Résumé
BACKGROUND:Pelvic tilt,which is often seen in hip diseases,is also a common functional problem after total hip arthroplasty. OBJECTIVE:To investigate the mechanism of occurrence and recovery of pelvic tilt after unilateral total hip arthroplasty in patients with femoral head necrosis. METHODS:The clinical data of 100 patients with femoral head necrosis who underwent unilateral total hip arthroplasty in the Department of Femoral Head Necrosis,Bone Injury Center of First Affiliated Hospital of Guangzhou University of Chinese Medicine were collected retrospectively from June 2021 to February 2023.The patients were divided into three groups,namely,groups A(<2°,n=48),B(2°-3°,n=34),and C(>3°,n=18),according to the severity of pelvic tilt on postoperative 3 day.Statistical data were collected and compared between the pre-and postoperative periods of patients of these three groups in terms of the angle of the coronal plane of the pelvis tilt,the length of the gluteus medius muscles of the bilateral sides,the heights of the rotational centers of the femoral heads,the difference in the lengths of the gluteus medius muscles of the bilateral sides and the heights of the rotational centers of the femoral heads,and the ratio of changes in the angle of the pelvic tilt.Pearson correlation coefficient was used to examine the correlation between pelvic tilt angle and other indexes. RESULTS AND CONCLUSION:(1)Pelvic tilt aggravation occurred in the short term after surgery.(2)The ratio of change in pelvic tilt angle from postoperative 3 days to postoperative 1 month time period differed between the groups,with group C>group B>group A.There was a difference between group C and the other groups in the time period from postoperative 1 to postoperative 3 months,with the ratio of change being the smallest in group C.There was no difference in the ratio of change between the groups in the time period from postoperative 3 days to postoperative 3 months.(3)The difference in bilateral gluteus medius muscles decreased gradually after surgery,and there was no difference in the comparison of bilateral gluteus medius muscles in the time period from postoperative 3 months.(4)The difference between bilateral centers of rotation increased after surgery,and the difference between bilateral heights at 3 months after surgery was smaller than that before surgery.(5)The pelvic tilt angle at 3 days after surgery,the duration of the disease and the pelvic tilt angle at 3 months after surgery were significantly correlated(all P=0.000),and the difference between bilateral gluteus medius muscles before surgery and the pelvic tilt angle at 3 days after surgery was significantly correlated(P=0.006)(6)The functional pelvic tilt occurred in the patients with femoral head necrosis after total hip arthroplasty.Correction of the pelvic tilt after surgery was based on the adaptive restoration of the functional pelvic tilt angle after surgery.Functional pelvic tilt arises as a compensatory adaptation of the organism based on the short-term postoperative reconstruction of bony structures and the survival of cumulative soft tissue damage.
Résumé
Objective:To develop a deep transfer learning method for the differential diagnosis of osteonecrosis of the femoral head (ONFH) with other common hip diseases using anteroposterior hip radiographs.Methods:Patients suffering from ONFH, DDH, and other hip diseases including primary hip osteoarthritis, non-infectious inflammatory hip disease, and femoral neck fracture treated in the First Affiliated Hospital of Guangzhou University of Chinese Medicine from January 2018 to December 2020 were enrolled in the study. A clinical data set containing anteroposterior hip radiographs of the eligible patients was created. Data augmentation by rotating and flipping images was performed to enlarge the data set, then the data set was divided equally into a training data set and a testing data set. The ResNet-152, a deep neural network model, was used in the study, but the original Batch Normalization was replaced with Transferable Normalization to construct a novel deep transfer learning model. The model was trained to distinguish ONFH and DDH from other common hip diseases using anteroposterior hip radiographs on the training data set and its classification performance was evaluated on the testing data set.Results:The clinical data set was comprised of anteroposterior hip radiographs of 1024 hips, including 542 with ONFH, 296 with DDH, and 186 with other common hip diseases (56 hips with primary osteoarthritis, 85 hips with non-infectious inflammatory osteoarthritis, 45 hips with femoral neck fracture). After data augmentation, the size of the data set multiplied to 6144. The model was trained 100 050 times in each task. Accuracy was used as the representative parameter to evaluate the performance of the model. In the binary classification task to identify ONFH, the best accuracy was 95.80%. As for the multi-classification task for classification of ONFH and DDH from other hip diseases, the best accuracy was 91.40%. The plateau of the model was observed in each task after 50 000 times of training. The mean accuracy in plateaus was 95.35% (95% CI: 95.33%, 95.37%), and 90.85% (95% CI: 90.82%, 90.87%), respectively. Conclusion:The present study proves the encouraging performance of a deep transfer learning method for the first-visit classification of ONFH, DDH, and other hip diseases using the convenient and economical anteroposterior hip radiographs.