In the treatment of esophageal cancer, the high postoperative complication rate is an issue because of the extensive lymph node resection for curative purposes. To optimize the extent of resection, we developed a forceps-type coincidence radiation detector based on the concept of positron emission tomography (PET) for precise intraoperative localization of metastases. The forceps-type coincidence radiation detector consists of a pair of miniaturized PET detectors mounted on the tip of the forceps. The forceps are clamped over a suspected metastatic site intraoperatively to measure the radiation and identify the site of metastasis based on 18F-labeled fluorodeoxyglucose accumulation above a certain threshold. However, the sensitivity of the forceps-type coincidence radiation detector depends on the distance between the pair of detectors mounted on the tips of the forceps, and maintaining a constant distance between these detectors is difficult because the handle is held in the palm of the surgeon operating the device. Achieving stable coincidence counting requires correction of the coincidence radiation sensitivity according to the distance between the detectors during measurement. Utilizing the fact that the distance between detectors depends on the tip angle of the forceps, we developed a system that executes the correction based on the forceps tip angle. A linear encoder was used to measure the displacement of the forceps shaft and estimate the forceps tip angle from the amount of displacement. We also evaluated the effect of correcting radiation detection sensitivity using an experimentally developed system. The radiation detection sensitivity was corrected to a mean (± standard deviation) dose of 22.3 ± 1.3 kBq compared to the true value of 21.3 kBq. The average correction error was 5%, indicating the correction capability of the developed system. However, the variations in correction values pose a risk of missing metastases. In the future, the accuracy of the correction system will be improved, and experiments will be conducted in the clinical environment.

Modern hepatectomies are planned along anatomical segments of the liver, and intraoperative injection of indocyanine green enables visualization of these segments using near-infrared fluorescence (NIRF) laparoscopy. However, subsegmental resections that extend partially beyond boundaries of the segments are increasingly attempted in patients with liver insufficiency, requiring additional anatomical understanding of the lesions. Recently, augmented reality (AR) has gained attention as a technique for overlaying preoperative anatomical information directly onto the surgical field. Nonetheless, achieving real-time and precise alignment of preoperative data onto surgical objects remains a challenge. To address this issue, we propose an AR system using a multimodal tissue marker detectable by both X-ray and NIRF, and an object-detection machine-learning model (YOLOv9). The multimodal AR marker was administered to excised porcine liver samples, and their NIRF laparoscopic and X-ray computed tomography (CT) images were acquired. Marker coordinates in the NIRF laparoscopic images were obtained using the YOLOv9 model, and the correspondence between markers in the CT and NIRF views were automatically determined using our original algorithm. CT marker images were reprojected onto the laparoscopic images based on their coordinates. The system achieved an 80.2% marker detection success rate in NIRF images, a 78.4% registration success rate, and a mean reprojection error of 3.9 pixels, with an average processing speed of 28.9 fps. These results demonstrate the potential of our proposed system to realize real-time AR navigation during laparoscopic liver surgeries. Although clinical application would require a hybrid operating room equipped with CT at the time of marker administration, this technology has the potential to superimpose internal structures of the liver onto the organ surface in the laparoscopic view on video monitors.

Minimally invasive laparoscopic surgery is widely used because it reduces patient burden compared with open surgery, and robotic assistance has further improved surgical precision and ergonomics. However, conventional laparoscopy is limited by a narrow field of view, creating blind spots that can lead to perioperative complications. To overcome this limitation, we developed a planar follower robot equipped with multiple cameras to provide multi-angle intra-abdominal visualization. The system integrates an field programmable gate array (FPGA)-based multi-camera transmission board capable of transmitting eight video streams at 30 fps, together with a leader-follower mechanism that enables intuitive shape control of the planar robot. Experimental evaluation showed that all eight camera feeds were acquired stably for more than 8 hours, with an inter-camera delay of approximately 10 ms and an end-to-end latency of 230 ms. In a laparoscopic training box, real-time viewpoint adjustment with the leader device allowed visualization of forceps tips and hidden regions that are not visible with a conventional laparoscope. These results demonstrate that the system can flexibly adjust camera perspectives and reduce blind spots, supporting both surgeon-operated and robot-controlled procedures. Although the current prototype remains limited by camera configuration and insertion size, this study establishes the feasibility and potential utility of a planar multi-camera robot for enhancing intraoperative visualization.

A thermal endoscope capable of controlling tumor temperature has been developed to achieve minimally invasive endoscopic photothermal therapy (PTT) with high therapeutic efficacy. However, the tumor temperature cannot be controlled at short measurement distances from the heated target. We have proposed a temperature estimation method to control tumor temperature even at a close range of the target during endoscopic examination. The proposed method estimates the temperature of the laser irradiation point by measuring the temperatures of discrete points around the laser irradiation point. In this study, we verified the measurement principle of this method. We assumed that the temperature distribution on the surface of the target follows the Gaussian function. In the proposed method, the temperature at the laser irradiation point was estimated from the temperatures measured at three points around the laser irradiation point. A temperature estimation experiment was conducted by targeting a circular silicone rubber disk heated at the center with an electric heating wire using a thermal imaging sensor. The temperature of the heated point was set at 40-60℃, and the measurement distance was set at 10-50 mm. The coordinates of the three points used for estimation were initially set at (x₁, x₂, x₃) = (−6.4 mm, −3.2 mm, 4.9 mm) from the heated point. We also evaluated point configuration scaled down to 0.8 times and up to 1.2 times the original size. Linearity was observed between the heating point temperature and the estimated temperature. Temperature estimation at approximately 43℃, which was the target temperature of PTT, was possible when the measurement distance was 20 mm or less. These results suggest that the heating point temperature can be estimated at short distances from the target using the proposed method.