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X-Ray Diffraction for Breast Cancer Imaging

A Kapadia*, J Greenberg , D Nacouzi , D Hazineh , S McCall , Duke University Medical Center, Durham, NC

Presentations

(Tuesday, 7/16/2019) 1:15 PM - 1:45 PM

Room: Exhibit Hall | Forum 8

Purpose: Previously we described the development of a coherent-scatter spectral imaging system for identification of cancer. Here we describe the evolution of the technology for intraoperative margin assessment and present results from surgically resected breast tumors.

Methods: A prototype X-ray diffraction imaging system was built using a bremsstrahlung X-ray source, 2D flat-panel detector, coded-apertures, and a customized translation stage. System performance was evaluated using calibration phantoms of known materials. Surgically resected breast tumor specimens, obtained from mastectomy and lumpectomy procedures, were scanned prior to pathology workup. Each specimen was sliced, laid out on a tray, and scanned at multiple locations to generate a complete 2D map of the tissue. Each voxel in the map was analyzed using a neural network algorithm that classified it as normal or cancerous. Scatter images were generated for each specimen and analyzed to classify voxels with malignant tissue. Finally, the images were compared against histological analysis to evaluate the performance of the scanner.

Results: In all specimens scanned, the scatter images showed the location of cancerous regions within the specimen. The detection and classification was performed through automated spectral matching without the need for manual intervention. The scatter spectra corresponding to cancer tissue were found to be in agreement with those reported in literature. Inter-patient variability was found to be within limits reported in literature. The scatter images showed agreement with pathologist-identified regions of cancer. Spatial resolution for this configuration of the scanner was determined to be 2-3 mm, and the total scan time for each specimen was under 15 minutes.

Conclusion: This work demonstrates the utility of coherent scatter imaging in identifying cancer based on the scatter properties of the tissue. It presents the first results from coherent scatter imaging of fresh (unfixed) breast tissue using our coded-aperture scatter imaging approach for cancer identification.  

Funding Support, Disclosures, and Conflict of Interest: This work was funded by the NC Biotech Center under award #2018-BIG-6511

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