiazDepartment of Mathematics and Computer Science, University of Barcelona, Barcelona, Spain.
John M BooneDepartment of Radiology and Biomedical Engineering, University of California Davis Health, 4860 "Y" Street, suite 3100 Ellison building, Sacramento, CA, 95817, USA.
David R DanceNational Co-ordinating Centre for the Physics of Mammography, NCCPM, Royal Surrey County Hospital, Guildford, GU2 7XH, UK.
Ioannis SechopoulosDepartment of Medical Imaging, Radboud University Medical Center, 6500 HB Geert Grooteplein-Zuid, Nijmegen, The Netherlands.

Funding

Breast CT: Final Steps to TranslationR01CA181081 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI BOONE, JOHN M · 2015 to 2019
$2.9M
Image Quality Improvement and Performance Assessment of Dedicated Breast CTR01CA181171 · NCI · STICHTING RADBOUD UNIVERSITAIR MEDISCH CENTRUM I.O. · PI SECHOPOULOS, IOANNIS · 2015 to 2020
$1.1M
HHS | NIH | National Cancer Institute (NCI) R01CA181171NCI NIH HHS R01 CA181081NCI NIH HHS R01 CA181171Susan G. Komen Foundation for the Cure IIR13262248
6 · The paper itself

Abstract

purposeTo develop a patient-based breast density model by characterizing the fibroglandular tissue distribution in patient breasts during compression for mammography and digital breast tomosynthesis (DBT) imaging.

methodsIn this prospective study, 88 breast images were acquired using a dedicated breast computed tomography (CT) system. The breasts in the images were classified into their three main tissue components and mechanically compressed to mimic the positioning for mammographic acquisition of the craniocaudal (CC) and mediolateral oblique (MLO) views. The resulting fibroglandular tissue distribution during these compressions was characterized by dividing the compressed breast volume into small regions, for which the median and the 25th and 75th percentile values of local fibroglandular density were obtained in the axial, coronal, and sagittal directions. The best fitting function, based on the likelihood method, for the median distribution was obtained in each direction.

resultsThe fibroglandular tissue tends to concentrate toward the caudal (about 15% below the midline of the breast) and anterior regions of the breast, in both the CC- and MLO-view compressions. A symmetrical distribution was found in the MLO direction in the case of the CC-view compression, while a shift of about 12% toward the lateral direction was found in the MLO-view case.

conclusionsThe location of the fibroglandular tissue in the breast under compression during mammography and DBT image acquisition is a major factor for determining the actual glandular dose imparted during these examinations. A more realistic model of the parenchyma in the compressed breast, based on patient image data, was developed. This improved model more accurately reflects the fibroglandular tissue spatial distribution that can be found in patient breasts, and therefore might aid in future studies involving radiation dose and/or cancer development risk estimation.

Indexed as

Breast NeoplasmsMammographyBreastHumansProspective StudiesTissue DistributionTomography, X-Ray Computedbreast cancer riskbreast imagingcompressed breastdosimetryfibroglandular tissue

Identifiers

PMID33452822
PMCPMC7986202

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