Depth-resolved nanoscale nuclear architecture mapping for early prediction of cancer progression

Shikhar Uttam; Hoa V. Pham; Justin LaFace; Douglas J. Hartman; Yang Liu

doi:10.1117/12.2214688

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8 March 2016 Depth-resolved nanoscale nuclear architecture mapping for early prediction of cancer progression

Shikhar Uttam, Hoa V. Pham, Justin LaFace, Douglas J. Hartman, Yang Liu

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Proceedings Volume 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX; 969728 (2016) https://doi.org/10.1117/12.2214688
Event: SPIE BiOS, 2016, San Francisco, California, United States

Abstract

Effective management of patients who are at risk of developing invasive cancer is a primary challenge in early cancer detection. Techniques that can help establish clear-cut protocols for successful triaging of at-risk patients have the potential of providing critical help in improving patient care while simultaneously reducing patient cost. We have developed such a technique for early prediction of cancer progression that uses unstained tissue sections to provide depth-resolved nanoscale nuclear architecture mapping (nanoNAM) of heterogeneity in optical density alterations manifested in precancerous lesions during cancer progression. We present nanoNAM and its application to predicting cancer progression in a well-established mouse model of spontaneous carcinogenesis: ApcMin/+ mice.

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Shikhar Uttam, Hoa V. Pham, Justin LaFace, Douglas J. Hartman, and Yang Liu "Depth-resolved nanoscale nuclear architecture mapping for early prediction of cancer progression", Proc. SPIE 9697, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XX, 969728 (8 March 2016); https://doi.org/10.1117/12.2214688

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