Detection of human brain cancer infiltration ex vivo and in vivo using quantitative optical coherence tomography

Abstract

More complete brain cancer resection can prolong survival and delay recurrence. However, it is challenging to distinguish cancer from non-cancer tissues intraoperatively, especially at the transitional, infiltrative zones. This is especially critical in eloquent regions (e.g. speech and motor areas). This study tested the feasibility of label-free, quantitative optical coherence tomography (OCT) for differentiating cancer from non-cancer in human brain tissues. Fresh ex vivo human brain tissues were obtained from 32 patients with grades II-IV brain cancer and 5 patients with non-cancer brain pathologies. Based on volumetric OCT imaging data, pathologically confirmed brain cancer tissues (both high-grade and low-grade) had significantly lower optical attenuation values at both cancer core and infiltrated zones when compared with non-cancer white matter, and OCT achieved high sensitivity and specificity at an attenuation threshold of 5.5 mm-1 for brain cancer patients. We also used this attenuation threshold to confirm the intraoperative feasibility of performing in vivo OCT-guided surgery using a murine model harboring human brain cancer. Our OCT system was capable of processing and displaying a color-coded optical property map in real time at a rate of 110-215 frames per second, or 1.2-2.4 seconds for an 8-16 mm3 tissue volume, thus providing direct visual cues for cancer versus non-cancer areas. Our study demonstrates the translational and practical potential of OCT in differentiating cancer from non-cancer tissue. Its intraoperative use may facilitate safe and extensive resection of infiltrative brain cancers and consequently lead to improved outcomes when compared with current clinical standards.

Quantitative comparison of 3D third harmonic generation and fluorescence microscopy images

“…Such a qualitative link may verify that certain structures can be detected in both images, but remains indirect because it does not guarantee that each observed object or even the major part of it, indeed corresponds to, e. g., a brain cell. If the quantitative link between these novel images and fluorescence/H&E stained images can be established, it will facilitate and verify the interpretation of these novel images, and further strengthen their potential for real-time pathology of human brain tumors [6,21,24,25].…”

“…THG images of structurally normal and tumor tissues have been compared, not one-toone, with histopathological images of the same samples stained with hematoxylin and eosin (H&E) [6]. Similarly, the interpretation of other label free imaging techniques, such as simulated Raman scattering (SRS) microscopy and optical coherence tomography (OCT), has been qualitatively linked to H&E stained images [20,21,24].…”

“…The active contour models [33][34][35][36][37][38][39][40][41][42][43] became popular for automatic cell/nuclei segmentation at the beginning of this century when the classical CV model [33] was proposed. THG images, with Raman and other nonlinear microscopy images, differ from labeled-fluorescence images in their complexity, inherent to their high information density [5,6,20,21,24,25,[44][45][46][47]62]. A limited number of segmentation methods has been explored on THG images of several tissue types.…”

Highly Accurate Detection of Cancer In Situ with Intraoperative, Label-Free, Multimodal Optical Spectroscopy

“…OCT provides microscopic structural imaging. It has been used to detect brain cancer based on optical attenuation (14). RS provides vibrational molecular information based on inelastic light scattering from molecular species, including amino acids, lipids, proteins, and nucleic acid.…”

Review of intraoperative optical coherence tomography: technology and applications [Invited]

“…Additionally, variations in collagen orientation and content was also exploited to differentiate cancerous tissue from healthy ex vivo breast tissue using polarization-sensitive OCT [163]. Alternatively, Kut et al demonstrated that tissue scattering coefficients estimated from OCT volumes could be used to quantitatively differentiate between cancerous and noncancerous tissue and help guide brain tumor resections [164]. A color-coded map denoting regions of high scattering and low scattering, corresponding to healthy and normal tissue, respectively, was generated in real-time to provide visual feedback to the surgeon (Fig.…”