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

    loading  Checking for direct PDF access through Ovid

Abstract

Purpose:

To design volume-specific breast phantoms from breast CT (bCT) data sets and estimate the associated normalized mean glandular dose coefficients for breast CT using Monte Carlo methods.

Methods:

A large cohort of bCT data sets (N = 215) was used to evaluate breast volume into quintiles (plus the top 5%). The average radius profile was then determined for each of the six volume-specific groups and used to both fabricate physical phantoms and generate mathematical phantoms (V1-V6; “V” denotes classification by volume). The MCNP6 Monte Carlo code was used to model a prototype bCT system fabricated at our institution; and this model was validated against physical measurements in the fabricated phantoms. The mathematical phantoms were used to simulate normalized mean glandular dose coefficients for both monoenergetic source photons “DgNCT(E)” (8–70 keV in 1 keV intervals) and polyenergetic x-ray beams “pDgNCT” (35–70 kV in 1 kV intervals). The Monte Carlo code was used to study the influence of breast size (V1 vs. V5) and glandular fraction (6.4% vs. 45.8%) on glandular dose. The pDgNCT coefficients estimated for the V1, V3, and V5 phantoms were also compared to those generated using simple, cylindrical phantoms with equivalent volume and two geometrical constraints including; (a) cylinder radius determined at the breast phantom chest wall “Rcw”; and (b) cylinder radius determined at the breast phantom center-of-mass “RCOM”.

Results:

Satisfactory agreement was observed for dose estimations using MCNP6 compared with both physical measurements in the V1, V3, and V5 phantoms (R2 = 0.995) and reference bCT dose coefficients using simple phantoms (R2 = 0.999). For a 49 kV spectrum with 1.5 mm Al filtration, differences in glandular fraction [6.5% (5th percentile) vs. 45.8% (95th percentile)] had a 13.2% influence on pDgNCT for the V3 phantom, and differences in breast size (V1 vs. V5) had a 16.6% influence on pDgNCT for a breast composed of 17% (median) fibroglandular tissue. For cylindrical phantoms with a radius of RCOM, the differences were 1.5%, 0.1%, and 2.1% compared with the V1, V3, and V5 phantoms, respectively.

Conclusion:

Breast phantoms were designed using a large cohort of bCT data sets across a range of six breast sizes. These phantoms were then fabricated and used for the estimation of glandular dose in breast CT. The mathematical phantoms and associated glandular dose coefficients for a range of breast sizes (V1–V6) and glandular fractions (5th to 95th percentiles) are available for interested users.

Related Topics

    loading  Loading Related Articles