Journal of Biomedical Optics最新文献

Significance: Chronic or surgical wound infections in healthcare remain a worldwide problem without satisfying options. Systemic or topical antibiotic use is an inadequate solution, given the increase in antimicrobial-resistant microbes. Hence, antibiotic-free alternatives are needed. Antimicrobial photodynamic inactivation (aPDI) has been shown to be effective in wound disinfection. Among the impediments to the wide utility of aPDI for wounds is the high variability in reported photosensitizer and light dose to be effective and unintentional detrimental impact on the wound closure rates. Additionally, the time required by the healthcare professional to deliver this therapy is excessive in the present form of delivery.

Aim: We reviewed the dose ranges for various photosensitizers required to achieve wound disinfection or sterilization while not unintentionally inhibiting wound closure through concomitant photobiomodulation (PBM) processes.

Approach: To allow comparison of aPDI or PBM administered doses, we employ a unified dose concept based on the number of absorbed photons per unit volume by the photosensitizer or cytochrome C oxidase for aPDI and PBM, respectively.

Results: One notes that for current aPDI protocols, the absorbed photons per unit volume for wound disinfection or sterilization can lead to inhibiting normal wound closure through PBM processes.

Conclusion: Options to reduce the dose discrepancy between effective aPDI and PBM are discussed.

Significance: It is well known and accepted that the normal mitochondrial function in all cells in any organism is critical for the maintenance of cellular homeostasis. The development of in vivo technology to monitor mitochondrial function using nicotine-amide adenine dinucleotide (NADH) fluorescence started in the early 1950s. Until the early 1970s, the technology used for the light transfer between the light source and the monitored tissue as well as the detection system was very rigid and complicated. Monitoring of mitochondrial NADH redox states in vivo using the fluorescence approach could use a few techniques to transmit the light between the fluorometer and the monitored tissue.

Aim: I describe the introduction of optical fibers as a tool to illuminate the monitored tissue as well as the light emitted from the tissue. I also present the advantages of using optical fibers.

Approach: I describe in detail the introduction of ultraviolet (UV) transmitting optical fibers into the NADH monitoring system using various experimental protocols. The contact between the fiber optic probe and the monitored brain tissue was done by a special cannula cemented to the skull after removing a disk of bone in the parietal bone of the skull. In the same brain cannula, stainless steel electrodes, for electrocortical activity monitoring, were embedded in the wall of the light guide holder. The light guide holder was cemented to the skull by dental acrylic cement.

Results: Using the fiber optic probe to monitor NADH fluorescence together with microcirculatory blood flow measured by laser Doppler flowmeter provided the new very unique types of results not published before.

Conclusions: The introduction of UV-transmitting optical fibers, 50 years ago, to monitor tissue mitochondrial redox state opened up a new era in understanding the energy metabolism of tissues under in vivo conditions and in real time.

Significance: Protoporphyrin IX (PpIX) delayed fluorescence (DF) is inversely related to the oxygen present in tissues and has potential as a novel biomarker for surgical guidance and real-time tissue metabolism assessment. Despite the unique promise of this technique, its successful clinical translation is limited by the low intensity emitted.

Aim: We developed a systematic study of ways to increase the PpIX DF signal through acquisition sampling changes, allowing optimized imaging at video rates.

Approach: To accomplish signal increase, time-gating signal compression was achieved through changes in pulse frequency and power density, using sampling rates that are faster than the decay rate of the signal. The increased signal yield was tested and validated in vitro and then demonstrated in vivo, with comparison to settings that sample the full lifetime emission decay.

Results: Results in vitro and in vivo demonstrated that optimized timing could increase the detected intensity by a factor of 7. The images showed results that were superior than when sampling the full DF lifetime decay.

Conclusions: The proposed timing optimization enhances PpIX-based DF real-time imaging of tissue hypoxia. By increasing sampling frequency and adjusting the acquisition gate and pulse width, the collected signal intensity improved sevenfold, demonstrated both in vitro and in vivo. The technique was shown to enable better visualization of small and anatomically challenging hypoxic structures. The improved target-to-background ratio and compatibility with pressure-enhanced sensing of tissue oxygen technique were demonstrated.

Significance: The acetowhitening effect of acetic acid (AA) enhances light scattering of cell nuclei, an effect that has been widely leveraged to facilitate tissue inspection for (pre)cancerous lesions. Here, we show that a concomitant effect of acetowhitening-changes in refractive index composition-yields nuclear contrast enhancement in quantitative phase imaging (QPI) of thick tissue samples.

Aim: We aim to explore how changes in refractive index composition during acetowhitening can be captured through a novel epi-mode 3D QPI technique called quantitative oblique back-illumination microscopy (qOBM). We also aim to demonstrate the potential of using a machine learning-based approach to convert qOBM images of fresh tissues into virtually AA-stained images.

Approach: We implemented qOBM, an imaging technique that allows for epi-mode 3D QPI to observe phase changes induced by AA in thick tissue samples. We focus on detecting nuclear contrast changes caused by AA in mouse brain samples. As a proof of concept, we also applied a Cycle-GAN algorithm to convert the acquired qOBM images into virtually AA-stained images, simulating the effect of AA staining.

Results: Our findings demonstrate that AA-induced acetowhitening leads to significant nuclear contrast enhancement in qOBM images of thick tissue samples. In addition, the Cycle-GAN algorithm successfully converted qOBM images into virtually AA-stained images, further facilitating the nuclear enhancement process without any physical stains.

Conclusions: We show that the acetowhitening effect of acetic acid induces changes in refractive index composition that significantly enhance nuclear contrast in QPI. The application of qOBM with AA, along with the use of a Cycle-GAN algorithm to virtually stain tissues, highlights the potential of this approach for advancing label-free and slide-free, ex vivo, and in vivo histology.

Significance: Accurate identification between pathologic (e.g., tumors) and healthy brain tissue is a critical need in neurosurgery. However, conventional surgical adjuncts have significant limitations toward achieving this goal (e.g., image guidance based on pre-operative imaging becomes inaccurate up to 3 cm as surgery proceeds). Hyperspectral imaging (HSI) has emerged as a potential powerful surgical adjunct to enable surgeons to accurately distinguish pathologic from normal tissues.

Aim: We review HSI techniques in neurosurgery; categorize, explain, and summarize their technical and clinical details; and present some promising directions for future work.

Approach: We performed a literature search on HSI methods in neurosurgery focusing on their hardware and implementation details; classification, estimation, and band selection methods; publicly available labeled and unlabeled data; image processing and augmented reality visualization systems; and clinical study conclusions.

Results: We present a detailed review of HSI results in neurosurgery with a discussion of over 25 imaging systems, 45 clinical studies, and 60 computational methods. We first provide a short overview of HSI and the main branches of neurosurgery. Then, we describe in detail the imaging systems, computational methods, and clinical results for HSI using reflectance or fluorescence. Clinical implementations of HSI yield promising results in estimating perfusion and mapping brain function, classifying tumors and healthy tissues (e.g., in fluorescence-guided tumor surgery, detecting infiltrating margins not visible with conventional systems), and detecting epileptogenic regions. Finally, we discuss the advantages and disadvantages of HSI approaches and interesting research directions as a means to encourage future development.

Conclusions: We describe a number of HSI applications across every major branch of neurosurgery. We believe these results demonstrate the potential of HSI as a powerful neurosurgical adjunct as more work continues to enable rapid acquisition with smaller footprints, greater spectral and spatial resolutions, and improved detection.

Significance: Current methods for complex conjugate removal (CCR) in frequency-domain optical coherence tomography (FD-OCT) often require additional hardware components, which increase system complexity and cost. A software-based solution would provide a more efficient and cost-effective alternative.

Aim: We aim to develop a deep learning approach to effectively remove complex conjugate artifacts (CCAs) from OCT scans without the need for extra hardware components.

Approach: We introduce a deep learning method that employs generative adversarial networks to eliminate CCAs from OCT scans. Our model leverages both conventional intensity images and phase images from the OCT scans to enhance the artifact removal process.

Results: Our CCR-generative adversarial network models successfully converted conventional OCT scans with CCAs into artifact-free scans across various samples, including phantoms, human skin, and mouse eyes imaged in vivo with a phase-stable swept source-OCT prototype. The inclusion of phase images significantly improved the performance of the deep learning models in removing CCAs.

Conclusions: Our method provides a low-cost, data-driven, and software-based solution to enhance FD-OCT imaging capabilities by the removal of CCAs.

Significance: Developments of anti-gametocyte drugs have been delayed due to insufficient understanding of gametocyte biology. We report a systematic workflow of data processing algorithms to quantify changes in the absorption spectrum and cell morphology of single malaria-infected erythrocytes. These changes may serve as biomarkers instrumental for the future development of antimalarial strategies, especially for anti-gametocyte drug design and testing. Image-based biomarkers may also be useful for nondestructive, label-free malaria detection and drug efficacy evaluation in resource-limited communities.

Aim: We extend the application of hyperspectral microscopy to provide detailed insights into gametocyte stage progression through the quantitative analysis of absorbance spectra and cell morphology in malaria-infected erythrocytes.

Approach: Malaria-infected erythrocytes at asexual and different gametocytogenesis stages were imaged through hyperspectral confocal microscopy. The preprocessing of the hyperspectral data cubes to transform them to color images and spectral angle mapper (SAM) analysis were first used to segment hemoglobin (Hb)- and hemozoin (Hz)-abundant areas within the host erythrocytes. Correlations between changes in cell morphology and increasing Hz-abundant areas of the infected erythrocytes were then examined to test their potential as optical biomarkers to determine the progression of infection, involving transitions from asexual to various gametocytogenesis stages.

Results: Following successful segmentation of Hb- and Hz-abundant areas in malaria-infected erythrocytes through SAM analysis, a modest correlation between the segmented Hz-abundant area and cell shape changes over time was observed. A significant increase in both the areal fraction of Hz and the ellipticity of the cell confirms that the Hz fraction change correlates with the progression of gametocytogenesis.

Conclusions: Our workflow enables the quantification of changes in host cell morphology and the relative contents of Hb and Hz at various parasite growth stages. The quantified results exhibit a trend that both the segmented areal fraction of intracellular Hz and the ellipticity of the host cell increase as gametocytogenesis progresses, suggesting that these two metrics may serve as useful biomarkers to determine the stage of gametocytogenesis.

Significance: I explore hyperspectral imaging, a rapid and noninvasive technique with significant potential in biometrics and medical diagnosis. Personal identification was performed using cross-sectional hyperspectral images of palms, offering a simpler and more robust method than conventional vascular pattern identification methods.

Aim: I aim to demonstrate the potential of local cross-sectional hyperspectral palm images to identify individuals with high accuracy.

Approach: Hyperspectral imaging of palms, artificial intelligence (AI)-based region of interest (ROI) detection, feature vector extraction, and dimensionality reduction were utilized to validate personal identification accuracy using the area under the curve (AUC) and equal error rate (EER).

Results: The feature vectors extracted by the proposed method demonstrated higher intra-cluster similarity when the clustering data were reduced through uniform manifold approximation and projection compared with principal component analysis and $t$ -distributed stochastic neighbor embedding. A maximum AUC of 0.98 and an EER of 0.04% were observed.

Conclusions: I proposed a biometric method using cross-sectional hyperspectral imaging of human palms. The procedure includes AI-based ROI detection, feature extraction, dimension reduction, and intra- and inter-subject matching using Euclidean distances as a discriminant function. The proposed method has the potential to identify individuals with high accuracy.

Significance: Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. These areas can be assessed by monitoring cerebral hemodynamics and metabolism. Robust quantification of these biomarkers is complicated to perform during neurosurgery due to the critical context of the operating room. In actual devices, the inhomogeneities of the optical properties of the exposed brain cortex are poorly taken into consideration, which introduce quantification errors of biomarkers of brain functionality. Moreover, the best choice of spectral configuration is still based on an empirical approach.

Aim: We propose a digital instrument simulator to optimize the development of hyperspectral systems for intraoperative brain mapping studies. This simulator can provide realistic modeling of the cerebral cortex and the identification of the optimal wavelengths to monitor cerebral hemodynamics (oxygenated ${\mathrm{HbO}}_2$ and deoxygenated hemoglobin Hb) and metabolism (oxidized state of cytochromes $b$ and $c$ and cytochrome-c-oxidase oxCytb, oxCytc, and oxCCO).

Approach: The digital instrument simulator is computed with white Monte Carlo simulations of a volume created from a real image of exposed cortex. We developed an optimization procedure based on a genetic algorithm to identify the best wavelength combinations in the visible and near-infrared range to quantify concentration changes in ${\mathrm{HbO}}_2$ , Hb, oxCCO, and the oxidized state of cytochrome $b$ and $c$ (oxCytb and oxCytc).

Results: The digital instrument allows the modeling of intensity maps collected by a camera sensor as well as images of path length to take into account the inhomogeneities of the optical properties. The optimization procedure helps to identify the best wavelength combination of 18 wavelengths that reduces the quantification errors in ${\mathrm{HbO}}_2$ , Hb, and oxCCO by 47%, 57%, and 57%, respectively, compared with the gold standard of 121 wavelengths between 780 and 900 nm. The optimization procedure does not help to resolve changes in cytochrome $b$ and $c$ in a significant way but helps to better resolve oxCCO changes.

Conclusions: We proposed a digital instrument simulator to optimize the development of hyperspectral systems for intraoperative brain mapping studies. This digital instrument simulator and this optimization framework could be used to optimize the design of hyperspectral imaging devices.