Non-local means improves total-variation constrained photoacoustic image reconstruction

Photoacoustic/Optoacoustic tomography aims to reconstruct maps of the initial pressure rise induced by the absorption of light pulses in tissue. This reconstruction is an ill-conditioned and under-determined problem, when the data acquisition protocol involves limited detection positions. The aim of the work is to develop an inversion method which integrates denoising procedure within the iterative model-based reconstruction to improve quantitative performance of optoacoustic imaging. Among the model-based schemes, total-variation (TV) constrained reconstruction scheme is a popular approach. In this work, a two-step approach was proposed for improving the TV constrained optoacoustic inversion by adding a non-local means based filtering step within each TV iteration. Compared to TV-based reconstruction, inclusion of this non-local means step resulted in signal-to-noise ratio improvement of 2.5 dB in the reconstructed optoacoustic images.     

Two‐ and three‐photon absorption cross‐section characterization for high‐brightness,cell‐specific multiphoton fluorescence brain imaging

We demonstrate an accurate quantitative characterization of absolute two‐ and three‐photon absorption (2PA and 3PA) action cross sections of a genetically encodable fluorescent marker Sypher3s. Both 2PA and 3PA action cross sections of this marker are found to be remarkably high, enabling high‐brightness, cell‐specific two‐ and three‐photon fluorescence brain imaging. Brain imaging experiments on sliced samples of rat's cortical areas are presented to demonstrate these imaging modalities. The 2PA action cross section of Sypher3s is shown to be highly sensitive to the level of pH, enabling pH measurements via a ratiometric readout of the two‐photon fluorescence with two laser excitation wavelengths, thus paving the way toward fast optical pH sensing in deep‐tissue experiments.     

Miniaturized all fiber probe for optical coherence tomography and pH detection of biological tissue

We present a novel all-fiber probe with 710-μm outside diameter for combined optical coherence tomography and pH detection. In cancer surgery, a significant challenge is how to completely remove the malignant tumor without cutting too much normal tissue. The difference between cancer tissue and normal tissue not only lies in morphology and structure but also in tissue pH, where malignant tissue has a lower pH. This dual-modality probe combined optical coherence tomography and pH detection of biological tissue, is expected to determine whether the tissue is cancerous quickly and accurately. The probe utilizes a typical three-segment structure (double-clad fiber - no-core fiber - graded-index fiber). We obtained a lateral resolution of ~10.6 μm, a working distance of ~506 μm and a pH measurement accuracy of 0.01 pH unit for the probe. The performance of the all-fiber probe was verified through an ex vivo experiment using the porcine brain specimen.     

Histopathological correlations of bulk tissue polarimetric images: Case study

Polarimetric imaging and image analysis have gained increased interest in soft tissue analysis at the cellular level. However, polarimetric imaging has widely been tested on thin tissue sections to provide reliable information correlated with histopathological findings. Polarimetric bulk tissue analysis always offered an overall assessment of various tissue optical properties for diagnosis. In this study, the histopathological correlation of bulk tissue polarimetry images for soft tissues is discussed. The first-hand information on the use of bulk tissue Mueller polarimetry and image analysis as an alternative to tissue histopathology is presented for surgically extracted colon and breast tissues.     

Three‐dimensional mapping of the attenuation coefficient in optical coherence tomography to enhance breast tissue microarchitecture contrast

Effective intraoperative tumor margin assessment is needed to reduce re‐excision rates in breast‐conserving surgery (BCS). Mapping the attenuation coefficient in optical coherence tomography (OCT) throughout a sample to create an image (attenuation imaging) is one promising approach. For the first time, three‐dimensional OCT attenuation imaging of human breast tissue microarchitecture using a wide‐field (up to ~45 × 45 × 3.5 mm) imaging system is demonstrated. Representative results from three mastectomy and one BCS specimen (from 31 specimens) are presented with co‐registered postoperative histology. Attenuation imaging is shown to provide substantially improved contrast over OCT, delineating nuanced features within tumors (including necrosis and variations in tumor cell density and growth patterns) and benign features (such as sclerosing adenosis). Additionally, quantitative micro‐elastography (QME) images presented alongside OCT and attenuation images show that these techniques provide complementary contrast, suggesting that multimodal imaging could increase tissue identification accuracy and potentially improve tumor margin assessment.     

Adaptive Boosting (AdaBoost)‐based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment

The current gold standard diagnostic test for colorectal cancer remains histological inspections of endoluminal neoplasia in biopsy specimens. However, biopsy site selection requires visual inspection of the bowel, typically with a white‐light endoscope. Therefore, this technique is poorly suited to detect small or innocuous‐appearing lesions. We hypothesize that an alternative modality—multiwavelength spatial frequency domain imaging (SFDI)—would be able to differentiate various colorectal neoplasia from normal tissue. In this ex vivo study of human colorectal tissues, we report the optical absorption and scattering signatures of normal, adenomatous polyp and cancer specimens. An abnormal vs. normal adaptive boosting (AdaBoost) classifier is trained to dichotomize tissue based on SFDI imaging characteristics, and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95 is achieved. We conclude that AdaBoost‐based multiwavelength SFDI can differentiate abnormal from normal colorectal tissues, potentially improving endoluminal screening of the distal gastrointestinal tract in the future.     

Quantitative IR microscopy and spectromics open the way to 3D digital pathology

Currently, only mass‐spectrometry (MS) microscopy brings a quantitative analysis of chemical contents of tissue samples in 3D. Here, the reconstruction of a 3D quantitative chemical images of a biological tissue by FTIR spectro‐microscopy is reported. An automated curve‐fitting method is developed to extract all intense absorption bands constituting IR spectra. This innovation benefits from three critical features: (1) the correction of raw IR spectra to make them quantitatively comparable; (2) the automated and iterative data treatment allowing to transfer the IR‐absorption spectrum into a IR‐band spectrum; (3) the reconstruction of an 3D IR‐band matrix (x, y, z for voxel position and a 4^th dimension with all IR‐band parameters). Spectromics, which is a new method for exploiting spectral data for tissue metadata reconstruction, is proposed to further translate the related chemical information in 3D, as biochemical and anatomical tissue parameters. An example is given with oxidative stress distribution and the reconstruction of blood vessels in tissues. The requirements of IR microscopy instrumentation to propose 3D digital histology as a clinical routine technology is briefly discussed.

     

Three-dimensional spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography and coronary angiography

We present a three-dimensional (3D) spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography (IVOCT) and digital subtraction angiography (DSA). Centerline of vessel in DSA images is exacted by multi-scale filtering, adaptive segmentation, morphology thinning and Dijkstra's shortest path algorithm. We apply the cross-correction between lumen shapes of IVOCT and DSA images and match their stenosis positions to realize co-registration. By matching the location and tangent direction of the vessel centerline of DSA images and segmented lumen coordinates of IVOCT along pullback path, 3D spatial models of vessel lumen are reconstructed. Using 1121 distinct positions selected from eight vessels, the correlation coefficient between 3D IVOCT model and DSA image in measuring lumen radius is 0.94% and 97.7% of the positions fall within the limit of agreement by Bland–Altman analysis, which means that the 3D spatial reconstruction IVOCT models and DSA images have high matching level.     

Mesoscopic fluorescence lifetime imaging: Fundamental principles,clinical applications and future directions

Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm.     

Improved accuracy of quantitative birefringence imaging by polarization sensitive OCT with simple noise correction and its application to neuroimaging

Polarization-sensitive optical coherence tomography (PS-OCT) enables three-dimensional imaging of biological tissues based on the inherent contrast provided by scattering and polarization properties. In fibrous tissue such as the white matter of the brain, PS-OCT allows quantitative mapping of tissue birefringence. For the popular PS-OCT layout using a single circular input state, birefringence measurements are based on a straight-forward evaluation of phase retardation data. However, the accuracy of these measurements strongly depends on the signal-to-noise ratio (SNR) and is prone to mapping artifacts when the SNR is low. Here we present a simple yet effective approach for improving the accuracy of PS-OCT phase retardation and birefringence measurements. By performing a noise bias correction of the detected OCT signal amplitudes, the impact of the noise floor on retardation measurements can be markedly reduced. We present simulation data to illustrate the influence of the noise bias correction on phase retardation measurements and support our analysis with real-world PS-OCT image data.     

Organic solvent-based tissue clearing techniques and their applications

Revealing the true structure of tissues and organs with tissue slicing technology is difficult since images reconstructed in three dimensions are easily distorted. To address the limitations in tissue slicing technology, tissue clearing has been invented and has recently achieved significant progress in three-dimensional imaging. Currently, this technology can mainly be divided into two types: aqueous clearing methods and solvent-based clearing methods. As one of the important parts of this technology, organic solvent-based tissue clearing techniques have been widely applied because of their efficient clearing speed and high clearing intensity. This review introduces the primary organic solvent-based tissue clearing techniques and their applications.     

Hyperspectral imaging and characterization of allergic contact dermatitis in the short‐wave infrared

Short‐wave infrared hyperspectral imaging is applied to diagnose and monitor a case of allergic contact dermatitis (ACD) due to poison ivy exposure in one subject. This approach directly demonstrates increased tissue fluid content in ACD lesional skin with a spectral signature that matches the spectral signature of intradermally injected normal saline. The best contrast between the affected and unaffected skin is achieved through a selection of specific wavelengths at 1070, 1340 and 1605 nm and combining them in a pseudo‐red‐green‐blue color space. An image derived from these wavelengths normalized to unaffected skin defines a “tissue fluid index” that may aid in the quantitative diagnosis and monitoring of ACD. Further clinical testing of this promising approach towards disease detection and monitoring with tissue fluid content quantification is warranted.     

Handheld volumetric manual compression‐based quantitative microelastography

Compression optical coherence elastography (OCE) typically requires a mechanical actuator to impart a controlled uniform strain to the sample. However, for handheld scanning, this adds complexity to the design of the probe and the actuator stroke limits the amount of strain that can be applied. In this work, we present a new volumetric imaging approach that utilizes bidirectional manual compression via the natural motion of the user's hand to induce strain to the sample, realizing compact, actuator‐free, handheld compression OCE. In this way, we are able to demonstrate rapid acquisition of three‐dimensional quantitative microelastography (QME) datasets of a tissue volume (6 × 6 × 1 mm³) in 3.4 seconds. We characterize the elasticity sensitivity of this freehand manual compression approach using a homogeneous silicone phantom and demonstrate comparable performance to a benchtop mounted, actuator‐based approach. In addition, we demonstrate handheld volumetric manual compression‐based QME on a tissue‐mimicking phantom with an embedded stiff inclusion and on freshly excised human breast specimens from both mastectomy and wide local excision (WLE) surgeries. Tissue results are coregistered with postoperative histology, verifying the capability of our approach to measure the elasticity of tissue and to distinguish stiff tumor from surrounding soft benign tissue.     

Double-flow convolutional neural network for rapid large field of view Fourier ptychographic reconstruction

Fourier ptychographic microscopy is a promising imaging technique which can circumvent the space-bandwidth product of the system and achieve a reconstruction result with wide field-of-view (FOV), high-resolution and quantitative phase information. However, traditional iterative-based methods typically require multiple times to get convergence, and due to the wave vector deviation in different areas, the millimeter-level full-FOV cannot be well reconstructed once and typically required to be separated into several portions with sufficient overlaps and reconstructed separately, which makes traditional methods suffer from long reconstruction time for a large-FOV (of the order of minutes) and limits the application in real-time large-FOV monitoring of live sample in vitro. Here we propose a novel deep-learning based method called DFNN which can be used in place of traditional iterative-based methods to increase the quality of single large-FOV reconstruction and reducing the processing time from 167.5 to 0.1125 second. In addition, we demonstrate that by training based on the simulation dataset with high-entropy property (Opt. Express 28, 24 152 [2020]), DFNN could has fine generalizability and little dependence on the morphological features of samples. The superior robustness of DFNN against noise is also demonstrated in both simulation and experiment. Furthermore, our model shows more robustness against the wave vector deviation. Therefore, we could achieve better results at the edge areas of a single large-FOV reconstruction. Our method demonstrates a promising way to perform real-time single large-FOV reconstructions and provides further possibilities for real-time large-FOV monitoring of live samples with sub-cellular resolution.     

Optoacoustic monitoring of water content in tissue phantoms and human skin

Skin water content monitoring is important for diagnostics and management of edema, dehydration, and other skin conditions as well as for cosmetic applications. Because optoacoustic (OA) technique has high (optical) contrast and (ultrasound) resolution and significant probing depth, it may be suitable for accurate, noninvasive water content monitoring in the skin. In this work we studied OA response from skin tissue phantoms and human wrist skin in the wavelength range from 1370 nm to 1650 nm using a novel, tunable OPO OA system. We identified optimal wavelengths for OA water content monitoring in different skin layers. The results of our study suggest that the OA technique may become a valuable, quantitative tool for accurate, high-resolution water content monitoring in the skin and other tissues and may find wide applications in dermatology, cosmetology, and tissue trauma management.     

Polarization‐dependent second‐harmonic generation for collagen‐based differentiation of breast cancer samples

Nonlinear optical imaging techniques have been widely used to reveal biological structures for accurate diagnosis at the cellular as well as the tissue level. In the present study, polarization‐dependent second‐harmonic generation (PSHG) was used to determine collagen orientation in breast cancer biopsy tissues (grades 0, I, II and III). The obtained data were processed using fast Fourier transform (FFT) analysis, while second‐harmonic generation (SHG) anisotropy and the “ratio parameter” values were also calculated. Such measurements were shown to be able to distinguish collagen structure modifications in different cancer grades tested. The analysis presented herein suggests that PSHG imaging could provide a quantitative evaluation of the tumor state and the distinction of malignant from benign breast tissues. The obtained results also allowed the development of a biophysical model, which can explain the aforementioned differentiations and is in agreement with the simulations relating the SHG anisotropy values with the mechanical tension applied to the collagen during cancer progression. The current approach could be a step forward for the development of new, nondestructive, label free optical diagnostic tools for cancer reducing the need of recalls and unnecessary biopsies, while potentially improving cancer detection rates.     

A new deep learning method for image deblurring in optical microscopic systems

Deconvolution is the most commonly used image processing method in optical imaging systems to remove the blur caused by the point‐spread function (PSF). While this method has been successful in deblurring, it suffers from several disadvantages, such as slow processing time due to multiple iterations required to deblur and suboptimal in cases where the experimental operator chosen to represent PSF is not optimal. In this paper, we present a deep‐learning‐based deblurring method that is fast and applicable to optical microscopic imaging systems. We tested the robustness of proposed deblurring method on the publicly available data, simulated data and experimental data (including 2D optical microscopic data and 3D photoacoustic microscopic data), which all showed much improved deblurred results compared to deconvolution. We compared our results against several existing deconvolution methods. Our results are better than conventional techniques and do not require multiple iterations or pre‐determined experimental operator. Our method has several advantages including simple operation, short time to compute, good deblur results and wide application in all types of optical microscopic imaging systems. The deep learning approach opens up a new path for deblurring and can be applied in various biomedical imaging fields.     

First experience in clinical application of hyperspectral endoscopy for evaluation of colonic polyps

Early detection and resection of adenomatous polyps prevents their progression to colorectal cancer (CRC), significantly improving patient outcomes. Polyps are typically identified and removed during white-light colonoscopy. Unfortunately, the rate of interval cancers that arise between CRC screening events remains high, linked to poor visualization of polyps during screening and incomplete polyp removal. Here, we sought to evaluate the potential of a hyperspectral endoscope (HySE) to enhance polyp discrimination for detection and resection. We designed, built and tested a new compact HySE in a proof-of-concept clinical study. We successfully collected spectra from three tissue types in seven patients undergoing routine colonoscopy screening. The acquired spectral data from normal tissue and polyps, both pre- and post- resection, were subjected to quantitative analysis using spectral angle mapping and machine learning, which discriminated the data by tissue type, meriting further investigation of HySE as a clinical tool.     

Ex vivo three-dimensional elemental imaging of mouse brain tissue block by laser-induced breakdown spectroscopy

Measurement and reconstruction of an elemental image of large brain tissue will be beneficial to the diagnosis of neurological brain diseases. Herein, laser-induced breakdown spectroscopy (LIBS) is introduced for three dimensional (3D) elemental analysis of paraffin-embedded mouse brain tissue blocks. It is used for the first time towards the mapping of mouse brain block samples. A micro-LIBS prototype is developed for brain elemental imaging and a layer-by-layer approach is used to reconstruct the 3D distribution of Ca, Mg, Na, Cu, and P in the brain tissue. Images are captured with 50 μm lateral resolution and 300 μm depth resolution. The images show that the reclamation area of the cortex surface is enriched with Ca and Mg. In contrast, the Cu distribution is circular and is found primarily in the entirety of the cerebral cortex for the paraffin-embedded brain samples. Elemental imaging results suggest that the highest P intensity is found in the cerebellum nearby the middle sagittal plane in the left-brain paraffin block. These preliminary results indicate that LIBS is a potentially powerful tool for elemental bioimaging of the whole brain and may further improve the understanding of complex brain mechanisms.     

Reduction in required volume of imaging data and image reconstruction time for adaptive-illumination Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a promising super-resolution computational imaging technology. It stitches a series of low-resolution (LR) images in the Fourier domain by an iterative method. Thus, it obtains a large field of view and high-resolution quantitative phase images. Owing to its capability to perform high-spatial bandwidth product imaging, FPM is widely used in the reconstruction of conventional static samples. However, the influence of the FPM imaging mechanism limits its application in high-speed dynamic imaging. To solve this problem, an adaptive-illumination FPM scheme using regional energy estimation is proposed. Starting with several captured real LR images, the energy distribution of all LR images is estimated, and select the measurement images with large information to perform FPM reconstruction. Simulation and experimental results show that the method produces efficient imaging performance and reduces the required volume of data to more than 65% while ensuring the quality of FPM reconstruction.