松本 志郎

Abstract The advent of Artificial Intelligence (AI)-based object detection technology has made identification of position coordinates of surgical instruments from videos possible. This study aimed to find kinematic differences by surgical skill level. An AI algorithm was developed to identify X and Y coordinates of surgical instrument tips accurately from video. Kinematic analysis including fluctuation analysis was performed on 18 laparoscopic distal gastrectomy videos from three expert and three novice surgeons (3 videos/surgeon, 11.6 h, 1,254,010 frames). Analysis showed the expert surgeon cohort moved more efficiently and regularly, with significantly less operation time and total travel distance. Instrument tip movement did not differ in velocity, acceleration, or jerk between skill levels. The evaluation index of fluctuation β was significantly higher in experts. ROC curve cutoff value at 1.4 determined sensitivity and specificity of 77.8% for experts and novices. Despite the small sample, this study suggests AI-based object detection with fluctuation analysis is promising because skill evaluation can be calculated in real time with potential for peri-operational evaluation.

INTRODUCTION: An eyeglass gaze camera and a skeletal coordinate camera without sensors attached to the operator's body were used to monitor gaze and movement during a simulated surgical procedure. These new devices have the potential to change skill assessment for laparoscopic surgery. The suitability of these devices for skill assessment was investigated. MATERIAL AND METHODS: Six medical students, six intermediate surgeons, and four experts performed suturing tasks in a dry box. The tip positions of the instruments were identified from video recordings. Performance was evaluated based on instrument movement, gaze, and skeletal coordination. RESULTS: Task performance time and skeletal coordinates were not significantly different among skill levels. The total movement distance of the right instrument was significantly different depending on the skill level. The SD of the gaze coordinates was significantly different depending on skill level and was less for experts. The expert's gaze stayed in a small area with little blurring. CONCLUSIONS: The SD of gaze point coordinates correlates with laparoscopic surgical skill level. These devices may facilitate objective intraoperative skill evaluation in future studies.

We present three patients with T2 acinar cell carcinomas (ACC) (two of which were small) and discuss their clinical and pathological features. Case 1: A 34 year-old woman had a 2.6 cm iso- or hyperdense tumor. Enucleation was performed but final diagnosis was ACC and a pylorus preserving pancreaticoduodenectomy was performed. Case 2: A 35 year-old woman was found to have a 4.5 cm hypervascular tumor in the tail of the pancreas. Distal pancreatectomy was performed. Case 3: A 61 year-old man suffered from acute pancreatitis and was found to have an encapsulated 2.5 cm hypervascular tumor in the head of pancreas. Pylorus-preserving pancreaticoduodenectomy was performed. These three patients with T2 ACCs had common characteristics including well-demarcated exophytic tumors with slow and limited progress, distinctively different from large ACCs and pancreatic ductal adenocarcinomas. ACCs are important in the differential diagnosis of homogeneously or heterogeneously enhancing small pancreatic tumors.