Dataset Information

Noninvasive Nonlinear Optical Computational Histology.

ABSTRACT: Cancer remains a global health challenge, demanding early detection and accurate diagnosis for improved patient outcomes. An intelligent paradigm is introduced that elevates label-free nonlinear optical imaging with contrastive patch-wise learning, yielding stain-free nonlinear optical computational histology (NOCH). NOCH enables swift, precise diagnostic analysis of fresh tissues, reducing patient anxiety and healthcare costs. Nonlinear modalities are evaluated, including stimulated Raman scattering and multiphoton imaging, for their ability to enhance tumor microenvironment sensitivity, pathological analysis, and cancer examination. Quantitative analysis confirmed that NOCH images accurately reproduce nuclear morphometric features across different cancer stages. Key diagnostic features, such as nuclear morphology, size, and nuclear-cytoplasmic contrast, are well preserved. NOCH models also demonstrate promising generalization when applied to other pathological tissues. The study unites label-free nonlinear optical imaging with histopathology using contrastive learning to establish stain-free computational histology. NOCH provides a rapid, non-invasive, and precise approach to surgical pathology, holding immense potential for revolutionizing cancer diagnosis and surgical interventions.

SUBMITTER: Shen B

PROVIDER: S-EPMC10916666 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Noninvasive Nonlinear Optical Computational Histology.

Shen Binglin B Li Zhenglin Z Pan Ying Y Guo Yuan Y Yin Zongyi Z Hu Rui R Qu Junle J Liu Liwei L

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20231214 9

Cancer remains a global health challenge, demanding early detection and accurate diagnosis for improved patient outcomes. An intelligent paradigm is introduced that elevates label-free nonlinear optical imaging with contrastive patch-wise learning, yielding stain-free nonlinear optical computational histology (NOCH). NOCH enables swift, precise diagnostic analysis of fresh tissues, reducing patient anxiety and healthcare costs. Nonlinear modalities are evaluated, including stimulated Raman scatt ...[more]

PMID: 38095543

Similar Datasets

Project description:BackgroundPancreatic cancer is a lethal disease with a 5-year survival rate of only 1-5%. The acceleration of intraoperative histological examination would be beneficial for better management of pancreatic cancer, suggesting an improved survival. Nonlinear optical methods based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) of intrinsic optical biomarkers show the ability to visualize the morphology of fresh tissues associated with histology, which is promising for real-time intraoperative evaluation of pancreatic cancer.Methodology/principal findingsIn order to investigate whether the nonlinear optical imaging methods have the ability to characterize pancreatic histology at cellular resolution, we studied different types of pancreatic tissues by using label-free TPEF and SHG. Compared with other routine methods for the preparation of specimens, fresh tissues without processing were found to be most suitable for nonlinear optical imaging of pancreatic tissues. The detailed morphology of the normal rat pancreas was observed and related with the standard histological images. Comparatively speaking, the preliminary images of a small number of chemical-induced pancreatic cancer tissues showed visible neoplastic differences in the morphology of cells and extracellular matrix. The subcutaneous pancreatic tumor xenografts were further observed using the nonlinear optical microscopy, showing that most cells are leucocytes at 5 days after implantation, the tumor cells begin to proliferate at 10 days after implantation, and the extracellular collagen fibers become disordered as the xenografts grow.Conclusions/significanceIn this study, nonlinear optical imaging was used to characterize the morphological details of fresh pancreatic tissues for the first time. We demonstrate that it is possible to provide real-time histological evaluation of pancreatic cancer by the nonlinear optical methods, which present an opportunity for the characterization of the progress of spontaneous pancreatic cancer and further application in a non-invasive manner.

Project description:Nonlinear optical (NLO) pigments are compounds insoluble in solvents that exhibit phenomena related to nonlinear optical susceptibilities (χ(n) where n = 2,3,...), e.g., two-photon absorption (2PA) which is related to the imaginary part of χ(3). Determination of spectrally-resolved 2PA properties for NLO pigments of macromolecular nature, such as coordination polymers or crosslinked polymers, has long been a challenging issue due to their particulate form, precluding characterizations with standard techniques such as Z-scan. In this contribution, we investigate thus far unknown spectrally-resolved 2PA properties of a new subclass of NLO pigments-crosslinked conjugated polymers. The studied compounds are built up from electron-donating (triphenylamine) and electron-withdrawing (2,2'-bipyridine) structural fragments joined by vinylene (Pol1) or vinyl(4-ethynylphenyl) (Pol2) aromatic bridges. 2PA properties of these polymers have been characterized in broad spectral range by specially modified two-photon excited fluorescence (TPEF) techniques: solid state TPEF (SSTPEF) and internal standard TPEF (ISTPEF). The impact of self-aggregation of aromatic backbones on the 2PA properties of the polymers has been evaluated through extended comparisons of NLO parameters, i.e., 2PA cross sections (σ2) and molar-mass normalized 2PA merit factors (σ2/M) with those of small-molecular model compounds: Mod1 and Mod2. By doing this, we found that the 2PA response of Pol1 and Pol2 is improved 2-3 times versus respective model compounds in the solid state form. Further comparisons with 2PA results collected for diluted solutions of Mod1 and Mod2 supports the notion that self-aggregated structure contributes to the observed enhancement of 2PA response. On the other hand, it is clear that Pol1 and Pol2 suffer from aggregation-caused quenching phenomenon, well reflected in time-resolved fluorescence properties as well as in relatively low values of quantum yield of fluorescence. Accordingly, despite improved intrinsic 2PA response, the effective intensity of two-photon excited emission for Pol1 and Pol2 is slightly lower relative to Mod1 and Mod2. Finally, we explore temperature-resolved luminescence properties under one- (377 nm), two- (820 nm), and three-photon excitation (1020 nm) conditions of postsynthetically Eu3+-functionalized material, Pol1-Eu, and discuss its suitability for temperature sensing applications.

Dataset Information

Noninvasive Nonlinear Optical Computational Histology.

Publications

Noninvasive Nonlinear Optical Computational Histology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets