James R. Spencer,1,2 Joshua E. Carter,1,2 Crystal K. Leung,2 Shannon J. McCall,2 Joel A. Greenberg,3 Anuj J. Kapadia1,2,3
1Carl E. Ravin Advanced Imaging Labs., Duke Univ. Medical Ctr. (United States) 2Duke Univ. School of Medicine (United States) 3Duke Univ. (United States)
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A Coded Aperture Coherent Scatter Spectral Imaging (CACSSI) system was developed in our group to differentiate cancer and healthy tissue in the breast. The utility of the experimental system was previously demonstrated using anthropomorphic breast phantoms and breast biopsy specimens. Here we demonstrate CACSSI utility in identifying tumor margins in real time using breast lumpectomy specimens. Fresh lumpectomy specimens were obtained from Surgical Pathology with the suspected cancerous area designated on the specimen. The specimens were scanned using CACSSI to obtain spectral scatter signatures at multiple locations within the tumor and surrounding tissue. The spectral reconstructions were matched with literature form-factors to classify the tissue as cancerous or non-cancerous. The findings were then compared against pathology reports to confirm the presence and location of the tumor. The system was found to be capable of consistently differentiating cancerous and healthy regions in the breast with spatial resolution of 5 mm. Tissue classification results from the scanned specimens could be correlated with pathology results. We now aim to develop CACSSI as a clinical imaging tool to aid breast cancer assessment and other diagnostic purposes.
James R. Spencer,Joshua E. Carter,Crystal K. Leung,Shannon J. McCall,Joel A. Greenberg, andAnuj J. Kapadia
"Coded aperture coherent scatter spectral imaging for assessment of breast cancers: an ex-vivo demonstration", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101324K (9 March 2017); https://doi.org/10.1117/12.2253975
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James R. Spencer, Joshua E. Carter, Crystal K. Leung, Shannon J. McCall, Joel A. Greenberg, Anuj J. Kapadia, "Coded aperture coherent scatter spectral imaging for assessment of breast cancers: an ex-vivo demonstration," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101324K (9 March 2017); https://doi.org/10.1117/12.2253975