Coherent anti-Stokes Raman scattering (CARS) microscopy is an emerging nonlinear vibrational imaging technique that delivers label-free chemical maps of cells and tissues. In narrowband CARS, two spatiotemporally superimposed picosecond pulses, pump and Stokes, illuminate the sample to interrogate a single vibrational mode. Broadband CARS (BCARS) combines narrowband pump pulses with broadband Stokes pulses to record broad vibrational spectra. Despite recent technological advancements, BCARS microscopes still struggle to image biological samples over the entire Raman-active region (400–3100 cm–1). Here, we demonstrate a robust BCARS platform that answers this need. Our system is based on a femtosecond ytterbium laser at a 1035 nm wavelength and a 2 MHz repetition rate, which delivers high-energy pulses used to produce broadband Stokes pulses by white-light continuum generation in a bulk YAG crystal. Combining such pulses, pre-compressed to sub-20 fs duration, with narrowband pump pulses, we generate a CARS signal with a high (<9 cm–1) spectral resolution in the whole Raman-active window, exploiting both the two-color and three-color excitation mechanisms. Aided by an innovative post-processing pipeline, our microscope allows us to perform high-speed (≈1 ms pixel dwell time) imaging over a large field of view, identifying the main chemical compounds in cancer cells and discriminating tumorous from healthy regions in liver slices of mouse models, paving the way for applications in histopathological settings.

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The success of chemotherapy and radiotherapy anti-cancer treatments can result in tumor suppression or senescence induction. Senescence was previously considered a favorable therapeutic outcome, until recent advancements in oncology research evidenced senescence as one of the culprits of cancer recurrence. Its detection requires multiple assays, and nonlinear optical (NLO) microscopy provides a solution for fast, non-invasive, and label-free detection of therapy-induced senescent cells. Here, we develop several deep learning architectures to perform binary classification between senescent and proliferating human cancer cells using NLO microscopy images and we compare their performances. As a result of our work, we demonstrate that the most performing approach is the one based on an ensemble classifier, that uses seven different pre-trained classification networks, taken from literature, with the addition of fully connected layers on top of their architectures. This approach achieves a classification accuracy of over 90%, showing the possibility of building an automatic, unbiased senescent cells image classifier starting from multimodal NLO microscopy data. Our results open the way to a deeper investigation of senescence classification via deep learning techniques with a potential application in clinical diagnosis.

Recent studies have shown that common anticancer treatments can induce cell senescence rather than death, a critical phenotype governing tumor recurrence. This calls for the urgent development of safe, precise, and quick tools to unveil critical Therapy-Induced Senescence (TIS). Merging different coherent Raman and multiphoton techniques, we present label-free multimodal nonlinear optical (NLO) microscopy as a powerful tool to spot early TIS. We home-built a microscope including different NLO modalities: Stimulated Raman Scattering (SRS), forward and epi-detected Coherent Anti-Stokes Raman Scattering (CARS and E-CARS), and Two-Photon Excited Fluorescence (TPEF). The infrared laser source outputs synchronized narrowband 780 nm pump pulses and 950-1050 nm tunable Stokes pulses, so to match the CH-stretching region of the Raman spectrum. Thanks to the co-registration of these diverse techniques applied on label-free TIS cells and controls, we exposed quantitative hallmarks of early TIS, confirmed by comparing different optical signals monitored over 72 hours of treatment. TPEF from metabolic coenzymes combined with E-CARS from cardiolipin and cytochrome C indicated an early shrinking of mitochondria. CARS and SRS revealed lipid vesicles overproduction and accumulation. Nuclei enlarged irregularly, visualized via subtraction of SRS signals of proteins and lipids, and CARS from deoxyribose. We consider our results will strongly influence anticancer pre-clinical studies and translated clinical applications, helping to identify quickly, non-invasively, and quantitatively TIS in human tumors.