All-reflective tethered capsule endoscope for multimodal optical coherence tomography in the esophagus.

Significance: Esophageal cancer is becoming increasingly prevalent in Western countries. Early detection is crucial for effective treatment. Multimodal imaging combining optical coherence tomography (OCT) with complementary optical imaging techniques may provide enhanced diagnostic capabilities by simultaneously assessing tissue morphology and biochemical content. Aim: We aim to develop a tethered capsule endoscope (TCE) that can accommodate a variety of point-scanning techniques in addition to OCT without requiring design iterations on the optical or mechanical design. Approach: We propose a TCE utilizing exclusively reflective optics to focus and steer light from and to a double-clad fiber. Specifically, we use an ellipsoidal mirror to achieve finite conjugation between the fiber tip and the imaging plane. Results: We demonstrate a functional all-reflective TCE. We first detail the design, fabrication, and assembly steps required to obtain such a device. We then characterize its performance and demonstrate combined OCT at 1300 nm and visible spectroscopic imaging in the 500- to 700-nm range. Finally, we discuss the advantages and limitations of the proposed design. Conclusions: An all-reflective TCE is feasible and allows for achromatic high-quality imaging. Such a device could be utilized as a platform for testing various combinations of modalities to identify the optimal candidates without requiring design iterations.

Erratum: Model for the diffuse reflectance in spatial frequency domain imaging (Erratum).

[This corrects the article DOI: 10.1117/1.JBO.28.4.046002.].

Poloxamer-188 as a wetting agent for microfluidic resistive pulse sensing measurements of extracellular vesicles.

INTRODUCTION: Microfluidic resistive pulse sensing (MRPS) can determine the concentration and size distribution of extracellular vesicles (EVs) by measuring the electrical resistance of single EVs passing through a pore. To ensure that the sample flows through the pore, the sample needs to contain a wetting agent, such as bovine serum albumin (BSA). BSA leaves EVs intact but occasionally results in unstable MRPS measurements. Here, we aim to find a new wetting agent by evaluating Poloxamer-188 and Tween-20. METHODS: An EV test sample was prepared using an outdated erythrocyte blood bank concentrate. The EV test sample was diluted in Dulbecco's phosphate-buffered saline (DPBS) or DPBS containing 0.10% BSA (w/v), 0.050% Poloxamer-188 (v/v) or 1.00% Tween-20 (v/v). The effect of the wetting agents on the concentration and size distribution of EVs was determined by flow cytometry. To evaluate the precision of sample volume determination with MRPS, the interquartile range (IQR) of the particles transit time through the pore was examined. To validate that DPBS containing Poloxamer-188 yields reliable MRPS measurements, the repeatability of MRPS in measuring blood plasma samples was examined. RESULTS: Flow cytometry results show that the size distribution of EVs in Tween 20, in contrast to Poloxamer-188, differs from the control measurements (DPBS and DPBS containing BSA). MRPS results show that Poloxamer-188 improves the precision of sample volume determination compared to BSA and Tween-20, because the IQR of the transit time of EVs in the test sample is 11 µs, which is lower than 56 µs for BSA and 16 µs for Tween-20. Furthermore, the IQR of the transit time of particles in blood samples with Poloxamer-188 are 14, 16, and 14 µs, which confirms the reliability of MRPS measurements. CONCLUSION: The solution of 0.050% Poloxamer-188 in DPBS does not lyse EVs and results in repeatable and unimpeded MRPS measurements.

Subminute thermal damage to cell types present in the skin.

INTRODUCTION: Psoriasis is characterized by an increase in the proliferation of keratinocytes and nerve fiber activity, contributing to the typical skin lesions. Pulsed Dye Laser (PDL) treatment is effective for the treatment of psoriatic lesions but its mechanism remains unclear. One hypothesis is that PDL causes thermal damage by the diffusion of heat to neighboring structures in lesional skin. There is limited information on the thermal sensitivity of these neighboring skin cells when exposed to hyperthermia for durations lasting less than a minute. Our study aimed to investigate the cell-specific responses to heat using sub-minute exposure times and moderate to ablative hyperthermia. MATERIALS AND METHODS: Cultured human endothelial cells, smooth muscle cells, neuronal cells, and keratinocytes were exposed to various time (2-20 sec) and temperature (45-70 °C) combinations. Cell viability was assessed by measuring intracellular ATP content 24 h after thermal exposure and this data was used to calculate fit parameters for the Arrhenius model and CEM43 calculations. RESULTS: Our results show significant differences in cell survival between cell types (p < 0.0001). Especially within the range of 50-60 °C, survival of neuronal cells and keratinocytes was significantly less than that of endothelial and smooth muscle cells. No statistically significant difference was found in the lethal dose (LT50) of thermal energy between neuronal cells and keratinocytes. However, CEM43 calculations showed significant differences between all four cell types. CONCLUSION: The results imply that there is a cell-type-dependent sensitivity to thermal damage which suggests that neuronal cells and keratinocytes are particularly susceptible to diffusing heat from laser treatment. Damage to these cells may aid in modulating the neuro-inflammatory pathways in psoriasis. These data provide insight into the potential mechanisms of PDL therapy for psoriasis and advance our understanding of how thermal effects may play a role in its effectiveness.

Towards non-invasive tissue hydration measurements with optical coherence tomography.

The attenuation coefficient ( µ OCT ) measured by optical coherence tomography (OCT) has been used to determine tissue hydration. Previous dual-wavelength OCT systems could not attain the needed precision, which we attribute to the absence of wavelength-dependent scattering of tissue in the underlying model. Assuming that scattering can be described using two parameters, we propose a triple/quadrupole-OCT system to achieve clinically relevant precision in water volume fraction. In this study, we conduct a quantitative analysis to determine the necessary precision of µ OCT measurements and compare it with numerical simulation. Our findings emphasize that achieving a clinically relevant assessment of a 2% water fraction requires determining the attenuation coefficient with a remarkable precision of 0.01 m m - 1 . This precision threshold is influenced by the chosen wavelength for attenuation measurement and can be enhanced through the inclusion of a fourth wavelength range.

Modeling pulsed dye laser treatment of psoriatic plaques by combining numerical methods and image-derived lesion morphologies.

OBJECTIVES: Knowledge of the physical effects of pulsed dye laser (PDL) treatment of psoriatic lesions is essential in unraveling the remedial mechanisms of this treatment and hence also in maximizing in its disease-modifying potential. Therefore, the main objective of this study was to provide estimates of these physical effects (for laser wavelengths of 585 and 595 nm), with the aim of identifying pathogenic processes that may be affected by these conditions. METHODS: We modeled the laser light propagation and subsequent photothermal heating by numerically solving the transient diffusion and heat equations simultaneously. To this end, we used the finite element method in conjunction with an image-derived psoriatic lesion morphology (which was defined by segmenting blood vessels from a confocal microscopy image of a fluorescently labeled section of a 3 mm punch biopsy of a psoriatic lesion). The resulting predictions of the generated temperature field within the lesion were then used to assess the possibility of stalling or arresting some suspected pathogenic processes. RESULTS: According to our results, it is conceivable that perivascular nerves are thermally denatured, as almost all locations that reach 60°C were found to be within 18 µm (at 585 nm) and 11 µm (at 595 nm) of a blood vessel wall. Furthermore, activation of TRPV1 and TRPV2 channels in perivascular neuronal and immune cells is highly likely, since a critical temperature of 43°C is generated at locations within up to 350 µm of a vessel wall (at both wavelengths) and sustained for up to 700 ms (at 585 nm) and 40 ms (at 595 nm), while a critical temperature of 52°C is reached by locations within 80 µm (at 585 nm) and 30 µm (at 595 nm) of a vessel wall and sustained for up to 100 ms (at 585 nm) and 30 ms (at 595 nm). Finally, we found that the blood vessel coagulation-inducing temperature of 70°C is sustained in the vascular epithelium for up to 19 and 5 ms at 585 and 595 nm, respectively, rendering partial or total loss of vascular functionality a distinct possibility. CONCLUSIONS: The presented approach constitutes a useful tool to provide realistic estimates of the photothermal effects of PDL treatment of psoriatic plaques (as well as other selective photothermolysis-based treatments), yielding information that is essential in guiding future experimental studies toward unraveling the remedial mechanisms of these treatments.

Accuracy and precision of depth-resolved estimation of attenuation coefficients in optical coherence tomography.

Significance: Parametric imaging of the attenuation coefficient µOCT using optical coherence tomography (OCT) is a promising approach for evaluating abnormalities in tissue. To date, a standardized measure of accuracy and precision of µOCT by the depth-resolved estimation (DRE) method, as an alternative to least squares fitting, is missing. Aim: We present a robust theoretical framework to determine accuracy and precision of the DRE of µOCT. Approach: We derive and validate analytical expressions for the accuracy and precision of µOCT determination by the DRE using simulated OCT signals in absence and presence of noise. We compare the theoretically achievable precisions of the DRE method and the least-squares fitting approach. Results: Our analytical expressions agree with the numerical simulations for high signal-to-noise ratios and qualitatively describe the dependence on noise otherwise. A commonly used simplification of the DRE method results in a systematic overestimation of the attenuation coefficient in the order of µOCT2×Δ, where Δ is the pixel stepsize. When µOCT·|AFR|≲1.8, µOCT is reconstructed with higher precision by the depth-resolved method compared to fitting over the length of an axial fitting range |AFR|. Conclusions: We derived and validated expressions for the accuracy and precision of DRE of µOCT. A commonly used simplification of this method is not recommended as being used for OCT-attenuation reconstruction. We give a rule of thumb providing guidance in the choice of estimation method.

Preventing swarm detection in extracellular vesicle flow cytometry: a clinically applicable procedure.

Background: Flow cytometry is commonly used to detect cell-derived extracellular vesicles in body fluids such as blood plasma. However, continuous and simultaneous illumination of multiple particles at or below the detection limit may result in the detection of a single event. This phenomenon is called swarm detection and leads to incorrect particle concentration measurements. To prevent swarm detection, sample dilution is recommended. Since the concentration of particles differs between plasma samples, finding the optimal sample dilution requires dilution series of all samples, which is unfeasible in clinical routine. Objectives: Here we developed a practical procedure to find the optimal sample dilution of plasma for extracellular vesicle flow cytometry measurements in clinical research studies. Methods: Dilution series of 5 plasma samples were measured with flow cytometry (Apogee A60-Micro), triggered on side scatter. The total particle concentration between these plasma samples ranged from 2.5 × 109 to 2.1 × 1011 mL-1. Results: Swarm detection was absent in plasma samples when diluted ≥1.1 × 103-fold or at particle count rates <3.0 × 103 events·s-1. Application of either one of these criteria, however, resulted in insignificant particle counts in most samples. The best approach to prevent swarm detection while maintaining significant particle counts was by combining minimal dilution with maximum count rate. Conclusion: To prevent swarm detection in a series of clinical samples, the measurement count rate of a single diluted plasma sample can be used to determine the optimal dilution factor. For our samples, flow cytometer, and settings, the optimal dilution factor is ≥1.1 × 102-fold, while the count rate is <1.1 × 104 events·s-1.

Model for the diffuse reflectance in spatial frequency domain imaging.

Significance: In spatial frequency domain imaging (SDFI), tissue is illuminated with sinusoidal intensity patterns at different spatial frequencies. For low spatial frequencies, the reflectance is diffuse and a model derived by Cuccia et al. (doi 10.1117/1.3088140) is commonly used to extract optical properties. An improved model resulting in more accurate optical property extraction could lead to improved diagnostic algorithms. Aim: To develop a model that improves optical property extraction for the diffuse reflectance in SFDI compared to the model of Cuccia et al. Approach: We derive two analytical models for the diffuse reflectance, starting from the theoretical radial reflectance R ( ρ ) for a pencil-beam illumination under the partial current boundary condition (PCBC) and the extended boundary condition (EBC). We compare both models and the model of Cuccia et al. to Monte Carlo simulations. Results: The model based on the PCBC resulted in the lowest errors, improving median relative errors compared to the model of Cuccia et al. by 45% for the reflectance, 10% for the reduced scattering coefficient and 64% for the absorption coefficient. Conclusions: For the diffuse reflectance in SFDI, the model based on the PCBC provides more accurate results than the currently used model by Cuccia et al.

A compendium of single extracellular vesicle flow cytometry.

Flow cytometry (FCM) offers a multiparametric technology capable of characterizing single extracellular vesicles (EVs). However, most flow cytometers are designed to detect cells, which are larger than EVs. Whereas cells exceed the background noise, signals originating from EVs partly overlap with the background noise, thereby making EVs more difficult to detect than cells. This technical mismatch together with complexity of EV-containing fluids causes limitations and challenges with conducting, interpreting and reproducing EV FCM experiments. To address and overcome these challenges, researchers from the International Society for Extracellular Vesicles (ISEV), International Society for Advancement of Cytometry (ISAC), and the International Society on Thrombosis and Haemostasis (ISTH) joined forces and initiated the EV FCM working group. To improve the interpretation, reporting, and reproducibility of future EV FCM data, the EV FCM working group published an ISEV position manuscript outlining a framework of minimum information that should be reported about an FCM experiment on single EVs (MIFlowCyt-EV). However, the framework contains limited background information. Therefore, the goal of this compendium is to provide the background information necessary to design and conduct reproducible EV FCM experiments. This compendium contains background information on EVs, the interaction between light and EVs, FCM hardware, experimental design and preanalytical procedures, sample preparation, assay controls, instrument data acquisition and calibration, EV characterization, and data reporting. Although this compendium focuses on EVs, many concepts and explanations could also be applied to FCM detection of other particles within the EV size range, such as bacteria, lipoprotein particles, milk fat globules, and viruses.

Calibration procedure for enhanced mirror artifact removal in full-range optical coherence tomography using passive quadrature demultiplexing.

Significance: Passive quadrature demultiplexing allows full-range optical coherence tomography (FR-OCT). However, imperfections in the wavelength- and frequency-response of the demodulation circuits can cause residual mirror artifacts, which hinder high-quality imaging on both sides of zero delay. Aim: We aim at achieving high mirror artifact extinction by calibrated postprocessing of the FR-OCT signal. Approach: We propose a mathematical framework for the origin of the residual mirror peaks as well as a protocol allowing the precise measurement and correction of the associated errors directly from mirror measurements. Results: We demonstrate high extinction of the mirror artifact over the entire imaging range, as well as an assessment of the method's robustness to time and experimental conditions. We also provide a detailed description of the practical implementation of the method to ensure optimal reproducibility. Conclusion: The proposed method is simple to implement and produces high mirror artifact extinction. This may encourage the adoption of FR-OCT in clinical and industrial systems or loosen the performance requirements on the optical demodulation circuit, as the imperfections can be handled in postprocessing.

Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging.

Significance: Hyperspectral reflectance imaging can be used in medicine to identify tissue types, such as tumor tissue. Tissue classification algorithms are developed based on, e.g., machine learning or principle component analysis. For the development of these algorithms, data are generally preprocessed to remove variability in data not related to the tissue itself since this will improve the performance of the classification algorithm. In hyperspectral imaging, the measured spectra are also influenced by reflections from the surface (glare) and height variations within and between tissue samples. Aim: To compare the ability of different preprocessing algorithms to decrease variations in spectra induced by glare and height differences while maintaining contrast based on differences in optical properties between tissue types. Approach: We compare eight preprocessing algorithms commonly used in medical hyperspectral imaging: standard normal variate, multiplicative scatter correction, min-max normalization, mean centering, area under the curve normalization, single wavelength normalization, first derivative, and second derivative. We investigate conservation of contrast stemming from differences in: blood volume fraction, presence of different absorbers, scatter amplitude, and scatter slope-while correcting for glare and height variations. We use a similarity metric, the overlap coefficient, to quantify contrast between spectra. We also investigate the algorithms for clinical datasets from the colon and breast. Conclusions: Preprocessing reduces the overlap due to glare and distance variations. In general, the algorithms standard normal variate, min-max, area under the curve, and single wavelength normalization are the most suitable to preprocess data used to develop a classification algorithm for tissue classification. The type of contrast between tissue types determines which of these four algorithms is most suitable.

Precision of attenuation coefficient measurements by optical coherence tomography.

SIGNIFICANCE: Optical coherence tomography (OCT) is an interferometric imaging modality, which provides tomographic information on the microscopic scale. Furthermore, OCT signal analysis facilitates quantification of tissue optical properties (e.g., the attenuation coefficient), which provides information regarding the structure and organization of tissue. However, a rigorous and standardized measure of the precision of the OCT-derived optical properties, to date, is missing. AIM: We present a robust theoretical framework, which provides the Cramér -Rao lower bound σµOCT for the precision of OCT-derived optical attenuation coefficients. APPROACH: Using a maximum likelihood approach and Fisher information, we derive an analytical solution for σµOCT when the position and depth of focus are known. We validate this solution, using simulated OCT signals, for which attenuation coefficients are extracted using a least-squares fitting procedure. RESULTS: Our analytical solution is in perfect agreement with simulated data without shot noise. When shot noise is present, we show that the analytical solution still holds for signal-to-noise ratios (SNRs) in the fitting window being above 20 dB. For other cases (SNR<20 dB, focus position not precisely known), we show that the numerical calculation of the precision agrees with the σµOCT derived from simulated signals. CONCLUSIONS: Our analytical solution provides a fast, rigorous, and easy-to-use measure for OCT-derived attenuation coefficients for signals above 20 dB. The effect of uncertainties in the focal point position on the precision in the attenuation coefficient, the second assumption underlying our analytical solution, is also investigated by numerical calculation of the lower bounds. This method can be straightforwardly extended to uncertainty in other system parameters.

Quantitative Fluorescence Imaging of Perfusion-An Algorithm to Predict Anastomotic Leakage.

This study tests fluorescence imaging-derived quantitative parameters for perfusion evaluation of the gastric tube during surgery and correlates these parameters with patient outcomes in terms of anastomotic leakage. Poor fundus perfusion is seen as a major factor for the development of anastomotic leakage and strictures. Fluorescence perfusion imaging may reduce the incidence of complications. Parameters for the quantification of the fluorescence signal are still lacking. Quantitative parameters in terms of maximal intensity, mean slope and influx timepoint were tested for significant differences between four perfusion areas of the gastric tube in 22 patients with a repeated ANOVA test. These parameters were compared with patient outcomes. Maximal intensity, mean slope and influx timepoint were significantly different between the base of the gastric tube and the fundus (p < 0.0001). Patients who developed anastomotic leakage showed a mean slope of almost 0 in Location 4. The distance of the demarcation of ICG to the fundus was significantly higher in the three patients who developed anastomotic leakage (p < 0.0001). This study presents quantitative intra-operative perfusion imaging with fluorescence. Quantification of the fluorescence signal allows for early risk stratification of necrosis.

EDTA stabilizes the concentration of platelet-derived extracellular vesicles during blood collection and handling.

Citrate is the recommended anticoagulant for studies on plasma extracellular vesicles (EVs). Because citrate incompletely blocks platelet activation and the release of platelet-derived EVs, we compared EDTA and citrate in that regard. Blood from healthy individuals (n = 7) was collected and incubated with thrombin receptor-activating peptide-6 (TRAP-6) to activate platelets, subjected to pneumatic tube transportation (n = 6), a freeze-thaw cycle (n = 10), and stored before plasma preparation (n = 6). Concentrations of EVs from platelets (CD61+), activated platelets (P-selectin+), erythrocytes (CD235a+), and leukocytes (CD45+) were measured by flow cytometry. Concentrations of EVs from platelets and activated platelets increased 1.4-fold and 1.9-fold in EDTA blood upon platelet activation, and 4.2-fold and 9.6-fold in citrate blood. Platelet EV concentrations were unaffected by pneumatic tube transport in EDTA blood but increased in citrate blood, and EV concentrations of erythrocytes and leukocytes were comparable. The stability of EVs during a freeze-thaw cycle was comparable for both anticoagulants. Finally, the concentration of platelet EVs was stable during storage of EDTA blood for six hours, whereas this concentration increased 1.5-fold for citrate blood. Thus, EDTA improves the robustness of studies on plasma EVs.

Deep Learning-based Recurrence Prediction in Patients with Non-muscle-invasive Bladder Cancer.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by frequent recurrence of the disease, which is difficult to predict. OBJECTIVE: To combine digital histopathology slides with clinical data to predict 1- and 5-yr recurrence-free survival of NMIBC patients using deep learning. DESIGN, SETTING, AND PARTICIPANTS: Data of patients undergoing a transurethral resection of a bladder tumor between 2000 and 2018 at a Dutch academic medical center were selected. Corresponding histological slides were digitized. A three-step approach was used to predict 1- and 5-yr recurrence-free survival. First, a segmentation network was used to detect the urothelium on the digital histopathology slides. Second, a selection network was trained for the selection of patches associated with recurrence. Third, a classification network, combining the information of the selection network with clinical data, was trained to give the probability of 1- and 5-yr recurrence-free survival. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The accuracy of the deep learning-based model was compared with a multivariable logistic regression model using clinical data only. RESULTS AND LIMITATIONS: In the 1- and 5-yr follow-up cohorts, 359 and 281 patients were included with recurrence rates of 27% and 63%, respectively. The areas under the curve (AUCs) of the model combining digital histopathology slide data with clinical data were 0.62 and 0.76 for 1- and 5-yr recurrence predictions, respectively, which were higher than those of the model using digital histopathology slide data only (AUCs of 0.56 and 0.72, respectively) and the multivariable logistic regression (AUCs of 0.58 and 0.57, respectively). CONCLUSIONS: In our population, the deep learning-based model combining digital histopathology slides and clinical data enhances the prediction of recurrence (within 5 yr) compared with models using clinical data or image data only. PATIENT SUMMARY: By combining histopathology images and patient record data using deep learning, the prediction of recurrence in bladder cancer patients is enhanced.