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TOPICS: Tissues, Arteries, Monte Carlo methods, Near infrared spectroscopy, Blood, Tissue optics, 3D modeling, Signal detection, Photon transport, Skin
In recent years, the incidence rate of pulmonary embolism (PE) has increased dramatically. Currently, the correct diagnosis rate of PE in China is relatively low, and the diagnosis error rate and missed diagnosis rate were as high as about 80%. The most standard method of PE detection is pulmonary artery digital subtraction angiography (DSA), but pulmonary artery DSA is an invasive examination, and patients can have certain risks and discomfort. Noninvasive monitoring of PE remains challenging in cardiovascular medicine.
Aim
We attempt to study the light propagation in human thoracic tissues and explore the possibility of near-infrared spectroscopy (NIRS) in noninvasive detection of PE.
Approach
In this study, by utilizing the Monte Carlo simulation method for voxelized media and the Visible Chinese Human dataset, we quantified and visualized the photon migration in human thoracic region. The influence of the development (three levels) of PE on the light migration was observed.
Results
Results showed that around 4.6% light fluence was absorbed by the pulmonary tissue. The maximum signal sensitivity distribution reached 0.073% at the 2.8- to 3.1-cm light source–detector separation. The normalized light intensity was significantly different among different PE levels and formed a linear relationship (r2 = 0.998, p < 10 − 5).
Conclusions
The study found that photons could reach the pulmonary artery tissue, the light intensity was linearly related to the degrees of embolism, PE could be quantitatively diagnosed by NIRS. Meanwhile, the optimized distance in between the light source and detector, 2.8 to 3.1 cm, was recommended to be used in future potential noninvasive optical diagnosis of PE.
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Cancer therapy treatments produce extensive changes in the physiological and morphological properties of tissues, which are also individual dependent. Currently, a key challenge involves developing more tailored cancer therapy, and consequently, individual biological response measurement during therapy, such as tumor hypoxia, is of high interest. This is the first time human cerebral haemodynamics and cerebral tissue oxygenation index (TOI) changes were measured during the irradiation in clinical radiotherapy and functional near-infrared spectroscopy (fNIRS) technique was demonstrated as a feasible technique for clinical use in radiotherapy, based on 34 online patient measurements.
Aim
Our aim is to develop predictive biomarkers and noninvasive real-time methods to establish the effect of radiotherapy during treatment as well as to optimize radiotherapy dose planning for individual patients. In particular, fNIRS-based technique could offer an effective and clinically feasible online technique for continuous monitoring of brain tissue hypoxia and responses to chemo- and radiotherapy, which involves modulating tumor oxygenation to increase or decrease tumor hypoxia. We aim to show that fNIRS is feasible for repeatability measuring in patient radiotherapy, the temporal alterations of tissue oxygenation induced by radiation.
Approach
Fiber optics setup using multiwavelength fNIRS was built and combined with a medical linear accelerator to measure cerebral tissue oxygenation changes during the whole-brain radiotherapy treatment, where the radiation dose is given in whole brain area only preventing dosage to eyes. Correlation of temporal alterations in cerebral haemodynamics and TOI response to brain irradiation was quantified.
Results
Online fNIRS patient measurement of cerebral haemodynamics during clinical brain radiotherapy is feasible in clinical environment, and results based on 34 patient measurements show strong temporal alterations in cerebral haemodynamics and decrease in TOI during brain irradiation and confirmed the repeatability. Our proof-of-concept study shows evidently that irradiation causes characteristic immediate changes in brain tissue oxygenation.
Conclusions
In particular, TOI seems to be a sensitive parameter to observe the tissue effects of radiotherapy. Monitoring the real-time interactions between the subjected radiation dose and corresponding haemodynamic effects may provide important tool for the researchers and clinicians in the field of radiotherapy. Eventually, presented fNIRS technique could be used for improving dose planning and safety control for individual patients.
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All-optical cardiac electrophysiology enables the visualization and control of key parameters relevant to the detection of cardiac arrhythmias. Mapping such responses in human induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs) is of great interest for cardiotoxicity and personalized medicine applications.
Aim
We introduce and validate a very low-cost compact mapping system for macroscopic all-optical electrophysiology in layers of hiPSC-CMs.
Approach
The system uses oblique transillumination, low-cost cameras, light-emitting diodes, and off-the-shelf components (total < $15 , 000) to capture voltage, calcium, and mechanical waves under electrical or optical stimulation.
Results
Our results corroborate the equivalency of electrical and optogenetic stimulation of hiPSC-CMs, and Vm − [ Ca2 + ]i similarity in conduction under pacing. Green-excitable optical sensors are combinable with blue optogenetic actuators (chanelrhodopsin2) only under very low green light (<0.05 mW/mm2). Measurements in warmer culture medium yield larger spread of action potential duration and higher conduction velocities compared to Tyrode’s solution at room temperature.
Conclusions
As multiple optical sensors and actuators are combined, our results can help handle the “spectral congestion” and avoid parameter distortion. We illustrate the utility of the system for uncovering the action of cellular uncoupling agents and show extensibility to an epi-illumination mode for future imaging of thicker native or engineered tissues.
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Despite recent advances in multimodal optical imaging, oral imaging systems often do not provide real-time actionable guidance to the clinician who is making biopsy and treatment decisions.
Aim
We demonstrate a low-cost, portable active biopsy guidance system (ABGS) that uses multimodal optical imaging with deep learning to directly project cancer risk and biopsy guidance maps onto oral mucosa in real time.
Approach
Cancer risk maps are generated based on widefield autofluorescence images and projected onto the at-risk tissue using a digital light projector. Microendoscopy images are obtained from at-risk areas, and multimodal image data are used to calculate a biopsy guidance map, which is projected onto tissue.
Results
Representative patient examples highlight clinically actionable visualizations provided in real time during an imaging procedure. Results show multimodal imaging with cancer risk and biopsy guidance map projection offers a versatile, quantitative, and precise tool to guide biopsy site selection and improve early detection of oral cancers.
Conclusions
The ABGS provides direct visible guidance to identify early lesions and locate appropriate sites to biopsy within those lesions. This represents an opportunity to translate multimodal imaging into real-time clinically actionable visualizations to help improve patient outcomes.
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The assessment of liver function plays an important role in the diagnosis of nonalcoholic fatty liver disease (NAFLD). Current noninvasive imaging methods have limited applicability in this regard.
Aim
We report an application of multispectral photoacoustic imaging (PAI), an emerging modality, to visualize lipid accumulation and liver function in NAFLD.
Approach
We first demonstrated the liver function reserve with indocyanine green (ICG) to verify the organ’s dysfunction due to NAFLD in a rabbit model. We then noninvasively quantified lipid content in the liver using multispectral PAI. The in vivo PAI results were compared and verified with photoacoustic ex vivo images and liver biopsy.
Results
A significant difference in the lipidmean value was observed [lipidmean = 0.081 ± 0.0161 arbitrary units (a.u.) control versus NAFLD 0.198 ± 0.048 a.u., P = 0.003]. Similar to in vivo analysis, a significant difference in lipidmean was observed (lipidmean = 0.0673 ± 0.0165 versus 0.486 ± 0.073 a.u., P < 0.0001) between control and NAFLD group ex vivo. For liver function, the control group showed a rapid decrease after the peak point, whereas the elimination of ICG for the NAFLD group was slower.
Conclusions
Our study shows that PAI has the potential to provide a noninvasive biomarker for the assessment of liver function and lipid accumulation for NAFLD diagnosis and treatment.
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Accurate identification of tissues is critical for performing safe surgery. Combining multispectral imaging (MSI) with deep learning is a promising approach to increasing tissue discrimination and classification. Evaluating the contributions of spectral channels to tissue discrimination is important for improving MSI systems.
Aim
Develop a metric to quantify the contributions of individual spectral channels to tissue classification in MSI.
Approach
MSI was integrated into a digital operating microscope with three sensors and seven illuminants. Two convolutional neural network (CNN) models were trained to classify 11 head and neck tissue types using white light (RGB) or MSI images. The signal to noise ratio (SNR) of spectral channels was compared with the impact of channels on tissue classification performance as determined using CNN visualization methods.
Results
Overall tissue classification accuracy was higher with use of MSI images compared with RGB images, both for classification of all 11 tissue types and binary classification of nerve and parotid (p < 0.001). Removing spectral channels with SNR > 20 reduced tissue classification accuracy.
Conclusions
The spectral channel SNR is a useful metric for both understanding CNN tissue classification and quantifying the contributions of different spectral channels in an MSI system.
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