Background: Ureteral injury during laparoscopic surgery is rare, but when it occurs, it can be a serious problem. Near-infrared fluorescence (NIRF) with methylene blue (MB) administration is a promising technique for easier and potentially earlier intraoperative visualization of the ureter. Aim of this prospective study was to assess the feasibility of NIRF imaging of the ureter during laparoscopic colorectal surgery, using MB. Methods: Patients undergoing laparoscopic colorectal surgery were included and received intravenous injection of MB preoperatively. The ureter was visualized using a laparoscope, which offered both conventional and fluorescence imaging. Intraoperative recognition of the ureter was registered. The precision of ureter distinction with MB imaging was compared to the conventional laparoscopic view. Results: Ten patients were included. All procedures were initially performed using a laparoscopic approach. Dose per injection ranged between 0.125 mg/kg and 1.0 mg/kg bodyweight. There were no adverse effects attributable to MB administration. The ureter was successfully detected in five patients, with highest contrast between ureter and surrounding tissue at an administered dose of 0.75–1.0 mg/kg. The fluorescent signal was only picked up after the ureter was already visible in the conventional white light mode. Conclusion: Ureteral fluorescence imaging using MB proved to be safe and feasible. However, the present technique does not provide practical advantage over conventional laparoscopic imaging for identification of the ureter during laparoscopic colorectal surgery. Future research is necessary to explore more extensive dose finding, alternative fluorescent dyes, or improvement of the imaging system to make this application clinically beneficial.

Background Ureteric injury is reported to occur in 1–7.6% of colorectal surgeries. To reduce the incidence of ureteral injury, it is essential to identify the ureters. The use of near-infrared fluorescence (NIRF) imaging with intravenously administered dyes might be of added value for ureteral visualization during laparoscopy. The aim of this study is to assess the performance of three preclinical dyes; IRDye^® 800BK, IRDye^® 800NOS and IRDye^® 800CW, for near-infrared fluorescence laparoscopy of the ureter in pigs. Methods In three female Dutch landrace pigs, the new dyes were evaluated. In each pig, 1 dye was tested using a 6-mg intravenous dose in a concentration of 1 mg/ml. Imaging was performed in fluorescence mode and white light mode with a laparoscopic imaging system. In order to further evaluate the dyes, an ex vivo imaging experiment was performed, in which 8 decreasing concentrations per dye, diluted in PBS, were evaluated in a transparent test tube with NIRF mode at a distance of 1, 5 and 10 cm from the laparoscope. Results All three dyes were effective in allowing the identification of the ureter with NIRF imaging. The ureter became fluorescent after 35, 45 and 10 min, respectively, for IRDye^® 800BK, IRDye^® 800NOS and IRDye^® 800CW with a maximum target-to-background ratio (TBR) of 2.14, 0.66 and 1.44, respectively. In the ex vivo imaging experiment, all three dyes produced a strong fluorescence signal at all concentrations and all distances evaluated. Conclusions Intravenous administration of the preclinical dyes IRDye^® 800CW, IRDye^® 800 BK and IRDye^® 800NOS facilitated successful identification of the anatomical course of the ureter in living pig models. The highest measured TBR occurred with the use of IRDye^® 800BK. Ex vivo, a correlation was observed between the fluorescence intensities of the signal with the concentration of the dye and with the distance to the object.

Hyperspectral imaging (HSI) is a non-invasive imaging modality already applied to evaluate hepatic oxygenation and to discriminate different models of hepatic ischemia. Nevertheless, the ability of HSI to detect and predict the reperfusion damage intraoperatively was not yet assessed. Hypoxia caused by hepatic artery occlusion (HAO) in the liver brings about dreadful vascular complications known as ischemia-reperfusion injury (IRI). Here, we show the evaluation of liver viability in an HAO model with an artificial intelligence-based analysis of HSI. We have combined the potential of HSI to extract quantitative optical tissue properties with a deep learning-based model using convolutional neural networks. The artificial intelligence (AI) score of liver viability showed a significant correlation with capillary lactate from the liver surface (r = −0.78, p = 0.0320) and Suzuki’s score (r = −0.96, p = 0.0012). CD31 immunostaining confirmed the microvascular damage accordingly with the AI score. Our results ultimately show the potential of an HSI-AI-based analysis to predict liver viability, thereby prompting for intraoperative tool development to explore its application in a clinical setting.

Background Iatrogenic ureteric injury remains a risk in laparoscopic pelvic procedures. Near‐infrared fluorescence (NIRF) imaging is a promising new technique for enhanced intraoperative visualization of anatomical structures that could improve the safety of laparoscopic surgery. A new dye, IRDye® 800‐BK, has been developed for intraoperative visualization of the ureters using NIRF. The present study was a first evaluation of the performance of IRDye® 800‐BK for ureteric imaging during NIRF laparoscopy. Methods This study consisted of three parts: real‐time in vivo NIRF imaging using IRDye® 800‐BK in pigs during laparoscopic surgery, ex vivo NIRF imaging of freshly explanted pig ureters and ex vivo NIRF imaging of explanted human ureters. Results In all animals, both left and right ureters were visualized throughout the laparoscopic procedure for 120 min, with the best results at a dose of 0·15 mg dye per kg bodyweight. NIRF imaging was successful in all human and porcine ureters studied, with a range of dye concentrations. Conclusion NIRF imaging of the ureters using IRDye® 800‐BK was used successfully both in vivo in a porcine model, and ex vivo in porcine and human ureters.

Complete mesocolic excision (CME), which involves the adequate resection of the tumor-bearing colonic segment with “en bloc” removal of its mesocolon along embryological fascial planes is associated with superior oncological outcomes. However, CME presents a higher complication rate compared to non-CME resections due to a higher risk of vascular injury. Hyperspectral imaging (HSI) is a contrast-free optical imaging technology, which facilitates the quantitative imaging of physiological tissue parameters and the visualization of anatomical structures. This study evaluates the accuracy of HSI combined with deep learning (DL) to differentiate the colon and its mesenteric tissue from retroperitoneal tissue. In an animal study including 20 pig models, intraoperative hyperspectral images of the sigmoid colon, sigmoid mesentery, and retroperitoneum were recorded. A convolutional neural network (CNN) was trained to distinguish the two tissue classes using HSI data, validated with a leave-one-out cross-validation process. The overall recognition sensitivity of the tissues to be preserved (retroperitoneum) and the tissues to be resected (colon and mesentery) was 79.0 ± 21.0% and 86.0 ± 16.0%, respectively. Automatic classification based on HSI and CNNs is a promising tool to automatically, non-invasively, and objectively differentiate the colon and its mesentery from retroperitoneal tissue.