Macrophages (ΜΦs) are important immune effector cells that promote (M1 ΜΦs) or inhibit (M2 ΜΦs) inflammation and are involved in numerous physiological and pathogenic immune responses. Their precise role and relevance, however, are not fully understood for lack of non-invasive quantification methods. Here, we show that two-photon excited fluorescence lifetime imaging (TPE-FLIM), a label-free non-invasive method, can visualize ΜΦs in the human dermis in vivo. We demonstrate in vitro that human dermal ΜΦs exhibit specific TPE-FLIM properties that distinguish them from the main components of the extracellular matrix and other dermal cells. We visualized ΜΦs, their phenotypes and phagocytosis in the skin of healthy individuals in vivo using TPE-FLIM. Additionally, machine learning identified M1 and M2 MФs with a sensitivity of 0.88±0.04 and 0.82±0.03 and a specificity of 0.89±0.03 and 0.90±0.03, respectively. In clinical research, TPE-FLIM can advance the understanding of the role of MФs in health and disease.

For imaging of human ΜΦs, a two-photon tomograph (Dermainspect, JenLab GmbH, Jena, Germany), equipped with a tunable femtosecond Ti:sapphire laser (Mai Tai XF, Spectra Physics, USA, 710–920 nm, 100 fs pulses at a repetition rate of 80 MHz), was used at 3–5 mW for measurements of cells in vitro and skin biopsy sections ex vivo, as well as human dermis in vivo at 40–50 mW. The excitation wavelength was set to 760 nm, and a 410–680 nm band pass filter was used to detect two-photon excited autofluorescence (TPE-AF), whereas a 375–385 nm band pass filter was used to detect the second harmonic generation signals. The axial and lateral resolution was approximately 1.2–2.0 and 0.5 µm, respectively. The screening depth covers the entire papillary dermis and part of reticular dermis.

.sdt files are a proprietary file format that can be analyzed with SPCImage software (Becker&Hickl, Berlin, Germany)

Alternatively flimview: A Lightweight python package for FLIM image processing can be used (https://github.com/mgckind/flimview)

.ipynb is a Jupyter python script and contains the decision tree classifier

README file is included.