Use of independent component analysis to improve signal-to-noise ratio in multi-probe fluorescence microscopy.

In conventional multi-probe fluorescence microscopy, narrow bandwidth filters on detectors are used to avoid bleed-through artefacts between probes. The limited bandwidth reduces the signal-to-noise ratio of the detection, often severely compromising one or more channels. Herein, we describe a process of using independent component analysis to discriminate the position of different probes using only a dichroic mirror to differentiate the signals directed to the detectors. Independent component analysis was particularly effective in samples where the spatial overlap between the probes is minimal, a very common case in cellular microscopy. This imaging scheme collects nearly all of the emitted light, significantly improving the image signal-to-noise ratio. In this study, we focused on the detection of two fluorescence probes used in vivo, NAD(P)H and ANEPPS. The optimal dichroic mirror cutoff frequency was determined with simulations using the probes spectral emissions. A quality factor, defined as the cross-channel contrast-to-noise ratio, was optimized to maximize signals while maintaining spatial discrimination between the probes after independent component analysis post-processing. Simulations indicate that a ∼3 fold increase in signal-to-noise ratio using the independent component analysis approach can be achieved over the conventional narrow-band filtering approach without loss of spatial discrimination. We confirmed this predicted performance from experimental imaging of NAD(P)H and ANEPPS in mouse skeletal muscle, in vivo. For many multi-probe studies, the increased sensitivity of this 'full bandwidth' approach will lead to improved image quality and/or reduced excitation power requirements. Published [2014]. This article is a U.S. Government work and is in the public domain in the USA.