Shape analysis of simulated breast anatomical structures

Abstract

Recent advances in high-resolution 3D breast imaging, namely, digital breast tomosynthesis and dedicated breast CT, have enabled detailed analysis of the shape and distribution of anatomical structures in the breast. Such analysis is critically important, since the projections of breast anatomical structures make up the parenchymal pattern in clinical images which can mask the existing abnormalities or introduce false alarms; the parenchymal pattern is also correlated with the risk of cancer. As a first step towards the shape analysis of anatomical structures in the breast, we have analyzed an anthropomorphic software breast phantom. The phantom generation is based upon the recursive splitting of the phantom volume using octrees, which produces irregularly shaped tissue compartments, qualitatively mimicking the breast anatomy. The shape analysis was performed by fitting ellipsoids to the simulated tissue compartments. The ellipsoidal semi-axes were calculated by matching the moments of inertia of each individual compartment and of an ellipsoid. The distribution of Dice coefficients, measuring volumetric overlap between the compartment and the corresponding ellipsoid, as well as the distribution of aspect ratios, measuring relative orientations of the ellipsoids, were used to characterize various classes of phantoms with qualitatively distinctive appearance. A comparison between input parameters for phantom generation and the properties of fitted ellipsoids indicated the high level of user control in the design of software breast phantoms. The proposed shape analysis could be extended to clinical breast images, and used to inform the selection of simulation parameters for improved realism.

Description and Characterization of a Novel Method for Partial Volume Simulation in Software Breast Phantoms

“…We assumed the thickness was smaller than 1 mm, as observed from subgross breast histological sections (e.g., the sections shown in [39]). Also, we varied the relative random compartment orientation and the relative compartment size, [49].…”

“…To determine the influence of ligament boundary non-linearity on the accuracy of the proposed PV estimation, we generated four phantoms corresponding to the classes discussed [49]. We varied the relative compartment orientation , and the relative compartment size, , as shown in Table VII.…”

Reduction of artifacts in computer simulation of breast Cooper's ligaments

“…= Σ s and the skin thickness), where a parameter p was varied (p=1, corresponding to the original algorithm, p=2, 3). Qualitative evaluation of the proposed technique was performed by visual comparison of phantom slices and segmented ligament surfaces, and by simulating parallel X-ray projections.…”

“…Our recursive partitioning algorithm [1][2][3][4][5][6] provides an efficient method for fast simulation 7 of software breast phantoms, thus opening venues for virtual clinical trials 8 and other studies requiring a large number of simulated breasts, or breast images, with specified characteristics. The algorithm contains mechanisms to control thickness of Cooper's ligaments thus providing for realistic simulation of tissue.…”

Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity Among Minority Populations

“…Note that total execution time for the PV computation using the linear approximation was about times less than with the Monte Carlo method (N MC =63). To determine the influence of ligament boundary non-linearity on the accuracy of the proposed 590 PV estimation, we generated four 200m phantoms corresponding to the classes discussed [49].…”