Gao Yunliang, Tang Yuanyuan, Ren Da, Cheng Shunhua, Wang Yinhuai, Yi Lu, Peng Shuang
Department of Urology, The Second Xiangya Hospital, Central South University, Changsha, China.
Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China.
Front Oncol. 2021 Nov 15;11:724986. doi: 10.3389/fonc.2021.724986. eCollection 2021.
To evaluate the feasibility and effectivity of deep learning (DL) plus three-dimensional (3D) printing in the management of giant sporadic renal angiomyolipoma (RAML).
The medical records of patients with giant (>15 cm) RAML were retrospectively reviewed from January 2011 to December 2020. 3D visualized and printed kidney models were performed by DL algorithms and 3D printing technology, respectively. Patient demographics and intra- and postoperative outcomes were compared between those with 3D-assisted surgery (3D group) or routine ones (control group).
Among 372 sporadic RAML patients, 31 with giant ones were eligible for analysis. The median age was 40.6 (18-70) years old, and the median tumor size was 18.2 (15-28) cm. Seventeen of 31 (54.8%) had a surgical kidney removal. Overall, 11 underwent 3D-assisted surgeries and 20 underwent routine ones. A significant higher success rate of partial nephrectomy (PN) was noted in the 3D group (72.7% . 30.0%). Patients in the 3D group presented a lower reduction in renal function but experienced a longer operation time, a greater estimated blood loss, and a higher postoperative morbidity. Subgroup analysis was conducted between patients undergoing PN with or without 3D assistance. Despite no significant difference, patients with 3D-assisted PN had a slightly larger tumor size and higher nephrectomy score, possibly contributing to a relatively higher rate of complications. However, 3D-assisted PN lead to a shorter warm ischemia time and a lower renal function loss without significant difference. Another subgroup analysis between patients under 3D-assisted PN or 3D-assisted RN showed no statistically significant difference. However, the nearness of tumor to the second branch of renal artery was relatively shorter in 3D-assisted PN subgroup than that in 3D-assisted RN subgroup, and the difference between them was close to significant.
3D visualized and printed kidney models appear to be additional tools to assist operational management and avoid a high rate of kidney removal for giant sporadic RAMLs.
评估深度学习（DL）加三维（3D）打印技术在巨大散发性肾血管平滑肌脂肪瘤（RAML）治疗中的可行性和有效性。
回顾性分析2011年1月至2020年12月期间巨大（>15 cm）RAML患者的病历。分别采用DL算法和3D打印技术制作3D可视化和打印肾脏模型。比较3D辅助手术组（3D组）和常规手术组（对照组）患者的人口统计学资料及术中和术后结果。
在372例散发性RAML患者中，31例巨大RAML患者符合分析条件。中位年龄为40.6（18 - 70）岁，中位肿瘤大小为18.2（15 - 28）cm。31例患者中有17例（54.8%）接受了肾脏切除术。总体而言，11例患者接受了3D辅助手术，20例患者接受了常规手术。3D组部分肾切除术（PN）的成功率显著更高（72.7%对30.0%）。3D组患者肾功能下降程度较低，但手术时间较长，估计失血量较大，术后发病率较高。对接受或未接受3D辅助的PN患者进行亚组分析。尽管无显著差异，但接受3D辅助PN的患者肿瘤尺寸略大，肾切除评分更高，这可能导致并发症发生率相对较高。然而，3D辅助PN导致热缺血时间更短，肾功能损失更低，差异无统计学意义。对3D辅助PN或3D辅助肾切除术（RN）患者进行另一亚组分析，结果显示无统计学显著差异。然而，3D辅助PN亚组中肿瘤与肾动脉第二分支的距离比3D辅助RN亚组相对更短，两者之间的差异接近显著。
3D可视化和打印肾脏模型似乎是辅助手术管理、避免对巨大散发性RAML进行高比例肾脏切除的额外工具。
