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Significance: The reliability of functional near-infrared spectroscopy (fNIRS) measurements is reduced by systemic physiology. Short-channel regression algorithms aim at removing systemic “noise” by subtracting the signal measured at a short source–detector separation (mainly scalp hemodynamics) from the one of a long separation (brain and scalp hemodynamics). In literature, incongruent approaches on the selection of the optimal regressor signal are reported based on different assumptions on scalp hemodynamics properties. Aim: We investigated the spatial and temporal distribution of scalp hemodynamics over the sensorimotor cortex and evaluated its influence on the effectiveness of short-channel regressions. Approach: We performed hand-grasping and resting-state experiments with five subjects, measuring with 16 optodes over sensorimotor areas, including eight 8-mm channels. We performed detailed correlation analyses of scalp hemodynamics and evaluated 180 hand-grasping and 270 simulated (overlaid on resting-state measurements) trials. Five short-channel regressor combinations were implemented with general linear models. Three were chosen according to literature, and two were proposed based on additional physiological assumptions [considering multiple short channels and their Mayer wave (MW) oscillations]. Results: We found heterogeneous hemodynamics in the scalp, coming on top of a global close-to-homogeneous behavior (correlation 0.69 to 0.92). The results further demonstrate that short-channel regression always improves brain activity estimates but that better results are obtained when heterogeneity is assumed. In particular, we highlight that short-channel regression is more effective when combining multiple scalp regressors and when MWs are additionally included. Conclusion: We shed light on the selection of optimal regressor signals for improving the removal of systemic physiological artifacts in fNIRS. We conclude that short-channel regression is most effective when assuming heterogeneous hemodynamics, in particular when combining spatial- and frequency-specific information. A better understanding of scalp hemodynamics and more effective short-channel regression will promote more accurate assessments of functional brain activity in clinical and research settings., Neurophotonics, 7 (03)

New increasingly complex in vitro cancer cell models are being developed. These new models seem to represent the cell behavior in vivo more accurately and have better physiological relevance than prior models. An efficient testing method for selecting the most optimal drug treatment does not exist to date. One proposed solution to the problem involves isolation of cancer cells from the patients' cancer tissue, after which they are exposed to potential drugs alone or in combinations to find the most optimal medication. To achieve this goal, methods that can efficiently quantify and analyze changes in tested cell are needed. Our study aimed to detect and segment cells and structures from cancer cell cultures grown on vascular structures in phase-contrast microscope images using U-Net neural networks to enable future drug efficacy assessments. We cultivated prostate carcinoma cell lines PC3 and LNCaP on the top of a matrix containing vascular structures. The cells were imaged with a Cell-IQ phase-contrast microscope. Automatic analysis of microscope images could assess the efficacy of tested drugs. The dataset included 36 RGB images and ground-truth segmentations with mutually not exclusive classes. The used method could distinguish vascular structures, cells, spheroids, and cell matter around spheroids in the test images. Some invasive spikes were also detected, but the method could not distinguish the invasive cells in the test images. publishedVersion

Although the mortality rate of breast cancer has been reduced with the introduction of screening mammography, many women undergo unnecessary subsequent examinations due to inconclusive diagnoses. Therefore, spatial resolution and soft tissue contrast must meet very high standards. The former is necessary in order to be able to detect and distinguish closely spaced microcalcifications from each other. Thus, a high spatial resolution is demanded. Superposition of anatomical structures especially within dense breasts in conjunction with the inherently low soft tissue contrast of absorption images compromises image quality. This can be overcome by phase-contrast imaging. In this study, we analyze the spatial resolution of grating-based multimodal mammography dose-dependently using a mammographic phantom and one freshly dissected mastectomy specimen at an inverse Compton X-ray source. Here, the main focus was on estimating the spatial resolution with the sample in the beam path and discussing benefits and drawbacks of the method used as well as the estimation of the mean glandular dose. Finally, the possibility of improving the spatial resolution is investigated by comparison of the monochromatic grating-based mammography with the standard one. In almost all cases, the spatial resolution is higher in our proposed approach while the dose can be significantly reduced. Additionally, phase-contrast imaging helps to improve the detection of tumor lesions

Scanning laser ophthalmoscopes (SLOs) have the potential to perform high speed, high contrast, functional imaging of the human retina for diagnosis and follow-up of retinal diseases. Commercial SLOs typically use a monochromatic laser source or a superluminescent diode for imaging. Multispectral SLOs using an array of laser sources for spectral imaging have been demonstrated in research settings, with applications mainly aiming at retinal oxygenation measurements. Previous SLO-based oximetry techniques are predominantly based on wavelengths that depend on laser source availability. We describe an SLO system based on a supercontinuum (SC) source and a double-clad fiber using the single-mode core for illumination and the larger inner cladding for quasi-confocal detection to increase throughput and signal-to-noise ratio. A balanced detection scheme was implemented to suppress the relative intensity noise of the SC source. The SLO produced dual wavelength, high-quality images at 10 frames / s with a maximum 20 deg imaging field-of-view with any desired combination of wavelengths in the visible spectrum. We demonstrate SLO-based dual-wavelength oximetry in vessels down to 50 μm in diameter. Reproducibility was demonstrated by performing three different imaging sessions of the same volunteer, 8 min apart. Finally, by performing a wavelength sweep between 485 and 608 nm, we determined, for our SLO geometry, an approximately linear relationship between the effective path length of photons through the blood vessels and the vessel diameter..

The goal of understanding the architecture of neural circuits at the synapse level with a brain-wide perspective has powered the interest in high-speed and large field-of-view volumetric imaging at subcellular resolution. Here, we developed a method combining tissue expansion and light-sheet fluorescence microscopy to allow extended volumetric super resolution high-speed imaging of large mouse brain samples. We demonstrate the capabilities of this method by performing two color fast volumetric super resolution imaging of mouse CA1 and dentate gyrus molecular-, granule cell-, and polymorphic layers. Our method enables an exact evaluation of granule cell and neurite morphology within the context of large cell ensembles spanning several orders of magnitude in resolution. We found that imaging a brain region of 1 mm 3 in super resolution using light-sheet fluorescence expansion microscopy is about 17-fold faster than imaging the same region by a current state-of-the-art high-resolution confocal laser scanning microscope.

Significance: Parallel phase-shifting digital holographic microscope (PPSDHM) is powerful for three-dimensional (3D) measurements of dynamic specimens. However, the PPSDHM reported previously was directly fixed on the optical bench and imposed difficulties case, thus it is required to modify the specification of the microscope or transport the microscope to another location. Aim: We present a modularized PPSDHM. We construct the proposed PPSDHM and demonstrate the 3D measurement capability of the PPSDHM. Approach: The PPSDHM was designed as an inverted microscope to record transparent objects and modularized by integrating the optical elements of the PPSDHM on an optical breadboard. To demonstrate the effectiveness of the PPSDHM, we recorded a 3D motion-picture of moving Volvoxes at 1000 frames/s and carried out 3D tracking of the Volvoxes. Results: The PPSDHM was practically realized and 3D images of objects were successfully reconstructed from holograms recorded with a single-shot exposure. The 3D trajectories of Volvoxes were obtained from the reconstructed images. Conclusions: We established a modularized PPSDHM that is capable of 3D image acquisition by integrating the optical elements of the PPSDHM on an optical breadboard. The recording capability of 3D motion-pictures of dynamic specimens was experimentally demonstrated by the PPSDHM.

pA stable multimodal system is developed by combining two common-path digital holographic microscopes (DHMs): coherent and incoherent, for simultaneous recording and retrieval of three-dimensional (3-D) phase and 3-D fluorescence imaging (FI), respectively, of a biological specimen. The 3-D FI is realized by a single-shot common-path off-axis fluorescent DHM developed recently by our group. In addition, we accomplish, the phase imaging by another single-shot, highly stable common-path off-axis DHM based on a beam splitter. In this DHM configuration, a beam splitter is used to divide the incoming object beam into two beams. One beam serves as the object beam carrying the useful information of the object under study, whereas another beam is spatially filtered at its Fourier plane by using a pinhole and it serves as a reference beam. This DHM setup, owing to a common-path geometry, is less vibration-sensitive and compact, having a similar field of view but with high temporal phase stability in comparison to a two-beam Mach-Zehnder-type DHM. The performance of the proposed common-path DHM and the multimodal system is verified by conducting various experiments on fluorescent microspheres and fluorescent protein-labeled living cells of the mossitalicPhyscomitrella patens/italic. Moreover, the potential capability of the proposed multimodal system for 3-D live fluorescence and phase imaging of the fluorescent beads is also demonstrated. The obtained experimental results corroborate the feasibility of the proposed multimodal system and indicate its potential applications for the analysis of functional and structural behaviors of a biological specimen and enhancement of the understanding of physiological mechanisms and various biological diseases./p.

Successful outcomes of surgical cancer resection necessitate negative, cancer-free surgical margins. Currently, tissue samples are sent to pathology for diagnostic confirmation. Hyperspectral imaging (HSI) is an emerging, non-contact optical imaging technique. A reliable optical method could serve to diagnose and biopsy specimens in real-time. Using convolutional neural networks (CNNs) as a tissue classifier, we developed a method to use HSI to perform an optical biopsy of ex-vivo surgical specimens, collected from 21 patients undergoing surgical cancer resection. Training and testing on samples from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal aerodigestive tract tissues with an area under the curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity. Additionally, normal oral tissues can be sub-classified into epithelium, muscle, and glandular mucosa using a decision tree method, with an average AUC of 0.94, 90% accuracy, 93% sensitivity, and 89% specificity. After separately training on thyroid tissue, the CNN differentiates between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multi-nodular goiter (MNG) with an AUC of 0.93, 87% accuracy, 88% sensitivity, and 85% specificity. Classical-type papillary thyroid carcinoma is differentiated from benign MNG with an AUC of 0.91, 86% accuracy, 86% sensitivity, and 86% specificity. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multi-category diagnostic information for normal head-and-neck tissue, SCCa, and thyroid carcinomas. More patient data are needed in order to fully investigate the proposed technique to establish reliability and generalizability of the work.