Abstract
Purpose: :
To develop a system for discrimination of endogenous fluorophores. Such a system should be able to detect fluorophores, characterizing the state of metabolism at cellular level.
Methods: :
The system uses excitation and emission spectrum, and especially fluorescence lifetime as substance-specific properties. Considering the maximal permissible exposure, fluorescence lifetime measurements are only possible by laser scanning technique, when a high lateral resolution is required in fundus images. So, a Heidelberg Retina Angiograph is the basic device in the optimized set up. For excitation, picosecond pulse lasers at 446 and 468 nm are used. The time-resolved fluorescence is detected by time-correlated single photon counting in a short-wave channel (500-560 nm) and a long-wave channel (560-700 nm). The pulse repetition rate is 80 MHz. The time of 12.5 ns between two pulses is divided in 1024 time channels, allowing a time resolution of 12.5 ps. The lateral resolution is 40µmx40µm. To accumulate a sufficient number of photons in each time channel of each pixel, series of weak fluorescence images must be registered. For that reason infrared images at 820 nm are detected, simultaneously with fluorescence images. According to the infrared images, the fluorescence images were registered on line. The dynamic fluorescence is approximated by bi- or tri-exponential model function.
Results: :
Images of lifetimes, amplitudes, and of relative contribution can be presented in both spectral channels. In a healthy fundus, the shortest lifetime tau 1 will be detected in the macula and the longest lifetime in the optic disc in the short-wave channel. Quasi 3-dimensional images improve discovering of fluorescence inhomogenities. A ring-like structure was detected for tau 1 in the macula in early AMD. Histograms show the most frequent lifetime or amplitudes. In diagrams tau 2 vs. tau 1 both isolated fluorophores and separated ocular structures form characteristic clusters, improving interpretation of in vivo measurements.
Keywords: imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • imaging/image analysis: clinical • metabolism