scholarly journals Application of Classification Algorithms to Diffuse Reflectance Spectroscopy Measurements for Ex Vivo Characterization of Biological Tissues

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 736 ◽  
Author(s):  
Félix Fanjul-Vélez ◽  
Sandra Pampín-Suárez ◽  
José Luis Arce-Diego
Keyword(s):  
Operating Room ◽  
Diffuse Reflectance ◽  
Diffuse Reflectance Spectroscopy ◽  
Ex Vivo ◽  
Biological Tissues ◽  
Reflectance Spectroscopy ◽  
Healthy Tissue ◽  
Classification Algorithms ◽  
Discrimination Analysis ◽  
Tissue Identification

Biological tissue identification in real clinical scenarios is a relevant and unsolved medical problem, particularly in the operating room. Although it could be thought that healthy tissue identification is an immediate task, in practice there are several clinical situations that greatly impede this process. For instance, it could be challenging in open surgery in complex areas, such as the neck, where different structures are quite close together, with bleeding and other artifacts affecting visual inspection. Solving this issue requires, on one hand, a high contrast noninvasive technique and, on the other hand, powerful classification algorithms. Regarding the technique, optical diffuse reflectance spectroscopy has demonstrated such capabilities in the discrimination of tumoral and healthy biological tissues. The complex signals obtained, in the form of spectra, need to be adequately computed in order to extract relevant information for discrimination. As usual, accurate discrimination relies on massive measurements, some of which serve as training sets for the classification algorithms. In this work, diffuse reflectance spectroscopy is proposed, implemented, and tested as a potential technique for healthy tissue discrimination. A specific setup is built and spectral measurements on several ex vivo porcine tissues are obtained. The massive data obtained are then analyzed for classification purposes. First of all, considerations about normalization, detrending and noise are taken into account. Dimensionality reduction and tendencies extraction are also considered. Featured spectral characteristics, principal component or linear discrimination analysis are applied, as long as classification approaches based on k-nearest neighbors (k-NN), quadratic discrimination analysis (QDA) or Naïve Bayes (NB). Relevant parameters about classification accuracy are obtained and compared, including ANOVA tests. The results show promising values of specificity and sensitivity of the technique for some classification algorithms, even over 95%, which could be relevant for clinical applications in the operating room.

scholarly journals Comparing in vivo and ex vivo fiberoptic diffuse reflectance spectroscopy in colorectal cancer

2019 ◽  
Vol 1 (1-2) ◽  
Author(s):  
Elisabeth J.M. Baltussen ◽  
Susan G. Brouwer De Koning ◽  
Benno H.W. Hendriks ◽  
Katarzyna Jóźwiak ◽  
Henricus J.C.M. Sterenborg ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Diffuse Reflectance ◽  
Diffuse Reflectance Spectroscopy ◽  
Ex Vivo ◽  
Reflectance Spectroscopy

Medical applications of reflectance spectroscopy in the diffusive and sub-diffusive regimes

2018 ◽  
Vol 26 (6) ◽  
pp. 337-350 ◽  
Author(s):  
Sharmin Akter ◽  
Md. Golzar Hossain ◽  
Izumi Nishidate ◽  
Hisanao Hazama ◽  
Kunio Awazu
Keyword(s):  
Diffuse Reflectance ◽  
Diffuse Reflectance Spectroscopy ◽  
Biological Tissues ◽  
Disease Diagnosis ◽  
Structural Features ◽  
Reflectance Spectroscopy ◽  
Medical Applications ◽  
Light Spectrum ◽  
Tissue Morphology ◽  
Reflected Light

Diffuse reflectance spectroscopy is a widely used technique for medical applications that may analyze the optical characteristics of biological tissues. By using diffuse reflectance spectroscopy, different tissue types can be distinguished based on specific changes on reflected light spectrum that are a result of differences on a molecular level between compared tissues. Identification of the structural features of tissue can be performed by applying diffuse reflectance spectroscopy, and the spectra obtained from this technique could provide important diagnostic information about the tissue morphology and physiology. Moreover, different tissue types can be classified using diffuse reflectance spectroscopy, during surgery on the basis of their optical properties that are related to the tissue morphology and constituents. In recent years, several research groups have been shown the feasibility of diffuse reflectance spectroscopy in discriminating benign and malignant tissue, and thus making it a good competitor for margin assessment. Therefore, the diffuse reflectance spectroscopy has the possibility to become an important optical means for disease diagnosis, treatment and prognosis monitoring. This review represents a summary of the literature on diffuse reflectance spectroscopy and its important clinical applications.

scholarly journals Raman Spectroscopy Differentiates Each Tissue from the Skin to the Spinal Cord

2016 ◽  
Vol 125 (4) ◽  
pp. 793-804 ◽  
Author(s):  
T. Anthony Anderson ◽  
Jeon Woong Kang ◽  
Tatyana Gubin ◽  
Ramachandra R. Dasari ◽  
Peter T. C. So
Keyword(s):  
Raman Spectroscopy ◽  
Real Time ◽  
Diffuse Reflectance ◽  
Diffuse Reflectance Spectroscopy ◽  
Ex Vivo ◽  
Needle Insertion ◽  
Reflectance Spectroscopy ◽  
Epidural Needle ◽  
Needle Placement ◽  
Porcine Tissue

Abstract Background Neuraxial anesthesia and epidural steroid injection techniques require precise anatomical targeting to ensure successful and safe analgesia. Previous studies suggest that only some of the tissues encountered during these procedures can be identified by spectroscopic methods, and no previous study has investigated the use of Raman, diffuse reflectance, and fluorescence spectroscopies. The authors hypothesized that real-time needle-tip spectroscopy may aid epidural needle placement and tested the ability of spectroscopy to distinguish each of the tissues in the path of neuraxial needles. Methods For comparison of detection methods, the spectra of individual, dissected ex vivo paravertebral and neuraxial porcine tissues were collected using Raman spectroscopy (RS), diffuse reflectance spectroscopy, and fluorescence spectroscopy. Real-time spectral guidance was tested using a 2-mm inner-diameter fiber-optic probe-in-needle device. Raman spectra were collected during the needle’s passage through intact paravertebral and neuraxial porcine tissue and analyzed afterward. The RS tissue signatures were verified as mapping to individual tissue layers using histochemical staining and widefield microscopy. Results RS revealed a unique spectrum for all ex vivo paravertebral and neuraxial tissue layers; diffuse reflectance spectroscopy and fluorescence spectroscopy were not distinct for all tissues. Moreover, when accounting for the expected order of tissues, real-time Raman spectra recorded during needle insertion also permitted identification of each paravertebral and neuraxial porcine tissue. Conclusions This study demonstrates that RS can distinguish the tissues encountered during epidural needle insertion. This technology may prove useful during needle placement by providing evidence of its anatomical localization.

scholarly journals Diffuse reflectance photometric system for noninvasive blood glucose control

2021 ◽  
Vol 2091 (1) ◽  
pp. 012014
Author(s):  
K V Pozhar ◽  
M O Mikhailov ◽  
E A Polyakova ◽  
E L Litinskaia
Keyword(s):  
Diffuse Reflectance ◽  
Diffuse Reflectance Spectroscopy ◽  
Blood Glucose Control ◽  
Biological Tissues ◽  
Reflectance Spectroscopy ◽  
Measuring System ◽  
Photometric System ◽  
Pulsed Mode ◽  
Laser Sources ◽  
Fixed System

Abstract The paper considers the method of diffuse reflectance spectroscopy for noninvasive glucose level measuring in biological tissues. It is proposed a portable implementation of the system, based on a laser diode with a wavelength of 1600 nm and a power of 30 mW, operating in a pulsed mode, as well as a set of NIR-photodiodes located around the laser. The measuring system has been tested on model solutions with diffuse reflectance from polystyrene and pigskin. In the course of measurements on fixed system, an error of ~17 mg/dl is observed, which can be reduced by improving miniature laser sources.

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