ABSTRACT
Optical coherence tomography (OCT) is a promising tool for intraoperative tissue morphology determination. Several studies suggest that attenuation coefficient derived from the OCT images, can differentiate between tissues of different morphology, such as normal and pathological structures of the brain, skin, and other tissues. In the present study, the depth-resolved method for attenuation coefficient calculation was adopted for the real-world situation of the depth-dependent OCT sensitivity and additive imaging noise with nonzero mean. It was shown that in the case of sharp focusing (~10 µm spot full width at half maximum [FWHM] or smaller at 1.3 µm central wavelength) only the proposed method for depth-dependent sensitivity compensation does not introduce misleading artifacts into the calculated attenuation coefficient distribution. At the same time, the scanning beam focus spot with FWHM greater than 10 µm at 1.3 µm central wavelength allows one to use multiple approaches to the attenuation coefficient calculation without introducing noticeable bias. This feature may hinder the need for robust corrections for the depth-resolved attenuation coefficient estimations from the community.
Subject(s)
Skin , Tomography, Optical Coherence , Tomography, Optical Coherence/methods , Brain/diagnostic imaging , Algorithms , CarmustineABSTRACT
Introduction: To improve the quality of brain tumor resections, it is important to differentiate zones with myelinated fibers destruction from tumor tissue and normal white matter. Optical coherence tomography (OCT) is a promising tool for brain tissue visualization and in the present study, we demonstrate the ability of cross-polarization (CP) OCT to detect damaged white matter and differentiate it from normal and tumor tissues. Materials and methods: The study was performed on 215 samples of brain tissue obtained from 57 patients with brain tumors. The analysis of the obtained OCT data included three stages: 1) visual analysis of structural OCT images; 2) quantitative assessment based on attenuation coefficients estimation in co- and cross-polarizations; 3) building of color-coded maps with subsequent visual analysis. The defining characteristics of structural CP OCT images and color-coded maps were determined for each studied tissue type, and then two classification tests were passed by 8 blinded respondents after a training. Results: Visual assessment of structural CP OCT images allows detecting white matter areas with damaged myelinated fibers and differentiate them from normal white matter and tumor tissue. Attenuation coefficients also allow distinguishing all studied brain tissue types, while it was found that damage to myelinated fibers leads to a statistically significant decrease in the values of attenuation coefficients compared to normal white matter. Nevertheless, the use of color-coded optical maps looks more promising as it combines the objectivity of optical coefficient and clarity of the visual assessment, which leads to the increase of the diagnostic accuracy of the method compared to visual analysis of structural OCT images. Conclusions: Alteration of myelinated fibers causes changes in the scattering properties of the white matter, which gets reflected in the nature of the received CP OCT signal. Visual assessment of structural CP OCT images and color-coded maps allows differentiating studied tissue types from each other, while usage of color-coded maps demonstrates higher diagnostic accuracy values in comparison with structural images (F-score = 0.85-0.86 and 0.81, respectively). Thus, the results of the study confirm the potential of using OCT as a neuronavigation tool during resections of brain tumors.
ABSTRACT
A pilot post-mortem study identifies a strong correlation between the attenuation coefficient estimated from the OCT data and some morphological features of the sample, namely the number of nuclei in the field of view of the histological image and the fiber structural parameter introduced in the study to quantify the difference in the myelinated fibers arrangements. The morphological features were identified from the histopathological images of the sample taken from the same locations as the OCT images and stained with the immunohistochemical (IHC) staining specific to the myelin. It was shown that the linear regression of the IHC quantitative characteristics allows adequate prediction of the attenuation coefficient of the sample. This discovery opens the opportunity for the usage of the OCT as a neuronavigation tool.
ABSTRACT
Advanced stage glioma is the most aggressive form of malignant brain tumors with a short survival time. Real-time pathology assisted, or image guided surgical procedures that eliminate tumors promise to improve the clinical outcome and prolong the lives of patients. Our work is focused on the development of a rapid and sensitive assay for intraoperative diagnostics of glioma and identification of optical markers essential for differentiation between tumors and healthy brain tissues. We utilized fluorescence lifetime imaging (FLIM) of endogenous fluorophores related to metabolism of the glioma from freshly excised brains tissues. Macroscopic time-resolved fluorescence images of three intracranial animal glioma models and surgical samples of patients' glioblastoma together with the white matter have been collected. Several established and new algorithms were applied to identify the imaging markers of the tumors. We found that fluorescence lifetime parameters characteristic of the glioma provided background for differentiation between the tumors and intact brain tissues. All three rat tumor models demonstrated substantial differences between the malignant and normal tissue. Similarly, tumors from patients demonstrated statistically significant differences from the peritumoral white matter without infiltration. While the data and the analysis presented in this paper are preliminary and further investigation with a larger number of samples is required, the proposed approach based on the macroscopic FLIM has a high potential for diagnostics of glioma and evaluation of the surgical margins of gliomas.
