Evidence map›Paper›PMID 22894430›Full record

ArticleMedical physics2012

Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry.

Ioannis Sechopoulos, Kristina Bliznakova, Xulei Qin, Baowei Fei, Steve Si Jia Feng

Open access · bronzeAbstract read
In one paragraph

Article in Medical physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

25 citing papers in PubMed, 80 citations in OpenAlex.

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  16. Review
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  18. Dosimetry in x-ray-based breast imaging.Physics in medicine and biology · 2016
    Article
  19. Article
  20. Register cardiac fiber orientations from 3D DTI volume to 2D ultrasound image of rat hearts.Proceedings of SPIE--the International Society for Optical Engineering · 2015
    Article
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

5 authors at 3 institutions in 2 countries.

Ioannis SechopoulosDepartment of Radiology and Imaging Sciences and Winship Cancer Institute, Emory University School of Medicine, 1701 Upper Gate Drive Northeast, Suite 5018, Atlanta, Georgia 30322, USA. isechop@emory.edu
Kristina Bliznakova
Xulei Qin
Baowei Fei
Steve Si Jia Feng
Emory University · USGeorgia Institute of Technology · USUniversity of Patras · GR

Funding

uPAR Targeted in Vivo Molecular Magnetic Resonance Imaging of....P50CA128301 · NCI · EMORY UNIVERSITY · PI SCHUSTER, DAVID MICHAEL · 2008 to 2012
$6.8M
MOLECULAR IMAGING DIRECTED, 3D ULTRASOUND-GUIDED, BIOPSY SYSTEMR01CA156775 · NCI · UNIVERSITY OF TEXAS DALLAS · PI FEI, BAOWEI · 2011 to 2016
$1.7M
Image Quality Improvement and Breast Compression Reduction in Breast TomosynthesiR01CA163746 · NCI · RADBOUD UNIVERSITY NIJMEGEN MED CTR · PI SECHOPOULOS, IOANNIS · 2012 to 2015
$1.2M
NCI NIH HHS P50 CA128301NCI NIH HHS P50CA128301NCI NIH HHS R01 CA156775NCI NIH HHS R01CA156775NCI NIH HHS R01 CA163746NCI NIH HHS R01CA163746
6 · The paper itself

Abstract

purposeTo compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation.

methodsTwenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio-caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast CT (uncompressed breasts). For the mammography simulations the x-ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x-ray spectra were used, corresponding to the x-ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared.

resultsFor mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Test p = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution.

conclusionsThe normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x-ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x-ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further work is required to better characterize this overestimation and potentially develop new metrics or correction factors to better estimate the true glandular dose to breasts undergoing imaging with ionizing radiation.

Indexed as

BreastBreast NeoplasmsComputer SimulationFemaleHumansMammographyModels, StatisticalMonte Carlo MethodRadiation, IonizingRadiometryReproducibility of ResultsTissue DistributionTomography, X-Ray ComputedX-Rays

Identifiers

PMID22894430
PMCPMC3416880
OpenAlexW2034105142

What OpenQuestion holds

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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.