RESUMO
Stratification of the risk of lymph node metastasis (LNM) in patients with non-curative resection after endoscopic resection (ER) for early gastric cancer (EGC) is crucial in determining additional treatment strategies and preventing unnecessary surgery. Hence, we developed a machine learning (ML) model and validated its performance for the stratification of LNM risk in patients with EGC. We enrolled patients who underwent primary surgery or additional surgery after ER for EGC between May 2005 and March 2021. Additionally, patients who underwent ER alone for EGC between May 2005 and March 2016 and were followed up for at least 5 years were included. The ML model was built based on a development set (70%) using logistic regression, random forest (RF), and support vector machine (SVM) analyses and assessed in a validation set (30%). In the validation set, LNM was found in 337 of 4428 patients (7.6%). Among the total patients, the area under the receiver operating characteristic (AUROC) for predicting LNM risk was 0.86 in the logistic regression, 0.85 in RF, and 0.86 in SVM analyses; in patients with initial ER, AUROC for predicting LNM risk was 0.90 in the logistic regression, 0.88 in RF, and 0.89 in SVM analyses. The ML model could stratify the LNM risk into very low (<1%), low (<3%), intermediate (<7%), and high (≥7%) risk categories, which was comparable with actual LNM rates. We demonstrate that the ML model can be used to identify LNM risk. However, this tool requires further validation in EGC patients with non-curative resection after ER for actual application.
RESUMO
Typical pneumatic soft micro actuators can be manufactured without using heavy driving components such as pumps and power supplies by adopting an independent battery-powered mechanism. In this study, a thermopneumatically operated soft micro bellows actuator was manufactured, and the standalone operation of the actuator was experimentally validated. Thermopneumatic actuation is based on heating a sealed cavity inside the elastomer of the actuator to raise the pressure, leading to deflection of the elastomer. The bellows actuator was fabricated by casting polydimethylsiloxane (PDMS) using the 3D-printed soluble mold technique to prevent leakage, which is inherent in conventional soft lithography due to the bonding of individual layers. The heater, manufactured separately using winding copper wire, was inserted into the cavity of the bellows actuator, which together formed the thermopneumatic actuator. The 3D coil heater and bellows allowed immediate heat transfer and free movement in the intended direction, which is unachievable for conventional microfabrication. The fabricated actuator produced a stroke of 2184 µm, equivalent to 62% of the body, and exerted a force of 90.2 mN at a voltage of 0.55 V. A system in which the thermopneumatic actuator was driven by alkaline batteries and a control circuit also demonstrated a repetitive standalone operation.
