Adaptive Optimization of Vascular-Targeted Photodynamic Therapy Efficiency Based on Hyperspectral-Photoacoustic Dual-Modality Imaging Feedback.

Vascular targeted photodynamic therapy (V-PDT) has been widely utilized for the prevention or treatment of vascular-related diseases, including age-related macular degeneration, port-wine stains and prostate cancer. In order to quantitative assessment the blood vessel damage during V-PDT, nude mice were implanted with Titanium dorsal skin window chambers for in vivo V-PDT studies. For treatments, various irradiances including 50, 75, 100 and 200 mW/cm2 provided by a 532 nm semiconductor laser were performed with the same total light dose of 30 J/cm2 after the mice were intravenously injection of Rose Bengal for 25 mg/Kg body weight. Laser speckle imaging and microscope were used to monitor blood flow dynamics and vessel constriction during and after V-PDT, respectively. The V-PDT induced vessel damages between different groups were compared. The results show that significant difference in blood vessel damage was found between the lower irradiances (50, 75 and 100 mW/cm2) and higher irradiance (200 mW/cm2), and the blood vessel damage induced by V-PDT is positively correlated with irradiance. This study implies that the optimization of irradiance is required for enhancing V-PDT therapeutic efficiency.

Vascular-targeted photodynamic therapy (V-PDT) offers great promise as a treatment modality for vascular-related diseases. The injury of targeted blood vessels correlates to the singlet oxygen generation, which is affected by dosimetric parameters, including photosensitizer concentration, hemoglobin oxygenation concentration, and blood flow velocity. In this study, we developed an optical imaging system that combining hyperspectral imaging (HSI), dual-wavelength reflection imaging (DWRI) (λ₁ = 500 nm and λ₂ = 660 nm) and laser speckle imaging (LSI). The capability for monitoring dosimetric parameters has been demonstrated for in vivo imaging of hemoporfin-mediated V-PDT in a dorsal skinfold window chamber model. The HSI allows for simultaneously monitoring the changes of photosensitizer concentration and vasoconstriction of blood vessels, while the DWRI and LSI were used to measure hemoglobin oxygenation concentration and blood flow velocity, respectively. This study suggests that our home-built optical imaging system holds the potential for assessing the V-PDT efficiency in vivo and optimizing the treatment protocol.

Objective: Monitoring emerging vascular-targeted photodynamic therapy (VTP) and understanding the time-dynamics of treatment effects remains challenging. We interrogated whether handheld multispectral optoacoustic tomography (MSOT) could noninvasively monitor the effect of VTP using WST11, a vascular-acting photosensitizer, on tumor tissues over time using a renal cell cancer mouse model. We also investigated whether MSOT illumination can induce VTP, to implement a single-modality theranostic approach.Materials and Methods: Eight BalB/c mice were subcutaneously implanted with murine renal adenocarcinoma cells (RENCA) on the flank. Three weeks later VTP was performed (10 min continuous illumination at 753 nm following intravenous infusion using WST11 or saline as control. Handheld MSOT images were collected prior to VTP administration and subsequently thereafter over the course of the first hour, at 24 and 48 h. Data collected were unmixed for blood oxygen saturation in tissue (SO2) based on the spectral signatures of deoxy- and oxygenated hemoglobin. Changes in oxygen saturation over time, relative to baseline, were examined by paired t-test for statistical significance (p < 0.05). In-vivo findings were corroborated by histological analyses of the tumor tissue.Results: MSOT is shown to prominently resolve changes in oxygen saturation in tumors within the first 20 min post WST11-VTP treatment. Within the first hour post-treatment, SO2 decreased by more than 60% over baseline (p < 0.05), whereas it remained unchanged (p > 0.1) in the sham-treated group. Moreover, unlike in the control group, SO2 in treated tumors further decreased over the course of 24 to 48 h post-treatment, concomitant with the propagation of profound central tumor necrosis present in histological analysis. We further show that pulsed MSOT illumination can activate WST11 as efficiently as the continuous wave irradiation employed for treatment.Conclusion: Handheld MSOT non-invasively monitored WST11-VTP effects based on the SO2 signal and detected blood saturation changes within the first 20 min post-treatment. MSOT may potentially serve as a means for both VTP induction and real-time VTP monitoring in a theranostic approach.

Vascular-targeted photodynamic therapy (V-PDT) is a promising treatment for benign vascular proliferative disorders. However, its efficacy largely depends on clinicians’ experience due to the lack of reliable methods for efficacy prediction. To provide an objective prediction approach, a hyperspectral imaging (HSI) system was developed to achieve real-time, non-invasive visualization of V-PDT dose parameters, including photosensitizer distribution, oxygen concentration, and vasoconstriction. Based on these measurements, we proposed a photodynamic therapy efficacy prediction index (PEPI)—a new metric that integrates the dynamic changes of both photosensitizer and oxygen throughout the treatment process, thereby providing critical insights for optimizing treatment protocols. Experimental results obtained in vivo using a dorsal skinfold window model demonstrate that the system accurately detects V-PDT dose parameters, and the proposed efficacy prediction parameters exhibit a strong positive correlation with treatment outcomes. This work highlights the potential of hyperspectral imaging to advance V-PDT toward more precise, individualized, and effective clinical applications, paving the way for its broader adoption in the field of precision medicine.

Objective:Monitoring dynamic changes during vascular targeted photodynamic therapy (V-PDT) for port-wine stains (PWS) is crucial for achieving an optimal therapeutic outcome. The present investigation is a preliminary research study designed to quantify and monitor the vascular parameters, e.g., blood volume fraction (Material and methods:A portable DRS detection system was developed with an appropriate source-detector distance of 520 μm for fiber-optic probe. The diffuse reflectance spectra from 450 to 800 nm in specific regions of interest (ROIs) within a PWS lesion were recorded before and 3, 5, 10, 15, and 20 min during V-PDT. In order to extract the optical properties and vascular parameters of the PWS lesion, a modified well-known diffusion theory model with a correction factor for the vessel package effect was employed to analyze the steady state-diffuse reflectance spectra.Results:The corrected reflectance spectra of the PWS lesion can be fitted very well with the modified diffusion theory model. Differences in pretreatment values ofConclusion:The ability of using DRS for quantifying and monitoring the

Hyperspectral imaging (HSI) techniques play an important role in the food industry for providing rapid, nondestructive, and chemical-free detection method, whereas a microscope can provide detailed information about the microstructure of a food item. As an emerging imaging spectroscopy technique, hyperspectral microscope imaging (HMI) technique combines the advantages of HSI with microscopic imaging and has been gradually applied in the food industry. This review introduces the principles of different kinds of HMI techniques, such as fluorescence HMI, visible/near-infrared HMI, Raman HMI, and infrared HMI. Moreover, detailed applications of HMI techniques are summarized, including evaluation of structures of nutrients, and detection of microorganisms and residues. On the other hand, some challenges and future trends in the applications of these techniques are also discussed. It is concluded that by integrating HSI with microscopy, HMI can not only provide both spectral and spatial information about food substances but also provide their chemical information at the molecular or cellular level. Therefore, HMI techniques have great potentials in nondestructive evaluation of structures of nutrients, and detection of microorganisms and residues for the food industry.

Microscopic hyperspectral imaging technology has been widely used in pathological analysis as it can obtain both spatial and spectral information of samples. However, most hyperspectral imaging systems can only capture images in a single field of view. Therefore, an image mosaic is one of the most important steps in a large-scale microscopic hyperspectral imaging system. This paper proposes a microscopic hyperspectral image (HSI) mosaic method based on Speeded-Up Robust Features (SURF) and linear synthesis to achieve large-scale HSIs. In contrast to other SURF-based image mosaic methods, the proposed method leverages both image content and coordinate information to improve the accuracy and stability of the image mosaic. In addition, multiple bands of HSIs with different texture information and grayscale are applied in image matching to take full advantage of spatial redundancy. Simultaneously, a blank microscopic HSI screening method is introduced in this paper to pick out a clearer blank image for better preprocessing, i.e. removing interference in the optical path and the interference of dust on slides. Finally, the preprocessed images are synthesized by linear-based synthesis methods due to their simple synthesis structure and better universality. Additionally, a file format, i.e. hyperslide, is defined for large-scale HSIs and can be browsed with HyperViewer software. Experimental results show that the proposed microscopic HSI mosaic method can obtain high-quality large-scale microscopic HSIs of tissue sections.

Heart pumps blood through the blood vessels to provide body with oxygen and nutrients. As the result, the blood flow, volume and oxygenation in arteries has a pulsatile nature. Measuring these pulsatile parameters enables more precise monitoring of oxygen metabolic rate and is thus valuable for researches and clinical applications. Photoacoustic microscopy (PAM) is a proven label-free method for in vivo measuring blood oxygenation at single blood vessel level. However, studies using PAM to observe the pulsatile nature of blood oxygenation in arteries were not reported. In this paper, we use optical-resolution PAM (OR-PAM) technology to study the blood oxygenation dynamics of pulsatile arteries. First, the ability of our OR-PAM system to accurately reflect the change of optical absorption in imaged objects is demonstrated in a phantom study. Then the system is used to image exposed cortical blood vessels of cat. The pulsatile nature of blood volume and oxygenation in arteries is clearly reflected in photoacoustic (PA) signals, whereas it’s not observable in veins. By using a multi-wavelength laser, the dynamics of the blood oxygenation of pulsatile arteries in cardiac cycles can be measured, based on the spectroscopic method.

Optical resolution photoacoustic microscopy (OR-PAM) possesses optical resolution and reveals endogenous optical absorption contrast, promising to be a valuable tool for in vivo microvascular imaging. In laser dermatology, OR-PAM can provide fruitful structural and functional information about the targeted microvascular lesions, such as their threedimensional (3D) morphology, precise location inside the tissue, and blood oxygenation within single vessels, which will facilitate accurate diagnosis and proper treatment. More importantly, the advantages of noninvasiveness and measurement consistency also permit OR-PAM to monitor the healing process of the laser-surgical wound noninvasively. In this work, we employed OR-PAM to monitor the healing process of microvascular lesions induced by nanosecond-pulsed laser. Our results indicate that OR-PAM could be a very useful tool in laser dermatology and laser microsurgery.

Inadequate blanching in fresh-cut potatoes causes browning during storage, but it cannot be detected immediately post-processing. Moreover, browning patterns during storage vary with blanching conditions. Therefore, predictive models based on hyperspectral imaging (HSI) and hyperspectral microscopy imaging (HMI) were developed to investigate blanching-dependent alterations in polyphenol oxidase (PPO) activity and total phenolic content (Rp2 = 0.71–0.87). HSI visualization maps showed a spatial concordance between regions exhibiting high residual PPO and storage-induced browning. HMI maps revealed mild and extensive browning in untreated samples due to an intact cellular structure delaying PPO-phenolic compound interactions, and strong but localized browning in insufficiently blanched samples due to partial cell disruption, which facilitated enzyme-substrate interactions. Contrastingly, sufficiently blanched samples did not exhibit browning due to PPO inactivation. These results suggest that HSI and HMI integration can function as a monitoring tool for early detection of browning and improve our understanding of the underlying mechanisms.

Modern optical microscopy1, including confocal microscopy, two-photon microscopy and optical coherence tomography (OCT), has revolutionized life sciences by providing detailed information of biological samples with cellular and subcellular resolutions, and has become an essential tool for biomedical research labs. However, optical microscopy typically has a limited penetration depth of ~1 mm in biological tissue due to strong optical scattering2, 3. Moreover, with respective contrast mechanisms, confocal and two-photon microscopy usually rely on fluorescent labeling of the samples and OCT still lacks sensitivity to many biological functions. In contrast, optical-resolution photoacoustic microscopy (OR-PAM) has emerged over the last decade as a complementary imaging tool to the existing optical microscopy by taking advantage of its unique optical absorption contrast4. By acoustically detecting the optical absorption in the tissue, OR-PAM has been proven a powerful tool for anatomical, functional and molecular imaging with endogenous or exogenous contrast agents. In particular, using hemoglobin as the endogenous optical absorber, OR-PAM currently represents the most sensitive blood detector and has been widely used for in vivo imaging of the blood perfusion and oxygenation, especially for cancer and brain studies. Nevertheless, the acoustic detection in OR-PAM is a double-edged sword; on the one hand, it provides a relatively deep penetration with one-way optical attenuation and negligible acoustic attenuation, but on the other hand, the acoustic detection typically needs a coupling medium, such as water and ultrasound gel, between the tissue surface and the ultrasound transducer. The need for acoustic coupling has become one of the major factors that has hindered the wide adoption of OR-PAM by biomedical researchers whenever the biological samples are not compatible with an aquatic environment. Therefore, contact-free detection of the photoacoustic signals (that is, without the need for acoustic coupling) has captured the attention of the photoacoustic imaging community and resulted in many exciting advancements. If successful, the contact-free photoacoustic technologies will free up the working space and greatly expand the territory of PAM applications.

The purpose of this study is to investigate hyperspectral microscopic imaging and deep learning methods for automatic detection of head and neck squamous cell carcinoma (SCC) on histologic slides. Hyperspectral imaging (HSI) cubes were acquired from pathologic slides of 18 patients with SCC of the larynx, hypopharynx, and buccal mucosa. An Inception-based two-dimensional convolutional neural network (CNN) was trained and validated for the HSI data. The automatic deep learning method was tested with independent data of human patients. This study demonstrated the feasibility of using hyperspectral microscopic imaging and deep learning classification to aid pathologists in detecting SCC on histologic slides.

.SignificanceAutomatic, fast, and accurate identification of cancer on histologic slides has many applications in oncologic pathology.AimThe purpose of this study is to investigate hyperspectral imaging (HSI) for automatic detection of head and neck cancer nuclei in histologic slides, as well as cancer region identification based on nuclei detection.ApproachA customized hyperspectral microscopic imaging system was developed and used to scan histologic slides from 20 patients with squamous cell carcinoma (SCC). Hyperspectral images and red, green, and blue (RGB) images of the histologic slides with the same field of view were obtained and registered. A principal component analysis-based nuclei segmentation method was developed to extract nuclei patches from the hyperspectral images and the coregistered RGB images. Spectra-based support vector machine and patch-based convolutional neural networks (CNNs) were implemented for nuclei classification. The CNNs were trained with RGB patches (RGB-CNN) and hyperspectral patches (HSI-CNN) of the segmented nuclei and the utility of the extra spectral information provided by HSI was evaluated. Furthermore, cancer region identification was implemented by image-wise classification based on the percentage of cancerous nuclei detected in each image.ResultsRGB-CNN, which mainly used the spatial information of nuclei, resulted in a 0.81 validation accuracy and 0.74 testing accuracy. HSI-CNN, which utilized the spatial and spectral features of the nuclei, showed significant improvement in classification performance and achieved 0.89 validation accuracy as well as 0.82 testing accuracy. Furthermore, the image-wise cancer region identification based on nuclei detection could generally improve the cancer detection rate.ConclusionsWe demonstrated that the morphological and spectral information contribute to SCC nuclei differentiation and that the spectral information within hyperspectral images could improve classification performance.

The purpose of this study is to develop hyperspectral imaging (HSI) for automatic detection of head and neck cancer cells on histologic slides. A compact hyperspectral microscopic system is developed in this study. Histologic slides from 15 patients with squamous cell carcinoma (SCC) of the larynx and hypopharynx are imaged with the system. The proposed nuclei segmentation method based on principle component analysis (PCA) can extract most nuclei in the hyperspectral image without extracting other sub-cellular components. Both spectra-based support vector machine (SVM) and patch-based convolutional neural network (CNN) are used for nuclei classification. CNNs were trained with both hyperspectral images and pseudo RGB images of extracted nuclei, in order to evaluate the usefulness of extra information provided by hyperspectral imaging. The average accuracy of spectra-based SVM classification is 68%. The average AUC and average accuracy of the HSI patch-based CNN classification is 0.94 and 82.4%, respectively. The hyperspectral microscopic imaging and classification methods provide an automatic tool to aid pathologists in detecting SCC on histologic slides.

The combination of optical resolution photoacoustic microscopy (ORPAM) and optical coherence tomography (OCT) is capable of providing complementary imaging contrasts. Unfortunately, the miniaturization of ORPAM remains a major challenge in the development of a handheld dual-modality imaging microscope with OCT. Here, we report the design and evaluation of an integrated ORPAM and OCT imaging probe using a two-dimensional MEMS (micro-electro-mechanical-system)-based optical scanner. This microscope, weighting 35.4 g, has an ultracompact size of 65×30×18 mm3, and an effective imaging area of 2×2 mm2. The experimental lateral resolutions are 3.7 μm (ORPAM) and 5.6 μm (OCT), and the axial resolutions are measured as 120 μm (ORPAM) and 7.3 μm (OCT). Besides phantom and animal experiments, we carried out oral imaging of a healthy volunteer to show the clinical feasibility of this technique.