Study Design: Retrospective cohort study. Objective: The objective was to prove the association between anatomic pelvis parameters and specific types of lumbar spinal degeneration. Summary of Background Data: Different spinopelvic sagittal profile types are suggested to be associated with specific degenerative lumbar spine pathologies. Because pelvic morphology plays a key role defining the spinal shape as well as its load and function it thereby potentially predisposes the development of spinal degeneration. Materials and Methods: Patients with symptomatic lumbar spinal degeneration who were surgically treated in 2 spine departments from March 2011 until August 2016 were included in this retrospective analysis. Single-level degenerative pathologies were classified as lumbar disc herniation (LDH), degenerative disc disease (DDD), lumbar spinal stenosis (LSS), and degenerative spondylolisthesis (DSPL). The constant anatomic pelvic parameters pelvic incidence (PI), pelvic radius (PR), and sacral table angle (STA) were assessed in lateral radiographs of the lumbar spine and compared between the pathologies. Results: In total, 249 patients were assigned to the LDH (n=73), DDD (n=67), LSS (n=42), and DSPL (n=67) groups. Group comparisons revealed significant differences in the anatomic pelvic parameters PR (LDH, 139.5±10.8 mm; DDD, 135.9±14.0 mm; LSS, 127.8±14.3 mm; DSPL, 135.8±12.7 mm; P<0.001), PI (LDH, 53.1±10.0 degrees; DDD, 50.0±9.9 degrees; LSS, 54.5±9.6 degrees; DSPL, 57.1±10.8 degrees; P=0.001), and STA (LDH, 95.3±12.7 degrees; DDD, 105.4±9.0 degrees; LSS, 105.9±11.5 degrees; DSPL, 98.6±9.5 degrees; P<0.001). Post hoc tests indicated significant differences between the PR of the LSS group and that of all other subgroups (P<0.012), the PI of the DDD group and that of DSPL (P<0.001), and the STA of the LDH/DSPL groups and that of the LSS/DDD group (P<0.005). Conclusions: We found all the constant anatomic parameters to be specific for distinct types of degeneration, suggesting pelvis shape is a predisposing factor for their development. Level of Evidence: Level III.

Study Design: Retrospective, mono-centric cohort research study. Objectives: The analysis of cervical sagittal balance parameters is essential for preoperative planning and dependent on the physician’s experience. A fully automated artificial intelligence-based algorithm could contribute to an objective analysis and save time. Therefore, this algorithm should be validated in this study. Methods: Two surgeons measured C2-C7 lordosis, C1-C7 Sagittal Vertical Axis (SVA), C2-C7-SVA, C7-slope and T1-slope in pre- and postoperative lateral cervical X-rays of 129 patients undergoing anterior cervical surgery. All parameters were measured twice by surgeons and compared to the measurements by the AI algorithm consisting of 4 deep convolutional neural networks. Agreement between raters was quantified, among other metrics, by mean errors and single measure intraclass correlation coefficients for absolute agreement. Results: ICC-values for intra- (range: .92-1.0) and inter-rater (.91-1.0) reliability reflect excellent agreement between human raters. The AI-algorithm could determine all parameters with excellent ICC-values (preop:0.80-1.0; postop:0.86-.99). For a comparison between the AI algorithm and 1 surgeon, mean errors were smallest for C1-C7 SVA (preop: −.3 mm (95% CI:-.6 to −.1 mm), post: .3 mm (.0-.7 mm)) and largest for C2-C7 lordosis (preop:-2.2° (−2.9 to −1.6°), postop: 2.3°(-3.0 to −1.7°)). The automatic measurement was possible in 99% and 98% of pre- and postoperative images for all parameters except T1 slope, which had a detection rate of 48% and 51% in pre- and postoperative images. Conclusion: This study validates that an AI-algorithm can reliably measure cervical sagittal balance parameters automatically in patients suffering from degenerative spinal diseases. It may simplify manual measurements and autonomously analyze large-scale datasets. Further studies are required to validate the algorithm on a larger and more diverse patient cohort.

Aims: The aim of the present study was to answer the question whether curve morphology and location have an influence on rigid conservative treatment in patients with adolescent idiopathic scoliosis (AIS). Methods: We retrospectively analyzed AIS in 127 patients with single and double curves who had been treated with a Chêneau brace and physiotherapeutic specific exercises (B-PSE). The inclusion criteria were the presence of structural major curves ≥ 20° and < 50° (Risser stage 0 to 2) at the time when B-PSE was initiated. The patients were divided into two groups according to the outcome of treatment: failure (curve progression to ≥ 45° or surgery) and success (curve progression < 45° and no surgery). The main curve type (MCT), curve magnitude, and length (overall, above and below the apex), apical rotation, initial curve correction, flexibility, and derotation by the brace were compared between the two groups. Results: In univariate analysis treatment failure depended significantly on: 1) MCT (p = 0.008); 2) the apical rotation of the major curve before (p = 0.007) and during brace treatment (p < 0.001); 3) the initial and in-brace Cobb angles of the major (p = 0.001 and p < 0.001, respectively) and minor curves (p = 0.015 and p = 0.002); 4) major curve flexibility (p = 0.005) and the in-brace curve correction rates (major p = 0.008, minor p = 0.034); and 5) the length of the major curve (LoC) above (p < 0.001) and below (p = 0.002) the apex. Furthermore, MCT (p = 0.043, p = 0.129, and p = 0.017 in MCT comparisons), LoC (upper length p = 0.003, lower length p = 0.005), and in-brace Cobb angles (major p = 0.002, minor p = 0.027) were significant in binary logistic regression analysis. Conclusion: Curve size, location, and morphology were found to influence the outcome of rigid conservative treatment of AIS. These findings may improve future brace design and patient selection for conservative treatment. Cite this article: Bone Joint J 2021;103-B(2):373–381.

A retrospective controlled cohort study was performed for postoperative 3-dimensional muscle evaluation. Our aim was to establish a method for spatially continuous 3-dimensional analysis of the lumbar paravertebral muscles after instrumented circumferential single-level fusion. Paravertebral muscle degeneration is thought to contribute to postoperative low back pain. Previous analysis methods did not regard on implant associated artifacts and on the multisegmental 3-dimensional character of the paravertebral muscles. At 1 week and 12 months postoperatively, thin slice computed tomography scans of the lumbar paravertebral muscles were digitally analyzed and compared for 20 patients with chronic low back pain owing to monosegmental degenerative disc disease ≥ Modic II° and high intensity zones at L4/5. Tissue-specific regions of all slices were determined for automated calculation of fat and muscle volume, and localization of fatty degenerated areas in a 3-dimensional computer reconstruction model. All computed tomography scans were successfully digitally reconstructed and evaluated. A significant decrease of paravertebral muscle volume and an increase in volume fraction of fatty degeneration was observed at 12 months (Vmuscle 127.4±28.5 cm3, V%fat 48.67±3.63%) compared with 1 week postoperatively (Vmuscle 217.4±34.2 cm3, V%fat 12.57±2.28%). Fat tissue areas were most often located close to the spinal processes and anterolateral, close to the transverse processes. We established a 3-dimensional image analysis method for evaluating postoperative changes in the lumbar paravertebral muscles of patients, after circumferential single-level fusion, consistently accounting for implant-associated artifacts. We were able to demonstrate volume atrophy and an increase of fatty degeneration after 12 months compared with 1 week postoperatively.