The structural characteristics of bile duct tissue can indirectly reflect the physiological function of the bile duct, so understanding the pathological process of bile duct tissue can improve the prognosis of intrahepatic cholangiocarcinoma. However, the existing technology cannot accurately and quickly determine the stage of the bile duct tissue lesion, which will have a certain impact on the treatment. In this study, normal bile ducts, inflammatory bile ducts, and intrahepatic cholangiocarcinoma were distinguished using label-free multiphoton microscopy (MPM). The experimental results show that high-resolution images can clearly distinguish normal bile duct, inflammatory bile duct and intrahepatic cholangiocarcinoma through cell morphology and tissue structure. Therefore, MPM can be used as an effective optical tool for the diagnosis of intrahepatic cholangiocarcinoma in unstained histological sections. It is expected in the future that MPM can play a greater role in the clinic.
The mortality rate of gastric cancer ranks second in the world. The prognosis of early gastric cancer is good, while the prognosis of advanced gastric cancer is poor. Therefore, early diagnosis of gastric cancer is the key to determining the prognosis of patients. Traditional pathological analysis takes a long time, and the results may have some subjectivity and randomness. Therefore, we propose a method for distinguishing normal and early gastric cancer sites by multiphoton microscopy combined with acridine orange rapid staining. The experimental results confirmed that multiphoton microscopy combined with acridine orange staining can effectively describe the normal microstructure of the human gastric mucosa，and these results laid the experimental foundation for the establishment of clinical diagnostic criteria for gastric cancer.
Ovarian cancer accounts for the highest mortality rate among all gynecologic cancers. Current diagnosis methods of ovarian cancer are time-consuming and labor-intensive. We previously found that the organization changes within the extracellular matrix fiber network can occur during cancer progression. It is desired to monitor these organization changes of extracellular matrix in a rapid way so that it can be used for cancer diagnosis. The principal component of the extracellular matrix fibers is mainly collagen. Detecting the change of collagen orientation can improve our understanding of this deadly cancer and benefit clinical diagnosis and treatments. Collagen with highly non-centrosymmetric molecular assemblies can produce SHG signal, which can be detected by multiphoton microscopy. Multiphoton microscopy is a promising non-invasive, label-free nonlinear imaging technique, which has been proven to be an important diagnostic tool for the visualization of collagen. It also possesses intrinsic advantage for 3D visualization. In this study, we use multiphoton microscopy to obtain 3D image stacks of ovarian cancer and normal tissue without the need for tedious and cumbersome tissue processing. SHG from collagen was excited using 810 nm light and the emission signal was detected in the range of 395-415nm. Then the 3D collagen orientation parameter and collagen directional variance for discriminating cancer and normal tissue was gotten by using a specific 3D image processing method. Our results show that the 3D collagen directional variances between ovarian cancer and normal tissue are distinct (p<0.05). In conclusion, the association of multiphoton microscopy with specific 3D image processing method provides a powerful tool for ovarian cancer diagnosis. It may also help physicians to improve clinical outcomes of patients with ovarian cancer.
Alterations in the elastic fibers have been implicated in lung cancer. However, the label-free, microscopic imaging of elastic fibers in situ remains a major challenge. Here, we present the use of intrinsic two-photon excited fluorescence (TPEF) signal as a novel means for quantification of the elastic fibers in intact fresh human lung tissues. We obtained the TPEF images of elastic fibers from ex vivo the human lung tissues. We found that three features, including the elastic fibers area, the elastic fibers orientation, the elastic fibers structure, provide the quantitative identification of lung cancer and the direct visual cues for cancer versus non-cancer areas. These results suggest that the TPEF signal can be used as the label-free optical biomarkers for rapid clinical lung diagnosis and instant image-guided surgery.