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Quantitative imaging in breast tomosynthesis and CT: Comparison of detection and estimation task performance.

Publication ,  Journal Article
Richard, S; Samei, E
Published in: Med Phys
June 2010

PURPOSE: This work investigates a framework for modeling volumetric breast imaging to compare detection and estimation task performance and optimize quantitative breast imaging. METHODS: Volumetric reconstructions of a breast phantom, which incorporated electronic, quantum, and anatomical noise with embedded spherical lesions, were simulated over a range of acquisition angles varying from 4° to 204° with a constant total acquisition dose of 1.5 mGy. A maximum likelihood estimator was derived in terms of the noise power spectrum, which yielded figures of merit for quantitative imaging performance in terms of accuracy and precision. These metrics were computed for estimation of lesion area, volume, and location. Estimation task performance was optimized as a function of acquisition angle and compared to the performance of a more conventional lesion detection task. RESULTS: Results revealed tradeoffs between electronic, quantum, and anatomical noise. The detection of a 4 mm sphere was optimal at an acquisition angle of 84°, where reconstructed images using a smaller acquisition angle exhibited increased anatomical noise and reconstructed images using a larger acquisition angle exhibited increased quantum and electronic noise. For all estimation tasks, accuracy was found to be fairly constant as a function acquisition angle indicating adequate system calibration, whereas a more significant dependence on acquisition angle was observed for precision performance. Precision for the 2D area estimation task was optimal at ∼104°, while precision of the 3D volume estimation task was optimal at larger angles (∼124°). Precision for the localization task showed orientation dependence where localization was significantly inferior in the depth direction. Overall, precision for localization was optimal at larger angles (i.e., >125°) compared to the size estimation tasks. Results suggested that for quantitative imaging tasks, the acquisition angle should be larger than currently used in conventional breast tomosynthesis for lesion detection. CONCLUSIONS: Analysis of quantitative imaging performance using Fourier-based metrics highlights the difference between estimation and detection task in volumetric breast imaging and provides a meaningful framework for optimizing the performance of breast imaging systems for quantitative imaging applications.

Duke Scholars

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

June 2010

Volume

37

Issue

6Part1

Start / End Page

2627 / 2637

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Phantoms, Imaging
  • Pattern Recognition, Automated
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Humans
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Richard, S., & Samei, E. (2010). Quantitative imaging in breast tomosynthesis and CT: Comparison of detection and estimation task performance. Med Phys, 37(6Part1), 2627–2637. https://doi.org/10.1118/1.3429025
Richard, Samuel, and Ehsan Samei. “Quantitative imaging in breast tomosynthesis and CT: Comparison of detection and estimation task performance.Med Phys 37, no. 6Part1 (June 2010): 2627–37. https://doi.org/10.1118/1.3429025.
Richard, Samuel, and Ehsan Samei. “Quantitative imaging in breast tomosynthesis and CT: Comparison of detection and estimation task performance.Med Phys, vol. 37, no. 6Part1, June 2010, pp. 2627–37. Pubmed, doi:10.1118/1.3429025.

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

June 2010

Volume

37

Issue

6Part1

Start / End Page

2627 / 2637

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Phantoms, Imaging
  • Pattern Recognition, Automated
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Humans