Capillary Refill Time (CRT) assesses peripheral perfusion in resource-limited settings. However, the repeatability and reproducibility of CRT measurements are limited for individuals with darker skin. This paper presents quantitative CRT measurements demonstrating good performance and repeatability across all Fitzpatrick skin phototypes. The study involved 22 volunteers and utilized controlled compression at 7 kPa, an RGB video camera, and cocircular polarized white LED light. CRT was determined by calculating the time constant of an exponential regression applied to the mean pixel intensity of the green (G) channel. An adaptive algorithm identifies the optimal regression region for noise reduction, and flags inappropriate readings. The results indicate that 80% of the CRT readings fell within a 20% range of the expected CRT value. The repetition standard deviation was 17%. These findings suggest the potential for developing reliable and reproducible quantitative CRT methods for robust measurements in patient triage, monitoring, and telehealth applications.

A document by Alexander E. Moskalensky. Click on the document to view its contents.

A computational modeling is employed for quantitative assessment of weld formation and area of tissue temperature necrosis during the human skin laser soldering. The evaluation is carried out depending on the components composition of using solders, including bovine serum albumin (BSA), indocyanine green (ICG), and carbon nanotubes (CNT), as well as the angle of incidence of laser light and its pulse duration. The influence of CNT on the change of thermodynamic characteristics of albumin denaturation and the rate of formation of the laser weld is investigated. The obtained results suggest to limit the duration of laser light pulse by temperature relaxation time to minimize transfer of thermal energy to reduce the heating of human skin tissues. The developed model has a great potential for further optimization of laser soldering of biological tissues technology with greater efficiency in minimizing the weld area.

During thyroid surgery fast and reliable intra-operative pathological feedback has the potential to avoid a two-stage procedure and significantly reduce health care costs in patients undergoing a diagnostic hemithyroidectomy (HT). We explored higher harmonic generation (HHG) microscopy, which combines second harmonic generation (SHG), third harmonic generation (THG), and multiphoton excited autofluorescence (MPEF) for this purpose. With a compact, portable HHG microscope, images of freshly excised healthy tissue, benign nodules (follicular adenoma) and malignant tissue (papillary carcinoma, follicular carcinoma and spindle cell carcinoma) were recorded. The images were generated on unprocessed tissue within minutes and show relevant morphological thyroid structures in good accordance with the histology images. The thyroid follicle architecture, cells, cell nuclei (THG), collagen organization (SHG) and the distribution of thyroglobulin and/or thyroid hormones T3 or T4 (MPEF) could be visualized. We conclude that SHG/THG/MPEF imaging is a promising tool for clinical intraoperative assessment of thyroid tissue.

Optical coherence tomography angiography (OCTA) has successfully demonstrated its viability for clinical applications in dermatology. Due to the high optical scattering property of skin, extracting high-quality OCTA images from skin tissues requires at least six-repeated scans. While the motion artifacts from the patient and the free hand-held probe can lead to a low-quality OCTA image. Our deep-learning-based scan pipeline enables fast and high-quality OCTA imaging with 0.3-second data acquisition. We utilize a fast scanning protocol with a 60 µm/pixel spatial interval rate and introduce Angiography-Reconstruction-Transformer (ART) for 4× super-resolution of low transverse resolution OCTA images. The ART outperforms state-of-the-art networks in OCTA image super-resolution and provides a lighter network size. ART can restore microvessels while reducing the processing time by 85%, and maintaining improvements in structural similarity and peak-signal-to-noise ratio. This study represents that ART can achieve fast and flexible skin OCTA imaging while maintaining image quality.

Histopathology for tumor margin assessment is time-consuming and expensive. High-resolution full-field optical coherence tomography (FF-OCT) images fresh tissues rapidly at cellular resolution, facilitating evaluation. We imaged fresh ex vivo skin tissues (normal and neoplastic) from Mohs surgery. FF-OCT features were defined and diagnostic accuracy for malignancies was performed by the two experts OCT readers via a blinded analysis. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 BCCs and 17 SCCs). The average reader diagnostic accuracy was 88.1%, a sensitivity of 93.7%, and a specificity of 58.3%. The AI model achieved a diagnostic accuracy of 87.6%±5.9%, sensitivity of 93.2%±2.1%, and specificity of 81.2%±9.2%. A mean intersection-over-union of 60.3%±10.1% was achieved delineating nodular BCC from normal. We envision FF-OCT for rapid evaluation of surgical margins and AI tumor detection leading to widespread technique integration.

The Optical Kerr Effect was investigated for the first time in biological tissues. This nonlinear optical effect was explored in both human brain and avian breast tissues using a time-resolved femtosecond pump-probe Optical Kerr Gate. The Optical Kerr Effect describes the nonlinear change in a material’s refractive index in response to an electric field. It is fundamental to spectral effects that are commonly used in biological science. The tested tissues produced a unique ultrafast (700-800 fs) doubled peaked Kerr signal, which is indicative of temporal interplay between the different components (electronic plasma, and molecular) that make up the Kerr index. Temporal properties varied between samples suggesting that this method could be used as a new diagnostic. Understanding this Kerr behavior can help improve current spectral diagnostic techniques, such as SRS, and potentially create a new Kerr based biopsy method for the detection of diseased tissues, such as cancer and Alzheimer’s.

The aim of this study was to develop a clinical SWIR reflectance handpiece to assess the activity of lesions on the occlusal surfaces. The time-resolved reflectivity of ten active and ten arrested occlusal caries lesions on extracted teeth was monitored at 1470 nm using a benchtop system and a modified clinical prototype during forced air drying. The presence of a highly mineralized surface zone measured with microcomputed tomography (microCT) was used to indicate lesion activity. Multiple kinetic parameters were extracted from the acquired SWIR time versus intensity dehydration curves and used to assess lesion activity. Three parameters: delay, %I fin, and rate calculated from the SWIR dehydration curves were significantly different (P < 0.05) between active and arrested lesions. The modified clinical probe was able to completely dehydrate all the active lesion areas in the occlusal pits and fissures in less than 30 seconds.

Colorectal cancer is one of the most prevalent malignancies worldwide, and long-term chronic colitis is considered to be an important factor in the etiological study of colorectal cancer. As an emerging detection technology, the non-invasive, non-ionizing, and fingerprint spectroscopic features of terahertz technology have tremendous application prospects in disease diagnosis. Therefore, this study aims to explore the value of terahertz technology in colitis-related cancers by constructing an inflammation-associated mouse colorectal cancer model. In this paper, we found that the terahertz spectroscopy technique can effectively distinguish colitis-associated cancer from normal tissue, and for the first time, we searched that 1.8 THz may be the best terahertz frequency for diagnosing colorectal cancer in mice, suggesting that we can use the terahertz technique for rapid diagnosis of colorectal cancer histopathology.

We report on the spectroscopic investigation of common bacteria encountered in biopharmaceutical industries with spectroscopic definition and specificity using mid-infrared laser spectroscopy. This study describes the detection of three different bacteria species using quantum cascade laser spectroscopy coupled to a grazing angle probe (QCL-GAP). Stainless steel substrates were used as support for the bacterial samples. QCL-GAP spectroscopy was assisted by multivariate analysis (MVA) to assemble a powerful spectroscopic technique with classification, identification, and quantification resources. The bacterial species analyzed, Staphylococcus aureus, Staphylococcus epidermidis, and Micrococcus luteus, were used to challenge the technique’s capability to discriminate microorganisms from the same family. Principal component analysis and partial least squares-discriminant analysis differentiated between the bacterial species using QCL-GAP. Spectral differences in the bacterial membrane were used to determine if these microorganisms were present in the samples analyzed. Results herein provided effective discrimination for the bacteria under study with high sensitivity and specificity values.

Metformin hydrochloride, an antihyperglycemic agent, and sulindac, a nonsteroidal anti-inflammatory drug, are FDA-approved drugs known to exert anticancer effects. Previous studies demonstrated sulindac and metformin’s anticancer properties through mitochondrial dysfunction and inhibition of mitochondrial electron transport chain (ETC) complex I, as well as key signaling pathways. In this study, various drugs were adminsitered to A549 lung cancer cells, and results revealed that a combination of sulindac and metformin enhanced cell death compared to administration of the drugs separately. To measure superoxide production over time, we employed a time-lapse fluorescence imaging technique using mitochondrial-targeted hydroethidine. Fluorescence microscopy data showed largest increases in superoxide production in the combination treatment of metformin and sulindac. Results showed significant differences between the combined drug treatment and control groups, as well as between the positive control and control groups. This approach can be utilized to quantify anticancer efficacy of drugs, creating possibilities for additional therapeutic options.

The objective of this study is to evaluate the effect of photobiomodulation (PBM) on pain control during pterygomandibular puncture. A patient received anesthesia on both sides of the mouth in a randomized manner. On the right side, an 808nm infrared low-level laser was applied before local anesthesia. On the left side, a sham laser was applied using the same technique. There was a 50% reduction in pain levels on the PBM-treated side compared to the sham PBM side, as measured by the visual analog scale. Sensitivity tests revealed that anesthesia was more effective on the PBM side. There was no significant difference in blood pressure before and after anesthesia on either side. While these findings are based on a single case report, they suggest that photobiomodulation before anesthesia may alleviate puncture pain associated with anesthesia. Nevertheless, further well-designed clinical trials are necessary to confirm the effectiveness of this complementary therapy.

The cochlea forms a key element of the human auditory system in the temporal bone. Damage to the cochlea continues to produce significant impairment for sensory reception of environmental stimuli. To improve this impairment, the optical cochlear implant forms a new research approach. A prerequisite for this method is to understand how light propagation, as well as scattering, reflection and absorption, takes place within the cochlea. We offer a method to study the light distribution in the human cochlea through phantom materials and Monte-Carlo simulations. The calculation of an angular distribution after scattering requires a phase function. Often approximate functions like Henyey-Greenstein, two-term Henyey-Greenstein or Legendre polynomial decompositions are used as phase function. An alternative is to exactly calculate a Mie distribution for each scattering event. This method provides a better fit to the data measured in this work.

Vascular network labeling in transparent tissues provides more complete information on blood vessels. To achieve a fast and efficient method for vascular network labeling in transparent tissues, we compared various vascular labeling methods under different tissue clearing protocols. FITC-dextran labeling and CUBIC cleaning treatment were found to be the best options for vascular network labeling in cleared mouse tissues. Satisfactory labeling of vascular networks in various organs can be achieved by selecting FITC-dextran with different molecular weights and different administration methods.

For patients with acute ischemic stroke, histological quantification of thrombus composition provides evidence for determining appropriate treatment. However, the traditional manual segmentation of stained thrombi is laborious and inconsistent. In this study, we propose a label-free method that combines optical diffraction tomography (ODT) and deep learning (DL) to automate the histological quantification process. The DL model classifies ODT image patches with 95% accuracy, and the collective prediction generates a whole-slide map of red blood cells and fibrin. The resulting whole-slide composition displays an average error of 1.1% and does not experience staining variability, facilitating faster analysis with reduced labor. The present approach will enable rapid and quantitative evaluation of blood clot composition, expediting the preclinical research and diagnosis of cardiovascular diseases.

To alleviate the ill-posed of the inverse problem in Fluorescent molecular tomography (FMT), many regularization methods based on L 2 or L 1 norm have been proposed. Whereas, the quality of regularization parameters affect the performance of the reconstruction algorithm. Some classical parameter selection strategies usually need initialization of parameter range and high computing costs, which is not universal in the practical application of FMT. In this paper, an universally applicable adaptive parameter selection method based on maximizing the probability of data (MPD) strategy was proposed. This strategy used maximum a posteriori (MAP) estimation and maximum likelihood (ML) estimation to establish a regularization parameters model. The stable optimal regularization parameters can be determined by multiple iterative estimates. Numerical simulations and in vivo experiments show that MPD strategy can obtain stable regularization parameters for both regularization algorithms based on L 2 or L 1 norm and achieve good reconstruction performance.

We present a method to use a birefringent crystal for generating two illumination beams in a digital scanned laser light-sheet microscopy (DSLM) system. Upon this, a conventional confocal DSLM can be easily upgraded to a dual-slit confocal DSLM with two-fold imaging speed. We have implemented this method to our bidirectional DSLM system, locating two identical calcite crystals on both illumination paths from both sides of the sample. The neurons of in vivo larval zebrafish have been fast imaged with sterling image quality, especially ~2.5 times higher contrast, compared to the conventional DSLM.

A document by Caio Calarga C. Click on the document to view its contents.