Label-free, two-photon imaging of freshly excised human cervical tissue biopsies captures depth-dependent changes in cellular metabolism.
Polleys, Christopher.
2022
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Precancerous lesions manifest within the epithelium of the human cervix. Epithelial tissues are largely superficial, and are therefore a suitable target for high-resolution, label-free, two-photon excitation fluorescence (TPEF) imaging. Endogenous sources of contrast such as reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavin adenine dinucleotide (FAD) provide a ... read morewindow into the cellular metabolism of human cervical tissues. Cellular metabolism can be quantified using metrics such as optical redox ratio (RR) and mitochondrial clustering. Optical RR can be defined as the per pixel intensity ratio of FAD/(NAD(P)H + FAD) The mean and interquartile range (IQR) of optical RR values for a given field can be calculated to assess intrafield heterogeneity in redox state. Depth-dependent heterogeneity can also be assessed by evaluating the average and sample variance of optical RR metrics for optical sections sampled through the full thickness of the epithelium. Mitochondrial clustering is quantified on a per-field basis via a Fourier-based analysis of NAD(P)H intensity variations within segmented regions of cellular cytoplasm. The depth-dependent mean and sample variance of mitochondrial clustering provides information as to how mitochondrial organization changes with depth in human cervical tissues. Metrics of mitochondrial organization and optical redox ratio can quantify how fully differentiated, benign human cervical tissues demonstrate great metabolic heterogeneity though depth. By contrast, such metrics can capture increases in mitochondrial clustering, increases in optical RR IQR, and decreases in mean optical RR in both the superficial and deeper regions of cervical tissues containing precancerous lesions. Overall, these tissues exhibit low levels of depth-dependent heterogeneity. A wide range of functional metabolic metrics can be extracted from analysis of label-free, TPEF images, and motivates developments to pursue such measurements in vivo to improve cervical pre-cancer diagnosis.
3-minute talk presented at the Tufts Graduate Student Council's 27th Graduate Student Research Symposium, April 20, 2022.read less - Polleys, Christopher. "Label-free, two-photon imaging of freshly excised human cervical tissue biopsies captures depth-dependent changes in cellular metabolism." Presentation at the 27th Graduate Research Symposium, Tufts University, April 20, 2022.
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