Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

Abstract

Abstract. A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

Correlation of X-ray diffraction signatures of breast tissue and their histopathological classification

“…Alternative X-ray scattering based technologies currently being investigated for tissue classification include coded aperture coherent scatter imaging 19 , 20 and diffraction enhanced CT 21 – 23 . This paper looks at the correlation between histopathological analysis and X-ray diffraction signatures for a range of breast tissue samples as a step towards establishing the viability of diffraction signature analysis for classifying tissue samples.…”

Accuracy assessment and characterization of x-ray coded aperture coherent scatter spectral imaging for breast cancer classification

“…19 Mapping out the spatial distribution of cancer in the surgically resected tissue sample is one of the most important tasks in determining the success of the lumpectomy procedure because information about the margins is used to conclude whether the entire tumor volume was successfully removed within the resected specimen. 20 In prior work, 21 we demonstrated CACSSI's ability to detect cancerous tumors in ex vivo breast samples. We also described a Monte Carlo simulation of a CACSSI system and demonstrated its ability to accurately map out the distribution of cancer in a breast sample.…”

“…The breast tissue phantom used in this work was first described in Ref. 21. It was developed as follows.…”

Detector comparison for high-resolution 3D x-ray diffraction imaging for biospecimen analysis

“…[1][2][3] . Additionally, these types of measurements can be made within a standard lab setting using conventional X-ray sources and detectors, while employing XRDI techniques such as a coded aperture architecture to incorporate spatial resolution 2,9,10 . Evaluating optically thin samples made of biologically relevant materials has yielded high accuracy results but the applicability of these studies to in-vivo imaging is limited.…”