An adaptable research platform for ex vivo normothermic machine perfusion of the liver.

PURPOSE: This paper presents an assessment of a low-cost organ perfusion machine designed for use in research settings. The machine is modular and versatile in nature, built on a robotic operating system (ROS2) pipeline allowing for the addition of specific sensors for different research applications. Here we present the system and the development stages to achieve viability of the perfused organ. METHODS: The machine's perfusion efficacy was assessed by monitoring the distribution of perfusate in livers using methylene blue dye. Functionality was evaluated by measuring bile production after 90 min of normothermic perfusion, while viability was examined using aspartate transaminase assays to monitor cell damage throughout the perfusion. Additionally, the output of the pressure, flow, temperature, and oxygen sensors was monitored and recorded to track the health of the organ during perfusion and assess the system's capability of maintaining the quality of data over time. RESULTS: The results show the system is capable of successfully perfusing porcine livers for up to three hours. Functionality and viability assessments show no deterioration of liver cells once normothermic perfusion had occurred and bile production was within normal limits of approximately 26 ml in 90 min showing viability. CONCLUSION: The developed low-cost perfusion system presented here has been shown to keep porcine livers viable and functional ex vivo. Additionally, the system is capable of easily incorporating several sensors into its framework and simultaneously monitor and record them during perfusion. The work promotes further exploration of the system in different research domains.

Organ curvature sensing using pneumatically attachable flexible rails in robotic-assisted laparoscopic surgery.

In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney often due to the presence of a mass. A drop-in ultrasound probe paired to a surgical robot is deployed to execute multiple swipes over the kidney surface to localise the mass and define the margins of resection. This sub-task is challenging and must be performed by a highly-skilled surgeon. Automating this sub-task may reduce cognitive load for the surgeon and improve patient outcomes. The eventual goal of this work is to autonomously move the ultrasound probe on the surface of the kidney taking advantage of the use of the Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used for organ scanning and repositioning. First, we integrate a shape-sensing optical fibre into the PAF rail system to evaluate the curvature of target organs in robotic-assisted laparoscopic surgery. Then, we investigate the impact of the PAF rail's material stiffness on the curvature sensing accuracy, considering that soft targets are present in the surgical field. We found overall curvature sensing accuracy to be between 1.44% and 7.27% over the range of curvatures present in adult kidneys. Finally, we use shape sensing to plan the trajectory of the da Vinci surgical robot paired with a drop-in ultrasound probe and autonomously generate an Ultrasound scan of a kidney phantom.

Evaluation of A Novel Organ Perfusion Research Platform.

This paper presents a novel, low cost, organ perfusion machine designed for use in research. The modular and versatile nature of the system allows for additional sensing equipment to be added or adapted for specific use. Here we introduce the system and present its preliminary evaluation by assessing its ability to maintain a predetermined input pressure. A proportional-integral-derivative (PID) controller was implemented and tested on a porcine liver to maintain input pressure to the hepatic artery and compared to bench tests. The results confirmed the effectiveness of the controller for maintaining input through the hepatic artery (HA) in a timely manner. Clinical Relevance-Machine Perfusion (MP) is proving to be an invaluable adjunct in clinical practice. With its ongoing success in the transplant arena, we propose MP for use in research. A cost-effective, versatile system that can be modified for specific research use to test new pharmacological therapies, imaging techniques or develop simulation training would be beneficial.

Endoscopic add-on stiffness probe for real-time soft surface characterisation in MIS.

This paper explores a novel stiffness sensor which is mounted on the tip of a laparoscopic camera. The proposed device is able to compute stiffness when interacting with soft surfaces. The sensor can be used in Minimally Invasive Surgery, for instance, to localise tumor tissue which commonly has a higher stiffness when compared to healthy tissue. The purely mechanical sensor structure utilizes the functionality of an endoscopic camera to the maximum by visually analyzing the behavior of trackers within the field of view. Two pairs of spheres (used as easily identifiable features in the camera images) are connected to two springs with known but different spring constants. Four individual indenters attached to the spheres are used to palpate the surface. During palpation, the spheres move linearly towards the objective lens (i.e. the distance between lens and spheres is changing) resulting in variations of their diameters in the camera images. Relating the measured diameters to the different spring constants, a developed mathematical model is able to determine the surface stiffness in real-time. Tests were performed using a surgical endoscope to palpate silicon phantoms presenting different stiffness. Results show that the accuracy of the sensing system developed increases with the softness of the examined tissue.