Time-domain 3D localization of fluorescent inclusions in athick scattering medium

摘要

We introduce an improved approach in the 3D localization of discrete fluorescent inclusions in a thick scattering medium. Previously our approach provided accurate localization of a single inclusion, showing the potential for direct timc-of-flight fluorescence diffuse optical tomography. Here, we localize various combinations of multiple fluorescent inclusions. We resort to time-domain (TD) detection of emitted fluorescence pulses after short pulse laser excitation. Our approach relies on a signal processing technique, dubbed numerical constant fraction discrimination (NCFD), for extracting in a stable manner the arrival time of early photons emitted by one or many fluorescent inclusions from measured time-of-flight (TOF) distributions. Our experimental set-up allows multi-view tomographic optical TD measurements over 360 degrees without contact with the medium. It uses an ultra-short pulse laser and ultra-fast time-correlated single photon counting (TCSPC) detection. Fluorescence time point-spread functions (FTPSFs) are acquired all around the phantom after laser excitation. From measured FTPSFs, the arrival time of a fluorescent wavefront at a detector position is extracted with our NCFD technique. Indocyanine green (ICG; absorption peak = 780nm, emission peak = 830nm) is used for the inclusions. Various experiments were conducted with this set-up in a stepwise fashion. First, single inclusion experiments are presented to provide background information. Second, we present results using two inclusions in a plane. Then, we move on with two inclusions located in different planes. Finally, we show results with a plurality of inclusions (＞2) distributed at arbitrary positions in the medium. Using an algorithm we have developed and tested on the acquired data, we successfully achieve to locate the inclusions. Here, results are obtained for discrete inclusions. In a close future, we expect to extend our method to continuous fluorescence distributions.