From morphology to clinical pathophysiology: multiphoton fluorescence lifetime imaging at patients' bedside

Abstract

Application of multiphoton microscopy in the field of biomedical research and advanced diagnostics promises unique insights into the pathophysiology of skin diseases. By means of multiphoton excitation, endogenous biomolecules like NADH, collagen or elastin show autofluorescence or second harmonic generation. Thus, these molecules provide information about the subcellular morphology, epidermal architecture and physiological condition of the skin. To gain a deeper understanding of the linkage between cellular structure and physiological processes, non-invasive multiphoton-based intravital tomography (MPT) and fluorescence lifetime imaging (FLIM) were combined within the scopes of inflammatory skin, chronic wounds and drug delivery in clinical application.

The optical biopsies generated via MPT were morphologically analyzed and aligned with classical skin histology. Because of its subcellular resolution, MPT provided evidence of a redistribution of mitochondria in keratinocytes, indicating an altered cellular metabolism. Independent morphometric algorithms reliably showed a perinuclear accumulation in lesional skin in contrast to an even distribution in healthy skin. Confirmatively, MPT-FLIM showed an obvious metabolic shift in lesions. Moreover, detection of the onset and progression of inflammatory processes could be achieved. The feasibility of primary in vivo tracking of applied therapeutic agents further broadened our scope: We examined the permeation and subsequent distribution of agents directly visualized in patients´ skin in short-term repetitive measurements. Furthermore, we performed MPT-FLIM follow-up investigations in the long-term course of therapy.

Therefore, clinical MPT-FLIM application offers new insights into the pathophysiology and the individual therapeutic course of skin diseases, facilitating a better understanding of the processes of inflammation and wound healing.

Bibliographical data

Original languageEnglish
ISSN0277-786X
DOIs
Publication statusPublished - 2017