Intelligent laparoscopic grasper with hybrid neural networks for real-time vascular detection in minimally invasive surgery

We address the challenge of inadequate force feedback in laparoscopic surgery, which increases the risk of vessel injury. By integrating fiber Bragg grating (FBG) sensors with a laparoscopic grasper and employing a convolutional neural network combined with long short-term memory (CNN-LSTM) algorithm, this approach enables real-time, accurate vessel identification, potentially reducing surgical complications. Laparoscopic surgery is often hindered by inadequate force feedback, especially in complex scenarios involving tumor invasion and pelvic-abdominal adhesion, leading to challenges in locating blood vessels and an increased risk of vessel injury. Thus, it is desirable to develop a laparoscopic system capable of distinguishing the location and type of the vessels during surgery, which requires a compact and highly sensitive sensor integrated with a laparoscopic grasper. We present an innovative laparoscopic grasper integrated with FBG force sensors for real-time force feedback, employing silicone and porcine vessel models to simulate varying depths and tissue coverage. The device successfully captured specific vessel signals, which were processed through a CNN-LSTM algorithm, enabling real-time vessel identification in minimally invasive surgery (MIS). The intelligent laparoscopic grasper successfully obtained distinct vessel signals under varying conditions. As a result, the mean vessel gripping force for porcine vessel model III was 0.059 N under fatty tissue and 0.032 N under muscle tissue ( p<0.001 ). The CNN-LSTM algorithm achieved a precision of 97.06% in vessel identification across different tissue coverages. The FBG sensor-integrated laparoscopic grasper, assisted by the processing of the CNN-LSTM algorithm, demonstrated the ability to identify vessels ex vivo across different models. This technology holds potential for real-time and accurate vessel identification during MIS, which could significantly reduce the occurrence of unnecessary vessel injuries.