Quantitative Molecular Imaging of Breast Microcalcification Composition using Photon-Counting Spectral Computed Tomography Article Swipe
Tyler E. Curtis
,
Ryan K. Roeder
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.09.16.300509
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.09.16.300509
Mammographic screening for breast cancer is unable to distinguish molecular differences between hydroxyapatite (HA) microcalcifications (μcals) that are associated with malignancy and calcium oxalate (CaOx) μcals that are benign. Therefore, the objective of this study was to investigate quantitative material decomposition of model breast μcals of clinically-relevant composition and size using spectral photon-counting computed tomography (PCCT). Model μcals composed of HA, CaOx, and dicalcium phosphate (DCP) were treated as materials containing spatially coincident elemental compositions of calcium (Ca), phosphorus (P), and oxygen (O). Elemental decomposition was performed using constrained maximum-likelihood estimation in the image domain. Images were acquired with a commercial, preclinical PCCT system (MARS Bioimaging) with five energy bins selected to maximize counts at low photon energies and spectral differences between Ca and P. Elemental concentrations of Ca and P within the each μcal composition were accurately identified and quantified with a root-mean-squared error < 12%. HA and CaOx μcals, < 1 mm is size, were accurately discriminated by the measured P content with an area under the receiver operating characteristic curve (AUC) > 0.9. The mole fraction of P, P/(Ca+P), was able to discriminate all three μcal compositions with AUC > 0.8 for μcals < 1 mm is size and AUC = 1 for μcals > 2 mm in size. The overall accuracy for the classification of μcal types and quantification of P was robust against different assumptions in the elemental decomposition calibration, but quantification of Ca was improved with assumptions that most accurately accounted for the molar volume of each element within μcal compositions. Thus, PCCT enabled quantitative molecular imaging of breast μcal composition, which is not possible with current clinical molecular imaging modalities.
Related Topics
Concepts
Elemental analysis
Calcium oxalate
Computed tomography
Microcalcification
Nuclear medicine
Decomposition
Computed radiography
Materials science
Radiodensity
Biomedical engineering
Mammography
Analytical Chemistry (journal)
Medicine
Radiology
Chemistry
Calcium
Radiography
Breast cancer
Chromatography
Image quality
Cancer
Computer science
Artificial intelligence
Internal medicine
Image (mathematics)
Metallurgy
Organic chemistry
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2020.09.16.300509
- https://www.biorxiv.org/content/biorxiv/early/2020/09/18/2020.09.16.300509.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3087659707
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3087659707Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2020.09.16.300509Digital Object Identifier
- Title
-
Quantitative Molecular Imaging of Breast Microcalcification Composition using Photon-Counting Spectral Computed TomographyWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-18Full publication date if available
- Authors
-
Tyler E. Curtis, Ryan K. RoederList of authors in order
- Landing page
-
https://doi.org/10.1101/2020.09.16.300509Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2020/09/18/2020.09.16.300509.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2020/09/18/2020.09.16.300509.full.pdfDirect OA link when available
- Concepts
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Elemental analysis, Calcium oxalate, Computed tomography, Microcalcification, Nuclear medicine, Decomposition, Computed radiography, Materials science, Radiodensity, Biomedical engineering, Mammography, Analytical Chemistry (journal), Medicine, Radiology, Chemistry, Calcium, Radiography, Breast cancer, Chromatography, Image quality, Cancer, Computer science, Artificial intelligence, Internal medicine, Image (mathematics), Metallurgy, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2022: 1Per-year citation counts (last 5 years)
- References (count)
-
46Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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