Using three-dimensional virtual imaging of renal masses to improve prediction of robotic-assisted partial nephrectomy Tetrafecta with SPARE score.

IF 2.8 2区 医学 Q2 UROLOGY & NEPHROLOGY
HaoXiang Huang, Bohong Chen, Cong Feng, Wei Chen, Dapeng Wu
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引用次数: 0

Abstract

Objective: To improve the predictability of outcomes in robotic-assisted partial nephrectomy, we utilized three-dimensional virtual imaging for SPARE nephrometry scoring. We compared this method with a conventional two-dimensional scoring system to determine whether 3D virtual images offer enhanced predictive accuracy for Tetrafecta outcomes.

Methods: We retrospectively collected basic information, demographic data, and perioperative indices from patients who underwent robot-assisted partial nephrectomy for renal masses at the Department of Urology, First Affiliated Hospital of Xi'an Jiaotong University. A three-dimensional visualization system (IPS system, Yorktal) was employed to reconstruct the patients' imaging data using AI-based automatic segmentation, resulting in a three-dimensional visualization model (3DVM). This model was then imported into the virtual surgical planning software (Touch Viewer System, Yorktal) for automatic measurement of the SPARE score. Tetrafecta was defined as a warm ischemic time (WIT) of less than 25 min, negative surgical margins, absence of major perioperative complications, and no decline in postoperative renal function. The receiver operating characteristic (ROC) curve was utilized to evaluate the sensitivity and specificity of the SPARE score.

Results: A total of 141 patients were included in this study, with a mean age of 55.6 ± 11.14 years and a mean tumor size of 3.5 ± 1.2 cm. All variables, except for estimated blood loss (EBL) (Coefficient = 0.056, 0.035; P = 0.514, 0.685), showed significant correlation with the SPARE score when comparing CT and 3D virtual models (Tetrafecta: Coefficient = 0.408, 0.56; P < 0.001, < 0.001; WIT: Coefficient = 0.340, 0.237; P < 0.001, 0.007; ΔeGFR: Coefficient = 0.212, 0.257; P = 0.012, 0.002). The area under the curve (AUC) values from the ROC curves indicated that the 3D virtual model group had significantly better performance than the 2D image group for the SPARE score. However, there was no significant difference in the ROC curves for the SPARE complexity category between the two imaging modalities (AUC for SPARE category with 3DVM = 0.658 vs. AUC for SPARE category with CT = 0.643, P = 0.59; AUC for SPARE score with 3DVM = 0.854 vs. AUC for SPARE score with CT = 0.755, P < 0.001).

Conclusions: The SPARE score combined with 3DVM has a more accurate predictive ability for Tetrafecta of RAPN compared to the traditional 2D SPARE score.

利用肾脏肿块的三维虚拟成像提高机器人辅助部分肾切除术的预测。
目的:为了提高机器人辅助部分肾切除术结果的可预测性,我们利用三维虚拟成像技术进行SPARE肾测量评分。我们将这种方法与传统的二维评分系统进行了比较,以确定3D虚拟图像是否能提高四趾炎结果的预测准确性。方法:回顾性收集在西安交通大学第一附属医院泌尿外科行机器人辅助肾部分切除术的患者的基本信息、人口学资料和围手术期指标。采用三维可视化系统(IPS系统,Yorktal)对患者影像数据进行基于人工智能的自动分割重建,得到三维可视化模型(3DVM)。然后将该模型导入虚拟手术计划软件(Touch Viewer System, Yorktal)中,自动测量SPARE评分。Tetrafecta被定义为热缺血时间(WIT)小于25分钟,阴性手术切缘,无主要围手术期并发症,术后肾功能无下降。采用受试者工作特征(ROC)曲线评价SPARE评分的敏感性和特异性。结果:本研究共纳入141例患者,平均年龄55.6±11.14岁,平均肿瘤大小3.5±1.2 cm。除估计失血量(EBL)外,所有变量(系数= 0.056,0.035;P = 0.514, 0.685),与CT与3D虚拟模型的SPARE评分有显著相关性(Tetrafecta:系数= 0.408,0.56;P结论:与传统2D SPARE评分相比,SPARE评分联合3DVM对RAPN四趾症的预测能力更准确。
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来源期刊
World Journal of Urology
World Journal of Urology 医学-泌尿学与肾脏学
CiteScore
6.80
自引率
8.80%
发文量
317
审稿时长
4-8 weeks
期刊介绍: The WORLD JOURNAL OF UROLOGY conveys regularly the essential results of urological research and their practical and clinical relevance to a broad audience of urologists in research and clinical practice. In order to guarantee a balanced program, articles are published to reflect the developments in all fields of urology on an internationally advanced level. Each issue treats a main topic in review articles of invited international experts. Free papers are unrelated articles to the main topic.
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