29 February 2016 Large area 3-D optical coherence tomography imaging of lumpectomy specimens for radiation treatment planning
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Proceedings Volume 9689, Photonic Therapeutics and Diagnostics XII; 968946 (2016); doi: 10.1117/12.2213404
Event: SPIE BiOS, 2016, San Francisco, California, United States
Abstract
Our long term goal is to develop a high-resolution imaging method for comprehensive assessment of tissue removed during lumpectomy procedures. By identifying regions of high-grade disease within the excised specimen, we aim to develop patient-specific post-operative radiation treatment regimens. We have assembled a benchtop spectral-domain optical coherence tomography (SD-OCT) system with 1320 nm center wavelength. Automated beam scanning enables “sub-volumes” spanning 5 mm x 5 mm x 2 mm (500 A-lines x 500 B-scans x 2 mm in depth) to be collected in under 15 seconds. A motorized sample positioning stage enables multiple sub-volumes to be acquired across an entire tissue specimen. Sub-volumes are rendered from individual B-scans in 3D Slicer software and en face (XY) images are extracted at specific depths. These images are then tiled together using MosaicJ software to produce a large area en face view (up to 40 mm x 25 mm). After OCT imaging, specimens were sectioned and stained with HE, allowing comparison between OCT image features and disease markers on histopathology. This manuscript describes the technical aspects of image acquisition and reconstruction, and reports initial qualitative comparison between large area en face OCT images and HE stained tissue sections. Future goals include developing image reconstruction algorithms for mapping an entire sample, and registering OCT image volumes with clinical CT and MRI images for post-operative treatment planning.
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Cuihuan Wang, Leonard Kim, Nicola Barnard, Atif Khan, Mark C. Pierce, "Large area 3-D optical coherence tomography imaging of lumpectomy specimens for radiation treatment planning", Proc. SPIE 9689, Photonic Therapeutics and Diagnostics XII, 968946 (29 February 2016); doi: 10.1117/12.2213404; https://doi.org/10.1117/12.2213404
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