Method to Determine Tissue Fluorescence Efficiency in vivo and Predict Signal-to-Noise Ratio for Spectrometers
- 1 July 1998
- journal article
- research article
- Published by SAGE Publications in Applied Spectroscopy
- Vol. 52 (7) , 943-951
- https://doi.org/10.1366/0003702981944751
Abstract
Recent clinical trials have demonstrated the potential of fluorescence spectroscopy for in vivo diagnosis of pathology. There is significant potential to reduce the cost and complexity of instrumentation to measure tissue spectra; however, careful analysis is required to maximize performance and minimize cost. One measure of performance is the signal-to-noise ratio (SNR) of the resulting data. This paper describes a method to predict the SNR of a given optical design for a particular tissue application. In order to calculate the expected SNR, two pieces of information are required: (1) the throughput and inherent noise of the system and (2) a quantitative relationship between the illumination energy and the resulting tissue fluorescence available for collection, which we define as the tissue fluorescence efficiency (FE). We present a method to calculate the fluorescence efficiency of tissue from in vivo measurements of tissue fluorescence. We report FE measurements of the normal and precancerous human cervix in vivo at 337, 380, and 460 nm excitation. We also present and evaluate a method to estimate the throughput and noise of various spectrometers and predict the expected SNR for tissue spectra by using the measured tissue FE. For squamous cervical tissue, as the degree of the disease increases, FE decreases, and as the excitation wavelength increases, FE decreases. Cervical tissue FE varies more than two orders of magnitude, depending on the tissue type and on the excitation wavelength used. Our SNR calculations, based on measured values of tissue FE, demonstrate agreement within a factor of 1.3 of the measured SNR on average. This method can be used to estimate the performance of different spectrometer designs for clinical use.Keywords
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