The aim of “Precision Surgery” is to reduce the impact of surgeries on patients’ global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called “ikidney”, based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6–13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process.
“精准外科”的目标在于降低手术对患者整体健康的影响。近年来，器官三维虚拟模型（3DVMs）的应用为此提供了术中引导，能够显示隐藏的解剖目标，从而限制手术中对健康组织的剥离及后续损伤。为实现手术区域三维虚拟模型的自动叠加，我们基于卷积神经网络（CNNs）开发并测试了一款名为“ikidney”的新型软件。自2022年1月至2023年4月，研究纳入了适合接受机器人辅助肾部分切除术（RAPN）的局限性肾肿瘤患者。由生物工程师、软件开发人员和外科医生组成的团队利用卷积神经网络，共同创建了用于自动三维增强现实引导下RAPN的超高精度三维模型。研究收集了所有患者的人口统计学及临床资料，共纳入13例患者。平均锚定时间为11秒（范围6-13秒）。在静态场景中，有1例患者出现三维模型自动配准的短暂意外失败；在动态场景中，另有1例患者发生类似情况。其中1例失败案例中，术中使用超声探头定位肿瘤，并转为超声引导而非增强现实引导完成手术。所有病例均未记录到重大术中或术后并发症（即Clavien-Dindo分级>2级）。人工智能凭借其自主执行特定任务的能力，为临床实践开辟了诸多新领域。本研究将卷积神经网络应用于RAPN术中三维虚拟模型的自动叠加，显著提升了配准过程的精确度。
肿瘤(癌症)患者之家