Endoscopic sensing of alveolar pH.

D Choudhury,K Dhaliwal,J M Stone,M Bradley,S Seth,T R Choudhary,F Yu,M G Tanner,R R Thomson,T A Birks,B Mills,S Mcaughtrie,I K Mati,T H Craven,C K I Williams,C J Campbell

doi:10.1364/boe.8.000243

Abstract

Previously unobtainable measurements of alveolar pH were obtained using an endoscope-deployable optrode. The pH sensing was achieved using functionalized gold nanoshell sensors and surface enhanced Raman spectroscopy (SERS). The optrode consisted of an asymmetric dual-core optical fiber designed for spatially separating the optical pump delivery and signal collection, in order to circumvent the unwanted Raman signal generated within the fiber. Using this approach, we demonstrate a ~100-fold increase in SERS signal-to-fiber background ratio, and demonstrate multiple site pH sensing with a measurement accuracy of ± 0.07 pH units in the respiratory acini of an ex vivo ovine lung model. We also demonstrate that alveolar pH changes in response to ventilation.

Highlights

The distal lung alveolar acinar regions are responsible for gas exchange
The optrode consisted of an asymmetric dual-core optical fiber designed for spatially separating the optical pump delivery and signal collection, in order to circumvent the unwanted Raman signal generated within the fiber
We demonstrate a ~100-fold increase in SERS signal-tofiber background ratio, and demonstrate multiple site pH sensing with a measurement accuracy of ± 0.07 pH units in the respiratory acini of an ex vivo ovine lung model

Summary

Introduction

The distal lung alveolar acinar regions are responsible for gas exchange. In health, the acini are devoid of infiltrating inflammatory cells and pathogens, while in inflammatory lung diseases such as pneumonia, the pathological hallmark involves dense infiltration by myeloid derived peripheral blood cells. Estimating the contribution of background in a SERS spectrum (s ) is a well-studied problem in the literature [34], where established methods are based on the assumption that the background (b) is smooth, and that the SERS signal (s) is composed of peaks at characteristic frequencies, depending on the reporter molecule. These methods tend to work well when the aforementioned assumptions are satisfied and in particular, when one is interested in the welldefined ‘narrow’ peaks. To avoid this issue we jointly estimate the background (b) from multiple SERS spectra

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