Estimation of anisotropy coefficient of swine pancreas, liver and muscle at 1064 nm based on goniometric technique

Systematic Optimization of Universal Real-Time Hypersensitive Fast Detection Method for HBsAg in Serum Based on SERS

Hepatitis B virus (HBV) is a major cause of liver cirrhosis and hepatocellular carcinoma, with HBV surface antigen (HBsAg) being a crucial marker in the clinical detection of HBV. Due to the significant harm and ease of transmission associated with HBV, HBsAg testing has become an essential part of preoperative assessments, particularly for emergency surgeries where healthcare professionals face exposure risks. Therefore, a timely and accurate detection method for HBsAg is urgently needed. In this study, a surface-enhanced Raman scattering (SERS) sensor with a sandwich structure was developed for HBsAg detection. Leveraging the ultrasensitive and rapid detection capabilities of SERS, this sensor enables quick detection results, significantly reducing waiting times. By systematically optimizing critical factors in the detection process, such as the composition and concentration of the incubation solution as well as the modification conditions and amount of probe particles, the sensitivity of the SERS immune assay system was improved. Ultimately, the sensor achieved a sensitivity of 0.00576 IU/mL within 12 min, surpassing the clinical requirement of 0.05 IU/mL by an order of magnitude. In clinical serum assay validation, the issue of false positives was effectively addressed by adding a blocker. The final sensor demonstrated 100% specificity and sensitivity at the threshold of 0.05 IU/mL. Therefore, this study not only designed an ultrasensitive SERS sensor for detecting HBsAg in actual clinical serum samples but also provided theoretical support for similar systems, filling the knowledge gap in existing literature.

Experimental validation of a recently developed model for single-fiber reflectance spectroscopy

SIGNIFICANCE

We recently developed a model for the reflectance measured with (multi-diameter) single-fiber reflectance (SFR) spectroscopy as a function of the reduced scattering coefficient μs', the absorption coefficient μa, and the phase function parameter psb. We validated this model with simulations.

AIM

We validate our model experimentally. To prevent overfitting, we investigate the wavelength-dependence of psb and propose a parametrization with only three parameters. We also investigate whether this parametrization enables measurements with a single fiber, as opposed to multiple fibers used in multi-diameter SFR (MDSFR).

APPROACH

We validate our model on 16 phantoms with two concentrations of Intralipid-20% (μs'=13 and 21  cm  -  1 at 500 nm) and eight concentrations of Evans Blue (μa  =  1 to 20  cm  -  1 at 605 nm). We parametrize psb as 10  -  5  ·    (  p1  (  λ  /  650  )    +  p2(λ/650)2  +  p3(λ/650)3  )  .

RESULTS

Average errors were 7% for μs', 11% for μa, and 16% with the parametrization of psb; and 7%, 17%, and 16%, respectively, without. The parametrization of psb improved the fit speed 25 times (94 s to <4  s). Average errors for only one fiber were 50%, 33%, and 186%, respectively.

CONCLUSIONS

Our recently developed model provides accurate results for MDSFR measurements but not for a single fiber. The psb parametrization prevents overfitting and speeds up the fit.

Subdiffuse scattering and absorption model for single fiber reflectance spectroscopy

Single fiber reflectance (SFR) spectroscopy is a technique that is sensitive to small-scale changes in tissue. An additional benefit is that SFR measurements can be performed through endoscopes or biopsy needles. In SFR spectroscopy, a single fiber emits and collects light. Tissue optical properties can be extracted from SFR spectra and related to the disease state of tissue. However, the model currently used to extract optical properties was derived for tissues with modified Henyey-Greenstein phase functions only and is inadequate for other tissue phase functions. Here, we will present a model for SFR spectroscopy that provides accurate results for a large range of tissue phase functions, reduced scattering coefficients, and absorption coefficients. Our model predicts the reflectance with a median error of 5.6% compared to 19.3% for the currently used model. For two simulated tissue spectra, our model fit provides accurate results.

Multispectral measurement of scattering-angular light distribution in apple skin and flesh samples

Knowledge of the optical properties of apple tissues such as skin and flesh is essential to better understand the light-tissue interaction process and to apply optical methods for apple quality inspection. This work aimed at estimating the anisotropy factor of thin skin and flesh samples extracted from three apple cultivars. The scattering-angular light distribution in each tissue sample was measured at four wavelengths (λ=633, 763, 784, and 852 nm), by means of a goniometer setup. Based on the recorded angular intensity I(θ,λ), the effective anisotropy factor g_eff of each tissue type was first estimated using the mean statistics applied to the random variable cos θ. Next, the measured data were fitted with three predefined and modified phase functions-Henyey-Greenstein (p_MHG), Gegenbauer kernel (p_MGK), and Mie (p_Mie)-in order to retrieve the corresponding anisotropy factors g_MHG, g_MGK, and g_MMie. Typically, the anisotropy factors of skin and flesh amount to 0.6-0.8 in the above-mentioned wavelength range.

Estimation of optical properties of neuroendocrine pancreas tumor with double-integrating-sphere system and inverse Monte Carlo model

The investigation of laser-tissue interaction is crucial for diagnostics and therapeutics. In particular, the estimation of tissue optical properties allows developing predictive models for defining organ-specific treatment planning tool. With regard to laser ablation (LA), optical properties are among the main responsible for the therapy efficacy, as they globally affect the heating process of the tissue, due to its capability to absorb and scatter laser energy. The recent introduction of LA for pancreatic tumor treatment in clinical studies has fostered the need to assess the laser-pancreas interaction and hence to find its optical properties in the wavelength of interest. This work aims at estimating optical properties (i.e., absorption, μ a , scattering, μ s , anisotropy, g, coefficients) of neuroendocrine pancreas tumor at 1064 nm. Experiments were performed using two popular sample storage methods; the optical properties of frozen and paraffin-embedded neuroendocrine tumor of the pancreas are estimated by employing a double-integrating-sphere system and inverse Monte Carlo algorithm. Results show that paraffin-embedded tissue is characterized by absorption and scattering coefficients significantly higher than frozen samples (μ a of 56 cm(-1) vs 0.9 cm(-1), μ s of 539 cm(-1) vs 130 cm(-1), respectively). Simulations show that such different optical features strongly influence the pancreas temperature distribution during LA. This result may affect the prediction of therapeutic outcome. Therefore, the choice of the appropriate preparation technique of samples for optical property estimation is crucial for the performances of the mathematical models which predict LA thermal outcome on the tissue and lead the selection of optimal LA settings.

Goniometric measurement for the estimation of anisotropy coefficient of human and animal pancreas

Estimation of optical properties of biologic tissues is determinant for laser dosimetry in medical applications. Tissues highly absorb and scatter the light in near infrared spectrum, where the laser provides therapeutic effects. Novel frontiers of clinical practice, e.g., the employment of laser light for the treatment of pancreatic cancer, require information about pancreas-laser interaction, which are crucial for therapy management. The property of biological tissues to scatter the light traveling through is described by the anisotropy coefficient (g). The relationship between g and the angular distribution of the scattered light is described by Henyey-Greenstein phase function. The measurement of angular distribution of scattered light is performed by the goniometric technique. This paper describes the estimation of g of ex vivo pancreas at 1064 nm, performed by a goniometric-based system, where a photodetector measures intensities of scattered light at fixed angles between -120° and 120°. A two-term Henyey-Greenstein phase function has been employed to estimate anisotropy coefficient for forward (gfs) and backward scattering (gbs). Experimental trails were performed to assess the repeatability of measurement system: percentage value of standard deviation is generally lower than 8% for angles higher (lower) than 13° (13°). Measurements were performed for the first time on healthy swine pancreas, aiming to investigate the influence of coagulation temperature: gfs decreases from 0.94 (at 25 °C) to 0.93 (at 80 °C). Afterwards, the same set up has been employed for the estimation of g of human pancreas affected by neuroendocrine tumor, which presented an estimated values for gfs of 0.89.