Literature DB >> 32233091

Effects of kV, filtration, dose, and object size on soft tissue and iodine contrast in dedicated breast CT.

Andrew M Hernandez1, Craig K Abbey2, Peymon Ghazi3, George Burkett1, John M Boone1,4.   

Abstract

PURPOSE: Clinical use of dedicated breast computed tomography (bCT) requires relatively short scan times necessitating systems with high frame rates. This in turn impacts the x-ray tube operating range. We characterize the effects of tube voltage, beam filtration, dose, and object size on contrast and noise properties related to soft tissue and iodine contrast agents as a way to optimize imaging protocols for soft tissue and iodine contrast at high frame rates.
METHODS: This study design uses the signal-difference-to-noise ratio (SDNR), noise-equivalent quanta (NEQ), and detectability (d´) as measures of imaging performance for a prototype breast CT scanner that utilizes a pulsed x-ray tube (with a 4 ms pulse width) at 43.5 fps acquisition rate. We assess a range of kV, filtration, breast phantom size, and mean glandular dose (MGD). Performance measures are estimated from images of adipose-equivalent breast phantoms machined to have a representative size and shape of small, medium, and large breasts. Water (glandular tissue equivalent) and iodine contrast (5 mg/ml) were used to fill two cylindrical wells in the phantoms.
RESULTS: Air kerma levels required for obtaining an MGD of 6 mGy ranged from 7.1 to 9.1 mGy and are reported across all kV, filtration, and breast phantom sizes. However, at 50 kV, the thick filters (0.3 mm of Cu or Gd) exceeded the maximum available mA of the x-ray generator, and hence, these conditions were excluded from subsequent analysis. There was a strong positive association between measurements of SDNR and d' (R2  > 0.97) within the range of parameters investigated in this work. A significant decrease in soft tissue SDNR was observed for increasing phantom size and increasing kV with a maximum SDNR at 50 kV with 0.2 mm Cu or 0.2 mm Gd filtration. For iodine contrast SDNR, a significant decrease was observed with increasing phantom size, but a decrease in SDNR for increasing kV was only observed for 70 kV (50 and 60 kV were not significantly different). Thicker Gd filtration (0.3 mm Gd) resulted in a significant increase in iodine SDNR and decrease in soft tissue SDNR but requires significantly more tube current to deliver the same MGD.
CONCLUSIONS: The choice of 60 kV with 0.2 mm Gd filtration provides a good trade-off for maximizing both soft tissue and iodine contrast. This scanning technique takes advantage of the ~50 keV Gd k-edge to produce contrast and can be achieved within operating range of the x-ray generator used in this work. Imaging at 60 kV allows for a greater range in dose delivered to the large breast sizes when uniform image quality is desired across all breast sizes. While imaging performance metrics (i.e., detectability index and SDNR) were shown to be strongly correlated, the methodologies presented in this work for the estimation of NEQ (and subsequently d') provides a meaningful description of the spatial resolution and noise characteristics of this prototype bCT system across a range of beam quality, dose, and object sizes.
© 2020 American Association of Physicists in Medicine.

Entities:  

Keywords:  MTF; NPS; breast CT; iodine contrast; spectral optimization; x-ray imaging

Mesh:

Substances:

Year:  2020        PMID: 32233091      PMCID: PMC7771224          DOI: 10.1002/mp.14159

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


  36 in total

1.  Dedicated breast CT: radiation dose and image quality evaluation.

Authors:  J M Boone; T R Nelson; K K Lindfors; J A Seibert
Journal:  Radiology       Date:  2001-12       Impact factor: 11.105

2.  Cone-beam CT for breast imaging: Radiation dose, breast coverage, and image quality.

Authors:  Avice O'Connell; David L Conover; Yan Zhang; Posy Seifert; Wende Logan-Young; Chuen-Fu Linda Lin; Lawrence Sahler; Ruola Ning
Journal:  AJR Am J Roentgenol       Date:  2010-08       Impact factor: 3.959

3.  Evaluating the impact of X-ray spectral shape on image quality in flat-panel CT breast imaging.

Authors:  Stephen J Glick; Samta Thacker; Xing Gong; Bob Liu
Journal:  Med Phys       Date:  2007-01       Impact factor: 4.071

4.  Average glandular dose coefficients for pendant-geometry breast CT using realistic breast phantoms.

Authors:  Andrew M Hernandez; John M Boone
Journal:  Med Phys       Date:  2017-08-20       Impact factor: 4.071

5.  Cascaded systems analysis of the 3D noise transfer characteristics of flat-panel cone-beam CT.

Authors:  Daniel J Tward; Jeffrey H Siewerdsen
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

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

Authors:  Ioannis Sechopoulos; Kristina Bliznakova; Xulei Qin; Baowei Fei; Steve Si Jia Feng
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

7.  X-ray characterisation of normal and neoplastic breast tissues.

Authors:  P C Johns; M J Yaffe
Journal:  Phys Med Biol       Date:  1987-06       Impact factor: 3.609

8.  Low-Dose Contrast-Enhanced Breast CT Using Spectral Shaping Filters: An Experimental Study.

Authors:  Andrey Makeev; Stephen J Glick
Journal:  IEEE Trans Med Imaging       Date:  2017-08-02       Impact factor: 10.048

9.  Generation and analysis of clinically relevant breast imaging x-ray spectra.

Authors:  Andrew M Hernandez; J Anthony Seibert; Anita Nosratieh; John M Boone
Journal:  Med Phys       Date:  2017-05-04       Impact factor: 4.071

10.  Practical considerations for noise power spectra estimation for clinical CT scanners.

Authors:  Steven Dolly; Hsin-Chen Chen; Mark Anastasio; Sasa Mutic; Hua Li
Journal:  J Appl Clin Med Phys       Date:  2016-05-08       Impact factor: 2.102

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  4 in total

1.  Cone-beam breast CT using an offset detector: effect of detector offset and image reconstruction algorithm.

Authors:  Hsin Wu Tseng; Andrew Karellas; Srinivasan Vedantham
Journal:  Phys Med Biol       Date:  2022-04-07       Impact factor: 4.174

2.  Sparse-view, short-scan, dedicated cone-beam breast computed tomography: image quality assessment.

Authors:  Hsin Wu Tseng; Andrew Karellas; Srinivasan Vedantham
Journal:  Biomed Phys Eng Express       Date:  2020-09-28

3.  Computer-aided diagnosis of masses in breast computed tomography imaging: deep learning model with combined handcrafted and convolutional radiomic features.

Authors:  Marco Caballo; Andrew M Hernandez; Su Hyun Lyu; Jonas Teuwen; Ritse M Mann; Bram van Ginneken; John M Boone; Ioannis Sechopoulos
Journal:  J Med Imaging (Bellingham)       Date:  2021-03-29

4.  High-resolution μ CT imaging for characterizing microcalcification detection performance in breast CT.

Authors:  Andrew M Hernandez; Amy E Becker; Su Hyun Lyu; Craig K Abbey; John M Boone
Journal:  J Med Imaging (Bellingham)       Date:  2021-07-20
  4 in total

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