Comprehensive understanding of brain functions necessitates high-speed imaging of neuronal and vascular dynamics across extensive volumes. Functional neuroimaging investigations with two-photon microscopy are commonly hindered by its limited depth of field which restricts imaging rates across multiple planes. We introduce needle-shaped beam two-photon microscopy (NB-2PM), a versatile platform for high-throughput neurovascular imaging at sub-cellular resolution across multiple depths. It employs customized diffractive optical elements to generate single- or multi-plane needle beams with up to 10 times elongated depth of field relative to Rayleigh lengths and engineered axial energy distribution to effectively offset light attenuation with depth. The proposed method was applied to snapshot volumetric vascular imaging and multi-plane neurovascular dynamic recordings of resting state and stimulus-evoked activity in mice. NB-2PM can seamlessly be integrated into existing microscopy systems, thus providing a scalable platform for gaining comprehensive insights into the functional architecture of murine brain.

Label-free single-cell 3D imaging is essential for accurate phenotyping by minimizing perturbations to native cellular states and facilitating downstream molecular analyses. Among the available modalities, 3D forward-scattering (dark-field) imaging offers the richest subcellular details but faces challenges from strong transmitted-beam interference. We present a high-throughput 3D forward-scattering imaging flow cytometry system employing optical needle-beam illumination, linear micro-mirror arrays for axial scatter detection, and spatiotemporal deconvolution algorithms. Experimental validations with microstructures, hydrogel beads, and HEK-293 cells confirm the method’s capability for robust subcellular resolution at ∼400 cells/s, enabling advanced label-free cellular diagnostics and analysis. This platform enables label-free, high-content cellular analysis and is readily adaptable to integrated cell sorting and AI-driven classification, offering broad potential for biomedical research and diagnostics.

Virtual biopsy enables non-invasive diagnosis through machine-learning analysis of high-resolution images. But difficulties in generating accurate co-registered training sets and the resolution/field-of-view (FOV) tradeoff have hindered clinical applications. We present a method enabling reliable and accurate co-registration of 3D cellular-resolution OCT of fresh human skin with downstream histology. Orientation data is encoded across the sample by photobleaching a fiduciary grid pattern into fluorescent gel encasing the tissue. These markers persist in histology sections, permitting accurate co-registration to the 3D volume within ~20µm, and enabling cellular-resolution imaging with a cm-level FOV by laterally tiling OCT volumes, crucial steps toward in-vivo high-resolution Virtual Biopsy.

This study presents a phase-modulation technique capable of flexibly extending the depth-of-field (DOF) of any diffraction pattern. This method, deep diffractive optics (DDO), involves integrating a needle-shaped beam phase modulator with a conventional phase pattern design. Our findings reveal that these current deep diffractive optics can significantly extend the depth-of-field over traditional diffractive optics by a factor of 5. This method holds broad potential for applications in various optical devices, systems, and emerging fields of photonics.

Optical imaging techniques provide low-cost, non-radiative images with high spatiotemporal resolution, making them advantageous for long-term dynamic observation of blood perfusion in stroke research and other brain studies compared to non-optical methods. However, high-resolution imaging in optical microscopy fundamentally requires a tight optical focus, and thus a limited depth of field (DOF). Consequently, large-scale, non-stitched, high-resolution images of curved surfaces, like brains, are difficult to acquire without z-axis scanning. To overcome this limitation, we developed a needle-shaped beam optical coherence tomography angiography (NB-OCTA) system, and for the first time, achieved a volumetric resolution of less than 8 μm in a non-stitched volume space of 6.4 mm × 4 mm × 620 μm in vivo. This system captures the distribution of blood vessels at 3.4-times larger depths than normal OCTA equipped with a Gaussian beam (GB-OCTA). We then employed NB-OCTA to perform long-term observation of cortical blood perfusion after stroke in vivo, and quantitatively analyzed the vessel area density (VAD) and the diameters of representative vessels in different regions over 10 days, revealing different spatiotemporal dynamics in the acute, sub-acute and chronic phase of post-ischemic revascularization. Benefiting from our NB-OCTA, we revealed that the recovery process is not only the result of spontaneous reperfusion, but also the formation of new vessels. This study provides visual and mechanistic insights into strokes and helps to deepen our understanding of the spontaneous response of brain after stroke.

Histological hematoxylin and eosin–stained (H&E) tissue sections are used as the gold standard for pathologic detection of cancer, tumor margin detection, and disease diagnosis. Producing H&E sections, however, is invasive and time-consuming. While deep learning has shown promise in virtual staining of unstained tissue slides, true virtual biopsy requires staining of images taken from intact tissue. In this work, we developed a micron-accuracy coregistration method [micro-registered optical coherence tomography (OCT)] that can take a two-dimensional (2D) H&E slide and find the exact corresponding section in a 3D OCT image taken from the original fresh tissue. We trained a conditional generative adversarial network using the paired dataset and showed high-fidelity conversion of noninvasive OCT images to virtually stained H&E slices in both 2D and 3D. Applying these trained neural networks to in vivo OCT images should enable physicians to readily incorporate OCT imaging into their clinical practice, reducing the number of unnecessary biopsy procedures.

High-resolution optical imaging is accompanied by a limited depth of field, making it challenging to obtain non-stitched, high-resolution images of samples with uneven surfaces without performing Z-axis scanning. To solve this problem, we introduced diffractive optical elements into the conventional OCT system and develop a needle-shaped beam OCT system with both long DOF and high resolution, which maintains 8 mu m lateral resolution over a depth range of 620 mu m. The system was then employed to perform a 10-day cortical blood perfusion observation after stroke, providing visual and mechanistic insight into stroke, deepening our understanding of the brain response after stroke.

Cellular resolution of optical coherence tomography (OCT) is vital to achieve precise diagnosis by offering high-quality images of virtual biopsy. Currently, the common solution is to apply dynamic focusing to axially translate the focus through the region of interest with a high numerical aperture (N.A.) objective, followed by Z-stacking to rebuild a high-resolution 3D volume. To accelerate the imaging acquisition, this work developed metasurface optical plates to generate multiple foci along axial direction. Two-/three-/seven-foci had been testified with bead phantom using a scanning OCT. Human skin and human brain samples were imaged with cellular resolution.

Cellular-resolution optical coherence tomography (OCT) is a powerful tool offering noninvasive histology-like imaging. However, like other optical microscopy tools, a high numerical aperture (N.A.) lens is required to generate a tight focus, generating a narrow depth of field, which necessitates dynamic focusing and limiting the imaging speed. To overcome this limitation, we developed a metasurface platform that generates multiple axial foci, which multiplies the volumetric OCT imaging speed by offering several focal planes. This platform offers accurate and flexible control over the number, positions, and intensities of axial foci generated. All-glass metasurface optical elements 8 mm in diameter are fabricated from fused-silica wafers and implemented into our scanning OCT system. With a constant lateral resolution of 1.1 μm over all depths, the multifocal OCT triples the volumetric acquisition speed for dermatological imaging, while still clearly revealing features of stratum corneum, epidermal cells, and dermal-epidermal junctions and offering morphological information as diagnostic criteria for basal cell carcinoma. The imaging speed can be further improved in a sparse sample, e.g., 7-fold with a seven-foci beam. In summary, this work demonstrates the concept of metasurface-based multifocal OCT for rapid virtual biopsy, further providing insights for developing rapid volumetric imaging systems with high resolution and compact volume.

Optical coherence tomography angiography (OCTA) has emerged as a highly competitive technique for visualizing blood perfusion without the need for exogenous contrast agents. However, for high-resolution optical imaging, a tight optical focus is usually needed to achieve the diffraction-limited resolution in optical microscopy, which results in a limited depth of field (DOF), making it challenging to obtain large-scale, non-stitched, high-resolution images of samples with uneven surfaces without performing Z-axis scanning. To solve this problem, we introduce the diffractive optical elements (DOEs) into the conventional Gaussian beam (GB) OCT system and develop a needle-shaped beam (NB) OCT system with both long DOF and high resolution, which maintains 8 μm lateral resolution over a depth range of 620 μm, allowing real-time, non-stitched, large-field imaging of samples with uneven surfaces. OCTA imaging of mouse brains with natural curvature was demonstrated in our work.

Optical coherence tomography (OCT) allows label-free, micron-scale 3D imaging of biological tissues’ fine structures with significant depth and large field-of-view. Here we introduce a novel OCT-based neuroimaging setting, accompanied by a feature segmentation algorithm, which enables rapid, accurate, and high-resolution in vivo imaging of 700 μm depth across the mouse cortex. Using a commercial OCT device, we demonstrate 3D reconstruction of microarchitectural elements through a cortical column. Our system is sensitive to structural and cellular changes at micron-scale resolution in vivo, such as those from injury or disease. Therefore, it can serve as a tool to visualize and quantify spatiotemporal brain elasticity patterns. This highly transformative and versatile platform allows accurate investigation of brain cellular architectural changes by quantifying features such as brain cell bodies’ density, volume, and average distance to the nearest cell. Hence, it may assist in longitudinal studies of microstructural tissue alteration in aging, injury, or disease in a living rodent brain.

Needle-shaped beams (NBs) featuring a long depth-of-focus (DOF) can drastically improve the resolution of microscopy systems. However, thus far, the implementation of a specific NB has been onerous due to the lack of a common, flexible generation method. Here we develop a spatially multiplexed phase pattern that creates many axially closely spaced foci as a universal platform for customizing various NBs, allowing flexible manipulations of beam length and diameter, uniform axial intensity, and sub-diffraction-limit beams. NBs designed via this method successfully extended the DOF of our optical coherence tomography (OCT) system. It revealed clear individual epidermal cells of the entire human epidermis, fine structures of human dermal-epidermal junction in a large depth range, and a high-resolution dynamic heartbeat of alive Drosophila larvae.

Histological hematoxylin and eosin–stained (H&E) tissue sections are used as the gold standard for pathologic detection of cancer, tumor margin detection, and disease diagnosis. Producing H&E sections, however, is invasive and time-consuming. Non-invasive optical imaging modalities, such as optical coherence tomography (OCT), permit label-free, micron-scale 3D imaging of biological tissue microstructure with significant depth (up to 1mm) and large fields-of-view, but are difficult to interpret and correlate with clinical ground truth without specialized training. Here we introduce the concept of a virtual biopsy, using generative neural networks to synthesize virtual H&E sections from OCT images. To do so we have developed a novel technique, "optical barcoding", which has allowed us to repeatedly extract the 2D OCT slice from a 3D OCT volume that corresponds to a given H&E tissue section, with very high alignment precision down to 25 microns. Using 1,005 prospectively collected human skin sections from Mohs surgery operations of 71 patients, we constructed the largest dataset of H&E images and their corresponding precisely aligned OCT images, and trained a conditional generative adversarial network on these image pairs. Our results demonstrate the ability to use OCT images to generate high-fidelity virtual H&E sections and entire 3D H&E volumes. Applying this trained neural network to in vivo OCT images should enable physicians to readily incorporate OCT imaging into their clinical practice, reducing the number of unnecessary biopsy procedures.

Optical-resolution photoacoustic microscopy can visualize wavelength-dependent optical absorption at the cellular level. However, this technique suffers from a limited depth of field due to the tight focus of the optical excitation beam, making it challenging to acquire high-resolution images of samples with uneven surfaces or high-quality volumetric images without z scanning. To overcome this limitation, we propose needle-shaped beam photoacoustic microscopy, which can extend the depth of field to around a 28-fold Rayleigh length via customized diffractive optical elements. These diffractive optical elements generate a needle-shaped beam with a well-maintained beam diameter, a uniform axial intensity distribution and negligible sidelobes. The advantage of using needle-shaped beam photoacoustic microscopy is demonstrated via both histology-like imaging of fresh slide-free organs using a 266 nm laser and in vivo mouse-brain vasculature imaging using a 532 nm laser. This approach provides new perspectives for slide-free intraoperative pathological imaging and in vivo organ-level imaging.

The conventional sequencing method has limitations in throughput, scalability, and speed. To overcome these, next-generation sequencing (NGS) can enable high throughput decoding of deoxyribonucleic acid (DNA) molecules up to the scale of the entire human genome. The Illumina/Solexa Genome Analyzer platform is an example of NGS technology, which can sequence in parallel many adaptor flanked fragments up to several hundred base pairs in length. The Helicos Genetic Analysis System is similar to Illumina in that it performs sequencing based on single nucleotide addition. The Ion Torrent chip technology is also based on the sequencing by synthesis method, during which a complementary strand is built based on the sequence of a template strand. NGS technologies enable high-throughput decoding of DNA molecules up to the entire human genome, and allow highly multiplexed and parallel sequencing, which overcomes conventional sequencing's limitations in throughput, scalability, and speed.

Histological haematoxylin and eosin–stained (H&E) tissue sections are used as the gold standard for pathologic detection of cancer, tumour margin detection, and disease diagnosis1. Producing H&E sections, however, is invasive and time-consuming. Non-invasive optical imaging modalities, such as optical coherence tomography (OCT), permit label-free, micron-scale 3D imaging of biological tissue microstructure with significant depth (up to 1mm) and large fields-of-view2, but are difficult to interpret and correlate with clinical ground truth without specialized training3. Here we introduce the concept of a virtual biopsy, using generative neural networks to synthesize virtual H&E sections from OCT images. To do so we have developed a novel technique, “optical barcoding”, which has allowed us to repeatedly extract the 2D OCT slice from a 3D OCT volume that corresponds to a given H&E tissue section, with very high alignment precision down to 25 microns. Using 1,005 prospectively collected human skin sections from Mohs surgery operations of 71 patients, we constructed the largest dataset of H&E images and their corresponding precisely aligned OCT images, and trained a conditional generative adversarial network4 on these image pairs. Our results demonstrate the ability to use OCT images to generate high-fidelity virtual H&E sections and entire 3D H&E volumes. Applying this trained neural network to in vivo OCT images should enable physicians to readily incorporate OCT imaging into their clinical practice, reducing the number of unnecessary biopsy procedures.

Focal size and depth-of-focus (DOF) are dependent by the numerical aperture (N.A.) of the lens. Consequently, a high-resolution image inherently results in a short DOF. In order to extend the DOF of a high N.A. lens, a novel diffractive optical element is developed to generate needle-shaped beams. The DOF can be enhanced from 12μm (two Rayleigh lengths) to 120μm with a constant diameter of 1.5μm (the same as the focal size). When applied to a virtual biopsy of human skin, the needle-shaped beam can reveal the individual cells in the epidermal layer.

Optical imaging is based on the detection of light that has interacted with tissue. Photons of light can interact with bodily tissue in multiple different ways, including transmission, reflection, refraction, scattering, absorption, and fluorescence. Fluorescence is a subtype of absorption where the absorbed energy is released as a lower energy photon. Scattering and absorption coefficients will determine how deep a light ray will penetrate a tissue. An exogenous fluorescence signal can be obtained by administering contrast agents to the subject in the form of small molecules or nanoparticles. Fluorescence Resonance Energy Transfer is a special case of fluorescence imaging that allows the use of activatable imaging agents. Raman imaging relies on the physics of light scattering in tissue. Raman imaging has high multiplexing capability, i.e. the ability to uniquely resolve multiple contrast agents in the same image.