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Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging.
Proc SPIE Int Soc Opt Eng 2017 Jan-Feb; 10054PS

Abstract

We are developing label-free hyperspectral imaging (HSI) for tumor margin assessment. HSI data, hypercube (x,y,λ), consists of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on the HSI image has an optical spectrum. We developed preprocessing and classification methods for HSI data. We used spectral features from HSI data for the classification of cancer and benign tissue. We collected surgical tissue specimens from 16 human patients who underwent head and neck (H&N) cancer surgery. We acquired both HSI, autofluorescence images, and fluorescence images with 2-NBDG and proflavine from the specimens. Digitized histologic slides were examined by an H&N pathologist. The hyperspectral imaging and classification method was able to distinguish between cancer and normal tissue from oral cavity with an average accuracy of 90±8%, sensitivity of 89±9%, and specificity of 91±6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94±6%, sensitivity of 94±6%, and specificity of 95±6%. Hyperspectral imaging outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study suggests that label-free hyperspectral imaging has great potential for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the hyperspectral imaging technology is warranted for its application in image-guided surgery.

Authors+Show Affiliations

Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA. Department of Biomedical Engineering, Georgia Institute of Technology and Emory University. Department of Mathematics & Computer Science, Emory University, Atlanta, GA. Winship Cancer Institute of Emory University, Atlanta, GA.Department of Biomedical Engineering, Georgia Institute of Technology and Emory University.Department of Otolaryngology, Emory University, Atlanta, GA.Department of Otolaryngology, Emory University, Atlanta, GA.Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA.Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA.Department of Otolaryngology, Emory University, Atlanta, GA.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30294063

Citation

Fei, Baowei, et al. "Tumor Margin Assessment of Surgical Tissue Specimen of Cancer Patients Using Label-free Hyperspectral Imaging." Proceedings of SPIE--the International Society for Optical Engineering, vol. 10054, 2017.
Fei B, Lu G, Wang X, et al. Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging. Proc SPIE Int Soc Opt Eng. 2017;10054.
Fei, B., Lu, G., Wang, X., Zhang, H., Little, J. V., Magliocca, K. R., & Chen, A. Y. (2017). Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging. Proceedings of SPIE--the International Society for Optical Engineering, 10054, doi:10.1117/12.2249803.
Fei B, et al. Tumor Margin Assessment of Surgical Tissue Specimen of Cancer Patients Using Label-free Hyperspectral Imaging. Proc SPIE Int Soc Opt Eng. 2017;10054 PubMed PMID: 30294063.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging. AU - Fei,Baowei, AU - Lu,Guolan, AU - Wang,Xu, AU - Zhang,Hongzheng, AU - Little,James V, AU - Magliocca,Kelly R, AU - Chen,Amy Y, Y1 - 2017/02/14/ PY - 2018/10/9/entrez PY - 2017/1/1/pubmed PY - 2017/1/1/medline KW - Hyperspectral imaging KW - cancer detection KW - fluorescence imaging KW - head and neck cancer KW - image classification KW - image quantification KW - image-guided surgery KW - label free KW - tumor margin assessment JF - Proceedings of SPIE--the International Society for Optical Engineering JO - Proc SPIE Int Soc Opt Eng VL - 10054 N2 - We are developing label-free hyperspectral imaging (HSI) for tumor margin assessment. HSI data, hypercube (x,y,λ), consists of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on the HSI image has an optical spectrum. We developed preprocessing and classification methods for HSI data. We used spectral features from HSI data for the classification of cancer and benign tissue. We collected surgical tissue specimens from 16 human patients who underwent head and neck (H&N) cancer surgery. We acquired both HSI, autofluorescence images, and fluorescence images with 2-NBDG and proflavine from the specimens. Digitized histologic slides were examined by an H&N pathologist. The hyperspectral imaging and classification method was able to distinguish between cancer and normal tissue from oral cavity with an average accuracy of 90±8%, sensitivity of 89±9%, and specificity of 91±6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94±6%, sensitivity of 94±6%, and specificity of 95±6%. Hyperspectral imaging outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study suggests that label-free hyperspectral imaging has great potential for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the hyperspectral imaging technology is warranted for its application in image-guided surgery. SN - 0277-786X UR - https://www.unboundmedicine.com/medline/citation/30294063/Tumor_margin_assessment_of_surgical_tissue_specimen_of_cancer_patients_using_label_free_hyperspectral_imaging_ L2 - https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/30294063/ DB - PRIME DP - Unbound Medicine ER -