BACKGROUND CONTEXT: Timely intervention in growing individuals, such as brace treatment, relies on early detection of adolescent idiopathic scoliosis (AIS). To this end, several screening methods have been implemented. However, these methods have limitations in predicting the Cobb angle. PURPOSE: This study aimed to evaluate the performance of a three-dimensional depth sensor imaging system with a deep learning algorithm, in predicting the Cobb angle in AIS. STUDY DESIGN: Retrospective analysis of prospectively collected, consecutive, nonrandomized series of patients at five scoliosis centers in Japan. PATIENT SAMPLE: One hundred and-sixty human subjects suspected to have AIS were included. OUTCOME MEASURES: Patient demographics, radiographic measurements, and predicted Cobb angle derived from the deep learning algorithm were the outcome measures for this study. METHODS: One hundred and sixty data files were shuffled into five datasets with 32 data files at random (dataset 1, 2, 3, 4, and 5) and five-fold cross validation was performed. The relationships between the actual and predicted Cobb angles were calculated using Pearson's correlation coefficient analyses. The prediction performances of the network models were evaluated using mean absolute error and root mean square error between the actual and predicted Cobb angles. The shuffling into five datasets and five-fold cross validation was conducted ten times. There were no studyspecific biases related to conflicts of interest. RESULTS: The correlation between the actual and the mean predicted Cobb angles was 0.91. The mean absolute error and root mean square error were 4.0˚and 5.4˚, respectively. The accuracy of the mean predicted Cobb angle was 94% for identifying a Cobb angle of ≥10˚and 89% for that of ≥20˚. FDA device/drug status: Not approved (SCOLIOMAP).

Some surgical strategies can maintain or restore thoracic kyphosis (TK); however, next-generation surgical schemes for adolescent idiopathic scoliosis (AIS) should consider anatomical corrections. A four-dimensional correction could be actively achieved by curving the rod. Thus, anatomically designed rods have been developed as notch-free, pre-bent rods for easier anatomical reconstruction. This study aimed to compare the initial curve corrections obtained using notch-free rods and manually bent, notched rods for the anatomical reconstruction of thoracic AIS. Two consecutive series of 60 patients who underwent anatomical posterior correction for main thoracic AIS curves were prospectively followed up. After multilevel facetectomy, except for the lowest instrumented segment, either notch-free or notched rods were used. Patient demographic data, radiographic measurements, and sagittal rod angles were analyzed within 1 week after surgery. Patients with notch-free rods had significantly higher postoperative TK than patients with notched rods (P < .001), but both groups achieved three-dimensional spinal corrections and significantly increased postoperative rates of patients with T6–T8 TK apex (P = .006 for notch-free rods and P = .008 for notched rods). The rod deformation angle at the concave side was significantly lower in the notch-free rods than in the notched rods (P < .001). The notch-free, pre-bent rod can maintain its curvature, leading to better correction or maintenance of TK after anatomical spinal correction surgery than the conventional notched rod. These results suggest the potential benefits of anatomically designed notch-free, pre-bent rods over conventional, manually bent rods.

An optimal surgical strategy for adolescent idiopathic scoliosis (AIS) is to provide maximal deformity correction while preserving spinal mobile segments as much as possible and obtaining a balanced posture. From a spatiotemporal deformity correction standpoint, we recently showed that anatomical four-dimensional (4D) spinal correction could be accomplished by curving the rod. In the surgical procedure, two rods are bent identically to confirm spinal anatomical alignment without referring to the intraoperative alignment of the deformity. Therefore, anatomically designed rods have been developed as notch-free, pre-bent rods for easier anatomical reconstruction. In addition to providing the best spinal instrumentation configurations as pre-bent rods, prediction of surgical outcome along with its biomechanical impact can be obtained by simulation of the surgical procedures with computer modeling. However, an objective model that can simulate the surgical outcome in patients with AIS has not been completely elucidated. The present study aimed to compare simulated deformity corrections based on our newly developed spatiotemporal morphological 4D planning simulation system incorporating pre-bent rods and actual deformity corrections in patients with AIS. A consecutive series of 47 patients who underwent anatomical posterior correction for AIS curves were prospectively evaluated. After multilevel facetectomy, except for the lowest instrumented segment, 11 types of pre-bent rods were used. Patient demographic data, radiographic measurements, and sagittal rod angles were analyzed within 1 week of surgery. Our simulation system incorporating pre-bent rods showed a significant correlation with the actual postoperative spinal alignment. The present study demonstrated the feasibility of our simulation system and the ability to simulate the surgical procedure using the pre-bent rods. The simulation system can be used to minimize the differences between the optimal and possible outcomes related to the instrumentation levels and rod shapes. Preoperative assumption of rod shape and length can contribute to a reduction in operative time which decreases blood loss and risk of infection. The results of the finite element analysis in the simulation system measured for each individual patient would also provide a more realistic representation of the surgical procedures.