This paper presents the use and characterization of an electrically focus tunable lens to perform axial scanning in a confocal microscope. Lateral and axial resolution are characterized over a >250 µm axial scan range. Confocal microscopy using optical axial scanning is demonstrated in epithelial tissue and compared to traditional stage scanning. By enabling rapid axial scanning, minimizing motion artifacts, and reducing mechanical complexity, this technique has potential to enhance in vivo threedimensional imaging in confocal endomicroscopy.

Abstract:There is an increasing interest in the application of fluorescence lifetime imaging (FLIM) for medical diagnosis. Central to the clinical translation of FLIM technology is the development of compact and highspeed clinically compatible systems. We present a handheld probe design consisting of a small maneuverable box fitted with a rigid endoscope, capable of continuous lifetime imaging at multiple emission bands simultaneously. The system was characterized using standard fluorescent dyes. The performance was then further demonstrated by imaging a hamster cheek pouch in vivo, and oral mucosa tissue both ex vivo and in vivo, all using safe and permissible exposure levels. Such a design can greatly facilitate the evaluation of FLIM for oral cancer imaging in vivo.

Abstract. Optical imaging techniques using a variety of contrast mechanisms are under evaluation for early detection of epithelial precancer; however, tradeoffs in field of view (FOV) and resolution may limit their application. Therefore, we present a multiscale multimodal optical imaging system combining macroscopic biochemical imaging of fluorescence lifetime imaging (FLIM) with subcellular morphologic imaging of reflectance confocal microscopy (RCM). The FLIM module images a 16 × 16 mm 2 tissue area with 62.5 μm lateral and 320 ps temporal resolution to guide cellular imaging of suspicious regions. Subsequently, coregistered RCM images are acquired at 7 Hz with 400 μm diameter FOV, <1 μm lateral and 3.5 μm axial resolution. FLIM-RCM imaging was performed on a tissue phantom, normal porcine buccal mucosa, and a hamster cheek pouch model of oral carcinogenesis. While FLIM is sensitive to biochemical and macroscopic architectural changes in tissue, RCM provides images of cell nuclear morphology, all key indicators of precancer progression.

Multispectral autofluorescence lifetime imaging (maFLIM) can be used to clinically image a plurality of metabolic and biochemical autofluorescence biomarkers of oral epithelial dysplasia and cancer. This study tested the hypothesis that maFLIM-derived autofluorescence biomarkers can be used in machine-learning (ML) models to discriminate dysplastic and cancerous from healthy oral tissue. Clinical widefield maFLIM endoscopy imaging of cancerous and dysplastic oral lesions was performed at two clinical centers. Endoscopic maFLIM images from 34 patients acquired at one of the clinical centers were used to optimize ML models for automated discrimination of dysplastic and cancerous from healthy oral tissue. A computer-aided detection system was developed and applied to a set of endoscopic maFLIM images from 23 patients acquired at the other clinical center, and its performance was quantified in terms of the area under the receiver operating characteristic curve (ROC-AUC). Discrimination of dysplastic and cancerous from healthy oral tissue was achieved with an ROC-AUC of 0.81. This study demonstrates the capabilities of widefield maFLIM endoscopy to clinically image autofluorescence biomarkers that can be used in ML models to discriminate dysplastic and cancerous from healthy oral tissue. Widefield maFLIM endoscopy thus holds potential for automated in situ detection of oral dysplasia and cancer.

Multispectral fluorescence lifetime imaging (m-FLIM) can potentially allow identifying the endogenous fluorophores present in biological tissue. Quantitative description of such data requires estimating the number of components in the sample, their characteristic fluorescent decays, and their relative contributions or abundances. Unfortunately, this inverse problem usually requires prior knowledge about the data, which is seldom available in biomedical applications. This work presents a new methodology to estimate the number of potential endogenous fluorophores present in biological tissue samples from time-domain m-FLIM data. Furthermore, a completely blind linear unmixing algorithm is proposed. The method was validated using both synthetic and experimental m-FLIM data. The experimental m-FLIM data include in-vivo measurements from healthy and cancerous hamster cheek-pouch epithelial tissue, and ex-vivo measurements from human coronary atherosclerotic plaques. The analysis of m-FLIM data from in-vivo hamster oral mucosa identified healthy from precancerous lesions, based on the relative concentration of their characteristic fluorophores. The algorithm also provided a better description of atherosclerotic plaques in term of their endogenous fluorophores. These results demonstrate the potential of this methodology to provide quantitative description of tissue biochemical composition.