Digital breast tomosynthesis guided near infrared spectroscopy: volumetric estimates of fibroglandular fraction and breast density from tomosynthesis reconstructions

Abstract

A multimodality system combining a clinical prototype digital breast tomosynthesis with its imaging geometry modified to facilitate near-infrared spectroscopic imaging has been developed. The accuracy of parameters recovered from near-infrared spectroscopy is dependent on fibroglandular tissue content. Hence, in this study, volumetric estimates of fibroglandular tissue from tomosynthesis reconstructions were determined. A kernel-based fuzzy c-means algorithm was implemented to segment tomosynthesis reconstructed slices in order to estimate fibroglandular content and to provide anatomic priors for near-infrared spectroscopy. This algorithm was used to determine volumetric breast density (VBD), defined as the ratio of fibroglandular tissue volume to the total breast volume, expressed as percentage, from 62 tomosynthesis reconstructions of 34 study participants. For a subset of study participants who subsequently underwent mammography, VBD from mammography matched for subject, breast laterality and mammographic view was quantified using commercial software and statistically analyzed to determine if it differed from tomosynthesis. Summary statistics of the VBD from all study participants were compared with prior independent studies. The fibroglandular volume from tomosynthesis and mammography were not statistically different (p=0.211, paired t-test). After accounting for the compressed breast thickness, which were different between tomosynthesis and mammography, the VBD from tomosynthesis was correlated with (r =0.809, p<0.001), did not statistically differ from (p>0.99, paired t-test), and was linearly related to, the VBD from mammography. Summary statistics of the VBD from tomosynthesis were not statistically different from prior studies using high-resolution dedicated breast computed tomography. The observation of correlation and linear association in VBD between mammography and tomosynthesis suggests that breast density associated risk measures determined for mammography are translatable to tomosynthesis. Accounting for compressed breast thickness is important when it differs between the two modalities. The fibroglandular volume from tomosynthesis reconstructions is similar to mammography indicating suitability for use during near-infrared spectroscopy.

Calibration and optimization of 3D digital breast tomosynthesis guided near infrared spectral tomography

“…DBT images were read by a breast radiologist (SPP), who outlined two regions of interest (ROIs) in the left breast. DBT images were segmented into adipose, fibroglandular, and two ROIs using software developed for DBT breast segmentation [20,21]. Parallel plane extension of the ROIs was assigned to be equal to the largest diameter of the lesions measured in the plane perpendicular to the x-ray beam.…”

Effects of breast density and compression on normal breast tissue hemodynamics through breast tomosynthesis guided near-infrared spectral tomography

“…The exact numbers include 53 NIRST mildly compressed, 53 NIRST fully compressed, and 53 DBT fully compressed image acquisitions. Figure 1 summarizes the characteristics of the women imaged, including their BMI, breast thickness, percent fibroglandular tissue, 18 breast density, bra cup size, and age. The average BMI was 28.5, nearly 29-the US average for older women.…”

“…The 11 DBT projection images were reconstructed using the filtered backprojection method and formatted into a threedimensional image stack and segmented into adipose and fibroglandular tissues using an algorithm that employs bilateral filtering to reduce out-of-plane artifacts. 17,18 These segmented images created a region-tagged mesh that incorporated anatomic information from the DBT data and were used to reconstruct the NIRST results.…”

Dedicated Cone-Beam Breast CT: Reproducibility of Volumetric Glandular Fraction with Advanced Image Reconstruction Methods

“…Clinically, breast density is reported using a four-point categorical scale based on radiologists' impression of the spatial distribution (area) of fibroglandular tissue and it suffers from inter-reader variability. Several commercial and research tools [41][42][43][44][45] are available for computing volumetric breast density or for estimating the risk for breast cancer from mammography and digital breast tomosynthesis images. Since BCT provides volumetric data, it is readily suitable for quantifying the volumetric fibroglandular fraction (VGF) [46], which is also referred to as the volumetric breast density [47].…”