An accurate tumor delineation in neurosurgery is still a very challenging problem which we are addressing with optical coherence elastography (OCE). Because of the highly viscoelastic properties of brain tissue, we developed a new Air-Jet based tissue excitation source and evaluated the tissue stiffness with a 3.2 MHz swept-source Optical Coherence Tomography (OCT) system with a line scan rate of 2.45 kHz. The phase based displacement per pixel is measured and stiffness maps are calculated for brain tumor samples. However, certain features in the stiffness maps are seemingly not correlatable to the tissue features in the histological sections. Therefore, the structural properties of the histological sections e.g. fiber orientation, cell nuclei concentration and the “onion structure” with their rotational direction for meningioma were given greater consideration. The structural information are extracted from the histological sections via color deconvolution and structural tensor analysis. First results show that the stiffness transitions correlate with some structures of the histological sections. In summary, the Air-Jet OCE seems to be capable of measuring the stiffness as well as the structural composition of the sample. The long-term aim of this project is to establish OCE to support tumor delineation in the field of neurosurgery.
Optical coherence elastography represents mechanical characteristics of biological tissue in so-called mechanical contrast maps. In addition to the standard intensity image, the contrast map illustrates numerous mechanical tissue features that would otherwise be undetectable. This is of great interest as abnormal physiological changes influence the mechanical behavior of the tissue. We demonstrate an advanced mechanical contrast approach based on the phase signal of our 3.2 MHz optical coherence tomography system. The robustness and performance of this contrast approach is evaluated and discussed based on preliminary results.
Optical coherence tomography is a powerful imaging technique to visualize and localize depth-dependent tissue structure to differentiate between healthy and pathological conditions. However, conventional OCT systems are only capable of detecting small areas. To overcome this limitation, we have developed a large area robotically assisted OCT (LARA-OCT) system for automatic acquisition of large OCT images. Using mosaic pattern acquisition and subsequent stitching, we previously demonstrated initial in vivo OCT skin images beyond 10 cm². To improve acquisition speed and reduce dead times, we here demonstrate and analyze LARA-OCT with a new drive-by continuous motion imaging protocol.
The long-term aim of this project is to establish optical coherence elastography for tumor delineation in the field of neurosurgery. Because of the challenging highly viscoelastic properties of brain tissue, we developed a new Air-Jet based excitation source. With pulse duration of up to 700 ms and real time force measurement, this novel system allows the sample to reach a semi-steady state. In parallel with a 3.2 MHz swept-source optical coherence tomography system over 800 line scans are acquired over the whole sample excitation process. The phase data is extracted, unwrapped and the displacement per pixel is calculated. This system enables the measurement of mechanical properties like stiffness and Young’s modulus, similar to the standard indentation measurement. As well as viscoelastic properties i.e. relaxation times, in non-contact. The first processing step is to split the excitation progression into three main time ranges: the high dynamic, the steady state, and the viscoelastic range. In each range typical features of the displacement curve are extracted for every pixel in the B-scan. For those features, various mechanical parameters are calculated mainly, the stiffness and Young’s modulus and stored as feature matrices. The results are processed, visualized and overlaid with either the OCT intensity image or the histological sections. Strain stress curves are generated for some selected positions in the B-scan leading to a specific viscoelastic hysteresis. The feature matrices will be utilized as a fingerprint for each tissue, and are the first step for an AI based classification of the tissue.
In neurosurgical tumor operations on the central nervous system, intraoperative haptic information often assists for discrimination between healthy and diseased tissue. Thus, it can provide the neurosurgeon with additional intraoperative source of information during resection, next to the visual information by the light microscope, fluorescent dyes and neuronavigation. One approach to obtain elastic and viscoelastic tissue characteristics non-subjectively is phase-sensitive optical coherence elastography (OCE), which is based on the principle of optical coherence tomography (OCT). While phase-sensitive OCE offers significantly higher displacement sensitivity inside a sample than commonly used intensity-based correlation methods, it requires a reliable algorithm to recover the phase signal, which is mathematically restricted in the -π to π range. This problem of phase wrapping is especially critical for inter-frame phase analysis since the time intervals between two referenced voxels is long. Here, we demonstrate a one-dimensional unwrapping algorithm capable of removing up to 4π-ambiguities between two frames in the complex phase data obtained from a 3.2 MHz-OCT system. The high sampling rate allows us to resolve large sample displacements induced by a 200 ms air pulse and acquires pixel-precise detail information. The deformation behavior of the tissue can be monitored over the entire acquisition time, offering various subsequent mechanical analysis procedures. The reliability of the algorithm and imaging concept was initially evaluated using different brain tumor mimicking phantoms. Additionally, results from human ex vivo brain tumor samples are presented and correlated with histological findings supporting the robustness of the algorithm.
Optical coherence tomography (OCT) is a powerful imaging technique to non-invasively differentiate between healthy skin and pathological conditions. Unfortunately, commercially available OCT-systems are typically slow and not capable of scanning large areas at reasonable speed. Since skin lesions may extend over several square centimeters, potential inflammatory infiltrates remain undetected. Here, we present large area robotically assisted OCT (LARA-OCT) for skin imaging. Therefor a collaborative robot is combined with an existing, home-built 3.3 MHz-OCT-system and for surface tracking an online probe-to-surface control is implemented which is solely based on the OCT surface signal. It features a combined surface-distance and surface-orientation closed-loop control algorithm, which enables automatic positioning and alignment of the probe across the target while imaging. This allows to acquire coherent OCT images of skin areas beyond 10 cm2.
Optical coherence elastography (OCE) offers the possibility of obtaining the mechanical behavior of a tissue. When also using a non-contact mechanical excitation, it mimics palpation without interobserver variability. One of the most frequently used techniques is phase-sensitive OCE. Depending on the system, depth-resolved changes in the sub-µm to nm range can be detected and visualized volumetrically. Such an approach is used in this work to investigate and detect transitions between healthy and tumorous brain tissue as well as inhomogeneities in the tumor itself to assist the operating surgeon during tumor resection in the future. We present time-resolved, phase-sensitive OCE measurements on various ex vivo brain tumor samples using an ultra-fast 3.2 MHz swept-source optical coherence tomography (SS-OCT) system with a frame rate of 2.45 kHz. 4 mm line scans are acquired which, in combination with the high imaging speed, allow monitoring and investigation of the sample's behavior in response to the mechanical load. Therefore, an air-jet system applies a 200 ms short air pulse to the sample, whose non-contact property facilitates the possibility for future in vivo measurements. Since we can temporally resolve the response of the sample over the entire acquisition time, the mechanical properties are evaluated at different time points with depth resolution. This is done by unwrapping the phase data and performing subsequent assessment. Systematic ex vivo brain tumor measurements were conducted and visualized as distribution maps. The study outcomes are supported by histological analyses and examined in detail.
We demonstrate ultra-large field of view OCT scanning using standard optics, a X-Y-galvanometer scanner and a synchronously driven motorized XYZ-positioning stage. The integration of a movable stage into our self-built 3.3 MHz- OCT system allows acquiring coherent ultra-large area images, fully leveraging the high speed potential of our system. For fast OCT-angiography, one galvanometer axis scanner is driven in a repetitive sawtooth pattern, fully synchronized to the movement of the linear stage, to obtain multiple measurements at each position. This technique requires exact synchronization, precise repositioning, and uniform movements with low tolerances to ensure a minimum revisitation error. We analyze error and performance of our setup and demonstrate angiographic imaging.
We demonstrate a 3.3 MHz A-scan rate OCT for rapid scanning of large areas of human skin. The mosaicking performance and different OCT imaging modalities including intervolume speckle contrast are evaluated.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.