Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don't readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality for breast tumor discrimination. Methods: An X‐ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear‐array energy‐sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample's spatial distribution and respective spectral data for each location. To model in‐vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center ‐ Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program
Purpose: To accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x‐ray scatter imaging system. Methods: A breast phantom has been designed to assess the capability of coded aperture coherent x‐ray scatter imaging system to classify different types of breast tissue (adipose, fibroglandular, tumor). The tissue‐equivalent phantom was modeled as a hollow plastic cylinder containing multiple cylindrical and spherical inserts that can be positioned, rearranged, or removed to model different breast geometries. Each enclosure can be filled with a tissue‐equivalent material and excised human tumors. In this study, beef and lard, placed inside 2‐mm diameter plastic Nalgene containers, were used as surrogates for fibroglandular and adipose tissue, respectively. The phantom was imaged at 125 kVp, 40 mA for 10 seconds each with a 1‐mm pencil beam. The raw data were reconstructed using a model‐based reconstruction algorithm and yielded the location and form factor, or momentum transfer (q) spectrum of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x‐ray diffraction (XRD) imaging. Results: The tissue equivalent phantom was found to accurately model different types of breast tissue by qualitatively comparing our measured form factors to those of adipose and fibroglandular tissue from literature. Our imaging system has been able to define the location and composition of the various materials in the phantom. Conclusion: This work introduces a new tissue equivalent phantom for testing and optimization of our coherent scatter imaging system for material classification. In future studies, the phantom will enable the use of a variety of materials including excised human tissue specimens in evaluating and optimizing our imaging system using pencil‐ and fan‐beam geometries. United States Department of Homeland Security Duke University Medical Center ‐ Department of Radiology Carl E Ravin Advanced Imaging Laboratories Duke University Medical Physics Graduate Program
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