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Abstract In surgery, the surgical smoke generated during tissue dissection and hemostasis can degrade the image quality, affecting tissue visibility and interfering with the further image processing. Developing reliable and interpretable computational imaging methods for restoring smoke‐affected surgical images is crucial, as typical image restoration methods relying on color‐texture information are insufficient. Here a computational polarization imaging method through surgical smoke is demonstrated, including a refined polarization difference estimation based on the discrete electric field direction, and a corresponding prior‐based estimation method, for better parameter estimation and image restoration performance. Results and analyses for ex vivo, the first in vivo animal experiments, and human oral cavity tests show that the proposed method achieves visibility restoration and color recovery of higher quality, and exhibits good generalization across diverse imaging scenarios with interpretability. The method is expected to enhance the precision, safety, and efficiency of advanced image‐guided and robotic surgery.

This study aims to review the status of the clinical use of monoclonal antibodies (mAbs) that have completed or are in ongoing clinical trials for targeted fluorescence-guided surgery (T-FGS) for the intraoperative identification of the tumor margins of extra-hematological solid tumors. For each of them, the targeted antigen, the mAb generic/commercial name and format, and clinical indications are presented, together with utility, doses, and the timing of administration. Based on the current scientific evidence in humans, the top three mAbs that could be prepared in a GMP-compliant bank ready to be delivered for surgical purposes are proposed to speed up the translation to the operating room and produce a few readily available “off-the-shelf” injectable fluorescent probes for safer and more effective solid tumor resection.

Abstract Gastrointestinal endoscopy is a subjective procedure that frequently requires tissue samples for diagnosis. Contact optical biopsy (OB) techniques have the aim of providing direct diagnosis of endoscopic areas without excising tissue samples but lack the wide‐area coverage required for locating and resecting lesions. This article presents a large‐area robotically deployed OB imaging platform for endoscopic detection of colorectal cancer as an add‐on for conventional endoscopes. In vitro, in silicon colon phantoms, the platform achieves an optical resolution of 0.5 line pairs per millimeter, while resolving simulated cancer lesions down to 0.75 mm diameter across large‐area images (55‐103 cm2). Large‐area OB images were generated in an ex vivo porcine colon. The platform allows centimeter‐sized large‐area OB imaging in vitro and ex vivo with submillimeter resolution, including automatic data segmentation of simulated cancer areas. The ability for robotic actuation and spectrum collection is also shown for ex vivo animal colon. If successful, this technology could widen access to user‐independent high‐quality endoscopy and early detection of gastrointestinal cancers.

Abstract Re-operation due to disease being inadvertently close to the resection margin is a major challenge in breast conserving surgery (BCS). Indocyanine green (ICG) fluorescence imaging could be used to visualize the tumor boundaries and help surgeons resect disease more efficiently. In this work, ICG fluorescence and color images were acquired with a custom-built camera system from 40 patients treated with BCS. Images were acquired from the tumor in-situ, surgical cavity post-excision, freshly excised tumor and histopathology tumour grossing. Fluorescence image intensity and texture were used as individual or combined predictors in both logistic regression (LR) and support vector machine models to predict the tumor extent. ICG fluorescence spectra in formalin-fixed histopathology grossing tumor were acquired and analyzed. Our results showed that ICG remains in the tissue after formalin fixation. Therefore, tissue imaging could be validated in freshly excised and in formalin-fixed grossing tumor. The trained LR model with combined fluorescence intensity (pixel values) and texture (slope of power spectral density curve) identified the tumor’s extent in the grossing images with pixel-level resolution and sensitivity, specificity of 0.75 ± 0.3, 0.89 ± 0.2.This model was applied on tumor in-situ and surgical cavity (post-excision) images to predict tumor presence.

Up to 19% of patients require re-excision surgery due to positive margins in breast-conserving surgery (BCS). Intraoperative margin assessment tools (IMAs) that incorporate tissue optical measurements could help reduce re-excision rates. This review focuses on methods that use and assess spectrally resolved diffusely reflected light for breast cancer detection in the intraoperative setting. Following PROSPERO registration (CRD42022356216), an electronic search was performed. The modalities searched for were diffuse reflectance spectroscopy (DRS), multispectral imaging (MSI), hyperspectral imaging (HSI), and spatial frequency domain imaging (SFDI). The inclusion criteria encompassed studies of human in vivo or ex vivo breast tissues, which presented data on accuracy. The exclusion criteria were contrast use, frozen samples, and other imaging adjuncts. 19 studies were selected following PRISMA guidelines. Studies were divided into point-based (spectroscopy) or whole field-of-view (imaging) techniques. A fixed-or random-effects model analysis generated pooled sensitivity/specificity for the different modalities, following heterogeneity calculations using the Q statistic. Overall, imaging-based techniques had better pooled sensitivity/specificity (0.90 (CI 0.76–1.03)/0.92 (CI 0.78–1.06)) compared with probe-based techniques (0.84 (CI 0.78–0.89)/0.85 (CI 0.79–0.91)). The use of spectrally resolved diffusely reflected light is a rapid, non-contact technique that confers accuracy in discriminating between normal and malignant breast tissue, and it constitutes a potential IMA tool.

The manufacturing process for GRIN lenses causes a symmetric birefringence variation which is considered a deficiency. Here, the authors show how this birefringence can generate vector vortex beams and form the basis of a Müller matrix polarimeter with potential for endoscopic label-free cancer diagnostics.

The importance of polarization aberrations has been recognized and studied in numerous optical systems and related applications. It is known that polarization aberrations are particularly crucial in certain photogrammetry and microscopy techniques that are related to vectorial information—such as polarization imaging, stimulated emission depletion microscopy, and structured illumination microscopy. Hence, a reduction in polarization aberrations would be beneficial to different types of optical imaging/sensing techniques with enhanced vectorial information. In this work, we first analyzed the intrinsic polarization aberrations induced by a high-NA lens theoretically and experimentally. The aberrations of depolarization, diattenuation, and linear retardance were studied in detail using the Mueller matrix polar-decomposition method. Based on an analysis of the results, we proposed strategies to compensate the polarization aberrations induced by high-NA lenses for hardware-based solutions. The preliminary imaging results obtained using a Mueller matrix polarimeter equipped with multiple coated aspheric lenses for polarization-aberration reduction confirmed that the conclusions and strategies proposed in this study had the potential to provide more precise polarization information of the targets for applications spanning across classical optics, remote sensing, biomedical imaging, photogrammetry, and vectorial optical-information extraction.

Mueller matrix polarimetry is a potentially powerful technique for obtaining microstructural information of biomedical specimens. Thus, it has found increasing application in both backscattering imaging of bulk tissue samples and transmission microscopic imaging of thin tissue slices. Recently, we proposed a technique to transform the 4 × 4 Mueller matrix elements into a group of parameters, which have explicit associations with specific microstructural features of samples. In this paper, we thoroughly analyze the relationships between the Mueller matrix transformation parameters and the characteristic microstructures of tissues by using experimental phantoms and Monte Carlo simulations based on different tissue mimicking models. We also adopt quantitative evaluation indicators to compare the Mueller matrix transformation parameters with the Mueller matrix polar decomposition parameters. The preliminary imaging results of bulk porcine colon tissues and thin human pathological tissue slices demonstrate the potential of Mueller matrix transformation parameters as biomedical diagnostic indicators. Also, this study provides quantitative criteria for parameter selection in biomedical Mueller matrix imaging.