Literature DB >> 20175478

Compositional breast imaging using a dual-energy mammography protocol.

Aurelie D Laidevant1, Serghei Malkov, Chris I Flowers, Karla Kerlikowske, John A Shepherd.   

Abstract

PURPOSE: Mammography has a low sensitivity in dense breasts due to low contrast between malignant and normal tissue confounded by the predominant water density of the breast. Water is found in both adipose and fibroglandular tissue and constitutes most of the mass of a breast. However, significant protein mass is mainly found in the fibroglandular tissue where most cancers originate. If the protein compartment in a mammogram could be imaged without the influence of water, the sensitivity and specificity of the mammogram may be improved. This article describes a novel approach to dual-energy mammography, full-field digital compositional mammography (FFDCM), which can independently image the three compositional components of breast tissue: water, lipid, and protein.
METHODS: Dual-energy attenuation and breast shape measures are used together to solve for the three compositional thicknesses. Dual-energy measurements were performed on breast-mimicking phantoms using a full-field digital mammography unit. The phantoms were made of materials shown to have similar x-ray attenuation properties of the compositional compartments. They were made of two main stacks of thicknesses around 2 and 4 cm. Twenty-six thickness and composition combinations were used to derive the compositional calibration using a least-squares fitting approach.
RESULTS: Very high accuracy was achieved with a simple cubic fitting function with root mean square errors of 0.023, 0.011, and 0.012 cm for the water, lipid, and protein thicknesses, respectively. The repeatability (percent coefficient of variation) of these measures was tested using sequential images and was found to be 0.5%, 0.5%, and 3.3% for water, lipid, and protein, respectively. However, swapping the location of the two stacks of the phantom on the imaging plate introduced further errors showing the need for more complete system uniformity corrections. Finally, a preliminary breast image is presented of each of the compositional compartments separately.
CONCLUSIONS: FFDCM has been derived and exhibited good compositional thickness accuracy on phantoms. Preliminary breast images demonstrated the feasibility of creating individual compositional diagnostic images in a clinical environment.

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Mesh:

Year:  2010        PMID: 20175478      PMCID: PMC2801735          DOI: 10.1118/1.3259715

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  46 in total

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Authors:  John A Shepherd; Karla M Kerlikowske; Rebecca Smith-Bindman; Harry K Genant; Steve R Cummings
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2.  Dual-energy X-ray absorptiometry: analysis of pediatric fat estimate errors due to tissue hydration effects.

Authors:  C G Testolin; R Gore; T Rivkin; M Horlick; J Arbo; Z Wang; G Chiumello; S B Heymsfield
Journal:  J Appl Physiol (1985)       Date:  2000-12

3.  Tissue analysis using dual energy CT.

Authors:  G J Michael
Journal:  Australas Phys Eng Sci Med       Date:  1992-03       Impact factor: 1.430

4.  The five-level model: a new approach to organizing body-composition research.

Authors:  Z M Wang; R N Pierson; S B Heymsfield
Journal:  Am J Clin Nutr       Date:  1992-07       Impact factor: 7.045

5.  An algorithm for noise suppression in dual energy CT material density images.

Authors:  W A Kalender; E Klotz; L Kostaridou
Journal:  IEEE Trans Med Imaging       Date:  1988       Impact factor: 10.048

6.  Bone density in young women is associated with body weight and muscle strength but not dietary intakes.

Authors:  N K Henderson; R I Price; J H Cole; D H Gutteridge; C I Bhagat
Journal:  J Bone Miner Res       Date:  1995-03       Impact factor: 6.741

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Authors:  L A Lehmann; R E Alvarez; A Macovski; W R Brody; N J Pelc; S J Riederer; A L Hall
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8.  The composition of body tissues.

Authors:  H Q Woodard; D R White
Journal:  Br J Radiol       Date:  1986-12       Impact factor: 3.039

9.  Chemical and elemental analysis of humans in vivo using improved body composition models.

Authors:  S B Heymsfield; M Waki; J Kehayias; S Lichtman; F A Dilmanian; Y Kamen; J Wang; R N Pierson
Journal:  Am J Physiol       Date:  1991-08

10.  Monte Carlo modelling of an extended DXA technique.

Authors:  G J Michael; C J Henderson
Journal:  Phys Med Biol       Date:  1998-09       Impact factor: 3.609

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  21 in total

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2.  Measurement of breast tissue composition with dual energy cone-beam computed tomography: a postmortem study.

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3.  Impact of positional difference on the measurement of breast density using MRI.

Authors:  Jeon-Hor Chen; Siwa Chan; Yi-Ting Tang; Jia Shen Hon; Po-Chuan Tseng; Angela T Cheriyan; Nikita Rakesh Shah; Dah-Cherng Yeh; San-Kan Lee; Wen-Pin Chen; Christine E McLaren; Min-Ying Su
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4.  Combined Benefit of Quantitative Three-Compartment Breast Image Analysis and Mammography Radiomics in the Classification of Breast Masses in a Clinical Data Set.

Authors:  Karen Drukker; Maryellen L Giger; Bonnie N Joe; Karla Kerlikowske; Heather Greenwood; Jennifer S Drukteinis; Bethany Niell; Bo Fan; Serghei Malkov; Jesus Avila; Leila Kazemi; John Shepherd
Journal:  Radiology       Date:  2018-12-11       Impact factor: 11.105

5.  Tight-frame based iterative image reconstruction for spectral breast CT.

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6.  Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system.

Authors:  Huanjun Ding; Justin L Ducote; Sabee Molloi
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7.  Statistical image-domain multimaterial decomposition for dual-energy CT.

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8.  Postmortem validation of breast density using dual-energy mammography.

Authors:  Sabee Molloi; Justin L Ducote; Huanjun Ding; Stephen A Feig
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9.  Breast tissue characterization with photon-counting spectral CT imaging: a postmortem breast study.

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10.  Multi-material decomposition using statistical image reconstruction for spectral CT.

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Journal:  IEEE Trans Med Imaging       Date:  2014-04-25       Impact factor: 10.048

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