Combined multiphoton fluorescence microscopy and photoacoustic imaging for stratigraphic analysis of paintings.

We demonstrate the effective combination of multiphoton and photoacoustic (PA) imaging for the high-resolution stratigraphic analysis of multilayered art objects with emphasis on paintings. A novel convolution-based algorithm is additionally applied for the precise discrimination of nonlinear signals, providing valuable information in regard to the thickness and composition of successive varnish and paint layers in the mock-up samples. On the other hand, PA contrast complements the extracted data by revealing well-hidden graphite underdrawings below the paint at high sensitivity levels. The final composite images are directly compared with cross-sectional brightfield observations, validating the capabilities of the bimodal diagnosis in terms of measurement accuracy and contrast specificity. The presented hybrid diagnostic approach has the potential to optimize delicate interventions in works of art such as the selective removal of aged materials, thus promoting a significantly improved restoration outcome.

Polarization Second Harmonic Generation Discriminates Between Fresh and Aged Starch-Based Adhesives Used in Cultural Heritage.

In this work, we report that polarization second harmonic generation (PSHG) microscopy, commonly used in biomedical imaging, can quantitatively discriminate naturally aged from fresh starch-based glues used for conservation or restoration of paintings, works of art on paper, and books. Several samples of fresh and aged (7 years) flour and starch pastes were investigated by use of PSHG. In these types of adhesives, widely used in cultural heritage conservation, second harmonic generation (SHG) contrast originates primarily from the starch granules. It was found that in aged glues, the starch SHG effective orientation (SHG angle, θ) shifts to significantly higher values in comparison to the fresh granules. This shift is attributed to the different degree of granule hydration between fresh and aged adhesives. Thus noninvasive high-resolution nonlinear scattering can be employed to detect and quantify the degree of deterioration of restoration adhesives and to provide guidance toward future conservation treatments.

Application of a Deep-Learning Technique to Non-Linear Images From Human Tissue Biopsies for Shedding New Light on Breast Cancer Diagnosis.

The development of label-free non-destructive techniques to be used as diagnostic tools in cancer research is of great importance for improving the quality of life for millions of patients. Previous studies have demonstrated that Third Harmonic Generation (THG) imaging could differentiate malignant from benign unlabeled human breast biopsies and distinguish the different grades of cancer. Towards the application of such technologies to clinic, in the present report, a deep learning technique was applied to THG images recorded from breast cancer tissues of grades 0, I, II, and III. By the implementation of a convolutional neural network (CNN) model, the differentiation of malignant from benign breast tissue samples and the discrimination of the different grades of cancer in a fast and accurate way were achieved. The obtained results provide a step ahead towards the use of optical diagnostic tools in conjunction with the CNN image classifier for the reliable and rapid malignancy diagnosis in clinic.

Monitoring aging-associated structural alterations in Caenorhabditis elegans striated muscles via polarization-dependent second-harmonic generation measurements.

The in-vivo elucidation of the molecular mechanisms underlying muscles dysfunction due to aging via non-invasive label free imaging techniques is an important issue with high biological significance. In this study, polarization-dependent second-harmonic generation (PSHG) was used to evaluate structural alterations in the striated muscles during Caenorhabditis elegans lifespan. Young and old wild-type animals were irradiated. The obtained results showed that it was not feasible to detect differences in the structure of myosin that could be correlated with the aging of the worms, via the implementation of the classical, widely used, cylindrical symmetry model and the calculation of the SHG anisotropy values. A trigonal symmetry model improved the extracted results; however, the best outcome was originated from the application of a general model. Myosin structural modifications were monitored via the estimation of the difference in spectral phases derived from discrete Fourier transform analysis. Age classification of the nematodes was achieved by employing both models, proving the usefulness of the usage of PSHG microscopy as a potential diagnostic tool for the investigation of muscle diseases.

Polarization-dependent second-harmonic generation for collagen-based differentiation of breast cancer samples.

Nonlinear optical imaging techniques have been widely used to reveal biological structures for accurate diagnosis at the cellular as well as the tissue level. In the present study, polarization-dependent second-harmonic generation (PSHG) was used to determine collagen orientation in breast cancer biopsy tissues (grades 0, I, II and III). The obtained data were processed using fast Fourier transform (FFT) analysis, while second-harmonic generation (SHG) anisotropy and the "ratio parameter" values were also calculated. Such measurements were shown to be able to distinguish collagen structure modifications in different cancer grades tested. The analysis presented herein suggests that PSHG imaging could provide a quantitative evaluation of the tumor state and the distinction of malignant from benign breast tissues. The obtained results also allowed the development of a biophysical model, which can explain the aforementioned differentiations and is in agreement with the simulations relating the SHG anisotropy values with the mechanical tension applied to the collagen during cancer progression. The current approach could be a step forward for the development of new, nondestructive, label free optical diagnostic tools for cancer reducing the need of recalls and unnecessary biopsies, while potentially improving cancer detection rates.

Third Harmonic Generation microscopy distinguishes malignant cell grade in human breast tissue biopsies.

The ability to distinguish and grade malignant cells during surgical procedures in a fast, non-invasive and staining-free manner is of high importance in tumor management. To this extend, Third Harmonic Generation (THG), Second Harmonic Generation (SHG) and Fourier-Transform Infrared (FTIR) spectroscopy were applied to discriminate malignant from healthy cells in human breast tissue biopsies. Indeed, integration of non-linear processes into a single, unified microscopy platform offered complementary structural information within individual cells at the submicron level. Using a single laser beam, label-free THG imaging techniques provided important morphological information as to the mean nuclear and cytoplasmic area, cell volume and tissue intensity, which upon quantification could not only distinguish cancerous from benign breast tissues but also define disease severity. Simultaneously, collagen fibers that could be detected by SHG imaging showed a well structured continuity in benign tumor tissues, which were gradually disoriented along with disease severity. Combination of THG imaging with FTIR spectroscopy could provide a clearer distinction among the different grades of breast cancer, since FTIR analysis showed increased lipid concentrations in malignant tissues. Thus, the use of non-linear optical microscopy can be considered as powerful and harmless tool for tumor cell diagnostics even during real time surgery procedures.