痛风影像学诊断方法分析及发展  

Analysis and development of imaging diagnosis of gout

作　　者：王广涛 王鹏君 李大成(综述)[1] 邢士超(审校)[1] WANG Guangtao;WANG Pengjun;LI Dacheng;XING Shichao(Qingdao University, The Affiliated Hospital of Qingdao University Qingdao, Qingdao 266003, P.R.China)

机构地区：[1]青岛大学青岛大学附属医院,山东青岛266003

出　　处：《医学影像学杂志》2021年第1期113-118,共6页Journal of Medical Imaging

基　　金：国家自然科学基金面上项目(编号:81671625);山东省青岛市产业培育计划(科技惠民专项)(编号:17-3-3-15-nsh);山东省青岛市市南区科技发展计划项目(编号:2013-13-008-YY)。

摘　　要：痛风是由于尿酸盐沉积产生的异质代谢性疾病,严重者可导致关节残疾引起肾功能损伤,但若能早期诊断该病或可逆转。众所周知,痛风不同时期有不同的临床表现和影像学表现。一般而言,在痛风早期,其双轨征特征明显,特异性高,适合采用超声法进行检测;在痛风反复发作期及慢性期,适合采用X线平片、CT和MRI等影像技术进行检测,其中MRI能够精确评价痛风石的大小和内部结构;而双能CT(DECT)能够识别关节周围、肌腱、软组织中的尿酸盐结晶等,因此应该根据不同需要选择适合的影像学检测方法。另外,鉴于医学科技发展趋势,未来痛风影像学发展将会利用云计算、大数据、人工智能等技术构建智能医学影像诊断系统,将朝着图像融合、智能化诊疗方向不断拓展。Gout is a heterogeneous metabolic disorder caused by urate deposition.Severe gout can lead to joint disability and renal function damage,but if diagnosed early,the disease may be reversible.It is well known that gout has different clinical and imaging manifestations in different periods.Generally speaking,in the early stage of gout,the dual-track sign has obvious characteristics and high specificity,and it is suitable to be detected by ultrasound;in the recurrent and chronic stage of gout,it is suitable to be detected by X-ray,CT and MRI imaging techniques,in which MRI can accurately evaluate the size and internal structure of gout stones;and dual-energy CT(DECT)can identify the uric acid crystals around joints,tendons and soft tissues.Therefore,appropriate imaging detection methods should be selected according to different needs.In addition,in view of the development trend of medical science and technology,the future development of gout imaging will use cloud computing,big data,artificial intelligence and other technologies to build intelligent medical image diagnosis system,develop a precise disease treatment system,and will continue to expand towards image fusion and intelligent diagnosis and treatment.

关 键 词：痛风 影像学 智能化 

分 类 号：R445[医药卫生—影像医学与核医学] R593[医药卫生—诊断学]