Rongli Zhang

Esophageal squamous cell carcinoma (ESCC) features atypical clinical manifestations and a low 5-year survival rate (< 5% in many developing countries where most of the disease occurs). Precise ESCC detection and grading toward timely and effective intervention are therefore crucial. In this study, we propose a multidimensional, slicing-free, and label-free histopathological evaluation method based on multispectral multiphoton fluorescence lifetime imaging microscopy (MM-FLIM) for precise ESCC identification. To assess the feasibility of this method, comparative imaging on fresh human biopsy specimens of different ESCC grades is performed. By constructing fluorescence spectrum- and lifetime-coded images, ESCC-induced morphological variations are unveiled. Further quantification of cell metabolism and stromal fibers reveals potential indicators for ESCC detection and grading. The specific identification of keratin pearls provides additional support for the early detection of ESCC. These findings demonstrate the viability of using MM-FLIM and the series of derived indicators for histopathological evaluation of ESCC. As there is an increasing interest in developing multiphoton endoscopes and multiphoton FLIM systems for clinical use, the proposed method would probably allow noninvasive, label-free, and multidimensional histological detection and grading of ESCC in the future.

The rupture of coronary atherosclerotic plaque (CAP) and the resulting intracoronary thrombosis account for most acute coronary syndromes. Thus, the early identification and risk assessment of CAP is crucial for timely medical intervention. In this study, we propose a quantitative and label-free method for human CAP identification using multiphoton microscopy (MPM) and three-dimensional (3D) image analysis techniques. By detecting the intrinsic MPM signals, the microstructures of collagen and elastin fibers within normal and CAP-lesioned human coronary artery walls were imaged. Using a 3D gray level co-occurrence matrix method and 3D weighted vector summation algorithm, quantitative indicators that characterize the spatial texture and orientation features of the fibers were extracted. We demonstrate that these indicators show superior accuracy and repeatability over 2D texture features in CAP discrimination. Furthermore, by combining the 3D microstructural indicators, a support vector machine model that classifies CAP from the normal arterial wall with an accuracy of >97% was established. In conjunction with advances in multiphoton endoscopy, the proposed method shows great potential in providing a quantitative, label-free, and real-time tool for the early identification and risk assessment of CAP in the future.

Cancer incidence and mortality are rapidly growing worldwide, resulting in heavy social and economic burdens. Early detection as well as precise intraoperative diagnosis of cancers is crucial to improving the prognosis and thus significantly decreasing the mortality. Two-photon excitation fluorescence lifetime imaging microscopy and spectroscopy not only shows the outstanding capability of label-free, intravital, high-resolution, three-dimensional imaging but also allows the quantitative biochemical characterizing of live tissues. Benefiting from these advantages, this technology is promising for early detection and demarcation of malignant tumors. However, its full potential has not been extensively evaluated in clinical settings. Here, we assess the feasibility of using two-photon excitation fluorescence lifetime imaging microscopy and spectroscopy to identify various cancers, including esophageal cancer, gastric cancer, and brain cancer. In terms of esophageal cancer, we compared the fresh human esophageal mucosal tissues of normal, squamous cell carcinoma, and adenocarcinoma. For gastric cancer, we performed a systematic investigation on fresh human gastric mucosal specimens at typical stages of gastric carcinogenesis. In addition, by developing a mouse chronic cranial window, we carried out a preliminary study on glioma margin identification in vivo. By extracting fluorescence spectrum and lifetime information of endogenous fluorophores, qualitative and quantitative indicators which are found to have the potential to discriminate normal, premalignant and different malignant lesions are derived. This study may shed new light on the early detection, precise intraoperative diagnosis, and classification of digestive tract cancers and brain cancers. With advances in endoscopy, two-photon excitation fluorescence lifetime imaging microscopy and spectroscopy has the potential to become a noninvasive, label-free, real-time histological and functional cancer detection tool in the future.