Department of Medical Equipment, The First Affiliated Hospital of University of South China, Hengyang, 421001 Hunan, China.
Department of Medical Equipment, The Second Affiliated Hospital of University of South China, Hengyang, 421001 Hunan, China.
Comput Math Methods Med. 2022 Apr 30;2022:2752444. doi: 10.1155/2022/2752444. eCollection 2022.
This research was aimed to explore the application value of intelligent algorithm-based digital images in Da Vinci robot-assisted treatment of patients with gastric cancer surgery. 154 patients were included as the research objects, with 89 cases in the control group underwent laparoscopic surgery, and 65 cases in the experimental group underwent robotic surgery. According to the propensity score, the patients in two groups were pair matched (1: 1), of which 104 cases (52 cases in each group) were successfully matched. The general data of patients, the changes in the images before and after the algorithm processing, the intraoperative and postoperative conditions, the pathological examination results, and the follow-up information were observed after matching. Compared with the original images, the images processed by the thread image edge detection algorithm had the significantly improved clarity, as well as highly reduced artifacts and noises. The sensitivity, specificity, and accuracy of image-assisted diagnosis were improved remarkably, showing the differences of statistical significance ( < 0.05). The total time of surgery, intraoperative bleeding, CRP (1d and 3d after surgery), and postoperative total abdominal drainage showed the significant differences as well ( < 0.05). The surgeries of patients in both groups met R0 resection (no tumor infiltration within 1 mm of the surgical margin), but there was a significant difference in the number of lymph node dissections ( < 0.05). The overall survival rates of patients in the experimental group and the control group were 83.0% and 76.1%, respectively, 2 years after surgery, with no significant difference ( > 0.05). The thread image edge detection algorithm produced a better processing effect on the images, which greatly improved the diagnostic sensitivity, specificity, and accuracy. Compared with endoscopic surgery, robotic surgery has better postoperative recovery, safety and reliability, and obvious advantages of minimally invasive surgery.
本研究旨在探讨基于智能算法的数字图像在达芬奇机器人辅助胃癌手术患者治疗中的应用价值。纳入 154 例患者作为研究对象,其中 89 例行腹腔镜手术的患者归入对照组,65 例行机器人手术的患者归入实验组。根据倾向评分进行 1:1 配对匹配,共成功匹配 104 例患者(每组 52 例)。观察两组患者的一般资料、算法处理前后图像的变化、术中及术后情况、病理检查结果及随访信息。与原始图像相比,经螺纹图像边缘检测算法处理后的图像清晰度显著提高,伪影和噪声明显降低。图像辅助诊断的灵敏度、特异度和准确度均显著提高,差异具有统计学意义( < 0.05)。手术总时间、术中出血量、术后第 1 天和第 3 天的 CRP 和术后总腹部引流均有显著差异( < 0.05)。两组患者的手术均达到 R0 切除(手术切缘 1mm 内无肿瘤浸润),但淋巴结清扫数量差异有统计学意义( < 0.05)。术后 2 年,实验组和对照组患者的总生存率分别为 83.0%和 76.1%,差异无统计学意义( > 0.05)。螺纹图像边缘检测算法对图像的处理效果更好,大大提高了诊断的灵敏度、特异度和准确度。与内镜手术相比,机器人手术具有更好的术后恢复、安全性和可靠性,微创优势明显。