术前和术中泌尿系结石成分分析的研究进展  

The progress of preoperative and intraoperative urinary calculi analysis

作　　者：王碧霄 梁磊[1] 李晋庭 刘宇保 邢宇翔[2] 肖博[1] 胡卫国[1] 李建兴[1] Wang Bixiao;Liang Lei;Li Jinting;Liu Yubao;Xing Yuxiang;Xiao Bo;Hu Weiguo;Li Jianxing(Department of Urology,Tsinghua Changgeng Hospital,School of Clinical Medicine,Tsinghua University,Beijing 102218,China;Department of Engineering Physics,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学附属北京清华长庚医院泌尿外科、清华大学临床医学院,北京102218 [2]清华大学工程物理系,北京100084

出　　处：《中华泌尿外科杂志》2023年第6期471-475,共5页Chinese Journal of Urology

摘　　要：近年来,泌尿系结石疾病发病率和复发率居高不下,结石成分分析对进一步了解泌尿系结石的病理生理过程、制订有效的预防策略和精准的治疗方案有重要意义。影像学评估是术前结石分析的主要方法,双能CT检查在对结石主要成分识别方面表现出应用潜力,光子计数能谱CT检查则有望实现像素级的结石成分精准化分析。术中结石成分分析主要依靠内窥镜下图像的自动化识别,利用机器学习算法可对常见结石成分进行较可信的预测,引人形态结构分类法(MCC)和术中肾乳头病变的观察和描述是对结石成分分析及代谢成因评估的重要补充。本文对术前、术中结石成分分析的研究进展进行综述,以提高临床医生对结石成分分析重要性的认识,为进一步开展相关临床研究提供方向。The incidence and recurrence rates of urinary stone diseases have remained high recently,and stone analysis is of great significance for further understanding of the pathophysiological processes of urinary stones and to develop effective prevention strategies and precise treatment.Imaging evaluation is the main method of preoperative stone analysis,and dual-energy CT has shown its potential in identifying common main components of stones.The emergence of photon counting spectral CT is expected to achieve accurate analysis of stone components at the pixel level.The intraoperative stone analysis mainly relies on the automatic recognition of endoscopic images,and using machine learning algorithms can more reliably predict common stone composition.It is of great significance for stone analysis and assessment of metabolic causes by introducing morpho-constitutional classification(MCC)and observing and describing the papillary renal lesions during operation.This article reviews the progress of preoperative and intraoperative stone analysis,in order to improve clinicians'understanding of the importance of stone analysis,and provide a direction for further clinical research.

关 键 词：尿路结石 结石分析 成分分析 双能CT 机器学习 

分 类 号：R699[医药卫生—泌尿科学]