DLS with Giulio Cerullo: Novel approaches to broadband coherent Raman microscopy

Abstract

Coherent Raman scattering (CRS) microscopy is a powerful nonlinear optical technique for chemical identification of (bio)-molecules based on their intrinsic vibrational spectrum and for high-speed label-free imaging of cells and tissues. Single-frequency CRS microscopy allows the detection of molecules with a specific Raman response but is not sufficient to distinguish different components within complex heterogeneous systems in which chemical species display spectrally overlapped resonances. For this reason, there is ongoing research aimed at extending CRS to broadband detection, combining the speed of coherent Raman spectroscopy with the information content of spontaneous Raman [1].

We first present a broadband CARS (B-CARS) system based on a high power ultrafast solid-state laser and white light continuum generation in a bulk material, acquiring high-quality spectra in a 1-ms time, limited by the spectrometer refresh rate, covering both the fingerprint and the CH stretching region [2, 3]. A convolutional neural network is used to denoise the B-CARS spectra and remove the unwanted non-resonant background [4]. Our instrument delivers high quality label-free images of therapy-induced senescent cells and liver tumor tissues.

Next, we present a broadband SRS system equipped with a home-built multichannel lock-in amplifier, simultaneously measuring the stimulated Raman signal over 32 frequencies within 44 µs, allowing for detailed, high spatial resolution mapping of spectrally congested samples [5]. We demonstrate the performance of our SRS microscope by discriminating the relative concentrations of different fatty acids in cultured hepatocytes at the single lipid droplet level and by identifying fibrosarcoma tumor lesions embedded within healthy tissue. Finally, we describe our effort to develop a commercial broadband SRS microscope suitable for a clinical environment [6] based on a compact, turnkey fiber laser system for application to histopathology and label-free tumour identification, staging and grading.

[1] Polli, D.; Kumar, V.; Valensise, C. M.; Marangoni, M.; Cerullo, G. Broadband Coherent Raman Scattering Microscopy. Laser Photonics Rev. (2018); 12, 1800020.
[2] Vernuccio, F.; Bresci, A.; Talone, B.; de la Cadena, A.; Ceconello, C.; Mantero, S.; Sobacchi, C.; Vanna, R.; Cerullo, G.; Polli, D. Fingerprint Multiplex CARS at High Speed Based on Supercontinuum Generation in Bulk Media and Deep Learning Spectral Denoising. Opt. Express (2022); 30, 30135.
[3] Vernuccio, F.; Vanna, R.; Ceconello, C. et al., “Full-spectrum CARS microscopy of cells and tissues with ultrashort white-light continuum pulses,” J. Phys. Chem. B (2023); 127, 4733–4745.
[4] Vernuccio, F.; Bresci, A.; Cimini, V.; Giuseppi, A.; Cerullo, G.; Polli, D.; Valensise, C. M. Artificial Intelligence in Classical and Quantum Photonics. Laser Photonics Rev. (2022); 16, 2100399.
[5] De la Cadena, A.; Vernuccio, F.; Ragni, A.; Sciortino, G.; Vanna, R.; Ferrante, C.; Pediconi, N.; Valensise, C.; Genchi, L.; Laptenok, S. P.; Doni, A.; Erreni, M.; Scopigno, T.; Liberale, C.; Ferrari, G.; Sampietro, M.; Cerullo, G.; Polli, D. Broadband Stimulated Raman Imaging Based on Multi-Channel Lock-in Detection for Spectral Histopathology. APL Photonics (2022); 7, 076104.
[6] https://www.cambridgeramanimaging.com/.

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