Application of artificial intelligence based on neural network radiation field in repair of soft tissue defects at lower limbs
10.3760/cma.j.cn115530-20230105-00009
- VernacularTitle:基于神经网络辐射场的人工智能技术在下肢软组织缺损修复中的应用
- Author:
Fei WU
1
;
Feng LIU
;
Zhibo SUN
;
Wenxia XIAO
;
Wenna LUO
;
Kan MA
;
Yue YANG
Author Information
1. 武汉大学人民医院骨外科，武汉 430060
- Keywords:
Soft tissue injuries;
Lower extremity;
Surgical flaps;
Tissue transplantation;
Artificial intelligence;
Neural network radiation field
- From:
Chinese Journal of Orthopaedic Trauma
2023;25(3):213-218
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the application of artificial intelligence based on the neural network radiation field in repair of soft tissue defects at lower limbs.Methods:A retrospective analysis was performed of the 23 patients who had been admitted to Department of Orthopedic Surgery, Renmin Hospital of Wuhan University from June 2020 to May 2022 for soft tissue defects at lower limbs. There were 14 males and 9 females, aged (38.6±6.7) years. Causes for soft tissue defects: traffic injury in 9 cases, benign or malignant primary soft tissue tumor in 6 cases, mechanical injury in 4 cases, crush injury in 2 cases, and chronic ulcer in 2 cases. Defect locations: the thigh in 3 cases, the lower leg in 7 cases, and the ankle and distal foot in 13 cases. The areas of soft tissue defect ranged from 6.0 cm×3.8 cm to 14.7 cm×12.8 cm. The defects were repaired and reconstructed by transplantation of an anterolateral femoral free flap in 7 cases and a pedicled flap in 16 cases with the assistance of artificial intelligence based on the neural network radiation field, a cutting-edge artificial intelligence algorithm that can quickly construct and process three-dimensional model images through volume rendering under the radiation field. The flap survival rate, aesthetic satisfaction before and after treatment, time for skin flap harvesting and transplantation, functional recovery of lower limbs and incidence of complications were recorded.Results:All the 23 patients were followed up for 32(28, 36) weeks. All the flaps were harvested smoothly and survived. The time for flap harvesting and transplantation was 65.8(50.0, 76.0) min. The aesthetic satisfaction scored (2.3±0.7) points before treatment and (8.4±1.6) points 4 weeks after treatment, showing a statistically significant difference ( P<0.05). The skin flaps healed well with no complications such as hematoma or infection in all but one patient who suffered from superficial necrosis at the distal skin flap due to venous crisis but healed with a scar. On average, the functional recovery of lower limbs scored 23.7(22.0, 25.0) points at 12 weeks after operation according to the Enneking evaluation system, and the functional recovery of lower limbs was 79% (23.7/30.0). Conclusion:Application of artificial intelligence based on the neural network radiation field can achieve ideal results in repair of soft tissue defects at lower limbs, due to its advantages of rapid and accurate surgical procedures, limited damage to the donor site, and a short learning curve.
