Optical biopsy using fluorescence spectroscopy for prostate cancer diagnosis

Binlin Wu; Xin Gao; Jason Smith; Jacob Bailin

doi:10.1117/12.2253517

13 February 2017 Optical biopsy using fluorescence spectroscopy for prostate cancer diagnosis

Binlin Wu, Xin Gao, Jason Smith, Jacob Bailin

Proceedings Volume 10038, Therapeutics and Diagnostics in Urology: Lasers, Robotics, Minimally Invasive, and Advanced Biomedical Devices; 100380U (2017) https://doi.org/10.1117/12.2253517
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Native fluorescence spectra are acquired from fresh normal and cancerous human prostate tissues. The fluorescence data are analyzed using a multivariate analysis algorithm such as non-negative matrix factorization. The nonnegative spectral components are retrieved and attributed to the native fluorophores such as collagen, reduced nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide (FAD) in tissue. The retrieved weights of the components, e.g. NADH and FAD are used to estimate the relative concentrations of the native fluorophores and the redox ratio. A machine learning algorithm such as support vector machine (SVM) is used for classification to distinguish normal and cancerous tissue samples based on either the relative concentrations of NADH and FAD or the redox ratio alone. The classification performance is shown based on statistical measures such as sensitivity, specificity, and accuracy, along with the area under receiver operating characteristic (ROC) curve. A cross validation method such as leave-one-out is used to evaluate the predictive performance of the SVM classifier to avoid bias due to overfitting.

Citation Download Citation

Binlin Wu, Xin Gao, Jason Smith, and Jacob Bailin "Optical biopsy using fluorescence spectroscopy for prostate cancer diagnosis", Proc. SPIE 10038, Therapeutics and Diagnostics in Urology: Lasers, Robotics, Minimally Invasive, and Advanced Biomedical Devices, 100380U (13 February 2017); https://doi.org/10.1117/12.2253517

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