Evaluation of a method to quantify posture and scapula position using biplanar radiography.

BACKGROUND: Recent studies have stated the relevance of having new parameters to quantify the position and orientation of the scapula with patients standing upright. Although biplanar radiography can provide 3D reconstructions of the scapula and the spine, it is not yet possible to acquire these images with patients in the same position. METHODS: Two pairs of images were acquired, one for the 3D reconstruction of the spine and ribcage and one for the 3D reconstruction of the scapula. Following 3D reconstructions, scapular alignment was performed in two stages, a coarse alignment based on manual annotations of landmarks on the clavicle and pelvis, and an adjusted alignment. Clinical parameters were computed: protraction, internal rotation, tilt and upward rotation. Reproducibility was assessed on an in vivo dataset of upright biplanar radiographs. Accuracy was assessed using supine cadaveric CT-scans and digitally reconstructed radiographs. FINDINGS: The mean error was less than 2° for all clinical parameters, and the 95 % confidence interval for reproducibility ranged from 2.5° to 5.3°. INTERPRETATION: The confidence intervals were lower than the variability measured between participants for the clinical parameters assessed, which indicates that this method has the potential to detect different patterns in pathological populations.

3D reconstruction of the scapula from biplanar X-rays for pose estimation and morphological analysis.

BACKGROUND: Patient-specific scapular shape in functional posture can be highly relevant to clinical research. Biplanar radiography is a relevant modality for that purpose with already two existing assessment methods. However, they are either time-consuming or lack accuracy. The aim of this study was to propose a new, more user-friendly and accurate method to determine scapular shape. METHODS: The proposed method relied on simplified manual inputs and an upgraded version of the first 3D estimate based on statistical inferences and Moving-Least Square (MLS) deformation of a template. Then, manual adjustments, with real-time MLS algorithm and contour matching adjustments with an adapted minimal path method, were added to improve the match between the projected 3D model and the radiographic contours. The accuracy and reproducibility of the method were assessed (with 6 and 12 subjects, respectively). FINDINGS: The shape accuracy was in average under 2 mm (1.3 mm in the glenoid region). The reproducibility study on the clinical parameters found intra-observer 95% confidence intervals under 3 mm or 3° for all parameters, except for glenoid inclination and Critical Shoulder Angle, ranging between 3° and 6°. INTERPRETATION: This method is a first step towards an accurate reconstruction of the scapula to assess clinical parameters in a functional posture. This can already be used in clinical research on non-pathologic bones to investigate the scapulothoracic joint in functional position.

Automatic 3-Dimensional Cephalometric Landmarking via Deep Learning.

The increasing use of 3-dimensional (3D) imaging by orthodontists and maxillofacial surgeons to assess complex dentofacial deformities and plan orthognathic surgeries implies a critical need for 3D cephalometric analysis. Although promising methods were suggested to localize 3D landmarks automatically, concerns about robustness and generalizability restrain their clinical use. Consequently, highly trained operators remain needed to perform manual landmarking. In this retrospective diagnostic study, we aimed to train and evaluate a deep learning (DL) pipeline based on SpatialConfiguration-Net for automatic localization of 3D cephalometric landmarks on computed tomography (CT) scans. A retrospective sample of consecutive presurgical CT scans was randomly distributed between a training/validation set (n = 160) and a test set (n = 38). The reference data consisted of 33 landmarks, manually localized once by 1 operator(n = 178) or twice by 3 operators (n = 20, test set only). After inference on the test set, 1 CT scan showed "very low" confidence level predictions; we excluded it from the overall analysis but still assessed and discussed the corresponding results. The model performance was evaluated by comparing the predictions with the reference data; the outcome set included localization accuracy, cephalometric measurements, and comparison to manual landmarking reproducibility. On the hold-out test set, the mean localization error was 1.0 ± 1.3 mm, while success detection rates for 2.0, 2.5, and 3.0 mm were 90.4%, 93.6%, and 95.4%, respectively. Mean errors were -0.3 ± 1.3° and -0.1 ± 0.7 mm for angular and linear measurements, respectively. When compared to manual reproducibility, the measurements were within the Bland-Altman 95% limits of agreement for 91.9% and 71.8% of skeletal and dentoalveolar variables, respectively. To conclude, while our DL method still requires improvement, it provided highly accurate 3D landmark localization on a challenging test set, with a reliability for skeletal evaluation on par with what clinicians obtain.

3D quasi-automatic spine length assessment using low dose biplanar radiography after surgical correction in thoracic idiopathic scoliosis.

OBJECTIVE: Surgical correction of thoracic scoliosis leads to a height improvement. Our objectives were to assess how the linear and developed spinal column lengths relate to the frontal and sagittal parameters after a surgical correction of thoracic idiopathic scoliosis, and whether the measurement of these lengths is reliable using quasi-automatic 3D reconstruction methods with biplanar X-rays. METHODS: Consecutive children with thoracic idiopathic scoliosis who underwent spinal fusion surgery and biplanar pre and postoperative X-rays in free-standing position were included prospectively. Quasi-automatic computed 3D reconstructions of the spine were done using a previously validated technique and allowed the automatic computation of geometrical spinopelvic parameters including OD-pelvis, linear, and developed T1-T12 and T1-L5 lengths. RESULTS: Thirty patients with scoliosis were included, and 240 reconstructions were performed (2 operators x2 repetitions x30 patients pre and postoperative). The main thoracic Cobb angle, T1-T12, T1-L5 linear and developed distance, OD-pelvis were significantly improved (p < 0.001). The gain of the main thoracic Cobb angle (31.6°;SD = 9°) was correlated to the gain of the linear distance T1-T12 (15.3 mm;SD=7.3 mm)(rho = 0.76;p < 0.0001) and T1-L5 (24.7 mm;SD = 8 mm)(rho = 0.64;p < 0.0001). The postoperative change of developed length between T1-L5 represented 41% of the gain in linear distance between the same vertebrae. Similarly, the gain of T1-T12 developed length was 50% of linear T1-T12 height gain. Both differences were significant (p = 0.01). Absolute bias using Bland & Altman plots was lower than 1 mm for linear distance (0.1%) and lower than 2 mm (0.3%) for developed distance. CONCLUSION: The gain in spinal length is correlated to the thoracic Cobb angle correction in the surgical treatment of idiopathic thoracic scoliosis. The new significant finding is that the developed spinal height gain represented approximately a little less than 50% of the linear spinal height gain and these parameters were reliable from a 3D quasi-automatic reconstruction of biplanar X-ray.

Effect of postural alignment alteration with age on vertebral strength.

EOS biplane radiographs of 117 subjects between 20 and 83 years were analyzed to compute the upper body lever arm over the L1 vertebra and its impact on vertebral strength. Postural sagittal alignment alteration was observed with age and resulted in a greater lever arm causing vertebral strength to decrease. PURPOSE: The purpose of this study was to analyze the impact of postural alignment changes with age on vertebral strength using finite element analysis and barycentremetry. METHODS: A total of 117 subjects from 20 to 83 years were divided in three age groups: young (20 to 40 years, 62 subjects), intermediate (40 to 60 years, 26 subjects), and elderly (60 years and over, 29 subjects). EOS biplane radiographs were acquired, allowing 3D reconstruction of the spine and body envelope as well as spinal, pelvic, and sagittal alignment parameter measurements. A barycentremetry method allowed the estimation of the mass and center of mass (CoM) position of the upper body above L1, relatively to the center of the L1 vertebra (lever arm). To investigate the effect of this lever arm, vertebral strength of a generic finite element model (with constant geometry and mechanical properties for all subjects) was successively computed applying the personalized lever arm of each subject. RESULTS: A combination of an increase in thoracic kyphosis, cervical lordosis, and pelvic tilt with a loss of lumbar lordosis was observed between the young and the older groups. Sagittal alignment parameters indicated a more forward position as age increased. The lever arm of the CoM above L1 varied from an average of 1 mm backward for the young group, to averages of 10 and 24 mm forward, respectively, for the intermediate and elderly group. As a result, vertebral strength decreased from 2527 N for the young group to 1820 N for the elderly group. CONCLUSION: The global sagittal alignment modifications observed with age were consistent with the literature. Posture alteration with age reduced vertebral strength significantly in this simplified loading model. Postural alignment seems essential to be considered in the evaluation of osteoporotic patients.

Analysis of apex and transitional vertebra of the spine according to pelvic incidence using orientation and position parameters.

OBJECTIVE: To identify the different apex and transitional vertebra according to the shape of the pelvis of individuals despite their difference in sagittal alignment using our measurement system. METHODS: Full-spine X-rays using EOS in standard stand-position of 99 volunteers were selected (47 women, 52 men, mean age 31 years old). Validated 3D reconstruction technique allows extraction of spinopelvic parameters, and position and rotation of each vertebra and lumbar disks. Subjects were divided into three groups: low PI (lowPI, n = 37), moderate PI (midPI, n = 52), high PI (highPI, n = 10), with, respectively, a PI below 45°, between 45° and 60° and above 60°. Occurrence of specific position and rotation values of apex and transitional vertebra were assessed in each group. RESULTS: Frequency curves tend to move cranially when the incidence increases except in cervicothoracic where T1 is a constant for all shapes of spine with occurrence approaching 90%. Angulation value of relevant vertebra and lumbar lordosis are significantly positively correlated for the whole population. CONCLUSIONS: Our study allowed the assessment of the distribution of spine curvatures according to the pelvic incidence. It describes the occurrence of localization of the apex and transitional vertebrae according to pelvic incidence. These results should be taken into account during the analysis of the sagittal balance, especially when planning deformity surgery in adults.

Accuracy and reliability of automatic three-dimensional cephalometric landmarking.

The aim of this systematic review was to assess the accuracy and reliability of automatic landmarking for cephalometric analysis of three-dimensional craniofacial images. We searched for studies that reported results of automatic landmarking and/or measurements of human head computed tomography or cone beam computed tomography scans in MEDLINE, Embase and Web of Science until March 2019. Two authors independently screened articles for eligibility. Risk of bias and applicability concerns for each included study were assessed using the QUADAS-2 tool. Eleven studies with test dataset sample sizes ranging from 18 to 77 images were included. They used knowledge-, atlas- or learning-based algorithms to landmark two to 33 points of cephalometric interest. Ten studies measured mean localization errors between manually and automatically detected landmarks. Depending on the studies and the landmarks, mean errors ranged from <0.50mm to>5mm. The two best-performing algorithms used a deep learning method and reported mean errors <2mm for every landmark, approximating results of operator variability in manual landmarking. Risk of bias regarding patient selection and implementation of the reference standard were found, therefore the studies might have yielded overoptimistic results. The robustness of these algorithms needs to be more thoroughly tested in challenging clinical settings. PROSPERO registration number: CRD42019119637.