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

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

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.

Conference Presentation

Citation Download Citation

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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