标本数字人确定性有限元分析，虽已应用于计算机辅助外科手术仿真领域，但是，它不能描述临床患者群体的不确定性生理病理因素，亦不能明确与临床随机试验的相关性；在新手术临床决策时，它对增强医学证据体的效果与机理尚不清楚。本项研究遵循实验室与临床双向转化理念，针对关节和脊柱的创伤、畸形或退变性疾病，以活体组织、器械材料和生理动荷载等为随机变量，建立符合生物力学实验统计和回顾性病例统计的活体数字人随机动态有限元模型和控制方程。据此，对应关节脊柱新手术的前瞻性随机对照试验(RCT)，并行设计随机动态有限元治疗模型和对照模型。在RCT实施前，用随机模型预测优化RCT方案；在RCT实施中，对随机生物力学证据和RCT证据作有机合成；在RCT实施后，扩大临床试验以检验其与随机模型及RCT的证据一致性。这将使外科医学证据体系产生结构性优化，并建立活体数字人模型随机试验与临床随机试验循证支撑的数字外科优化规划策略。

Deterministic finite element analysis (FEA) of individualized cadaver digital-human has been applied sometime in the discipline of computer aided surgery (CAS), however, the deterministic FEA cannot indicate the uncertain physiologic and pathological factors of the patient population. The correlations between the deterministic FEA and the clinical randomized trials cannot be found either. In the clinical decision making of new operations, the reinforcement effect and mechanism of deterministic FEA on the medical evidence body still remains unclear. .Abiding by the translational medicine principle from bedside to bench to bedside (B to B to B), the project aims to study surgery optmization of the trauma,deformation or degenerative disease of joint and spine. According to biomechanical experiment statistics and retrospective clinical case statistics, the joint/spine living tissues and implant materials as well as physiologic loads of living body are defined as random variables, then stochastic dynamic finite element models and control equations of living digital-human will be developed. Further, corresponding to the prospective randomized controlled trial (RCT) of new surgical operations, stochastic finite element models of treatment group and control group will be designed in parallel. Before the RCT, stochastic finite element models will be utilized to optimize the RCT plan. During the RCT, stochastic biomechanical model evidences and randomized clinical trial evidences will be synthesized organically. After the RCT, the expanded clinical trials will be carried out to evaluate the evidence consistency with the stochastic models and the RCT. .Through this project, the evidence body of surgical medicine will be structurally optimized. The evidence-based optimization strategy supported by stochastic biomechanical model tests of living digital-human and clinical randomized trials will be established for digital surgery medicine of joint and spine.