Caroline Girmen

We introduce a high-speed method for compensating the meniscus effect in phase-contrast microscopy that increases the area observable under phase-contrast conditions substantially while enabling rapid whole-microtiter-plate imaging. The meniscus effect in liquid-filled wells restricts phase-contrast imaging to a central region, here termed the phase-contrast area. Multiple compensation methods have been proposed, but an increased phase contrast area requires a high-throughput imaging process to limit total scan time. Our approach meets this need by combining meniscus effect compensation with high-speed scanning in a two-step workflow consisting of one scan to precompute condenser annulus positions and a second scan for imaging the specimen. Compensation is achieved by inserting a transparent LCD into the illumination path to display an adaptive virtual condenser annulus as a binary pattern. A continuous scanning mode enables high-speed imaging, in which shots are acquired during sample motion. The LCD is synchronized with the sample movement and image acquisition using path-synchronous triggers, with latency compensation for the LCD. Experiments show that the phase-contrast area increases by up to 8.96-fold relative to standard phase-contrast microscopy, depending on well size and magnification. We validated our approach against a slower and less complex stop-and-go method, which yielded similar phase-contrast areas, indicating no adverse effect of continuous acquisition on image quality. In contrast, the total scan time was reduced by a factor of up to 24.6 compared with stop-and-go, from 439 min to 17 min 52 s for 96-well MTPs at 10× magnification, achieved at frame rates of up to 60 frames per second, demonstrating the effectiveness of the proposed method.

Background/Objectives: Early and complete (R0) surgical resection is essential for optimal outcomes in pancreatic cancer. Optical coherence tomography (OCT) combined with artificial intelligence (AI) may offer real-time intraoperative guidance, potentially reducing reliance on frozen sections. This ex vivo study evaluated convolutional neural networks (CNNs) for distinguishing pancreatic ductal adenocarcinoma (PDAC) from normal pancreatic tissue in OCT images obtained ex vivo. Methods: Between October 2020 and April 2021, OCT scans were obtained from resected pancreatic specimens of 27 adult patients. Tumor and adjacent normal tissue were imaged using a 1310 nm OCT system, followed by histopathological confirmation. A total of 25 PDAC and 30 non-malignant scans were preprocessed and analyzed using cross-validated CNN models (ResNet50, DenseNet121, and MobileNetV2) with both 2D and 3D inputs. Results: Using five-fold stratified cross-validation on 9040 2D and 3000 3D samples (224 px resolution), the 3D DenseNet121 model achieved the highest performance, with an F1-score of 0.74, sensitivity of 72%, and specificity of 81%. Other architectures demonstrated comparable results. Conclusions: AI-assisted OCT can accurately differentiate PDAC from normal pancreatic tissue ex vivo, supporting its potential as a rapid intraoperative diagnostic adjunct. Further studies are warranted to assess its in vivo performance and utility in evaluating resection margins.

In this paper, a new measurement principle for decoupling mechanical and thermal signals in an OFDR measurement with integrated optical fibres is investigated. Previous methods for decoupling require additional measuring equipment or knowledge about the substrate properties. This new method is based solely on simultaneous measurements of two fibres with different temperature sensitivities resulting from different core doping processes. By exposing both fibres to the same thermal and mechanical load, the signal could be differentiated through the signal variations caused by the thermo-optical effect. The two fibres used in the tests have a sufficient response difference in the cryogenic temperature range. Therefore, the method is suitable for various applications, such as high-temperature superconductors as well as cryogenic and space applications.