This work presents a novel approach to the use of bidirectional swept sources. A MEMS-VCSEL light source with a bidirectional sweeping rate of 1.6MHz is used. Bidirectional sweeping poses a challenge as the tuning curve is different for each sweep. To exploit the full performance of the swept source, both sweeps within the bidirectional sweeping must be utilized and compensated. The proposed approach involves a software solution based on the Master-Slave protocol, where sets of theoretically inferred channelled spectra (masks) are prepared in advance for each sweep. The phase retrieval method called CMS (Complex Master Slave) is employed to handle bidirectional sweeping SS-OCT, involving the calculation of two sets of functions for each sweeping direction. The correct set of masks is used for each sweep direction to accurately represent A-Scan peaks. Differences in the sweep are analysed. Finally, the proposed method is successfully tested on posterior and anterior chambers.
Significance: In multiphoton microscopy, two-photon excited fluorescence (TPEF) spectra carry valuable information on morphological and functional biological features. For measuring these biomarkers, separation of different parts of the fluorescence spectrum into channels is typically achieved by the use of optical band pass filters. However, spectra from different biomarkers can be unknown or overlapping, creating a crosstalk in between the channels. Previously, establishing these channels relied on prior knowledge or heuristic testing.
Aim: The presented method aims to provide spectral bands with optimal separation between groups of specimens expressing different biomarkers.
Approach: We have developed a system capable of resolving TPEF with high spectral resolution for the characterization of biomarkers. In addition, an algorithm is created to simulate and optimize optical band pass filters for fluorescence detection channels. To demonstrate the potential improvements in cell and tissue classification using these optimized channels, we recorded spectrally resolved images of cancerous (HT29) and normal epithelial colon cells (FHC), cultivated in 2D layers and in 3D to form spheroids. To provide an example of an application, we relate the results with the widely used redox ratio.
Results: We show that in the case of two detection channels, our system and algorithm enable the selection of optimized band pass filters without the need of knowing involved fluorophores. An improvement of 31,5% in separating different 2D cell cultures is achieved, compared to using established spectral bands that assume NAD(P)H and FAD as main contributors of autofluorescence. The compromise is a reduced SNR in the images.
Conclusions: We show that the presented method has the ability to improve imaging contrast and can be used to tailor a given label-free optical imaging system using optical band pass filters targeting a specific biomarker or application.
Endoscopes and other optical, non-invasive diagnostic instruments require measurable parameters (biomarkers) that reliably represent early signs of cancer. These biomarkers are challenging to identify in complex tissues due to their dependence on environmental and disease specific influences. In Multiphoton Microscopy (MPM), signals are commonly separated into channels using optical filters. The choice of channels typically relies on generalized prior knowledge. In order to establish more disease specific biomarkers, a reliable cancer model is desired. We present a method to study biomarkers using spheroids as a cancer model. The spheroid development and harvesting are monitored using Optical Coherence Tomography (OCT). We further introduce a hyperspectral MPM system to investigate biomarkers in the autofluorescence of cancerous and normal cell lines. To improve the detection of the selected biomarkers, an algorithm suggests corresponding filters for diagnostic or research purposes.
We have developed a system capable of resolving Two-Photon Fluorescence Emission (TPFE) and Second Harmonic Generation (SHG) signals with high spectral resolution for the characterization of biomarkers. In Multiphoton Microscopy, those biomarkers are TPFE and SHG signals that carry valuable information on morphological and functional biological features, such as the presence of Green Fluorescent Protein (GFP) in a Zebrafish during the building of organs, or the ratio of pyridine nucleotide (NAD(P)H) and flavin adenine dinucleotide (FAD) in the classification of cancerous tissue. For this purpose, separation of different signals into channels is typically achieved by the use of optical filters. In doing so, signal spectra can be unknown or overlapping, creating a crosstalk in between the channels. Previously the choice of such filters relied on prior knowledge or heuristic testing. Our system allows for the study of biomarkers due to spectrally resolved imaging. It therefore enables the appropriate selection of channels, tailored to the application, when building fast diagnostic systems. Additionally, knowledge of the spectra can be used to avoid the crosstalk in between channels or compensate for it computationally. To demonstrate the capabilities of the system, we recorded spectrally resolved images of tissue and cell samples. Structural and functional biological features were identified and their spectra could be evaluated. Thus, appropriate filter setups for diagnostic imaging can be suggested and confirmed by means of integration over defined virtual channels.
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