摘要
女性盆底器官、肌肉及周围结缔组织的结构和功能的改变是造成女性盆底功能障碍性疾病(pelvic floor disorders,PFD)的主要原因,细致了解盆底病理生理状态下的空间解剖结构能够帮助临床医师做出精确诊断以优化治疗策略。磁共振成像(magnetic resonance imaging,MRI)技术的广泛应用提高了临床医师对于盆底构造的认识,但其对于盆底结构的展示仍停留于二维平面影像,无法直观展示三维空间结构。而基于MRI的三维重建技术能够将女性盆底器官结构转化为数字模型用以观察、测量甚至用于三维打印后进行逆向分析,极大地推动了临床对于PFD发病到治疗的认识并为个体化诊疗提供依据。尽管如此,现有MRI三维重建技术尚未成熟,如不同商业软件使用方式各有优劣、不同图形识别技术算法各异、三维重建模型尚无统一评价标准、建模效率与质量难以平衡等问题,均限制其成为有效的PFD的医学研究手段。为此,该文归纳基于MRI的女性盆底组织器官三维数字模型重建的研究进展,旨在为PFD的临床诊治及科学研究提供参考。
Changes in the structure and function of female pelvic floor organs,muscles and surrounding connective tissue are the main causes of pelvic floor disorders(PFD),and a detailed understanding of the spatial anatomy of the pelvic floor under physiological and pathological conditions can help clinicians make accurate diagnoses and optimize treatment strategies.The widespread use of magnetic resonance imaging(MRI)technology has improved clinicians'understanding of the pelvic floor structure,but presentation of the pelvic floor structure is still limited to two-dimensional planar images and the three-dimensional(3D)spatial structure cannot be visualized.The 3D reconstruction technology based on MRI can transform the structure of the female pelvic floor organs into digital models for observation,measurement and even 3D printing for inverse analysis,which greatly promotes the clinical understanding of the pathogenesis and treatment of PFD and provides basis for individualized treatment.However,the existing MRI-based 3D reconstruction technology is not yet mature,for example different advantages and disadvantages of different commercial softwares,different algorithms of different image recognition techniques,lack of uniform evaluation criteria for 3D reconstruction models,and difficulty of balancing modeling efficiency and quality,which limit it as an effective medical research tool for PFD.This paper reviews the research of 3D digital model reconstruction of female pelvic floor tissue and organs based on MRI,aiming to provide reference for clinical diagnosis,treatment and scientific research of PFD.
作者
陈立奇
薛卓维
吴氢凯
CHEN Liqi;XUE Zhuowei;WU Qingkai(Department of Obstetrics and Gynecology,Shanghai Sixth People's Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai 200233,China)
出处
《上海交通大学学报(医学版)》
CAS
CSCD
北大核心
2022年第3期381-386,共6页
Journal of Shanghai Jiao tong University:Medical Science
基金
国家自然科学基金(82071631,81771523)。
关键词
盆底
磁共振成像
三维成像
图形识别
深度学习
pelvic floor
magnetic resonance imaging(MRI)
three-dimensional imaging
pattern recognition
deep learning