Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions

Abstract

PurposeTwo-photon microscopy (2PM) is an emerging clinical imaging modality with the potential to non-invasively assess tissue metabolism and morphology in high-resolution. This study aimed to assess the translational potential of 2PM for improved detection of high-grade cervical precancerous lesions. Experimental Design2P images attributed to reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavoproteins (FP) were acquired from the full epithelial thickness of freshly excised human cervical tissue biopsies (N = 62). Fifteen biopsies harbored high-grade squamous intraepithelial lesions (HSILs), 14 biopsies harbored low-grade SILs (LSILs), and 33 biopsies were benign. Quadratic discriminant analysis (QDA) leveraged morphological and metabolic functional metrics extracted from these images to predict the presence of HSILs. We performed gene set enrichment analysis (GSEA) using datasets available on the Gene Expression Omnibus (GEO) to validate the presence of metabolic reprogramming in HSILs. ResultsIntegrating metabolic and morphological 2P-derived metrics from finely sampled, full-thickness epithelia achieved a high 90.8 {+/-} 6.1% sensitivity and 72.3 {+/-} 11.3% specificity of HSIL detection. Notably, sensitivity (91.4 {+/-} 12.0%) and specificity (77.5 {+/-} 12.6%) were maintained when utilizing metrics from only two images at 12- and 72-{micro}m from the tissue surface. Upregulation of glycolysis, fatty acid metabolism, and oxidative phosphorylation in HSIL tissues validated the metabolic reprogramming captured by 2P biomarkers. ConclusionLabel-free 2P images from as few as two epithelial depths enable rapid and robust HSIL detection through the quantitative characterization of metabolic and morphological reprogramming, underscoring the potential of this tool for clinical evaluation of cervical precancers. Translational Relevance StatementThe colposcopy and biopsy paradigm for cervical pre-cancer detection leads to an excessive number of unnecessary biopsies, with significant economic and psychological costs. This study highlights the potential of label-free, high-resolution two photon imaging to improve this paradigm by introducing real-time morphofunctional tissue assessments. In an extensive dataset comprising freshly excised high-grade and low-grade cervical intraepithelial lesions, along with benign metaplastic and inflamed human cervical tissue biopsies, we successfully characterize a loss of morphofunctional heterogeneity indicative of high-grade precancerous changes. Leveraging a combination of two-photon imaging-derived quantitative morphofunctional metrics, our findings showcase a substantial improvement in both sensitivity and specificity of high-grade lesion detection compared to the current gold standard of colposcopy followed by a single biopsy. The demonstrated enhancement in sensitivity and specificity highlights the prospect of integrating non-invasive, label-free metabolic imaging into clinical practice, offering a more effective and efficient approach to identify and manage cervical precancerous lesions.