Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothesized that deep-learning based stimulated Raman scattering (SRS) microscopy could provide automated and accurate diagnosis of laryngeal squamous cell carcinoma on fresh, unprocessed surgical specimens without fixation, sectioning or staining. Methods : We first compared 80 pairs of adjacent frozen sections imaged with SRS and standard hematoxylin and eosin histology to evaluate their concordance. We then applied SRS imaging on fresh surgical tissues from 45 patients to reveal key diagnostic features, based on which we have constructed a deep learning based model to generate automated histologic results. 18,750 SRS fields of views were used to train and cross-validate our 34-layered residual convolutional neural network, which was used to classify 33 untrained fresh larynx surgical samples into normal and neoplasia. Furthermore, we simulated intraoperative evaluation of resection margins on totally removed larynxes. Results : We demonstrated near-perfect diagnostic concordance (Cohen's kappa, κ > 0.90) between SRS and standard histology as evaluated by three pathologists. And deep-learning based SRS correctly classified 33 independent surgical specimens with 100% accuracy. We also demonstrated that our method could identify tissue neoplasia at the simulated resection margins that appear grossly normal with naked eyes. Conclusion : Our results indicated that SRS histology integrated with deep learning algorithm provides potential for delivering rapid intraoperative diagnosis that could aid the surgical management of laryngeal cancer.

We present the design and experimental results of a near-field scanning microwave microscope (NSMM) working at a frequency of 1GHz. Our microscope is unique in that the sensing probe is separated from the excitation electrode to significantly suppress the common-mode signal. Coplanar waveguides were patterned onto a silicon nitride cantilever interchangeable with atomic force microscope (AFM) tips, which are robust for high speed scanning. In the contact mode that we are currently using, the numerical analysis shows that contrast comes from both the variation in local dielectric properties and the sample topography. Our microscope demonstrates the ability to achieve high resolution microwave images on buried structures, as well as nano-particles, nano-wires, and biological samples.1

Black phosphorus is a layered semiconducting material, demonstrating strong layer-dependent optical and electronic properties. Probing the photophysical properties on ultrafast time scales is of central importance in understanding many-body interactions and nonequilibrium quasiparticle dynamics. Here, we applied temporally, spectrally, and spatially resolved pump-probe microscopy to study the transient optical responses of mechanically exfoliated few-layer black phosphorus, with layer numbers ranging from 2 to 9. We have observed layer-dependent resonant transient absorption spectra with both photobleaching and red-shifted photoinduced absorption features, which could be attributed to band gap renormalization of higher subband transitions. Surprisingly, coherent phonon oscillations with unprecedented intensities were observed when the probe photons were in resonance with the optical transitions, which correspond to the low-frequency layer-breathing mode. Our results reveal strong Coulomb interactions and electron-phonon couplings in photoexcited black phosphorus, providing important insights into the ultrafast optical, nanomechanical, and optoelectronic properties of this novel two-dimensional material.

The study of amyotrophic lateral sclerosis (ALS) and potential interventions would be facilitated if motor axon degeneration could be more readily visualized. Here we demonstrate that stimulated Raman scattering (SRS) microscopy could be used to sensitively monitor peripheral nerve degeneration in ALS mouse models and ALS autopsy materials. Three-dimensional imaging of pre-symptomatic SOD1 mouse models and data processing by a correlation-based algorithm revealed that significant degeneration of peripheral nerves could be detected coincidentally with the earliest detectable signs of muscle denervation and preceded physiologically measurable motor function decline. We also found that peripheral degeneration was an early event in FUS as well as C9ORF72 repeat expansion models of ALS, and that serial imaging allowed long-term observation of disease progression and drug effects in living animals. Our study demonstrates that SRS imaging is a sensitive and quantitative means of measuring disease progression, greatly facilitating future studies of disease mechanisms and candidate therapeutics.