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ObjectiveDespite advancements of intraoperative visualization, the difficulty to visually distinguish adenoma from adjacent pituitary gland due to textural similarities may lead to incomplete adenoma resection or impairment of pituitary function. The aim of this study was to investigate optical coherence tomography (OCT) imaging in combination with a convolutional neural network (CNN) for objectively identify pituitary adenoma tissue in an ex vivo setting.MethodsA prospective study was conducted to train and test a CNN algorithm to identify pituitary adenoma tissue in OCT images of adenoma and adjacent pituitary gland samples. From each sample, 500 slices of adjacent cross-sectional OCT images were used for CNN classification.ResultsOCT data acquisition was feasible in 19/20 (95%) patients. The 16.000 OCT slices of 16/19 of cases were employed for creating a trained CNN algorithm (70% for training, 15% for validating the classifier). Thereafter, the classifier was tested on the paired samples of three patients (3.000 slices). The CNN correctly predicted adenoma in the 3 adenoma samples (98%, 100% and 84% respectively), and correctly predicted gland and transition zone in the 3 samples from the adjacent pituitary gland.ConclusionTrained convolutional neural network computing has the potential for fast and objective identification of pituitary adenoma tissue in OCT images with high sensitivity ex vivo. However, further investigation with larger number of samples is required.

Multimodal imaging platforms offer a vast array of tissue information in a single image acquisition by combining complementary imaging techniques. By merging different systems, better tissue characterization can be achieved than is possible by the constituent imaging modalities alone. The combination of optical coherence tomography (OCT) with non-linear optical imaging (NLOI) techniques such as two-photon excited fluorescence (TPEF), second harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) provides access to detailed information of tissue structure and molecular composition in a fast, label-free and non-invasive manner. We introduce a multimodal label-free approach for morpho-molecular imaging and spectroscopy and validate the system in mouse skin demonstrating the potential of the system for colocalized acquisition of OCT and NLOI signals.

Using optical coherence tomography (OCT) intraoperatively for pituitary gland and adenoma differentiation, might lead to a more distinct resection of tumor tissue. Therefore, more gland tissue would be preserved and invasively grown adenoma tissue can be detected and removed. We evaluate the feasibility of laser scanning microscope based OCT for differentiation of healthy and tumor tissue on biopsies resected during surgery. The OCT images are compared to histopathological results. Resolution reduced OCT images are automatically analyzed to estimate the performance parameters for a possible endoscopic translation.

In this work, we present a significant step toward in vivo ophthalmic optical coherence tomography and angiography on a photonic integrated chip. The diffraction gratings used in spectral-domain optical coherence tomography can be replaced by photonic integrated circuits comprising an arrayed waveguide grating. Two arrayed waveguide grating designs with 256 channels were tested, which enabled the first chip-based optical coherence tomography and angiography in vivo three-dimensional human retinal measurements. Design 1 supports a bandwidth of 22 nm, with which a sensitivity of up to 91 dB (830 µW) and an axial resolution of 10.7 µm was measured. Design 2 supports a bandwidth of 48 nm, with which a sensitivity of 90 dB (480 µW) and an axial resolution of 6.5 µm was measured. The silicon nitride-based integrated optical waveguides were fabricated with a fully CMOS-compatible process, which allows their monolithic co-integration on top of an optoelectronic silicon chip. As a benchmark for chip-based optical coherence tomography, tomograms generated by a commercially available clinical spectral-domain optical coherence tomography system were compared to those acquired with on-chip gratings. The similarities in the tomograms demonstrate the significant clinical potential for further integration of optical coherence tomography on a chip system., Optical coherence tomography: chip promise The goal of an optical coherence tomography (OCT) imaging system that is integrated on a photonic chip has taken a step closer to reality. Elisabet Rank and coworkers from Austria have shown that arrayed waveguide gratings (AWGs), integrated-optical devices commonly used to separate different wavelength channels in an optical communications system, can be used to replace diffraction gratings in an OCT system. Several designs of silicon nitride AWGs with 256 channels in the near-infrared were fabricated and then tested in an OCT system which was able to capture in-vivo tomograms and angiography of the human eye’s retina, with comparable quality to a conventional system. The next stage of the OCT-on-a-chip research will focus on exploring the use of multimode interference structures, integrated photodiodes, and compact light sources.

Ultrahigh resolution optical coherence tomography (UHR-OCT) for differentiating pituitary gland versus adenoma tissue has been investigated for the first time, indicating more than 80% accuracy. For biomarker identification, OCT images of paraffin embedded tissue are correlated to histopathological slices. The identified biomarkers are verified on fresh biopsies. Additionally, an approach, based on resolution modified UHR-OCT ex vivo data, investigating optical performance parameters for the realization in an in vivo endoscope is presented and evaluated. The identified morphological features–cell groups with reticulin framework–detectable with UHR-OCT showcase a promising differentiation ability, encouraging endoscopic OCT probe development for in vivo application.

Our study targets improved and accelerated diagnostics of bladder cancer with optical coherence tomography (OCT) and Raman spectroscopy (RS) ex vivo. OCT provides structural information on the penetration depth of the lesion, whereas RS complements this information with molecular characteristics regarding the likelihood of growth and spreading. Hence, the diagnostic findings include the determination of stage and grade of a tumor. The bladder specimens were scanned with OCT to detect suspicious lesions. Thereby, OCT was used as a red-flag technology to examine the bladder wall for abnormal tissue. Malignant bladder wall could be discriminated from healthy tissue. Upon identification of a cancerous lesion, RS added diagnostic information with molecular characteristics of the tumor regarding the grade. Texture analysis of OCT tomograms followed by k-nearest neighbour classification determined the stage of the lesion. Principal component analysis (PCA) of Raman spectra allowed for dimension reduction which was also fed into a k-nearest neighbour classifier allowing for classification of low-grade and high-grade tumors. We obtained an accuracy of 71% and 93% for staging and grading, respectively.

We present a combination of optical coherence tomography (OCT) and Raman spectroscopy (RS) for improved diagnosis and discrimination of different stages and grades of bladder cancer ex vivo by linking the complementary information provided by these two techniques. Bladder samples were obtained from biopsies dissected via transurethral resection of the bladder tumor (TURBT). As OCT provides structural information rapidly, it was used as a red-flag technology to scan the bladder wall for suspicious lesions with the ability to discriminate malignant tissue from healthy urothelium. Upon identification of degenerated tissue via OCT, RS was implemented to determine the molecular characteristics via point measurements at suspicious sites. Combining the complementary information of both modalities allows not only for staging, but also for differentiation of low-grade and high-grade cancer based on a multivariate statistical analysis. OCT was able to clearly differentiate between healthy and malignant tissue by tomogram inspection and achieved an accuracy of 71% in the staging of the tumor, from pTa to pT2, through texture analysis followed by k-nearest neighbor classification. RS yielded an accuracy of 93% in discriminating low-grade from high-grade lesions via principal component analysis followed by k-nearest neighbor classification. In this study, we show the potential of a multi-modal approach with OCT for fast pre-screening and staging of cancerous lesions followed by RS for enhanced discrimination of low-grade and high-grade bladder cancer in a non-destructive, label-free and non-invasive way.