Depth-selective fiber-optic probe for characterization of superficial tissue at a constant physical depth

Dual-axis confocal configuration for depth sensitive fluorescence spectroscopy

The dual-axis confocal (DAC) configuration provides a high axial resolution, long working distance (WD), and large dynamic range. These properties can reveal depth-resolved fluorescence spectra. We present a depth sensitive fluorescence spectroscopy based on the DAC configuration. The system enables high axial resolution of 3.23 µm and a long WD of 3.73 mm compared to that of 4.68 µm and 2.1 mm for comparable single-axis confocal configurations, respectively. Besides, a DAC configuration also offers a superior dynamic range and rejection of out-of-focus scattered light based on the principle of Huygens-Fresnel integrals. Additionally, to locate the target layer, the collection path of the DAC configuration will be used as the other illumination path, forming a dual-axis illumination configuration. These beam paths are used to locate the target layer using a white light imaging system with a commercial low numerical aperture objective. A multi-layer fluorescence phantom of Barrett's esophagus containing fluorescein isothiocyanate and Alexa Fluor 514 was used to verify the principle of depth-resolved fluorescence spectroscopy. The results show that the DAC configuration can collect fluorescence spectra from microscopic regions with high axial resolution.

A burn depth detection system based on near infrared spectroscopy and ensemble learning

Near infrared (NIR) spectroscopy can effectively detect the changes in the burned tissue. However, due to the complex relationship between the spectral signals and the burn depth, simple methods of data analysis are difficult to solve this problem effectively. Therefore, in this paper, a machine learning method is introduced into the NIR spectral signal analysis, which is used to establish the relationship between NIR spectral signals and burn depth. First, based on the intensity of the spectral signal and the diffuse reflection theory, the optical properties that can reflect the change of burned tissue are extracted. And then the chained-agent genetic algorithm (CAGA) optimized support vector regression (SVR) is applied to establish a regression model between the optical property parameters and burn depth. Finally, the porcine model was used for verification. The experimental results demonstrate that the proposed CAGA-SVR integrated inversion model with optical properties can perform accurate inversion of burn depth and provide a reference for doctors.

Polarization gating spectroscopy of normal-appearing duodenal mucosa to detect pancreatic cancer

BACKGROUND

According to the field effect theory, by detecting microvasculature changes such as early increase in blood supply (EIBS) in the surrounding tissue, neoplastic lesions can be identified from a distance.

OBJECTIVE

To determine the feasibility and efficacy of a fiberoptic probe containing novel polarization gating spectroscopy technology to identify patients with pancreatic adenocarcinoma (PAC) by the field effect theory.

DESIGN

Prospective cohort (pilot) study.

SETTING

Outpatient tertiary care center.

PATIENTS

Adult (≥ 18 years) patients undergoing EGD-EUS were screened. Patients with PAC were included in the "cancer" group and patients without PAC were included in the "control" group. We excluded patients with other known malignancies and gastroduodenal premalignant lesions.

INTERVENTIONS AND MAIN OUTCOME MEASURES

Spectroscopic measurements of EIBS variables, such as deoxyhemoglobin concentration (DHb) and mean blood vessel radius (BVR), were obtained from 5 periampullary locations. The Mann-Whitney rank sum test was used for the statistical analysis (P ≤ .05).

RESULTS

Fourteen patients (mean age 72 years, 79% male) in the cancer group and 15 patients (mean age 63 years, 60% male) in the control group were included in the final analysis. At the ampullary site, both DHb (P = .001) and BVR (P = .03) were higher in PAC patients than in the control subjects. The DHb alone (92% sensitivity, 86% specificity) or in combination with BVR (92% sensitivity, 79% specificity) can differentiate PAC from control subjects with high accuracy.

LIMITATIONS

Small sample size, unmatched control subjects.

CONCLUSIONS

Spectroscopic measurements of EIBS by fiberoptic probes are feasible. Preliminary evidence suggests that in vivo measurement of normal-appearing duodenal tissue can differentiate PAC patients from a distance with high accuracy.

Algorithm for automated selection of application-specific fiber-optic reflectance probes

Several optical techniques and fiber-optic probe systems have been designed to measure the optical properties of tissue. While a wide range of options is often beneficial, it poses a problem to investigators selecting which method to use for their biomedical application of interest. We present a methodology to optimally select a probe that matches the application requirements. Our method is based both on matching a probe's mean sampling depth with the optimal diagnostic depth of the clinical application and on choosing a probe whose interrogation depth and path length is the least sensitive to alterations in the target medium's optical properties. Satisfying these requirements ensures that the selected probe consistently assesses the relevant tissue volume with minimum variability. To aid in probe selection, we have developed a publicly available graphical user interface that takes the desired sampling depth and optical properties of the medium as its inputs and automatically ranks different techniques in their ability to robustly target the desired depth. Techniques investigated include single fiber spectroscopy, differential path length spectroscopy, polarization-gating, elastic light scattering spectroscopy, and diffuse reflectance. The software has been applied to biological case studies.

Analytical light reflectance models for overlapping illumination and collection area geometries

Several biomedical applications, such as detection of dysplasia, require selective interrogation of superficial tissue structures less than a few hundred micrometers thick. Techniques and methods have been developed to limit the penetration depth of light in tissue, including the design of systems such as fiber-optic probes that have overlapping illumination and collection areas on the tissue surface. For such geometries, the diffusion approximation to the light-transport equation typically does not apply, and as a result there is no general model to extract tissue optical properties from reflectance measurements. In the current study, we employ Monte Carlo (MC) simulations to develop simple and compact analytical models for the light reflectance from these overlapping geometries. These models incorporate the size of the illumination and collection areas, the collection angle, the polarization of the incident light, and the optical properties of the sample. Moreover, these MC simulations use the Whittle-Matérn model to describe scattering from spatially continuous refractive index media such as tissue, which is more general than models based on the conventionally used Henyey-Greenstein model. We validated these models on tissue-simulating phantoms. The models developed herein will facilitate the extraction of optical properties and aid in the design of optical systems employing overlapping illumination and collection areas, including fiber-optic probes for in vivo tissue diagnosis.

Reply to "Comment on 'A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation'"

We compare the accuracy of TIM-OS and MMCM in response to the recent analysis made by Fang [Biomed. Opt. Express 2, 1258 (2011)]. Our results show that the tetrahedron-based energy deposition algorithm used in TIM-OS is more accurate than the node-based energy deposition algorithm used in MMCM.