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

Diffuse reflectance spectroscopy for accurate margin assessment in breast-conserving surgeries: importance of an optimal number of fibers

During breast-conserving surgeries, it remains challenging to accomplish adequate surgical margins. We investigated different numbers of fibers for fiber-optic diffuse reflectance spectroscopy to differentiate tumorous breast tissue from healthy tissue ex vivo up to 2 mm from the margin. Using a machine-learning classification model, the optimal performance was obtained using at least three emitting fibers (Matthew's correlation coefficient (MCC) of 0.73), which was significantly higher compared to the performance of using a single-emitting fiber (MCC of 0.48). The percentage of correctly classified tumor locations varied from 75% to 100% depending on the tumor percentage, the tumor-margin distance and the number of fibers.

Multi-Reflectance-Spectroscopy, Part I: Theory and Calculations Using Simulated Milk Samples

Optical methods are appropriate for monitoring of constituents in suspensions and emulsions. A simple multi-wavelength, multi-reflectance spectroscopic technique, called MRS-Technology, is introduced. Two different signals of a sample are measured: the reflectance from a small and from a large measuring volume corresponding to the reduced scattering coefficient μSCA' and to the sum of μSCA' and the absorption coefficient μ_ABS, respectively. Analytical relations between the MRS reflectance and μ_ABS as well as μSCA' are derived. The investigations on MRS method are carried out using milk as an example. For this purpose "virtual" milk samples are defined. μ_ABS and μSCA' are calculated by means of the Mie scattering theory in the ultraviolet-visible-shortwave near-infrared (UV-Vis-SWNIR) spectral range. Using this data analytical reflectances can be calculated based on MRS theory as well as numerical reflectances obtained by Monte Carlo (MC) simulation. Analytical and numerical results are compared and investigated. The spectral behavior of the analytical reflectances is very similar to that of the numerical MC reflectances in the case of medium and low absorptions. By means of simple multilinear regression techniques (MLR), simple correlations between fat and protein volume fractions and reflectances could be generated with acceptable root mean square error (RMSE) values. Each correlation shows that best results will be achieved by using reflectances at sample-specific wavelengths for small and large measuring volumes of a sample indicating the potential of the MRS-Technology.

Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles

SIGNIFICANCE

Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements.

AIM

The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications.

APPROACH

A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses.

RESULTS

EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus.

CONCLUSIONS

Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.

Using Diffuse Reflectance Spectroscopy to Distinguish Tumor Tissue From Fibrosis in Rectal Cancer Patients as a Guide to Surgery

BACKGROUND AND OBJECTIVES

In patients with rectal cancer who received neoadjuvant (chemo)radiotherapy, fibrosis is induced in and around the tumor area. As tumors and fibrosis have similar visual and tactile feedback, they are hard to distinguish during surgery. To prevent positive resection margins during surgery and spare healthy tissue, it would be of great benefit to have a real-time tissue classification technology that can be used in vivo.

STUDY DESIGN/MATERIALS AND METHODS

In this study diffuse reflectance spectroscopy (DRS) was evaluated for real-time tissue classification of tumor and fibrosis. DRS spectra of fibrosis and tumor were obtained on excised rectal specimens. After normalization using the area under the curve, a support vector machine was trained using a 10-fold cross-validation.

RESULTS

Using spectra of pure tumor tissue and pure fibrosis tissue, we obtained a mean accuracy of 0.88. This decreased to a mean accuracy of 0.61 when tumor measurements were used in which a layer of healthy tissue, mainly fibrosis, was present between the tumor and the measurement surface.

CONCLUSION

It is possible to distinguish pure fibrosis from pure tumor. However, when the measurements on tumor also involve fibrotic tissue, the classification accuracy decreases. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Tissue diagnosis during colorectal cancer surgery using optical sensing: an in vivo study

Background

In colorectal cancer surgery there is a delicate balance between complete removal of the tumor and sparing as much healthy tissue as possible. Especially in rectal cancer, intraoperative tissue recognition could be of great benefit in preventing positive resection margins and sparing as much healthy tissue as possible. To better guide the surgeon, we evaluated the accuracy of diffuse reflectance spectroscopy (DRS) for tissue characterization during colorectal cancer surgery and determined the added value of DRS when compared to clinical judgement.

Methods

DRS spectra were obtained from fat, healthy colorectal wall and tumor tissue during colorectal cancer surgery and results were compared to histopathology examination of the measurement locations. All spectra were first normalized at 800 nm, thereafter two support vector machines (SVM) were trained using a tenfold cross-validation. With the first SVM fat was separated from healthy colorectal wall and tumor tissue, the second SVM distinguished healthy colorectal wall from tumor tissue.

Results

Patients were included based on preoperative imaging, indicating advanced local stage colorectal cancer. Based on the measurement results of 32 patients, the classification resulted in a mean accuracy for fat, healthy colorectal wall and tumor of 0.92, 0.89 and 0.95 respectively. If the classification threshold was adjusted such that no false negatives were allowed, the percentage of false positive measurement locations by DRS was 25% compared to 69% by clinical judgement.

Conclusion

This study shows the potential of DRS for the use of tissue classification during colorectal cancer surgery. Especially the low false positive rate obtained for a false negative rate of zero shows the added value for the surgeons.

Trail registration This trail was performed under approval from the internal review board committee (Dutch Trail Register NTR5315), registered on 04/13/2015, https://www.trialregister.nl/trial/5175.

Investigation of reflectance sampling depth in biological tissues for various common illumination/collection configurations

Knowledge of light penetration characteristics is very important in almost all studies in biomedical optics. In this work, the reflectance sampling depth in biological tissues was investigated using Monte Carlo simulations for various common illumination/collection configurations. The analysis shows that the average sampling depth can be described by two simple empirical analytical expressions over the entire typical ranges of absorption and scattering properties relevant to in vivo biological tissue, regardless of the specific illumination/collection configuration details. These results are promising and helpful for the quick, efficient, and accurate design of reflectance studies for various biological tissue applications.

Review of diverse optical fibers used in biomedical research and clinical practice

Optical fiber technology has significantly bolstered the growth of photonics applications in basic life sciences research and in biomedical diagnosis, therapy, monitoring, and surgery. The unique operational characteristics of diverse fibers have been exploited to realize advanced biomedical functions in areas such as illumination, imaging, minimally invasive surgery, tissue ablation, biological sensing, and tissue diagnosis. This review paper provides the necessary background to understand how optical fibers function, to describe the various categories of available fibers, and to illustrate how specific fibers are used for selected biomedical photonics applications. Research articles and vendor data sheets were consulted to describe the operational characteristics of conventional and specialty multimode and single-mode solid-core fibers, double-clad fibers, hard-clad silica fibers, conventional hollow-core fibers, photonic crystal fibers, polymer optical fibers, side-emitting and side-firing fibers, middle-infrared fibers, and optical fiber bundles. Representative applications from the recent literature illustrate how various fibers can be utilized in a wide range of biomedical disciplines. In addition to helping researchers refine current experimental setups, the material in this review paper will help conceptualize and develop emerging optical fiber-based diagnostic and analysis tools.

Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy

The sampling depth of light for diffuse reflectance spectroscopy is analyzed both experimentally and computationally. A Monte Carlo (MC) model was used to investigate the effect of optical properties and probe geometry on sampling depth. MC model estimates of sampling depth show an excellent agreement with experimental measurements over a wide range of optical properties and probe geometries. The MC data are used to define a mathematical expression for sampling depth that is expressed in terms of optical properties and probe geometry parameters.