Intravital microscopy (IVM) emerged and matured as a powerful tool for elucidating pathways in biological processes. Although label-free multiphoton IVM is attractive for its non-perturbative nature, its wide application has been hindered, mostly due to the limited contrast of each imaging modality and the challenge to integrate them. Here we introduce simultaneous label-free autofluorescence-multiharmonic (SLAM) microscopy, a single-excitation source nonlinear imaging platform that uses a custom-designed excitation window at 1110 nm and shaped ultrafast pulses at 10 MHz to enable fast (2-orders-of-magnitude improvement), simultaneous, and efficient acquisition of autofluorescence (FAD and NADH) and second/third harmonic generation from a wide array of cellular and extracellular components (e.g., tumor cells, immune cells, vesicles, and vessels) in living tissue using only 14 mW for extended time-lapse investigations. Our work demonstrates the versatility and efficiency of SLAM microscopy for tracking cellular events in vivo, and is a major enabling advance in label-free IVM.

The preparation, staining, visualization, and interpretation of histological images of tissue is well-accepted as the gold standard process for the diagnosis of disease. These methods were developed historically, and are used ubiquitously in pathology, despite being highly time and labor intensive. Here we introduce a unique optical imaging platform and methodology for label-free multimodal multiphoton microscopy that uses a novel photonic crystal fiber source to generate tailored chemical contrast based on programmable supercontinuum pulses. We demonstrate collection of optical signatures of the tumor microenvironment, including evidence of mesoscopic biological organization, tumor cell migration, and (lymph-)angiogenesis collected directly from fresh ex vivo mammary tissue. Acquisition of these optical signatures and other cellular or extracellular features, which are largely absent from histologically processed and stained tissue, combined with an adaptable platform for optical alignment-free programmable-contrast imaging, offers the potential to translate stain-free molecular histopathology into routine clinical use.

Intraoperative imaging of tumor microenvironment reveals correlations between extracellular vesicle density and breast pathology.

Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.

Label-free molecular imaging of the tumor microenvironment interrelates well-known events in carcinogenesis across spatial scales.