【摘要】 目的利用螺旋CT定位肱三头肌每个头的神经入肌点(NEP)的位置。方法 10具20侧中国成年人尸体上肢,俯卧。设计经皮肤连接肱骨外上髁至内上髁的曲线为横向参考线(H);肩峰至肱骨外上髁的曲线为纵向参考线(L)。解剖暴露肱三头肌各NEP,涂抹硫酸钡,用螺旋CT扫描确定NEP在体表的投影点(P和P’)。Syngo系统下,经P平行于臂轴的直线与H、水平线与L的交点分别记为PH和PL,测量PH和PL在H和L上的百分位置及NEP的深度。结果肱三头肌长头、外侧头及内侧头神经支的PH分别位于H的(55.29±1.78)%、(55.28±1.76)%和(57.67±0.99)%处;PL分别位于L的(48.12±1.58)%、(50.45±1.23)%和(55.15±1.83)%处;经过P的NEP深度分别位于PP’线的(37.94±1.07)%、(36.26±1.69)%和(43.45±1.25)%处。结论这些参数可为提高肱三头肌神经阻滞的效率和疗效提供形态学依据。更多还原

【Abstract】 Objective To identify the location of the nerve entry points(NEP) of each head of triceps brachii muscle by spiral computed tomography( CT). Methods Twenty sides of upper arm of 10 Chinese adult cadavers were dissected and exposed in the prone position. A curved line on the skin surface joining the lateral epicondyle and the medial epicondyle of humerus were designated as the horizontal reference line( H),while another curved line joining the acromion to the lateral epicondyle of humerus was designated as the longitudinal reference line(L). Following dissection,the NEP of each head of triceps brachii muscle were labeled with barium sulfate and the projection point of NEP on the body surface( P and P’) was determined by spiral CT scanning. The intersection points through P of the Parallel to arm axis line and the H and through P of the horizontal line and the L were designated as PHand PL,respectively. The location of PHand PLon the H and L and the depth of NEP were measured by Syngo system. Results The PHof the long head,the lateral head and the medial head nerve branch of triceps brachii muscle were located at(55. 29 ± 1. 78) %,(55. 28 ± 1. 76) % and(57. 67 ± 0. 99) % of the H,respectively. The PLwas located at(48. 12 ± 1. 58) %,(50. 45 ± 1. 23) % and(55. 15 ± 1. 83) % of the L line,respectively. The depth of NEP after the P was located at(37. 94 ± 1. 07) %,(36. 26 ± 1. 69) % and(43. 45 ± 1. 25)% of the PP’ line,respectively. Conclusion These parameters could provide morphological basis for improving the efficiency and efficacy of nerve block of triceps brachii muscle.更多还原