Pancreatic cancer is the fourth leading cause of cancer-related mortality in the worldwide, with an overall 5-year survival rate of 1–5% 
. Better treatment can contribute to a significant improvement in patient survival 
. Intraoperative consultation which mainly involves the examination of the surgical excised specimen, is important for the surgeon to determine the most appropriate treatment options 
. However, it is subject to the time constraints. A single frozen section diagnosis with high level of accuracy takes 20 minutes, and it is much longer when multiple frozen sections are required to perform on a single specimen 
. Real-time histology of fresh or live tissues without sectioning or additional processing, would not only facilitate immediate establishment or confirmation of a diagnosis and stage intraoperatively that will influence the surgical procedure, but also make it possible to evaluate all the surgical margins so that the tumor is removed completely without compromising the normal part of the pancreas. Accurate surgical margin assessment allows the improvement of long-term survival, since positive surgical margins occur among 37–50% of patients undergoing surgical resection and the overall survival of these patients ranges between 8 and 14 months 
. Real-time detection of morphological patterns at the resolution of a single cell, which is an analogue of histology, indicates an attractive prospect for optimal intraoperative management of pancreatic cancer with favorable survival benefit.
Optical methods, taking advantage of non-invasion and high tempo-spatial resolution, can achieve in vivo
imaging and sensing in biomedical studies. Raman spectroscopy, which is based on the difference in the energy of the incident and scattered photons due to the molecular vibrations, is sensitive to the changes of chemical composition in cells and tissues. It has been applied to the differentiation of normal and cancerous pancreatic tissues from a mouse model 
. Reflectance and fluorescence spectroscopy can provide biochemical information of the tissues to distinguish different human pancreatic tissues, including normal pancreatic tissue, pancreatitis, and pancreatic adenocarcinoma 
. Photon-tissue interaction models have been further developed to provide quantitative links between the reflectance and fluorescence measurements and histological characteristics of human pancreatic tissues, such as the nuclear size 
. However, the spectral parameters are difficult to be directly matched with the morphological features revealed by the conventional histological examination, especially the changes of nuclear shape and organization of the extracellular matrix. More detailed characterization of the pancreatic morphology with cellular resolution using optical methods is necessary to improve the detection of pancreatic neoplasia, implicating a new means of real-time histology.
In recent years, nonlinear optical microscopy (NOM), primarily including TPEF and SHG, has emerged as a powerful tool to identify slight structural and functional changes at cellular resolution. NOM has the advantage of submicron spatial resolution, millisecond temporal resolution, and the optical sectioning ability in turbid tissues 
. One important nature of such an imaging modality is that the endogenous optical biomarkers in tissues can be employed to provide contrast, which makes it possible to detect human diseases without the need for fixation, sectioning, or staining. Intrinsic two-photon excited fluorescence (TPEF) biomarkers including reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] and flavin adenine dinucleotide (FAD) have been applied to reveal the morphology of the cells, since NAD(P)H and FAD are the major fluorophores in the cytoplasm 
. Meanwhile, the collagen fibers, which are important structural proteins in the extracellular matrix (ECM), can implement the intrinsic second harmonic generation (SHG) process in biological tissues to reflect the ECM pattern 
. In addition, the intracellular NAD(P)H and FAD are also related with the redox ratio of cells, which can be used as an indicator of the metabolic level of cells 
. NOM has been widely applied to visualize cellular and tissue structures in different cancer tissues including ovarian, bladder, gastric tissues, and so on 
We first, to our knowledge, characterized the morphological details of pancreatic tissues using label-free TPEF and SHG techniques. In an effort to evaluate the feasibility of NOM for the detailed morphological characterization of pancreatic tissues, we applied label-free TPEF and SHG techniques to normal rat pancreas and related with traditional histological staining images. Various routine means for the preparation of the specimens have been compared to acquire optimum nonlinear optical imaging of pancreatic tissues. The chemical-induced pancreatic cancer tissues were further characterized and compared with normal pancreatic specimens to validate the ability of NOM to reveal the neoplastic changes. In order to assess the potential of the label-free TPEF and SHG techniques to characterize different stages during the growth of pancreatic cancer, the subcutaneous pancreatic tumor xenografts harvested at different time points after implantation were quantitatively analyzed based on their morphological characteristics.