3D Reconstruction Of Spine Research Articles

3D external shape analysis and barycentremetry can provide early signs of progression in adolescent idiopathic scoliosis.

Our objective was to analysis the barycentremetry, obtained from the external envelope reconstruction of biplanar radiographs, in adolescent idiopathic scoliosis (AIS) and to determine whether assessing would help predict the distinction between progressive and stable AIS at the early stage. A retrospective study with a multicentre cohort of 205 AIS was conducted. All AIS underwent a biplanar X-ray between 2013 and 2020. Inclusion criteria were Cobb angle between 10° and 25°; Risser sign lower than 3; age higher than 10years; and no previous treatment. A 3D spine reconstruction was performed, and the barycentremetry parameters were computed, i.e., the center of mass position at the apex and the axial torque at the apex, the upper and lower junction. A severity index, helping to distinguish stable and progressive AIS, was computed on the first radiograph, and weighted according to these parameters. A clinical and radiographic monitoring determined if AIS were classified such a stable or progressive scoliosis. One hundred and sixty-two AIS were included (i.e., 87 were classified as stable and 75 as progressive). The apex center of mass position was different between the stable and progressive AIS groups (6mm, SD = 4mm for the whole cohort; 5mm, SD = 4mm for stable AIS versus 7mm, SD = 4mm for progressive AIS; p = 0.02). In AIS thoracic, the specificity and positive predictive value of the severity index increased by 19% and 16%, respectively, by adding the apex vertebral axial torque. Early assessment of the external envelope from biplanar X-ray reconstruction of idiopathic scoliosis showed that the apex centre of mass position was significantly different between progressive and stable scoliosis. The inclusion of the axial torque of the apex vertebra in the severity index is promising to help the clinician distinguish between stable and progressive thoracic AIS at an early stage. II - Prognostic studies.

Validity of a fast automated 3d spine reconstruction measurements for biplanar radiographs: SOSORT 2024 award winner.

To validate a fast 3D biplanar spinal radiograph reconstruction method with automatic extract curvature parameters using artificial intelligence (AI). Three-hundred eighty paired, posteroanterior and lateral, radiographs from the EOS X-ray system of children with adolescent idiopathic scoliosis were randomly selected from the database. For the AI model development, 304 paired images were used for training; 76 pairs were employed for testing. The validation was evaluated by comparing curvature parameters, including Cobb angles (CA), apical axial vertebral rotation (AVR), kyphotic angle (T1-T12 KA), and lordotic angle (L1-L5 LA), to manual measurements from a rater with 8years of scoliosis experience. The mean absolute differences ± standard deviation (MAD ± SD), the percentage of measurements within the clinically acceptable errors, the standard error of measurement (SEM), and the inter-method intraclass correlation coefficient ICC[2,1] were calculated. The average reconstruction speed of the 76 test images was recorded. Among the 76 test images, 134 and 128 CA were exported automatically and measured manually, respectively. The MAD ± SD for CA, AVR at apex, KA, and LA were 3.3° ± 3.5°, 1.5° ± 1.5°, 3.3° ± 2.6° and 3.5° ± 2.5°, respectively, and 98% of these measurements were within the clinical acceptance errors. The SEMs and the ICC[2,1] for the compared parameters were all less than 0.7° and > 0.94, respectively. The average time to display the 3D spine and report the measurements was 5.2 ± 1.3s. The developed AI algorithm could reconstruct a 3D scoliotic spine within 6s, and the automatic curvature parameters were accurately and reliably extracted from the reconstructed images.

Growth modulation response in vertebral body tethering depends primarily on magnitude of concave vertebral body growth

PurposeThere is variability in clinical outcomes with vertebral body tethering (VBT) partly due to a limited understanding of the growth modulation (GM) response. We used the largest sample of patients with 3D spine reconstructions to characterize the vertebra and disc morphologic changes that accompany growth modulation during the first two years following VBT.MethodsA multicenter registry was used to identify idiopathic scoliosis patients who underwent VBT with 2 years of follow-up. Calibrated biplanar X-rays obtained at longitudinal timepoints underwent 3D reconstruction to obtain precision morphological measurements. GM was defined as change in instrumented coronal angulation from post-op to 2-years.ResultsFifty patients (mean age: 12.5 ± 1.3yrs) were analyzed over a mean of 27.7 months. GM was positively correlated with concave vertebra height growth (r = 0.57, p < 0.001), 3D spine length growth (r = 0.36, p = 0.008), and decreased convex disc height (r = − 0.42, p = 0.002). High modulators (patients experiencing GM > 10°) experienced an additional 1.6 mm (229% increase) of mean concave vertebra growth during study period compared to the Poor Modulators (GM < − 10°) group, (2.3 vs. 0.7 mm, p = 0.039), while convex vertebra height growth was similar (1.3 vs. 1.4 mm, p = 0.91).ConclusionWhen successful, VBT enables asymmetric vertebra body growth, leading to continued postoperative coronal angulation correction (GM). A strong GM response is correlated with concave vertebral body height growth and overall instrumented spine growth. A poor GM response is associated with an increase in convex disc height (suspected tether rupture). Future studies will investigate the patient and technique-specific factors that influence increased growth remodeling.

Assessment of malalignment at early stage in adolescent idiopathic scoliosis: a longitudinal cohort study.

Our objective was to assess abnormalities of the odontoid-hip axis (OD-HA) angle in a mild scoliotic population to determine whether screening for malalignment would help predict the distinction between progressive and stable adolescent idiopathic scoliosis (AIS) at early stage. All patients (non-scoliotic and AIS) underwent a biplanar X-ray between 2013 and 2020. In AIS, inclusion criteria were Cobb angle between 10° and 25°; Risser sign lower than 3; age higher than 10years; and no previous treatment. A 3D spine reconstruction was performed, and the OD-HA was computed automatically. A reference corridor for OD-HA values in non-scoliotic subjects was calculated as the range [5th-95th percentiles]. A severity index, helping to distinguish stable and progressive AIS, was calculated and weighted according to the OD-HA value. Eighty-three non-scoliotic and 205 AIS were included. The mean coronal and sagittal OD-HA angles in the non-scoliotic group were 0.2° and -2.5°, whereas in AIS values were 0.3° and -0.8°, respectively. For coronal and sagittal OD-HA, 27.5% and 26.8% of AIS were outside the reference corridor compared with 10.8% in non-scoliotic (OR = 3.1 and 3). Adding to the severity index a weighting factor based on coronal OD-HA, for thoracic scoliosis, improved the positive predictive value by 9% and the specificity by 13%. Analysis of OD-HA suggests that AIS patients are almost three times more likely to have malalignment compared with a non-scoliotic population. Furthermore, analysis of coronal OD-HA is promising to help the clinician distinguish between stable and progressive thoracic scoliosis.

Fully automatic spinal scanning and measurement based on multi-source vision information

Ultrasound is a radiation-free alternative to X-ray in the clinical evaluation of human spine. Currently proposed spinal robot-assisted scanning systems rely on single-source vision information, which may result in scan path deviation or require human intervention. Additionally, Cobb angle measurement is almost conducted based on 3D reconstruction of spine. In this article, a fully automatic scanning system is proposed based on multi-source vision information. By fusing ultrasound and RGBD information of human back, the position and pose of the robot-held probe can be determined in real-time, ensuring that vertebrae appear in the center of ultrasound images, and the tight coupling between the probe and the human skin. We also develop an automated Cobb angle measurement method based on landmark localization. The in-vivo and phantom experiments demonstrate that the proposed system can enable the probe to track the human spine, and offer measurement results within error range of 5°.

BX2S-Net: Learning to reconstruct 3D spinal structures from bi-planar X-ray images

Grasping good understanding of the weight-bearing spatial structure of the spine of a human subject in a standing position is critical for the treatment of spinal disorders. Such disorders are commonly diagnosed via 2D X-ray imaging of the human subject in a standing position. However, 3D reconstruction techniques based on bi-planar X-ray imaging can enable better exploration and analysis of the spinal structure. In particular, compared to earlier deformable modeling approaches, the recently-developed deep-learning-based 3D reconstruction methods exhibit higher efficiency and generalizability. But these methods usually employ simple architectures with 2D encoders and 3D decoders. Thus, these methods have several drawbacks, namely, the existence of a semantic gap between dimensionally-inconsistent feature maps, the difficulty of jointly handling multi-view inputs, and the information source limitations for the decoding process. In order to better assist clinicians and tackle these problems, we propose a novel convolutional neural network framework, which we call BX2S-Net, to effectively achieve 3D spine reconstruction based on bi-planar X-ray images. In particular, a dimensionally-consistent encoder–decoder architecture is designed in conjunction with a dimensionality enhancement method in order to reduce the semantic gap between feature maps and achieve information fusion for multi-view inputs. A feature-guided progressive decoding process is developed on the decoder side, where a full-scale feature attention guidance (FFAG) module is introduced to efficiently aggregate image features and guide the decoding process at each level. In addition, a class augmentation method and a spatially-weighted cross-entropy loss function are used for network training with improved reconstruction quality for the vertebral edge region. The experimental results demonstrate the effectiveness of our model in reconstructing high-quality 3D spinal structures from bi-planar X-ray images. The code is available at https://github.com/NBU-CVMI/bx2s-net.

3D Spine Model Reconstruction Based on RGBD Images of Unclothed Back Surface.

Most 3D spine reconstruction methods require X-ray images as input, which usually leads to high cost and radiation damage. Therefore, these methods are hardly ever applied to large scale scoliosis screening or spine pose monitoring during treatment. We propose a novel, low-cost, easy-to-operate and none-radioactive 3D spine model reconstruction method, which is based on human back surface information without requiring X-ray images as input. Our method fits a pre-built Spine Priors Model (SPrM) to human back surface information and reconstructs the main part of spine with 17 vertebrae: lumbar vertebrae L1-L5 and thoracic vertebrae T1-T12. The Spine Priors Model is constructed according to human spine priors, including Statistical Spine Shape Model (SSSM), Spine Pose Model (SPM) and Spine Biomechanical Simplified Model (SBSM). The spine-related information on back surface, including back surface spinous curve and local symmetry nearby spinous curve is extracted from the RGBD images of human back surface. We formulate the spine optimization constraints from spine-related feature on back surface and spine priors, then optimize the spine model by gradient descent to get the optimal personalized shape parameters and pose parameters of the Spine Priors Model (SPrM). We assess our reconstruction by scoliosis Cobb angle error, and the result is comparable to current X-ray based methods.

Anterior vertebral body tethering for thoracic idiopathic scoliosis leads to asymmetric growth of the periapical vertebrae.

To evaluate 3D growth of the periapical vertebrae and discs in the 2years after anterior vertebral body tether (AVBT) placement in patients with idiopathic scoliosis (IS). Patients with IS treated with AVBT, ≥ 2years of follow-up, and 3D spine reconstructions created from simultaneous, biplanar radiographs were studied. Patients were divided into two groups: progressive scoliosis correction (PC) or no/limited correction (NPC). The average of the 3 apical vertebral and disc heights and angular measures were made. The rate of change for each measure (mm/mo, °/mo) from first erect to 2-year follow-up was compared between groups. Fourteen (Risser 0, Sanders 2-3) patients aged 11.4 ± 1.4years with right thoracic scoliosis of 52 ± 9° were included. There were 7 patients per group (6F, 1M). Mean follow-up was 3.6 ± 1.1 (range 2-5) years. PC left-sided vertebral height increased 0.13mm/months compared to 0.05mm/mo in the NPC group (p = 0.001). Right (tethered side) vertebral growth was not different (PC: 0.07mm/mo, NPC: 0.05mm/mo, p = 0.2).Coronal vertebral wedging occurred at - 0.11°/mo compared to - 0.02°/mo for the PC and NPC groups, respectively (p = 0.004). Coronal disc angulation change was - 0.12°/mo in the PC group and - 0.04°/mo in the NPC group (p = 0.03), and was associated with loss of right disc height (PC: - 0.06mm/mo) with little effect on the left disc height (PC: -0.01mm/mo). AVBT in immature patients with thoracic scoliosis can asymmetrically modulate growth of the periapical vertebrae and discs. Progressive reduction in scoliosis after AVBT was associated with greater concave growth rates in the vertebraeand loss of disc height on the convex side.

Intra-operative forecasting of growth modulation spine surgery outcomes with spatio-temporal dynamic networks.

In adolescent idiopathic scoliosis (AIS), non-invasive surgical techniques such as anterior vertebral body tethering (AVBT) enable to treat patients with mild and severe degrees of deformity while maintaining lower lumbar motion by avoiding spinal fusion. However, multiple features and characteristics affect the overall patient outcome, notably the 3D spine geometry and bone maturity, but also from decisions taken intra-operatively such as the selected tethered vertebral levels, which makes it difficult to anticipate the patient response. We propose here a forecasting method which can be used during AVBT surgery, exploiting the spatio-temporal features extracted from a dynamic networks. The model learns the corrective effect from the spine's different segments while taking under account the time differences in the initial diagnosis and between the serial acquisitions taken before and during surgery. Clinical parameters are integrated through an attention-based decoder, allowing to associate geometrical features to patient status. Long-term relationships allow to ensure regularity in geometrical curve prediction, using a manifold-based smoothness term to regularize geometrical outputs, capturing the temporal variations of spine correction. A dataset of 695 3D spine reconstructions was used to train the network, which was evaluated on a hold-out dataset of 72 scoliosis patients using the baseline 3D reconstruction obtained prior to surgery, yielding an overall reconstruction error of [Formula: see text]mm based on pre-identified landmarks on vertebral bodies. The model was also tested prospectively on a separate cohort of 15 AIS patients, demonstrating the integration within the OR theatre. The proposed predictive network allows to intra-operatively anticipate the geometrical response of the spine to AVBT procedures using the dynamic features.

Image-Guided Tethering Spine Surgery With Outcome Prediction Using Spatio-Temporal Dynamic Networks.

Recent fusionless surgical techniques for corrective spine surgery such as Anterior Vertebral Body Growth Modulation (AVBGM) allow to treat mild to severe spinal deformations by tethering vertebral bodies together, helping to preserve lower back flexibility. Forecasting the outcome of AVBGM from skeletally immature patients remains elusive with several factors involved in corrective vertebral tethering, but could help orthopaedic surgeons plan and tailor AVBGM procedures prior to surgery. We introduce an intra-operative framework forecasting the outcomes during AVBGM surgery in scoliosis patients. The method is based on spatial-temporal corrective networks, which learns the similarity in segmental corrections between patients and integrates a long-term shifting mechanism designed to cope with timing differences in onset to surgery dates, between patients in the training set. The model captures dynamic geometric dependencies in scoliosis patients, ensuring long-term dependency with temporal dynamics in curve evolution and integrated features from inter-vertebral disks extracted from T2-w MRI. The loss function of the network introduces a regularization term based on learned group-average piecewise-geodesic path to ensure the generated corrective transformations are coherent with regards to the observed evolution of spine corrections at follow-up exams. The network was trained on 695 3D spine models and tested on 72 operative patients using a set of 3D spine reconstructions as inputs. The spatio-temporal network predicted outputs with errors of 1.8 ± 0.8mm in 3D anatomical landmarks, yielding geometries similar to ground-truth spine reconstructions obtained at one and two year follow-ups and with significant improvements to comparative deep learning and biomechanical models.

Predictors of spontaneous lumbar curve correction in thoracic-only fusions: 3D analysis in AIS.

To evaluate how 3D parameters of the instrumented thoracic spine relate to the uninstrumented lumbar spine following thoracic-only fusion (TOF) for adolescent idiopathic scoliosis (AIS) and determine the factors predictive of lumbar correction. A multi-center retrospective review was conducted of AIS patients with Lenke 1-4 B or C curves undergoing fusion of their thoracic spine only with minimum 2-year follow-up and 3D spine reconstructions from biplanar radiography. Pre-operative to 2-year post-operative differences were evaluated. Pearson's correlations were used to identify 3D coronal, sagittal and axial relationships at 2years post-operative. Multivariate linear regression was used to identify variables most predictive of lumbar curve correction. Eighty-four AIS patients met inclusion (54 B modifiers, 30 C modifiers). Average pre-operative thoracic and lumbar curves were 54 ± 9° and 41 ± 7° and corrected to 19 ± 7° and 21 ± 7°, respectively. 3D T5-T12 thoracic kyphosis increased from 6 ± 13° to 26 ± 8°. Thoracic and lumbar apical rotation decreased from - 14 ± 6° to -5 ± 6° and 13 ± 5° to 11 ± 6°, respectively. Thoracic curve correction correlated with lumbar curve correction (r = 0.67, p = 0.001) and decreased LIV tilt correlated with smaller residual lumbar curve magnitude (r = 0.63, p < 0.001). Increasing 3D kyphosis of the instrumented segment correlated with increased percentage lumbar curve correction (r = 0.29, p = 0.009). Multivariate linear regression showed LIV tilt and thoracic curve magnitude as the most predictive variables of post-operative residual lumbar curve magnitude, and percent correction of the thoracic curve and change in 3D instrumented kyphosis as most predictive of percent correction of the lumbar curve. Analysis of 3D data highlights several considerations for AIS patients undergoing TOF. Maximizing thoracic curve correction, leveling the LIV, and to a lesser extent, restoring kyphosis in the instrumented segment are the factors most likely to result in greater correction of the instrumented lumbar curve following thoracic-only fusions in Lenke 1-4 B and C curves.

Towards a new 3D classification for adolescent idiopathic scoliosis.

Retrospective analysis of consecutive cases. To identify clinically relevant three-dimensional (3D) sub-groups for adolescent idiopathic scoliosis (AIS). Classifications for AIS are developed to assist surgeons in surgical planning and therapeutic management. However, current systems are based on two-dimensional (2D) parameters that do not completely describe the 3D deformity. Hence, variations in surgical results based on pre-operative 2D classifications may be attributed to the lack of 3D description. Subjects from a multicenter database of AIS patients were included in this study. All patients had bi-planar radiographs and 3D reconstruction of the entire spine. A clustering algorithm based on fuzzy c-means was utilized to identify sub-groups based on the following ten parameters measured on 3D reconstructions of the spine: Cobb angle, orientation of the plane of maximum curvature of the proximal thoracic, mid-thoracic (MT) and thoracolumbar (TLL) levels, axial rotation of the apical vertebra of the MT and TLL segments, T4-T12 thoracic kyphosis, and L1-S1 lumbar lordosis. Da Vinci views were also generated and analyzed for each patient in the study. A panel of four experienced spine surgeons from the SRS 3D Scoliosis Committee reviewed and evaluated each group to determine if cluster groups were clinically distinct from each other. The clustering algorithm was able to detect 11 sub-groups. The population size for each cluster varied from 11 to 290. Statistically significant differences were seen between the parameters for each group. Four spine surgeons reviewed the three most representative cases of each group and unanimously agreed that each cluster group represents a sub-group that was not defined in current classifications. This study presents a new method of classifying AIS based on a fuzzy clustering algorithm using parameters describing the 3D characteristics of the deformity. Further clinical validation is needed to confirm the usefulness of this classification system. IV.

Prediction outcomes for anterior vertebral body growth modulation surgery from discriminant spatiotemporal manifolds.

Anterior vertebral body growth modulation (AVBGM) is a minimally invasive surgical technique that gradually corrects spine deformities while preserving lumbar motion. However, identifying suitable patients for surgery is based on clinical judgment and surgical experience. This process would be facilitated by the identification of patients responding to AVBGM prior to surgery using data-driven models trained on previous instrumented cases. We introduce a statistical framework for predicting the surgical outcomes following AVBGM in adolescents with idiopathic scoliosis. A discriminant manifold is first constructed to maximize the separation between responsive and non-responsive groups of patients treated with AVBGM for scoliosis. The model then uses subject-specific correction trajectories based on articulated transformations in order to map spine correction profiles to a group-average piecewise-geodesic path. Spine correction trajectories are described in a piecewise-geodesic fashion to account for varying times at follow-up examinations, regressing the curve via a quadratic optimization process. To predict the evolution of correction, a baseline reconstruction is projected onto the manifold, from which a spatiotemporal regression model is built from parallel transport curves inferred from neighboring exemplars. The model was trained on 438 reconstructions and tested on 56 subjects using 3D spine reconstructions from follow-up examinations, with the probabilistic framework yielding accurate results with differences of [Formula: see text] in main curve angulation and a classification rate of 83.2%, and generating models similar to biomechanical simulations. The proposed method achieved a higher prediction accuracy and improved the modeling of spatiotemporal morphological changes in surgical patients treated with AVBGM.

Toward Automated 3D Spine Reconstruction from Biplanar Radiographs Using CNN for Statistical Spine Model Fitting.

To date, 3D spine reconstruction from biplanar radiographs involves intensive user supervision and semi-automated methods that are time-consuming and not effective in clinical routine. This paper proposes a new, fast, and automated 3D spine reconstruction method through which a realistic statistical shape model of the spine is fitted to images using convolutional neural networks (CNN). The CNNs automatically detect the anatomical landmarks controlling the spine model deformation through a hierarchical and gradual iterative process. The performance assessment used a set of 68 biplanar radiographs, composed of both asymptomatic subjects and adolescent idiopathic scoliosis patients, in order to compare automated reconstructions with ground truths build using multiple experts-supervised reconstructions. The mean (SD) errors of landmark locations (3D Euclidean distances) were 1.6 (1.3) mm, 1.8 (1.3) mm, and 2.3 (1.4) mm for the vertebral body center, endplate centers, and pedicle centers, respectively. The clinical parameters extracted from the automated 3D reconstruction (reconstruction time is less than one minute) presented an absolute mean error between 2.8° and 4.7° for the main spinal parameters and between 1° and 2.1° for pelvic parameters. Automated and expert's agreement analysis reported that, on average, 89% of automated measurements were inside the expert's confidence intervals. The proposed automated 3D spine reconstruction method provides an important step that should help the dissemination and adoption of 3D measurements in clinical routine.

Is rasterstereography a valid noninvasive method for the screening of juvenile and adolescent idiopathic scoliosis?

Aim of the study was to verify the accuracy of rasterstereography (RST), as radiation-free alternative to plain radiography (RAD) in the monitoring of spine deformity and scoliosis progression in juvenile and adolescent subjects with idiopathic scoliosis. 192 subjects underwent RST (by Formetric 4D device) and low-dose RAD (EOS Imaging, France) in the same session. A sub-group of 30 subjects, selected for conservative treatment with corrective bracing, was assessed at 6-months follow-up. The Cobb angles (CA) obtained by the 3D spine reconstruction from RAD were compared with those provided by RST. Thoracic kyphosis (TK) and lumbar lordosis (LL) were compared as well. RST provided lower CA compared to RAD (15° vs. 33°, mean values). The average difference in measuring CA was 18°, and the correlation coefficient was 0.55. Comparable TK was observed, whereas LL resulted underestimated by RST compared to RAD (34° vs. 43°, average values). The within-subjects correlation, measuring the accuracy of RST in monitoring the scoliosis progression, was 0.3. Accuracy of RST in identifying increased or decreased CA was 67%. Sensitivity and specificity were 64% and 69%. RST demonstrated moderate accuracy in measuring the scoliosis degree and low accuracy in monitoring the curve progression. Accordingly, it cannot be considered as a valid alternative to radiographic evaluation. However, since demonstrated capable of revealing the presence of spine deformity, it could be in principle considered for the early screening in large adolescent populations, but after accounting for a cost-benefit analysis with respect to other traditional approaches. These slides can be retrieved under Electronic Supplementary Material.

A reduced micro-dose protocol for 3D reconstruction of the spine in children with scoliosis: results of a phantom-based and clinically validated study using stereo-radiography.

The aim of this study was to validate the reproducibility of 3D reconstructions of the spine using a new reduced micro-dose protocol. First, semi-quantitative image analysis was performed using an anthropomorphic child phantom undergoing low-dose biplanar radiography. This analysis was used to establish a "lowest dose" allowing for acceptable visibility of spinal landmarks. Subsequently, a group of 18 scoliotic children, 12years of age or younger, underwent full-spine biplanar radiography with both micro-dose and the newly defined reduced micro-dose. An intra- and inter-observer reliability study of 3D reconstructions of the spine was performed according to the International Organization for Standardization (ISO)-5725 standard, with three operators. The reduced micro-dose setting corresponded to a theoretical reduction of radiation dose exposure of approximately 58%. In vivo results showed acceptable intra- and inter-observer reliability (for instance, 3.8° uncertainty on Cobb angle), comparable to previous studies on 3D spine reconstruction reliability and reproducibility based on stereo-radiography. A new reduced micro-dose protocol offered reliable 3D reconstructions of the spine in patients with mild scoliosis. However, the quality of 3D reconstructions from both reduced micro-dose and micro-dose was inferior to standard-dose protocol on most parameters. Standard-dose protocol remains the option of choice for most accurate assessment and 3D reconstruction of the spine. Still, this new protocol offers a preliminary screening option and a follow-up tool for children with mild scoliosis yielding extremely low radiation and could replace micro-dose protocol for these patients. • We investigated the reliability of 3D reconstructions of the spine based on a new stereo-radiography protocol reducing radiation dose by 58% compared with established micro-dose imaging protocol. • The new reduced micro-dose protocol offers a reproducible preliminary screening option and a follow-up tool in the necessarily frequent repeat imaging of children with mild scoliosis yielding extremely low radiation and could replace existing micro-dose protocol for these patients. • EOS standard-dose protocol remains the option of choice for exact radiographic assessment of scoliosis, offering more exact 3D reproducibility of the spine compared to both micro-dose and the new reduced micro-dose protocols.

Robustness of Whole Spine Reconstruction using Anterior-Posterior and Lateral Planar X-ray Images

The X-ray-based reconstruction methods using anterior-posterior (AP) and lateral (LAT) images assumes that the angle between the AP and LAT images is perpendicular. However, it is difficult to maintain the perfect perpendicular angle between the AP and LAT images when taking those two images sequentially in real situations. In this study, the robustness of a three-dimensional (3D) whole spine reconstruction method using AP and LAT planar X-ray images was analyzed by investigating cases in which the AP and LAT images were not taken perpendicularly. 3D models of the patient-specific spine from five subjects were reconstructed using AP and LAT X-Ray images and the 3D template models of C1 to L5 vertebrae based on B-spline free-form deformation (FFD) technology. The shape error, projected area error, and relative error in length were quantified by comparing the reconstructed model (FFD model) to the reference model (CT model). The results indicated that the reconstruction method might be considered robust in case that there is a small angular error, such as 5°, between the AP and LAT images. This study suggested that simple technical indications to obtain the perpendicular AP and LAT images in real situations can improve accuracy of 3D spine reconstruction.

Performance comparison of feature-based and CSCPG models for 3D spine reconstruction

3D deformity of the spine-like scoliosis is commonly assessed using stereo-radiographic technique. The Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) modelling fail in this case, as they are obtained with the patient in sleeping position. Also, they are associated with heavy cost and radiation hazards. We have developed two models namely, feature-based model and a Combined Stereo-Corresponding Point And Geometric (CSCPG) model for 3D spine reconstruction using biplanar x-rays. The spinal disorder is quantified using two parameters, namely axial vertebral rotation and spinal curvature using both these methods. Their performance is compared by considering Non-Stereo-Corresponding Point (NSCP) model as the gold standard method. The feature-based model is less accurate compared to the CSCPG model. The performance of the feature-based model is also poor in the case of deformity quantification. A statistical significance test is conducted in order to verify its suitability in diagnosis of the spinal disorders. The accuracy of feature-based model can be improved by incorporating additional landmark features from the biplanar radiographs. The proposed CSCPG model has accuracy closer to the gold standard technique and can be used a diagnostic tool for the spinal disorders.

3D quantitative evaluation of spine proprioceptive perception/motor control through instinctive self-correction maneuver in healthy young subjects' posture: an observational study.

Conservative treatment in spine deformities and spine related disorders is mainly based on proper individual proprioceptive and motor control training. For these reasons, conservative treatment involves the stimulation of individual capability of perceiving/reducing deformities, blocks and/or improper spine posture by voluntary control. The literature describes that habitually adopted relaxed postures often exacerbate low back pain. Typically, youths can be referred to therapeutic programs aimed at improving the quality of body posture along with fostering the awareness of the importance of correct posture. Few studies in literature outline the subject's individual instinctive ability to perceive properly and control his/her posture and produce an improvement through a self-correction maneuver. How do healthy young adult subjects perceive and control their posture and spine shape? Are they able to modify them in a correct way through an instinctive self-correction maneuver? Cross-sectional observational study. A cohort of asymptomatic young adult university students and workers were recruited at Clinic of Rehabilitation, University of Medical Sciences, Poznan, Poland. One hundred and twenty-one healthy subjects (57 females, 64 males), aged 19-34 years (mean age: 23.5±3.2 years). Subject's full body posture including 3D spine shape reconstruction, identified using 27 retro-reflective markers suitably located on anatomical landmarks has been measured by using a non-ionizing 3D optoelectronic stereo-photogrammetric approach and a 3D full skeleton biomechanical model. From the 3D full skeleton and spine reconstruction, eleven quantitative biomechanical parameters describing the nature of body posture have been computed to compare natural erect versus self-corrected standing attitudes. A great number of healthy participants (105, 87%) was unable to modify its spinal shape in the frontal plane. Conversely, the sagittal plane presented significant clinical changes in the thoracic spine, as males reached a greater thoracic spine extension (36.4±8.3) than females (40.8±8.7). When changes occurred, subjects were not able to focus and control their posture globally, but only on few aspects at a time. Instinctive posture proprioception and motor control do not produce an effective self-correction maneuver yielding a global improvement of body posture and spine shape. Self-correction maneuver producing an improvement of body posture and spine shape has to be learned with specific postural training. The 3D stereo-photogrammetric approach is effective in quantitatively describe subject's posture, motor control and proprioceptive capability.

Semiautomated 3D Spine Reconstruction from Biplanar Radiographic Images: Prediction of Intervertebral Loading in Scoliotic Subjects.

The present study proposes a semiautomatic software approach to reconstruct 3D subject-specific musculoskeletal model of thoracolumbar spine from radiographic digitized images acquired with EOS system. The approach is applied to evaluate the intervertebral loads in 38 standing adolescents with mild idiopathic scoliosis. For each vertebra, a set of landmarks was manually identified on radiographic images. The landmark coordinates were processed to calculate the following vertebral geometrical properties in the 3D space (i) location (ii) dimensions; and (iii) rotations. Spherical joints simulated disks, ligaments, and facet joints. Body weight distribution, muscles forces, and insertion points were placed according to physiological–anatomical values. Inverse static analysis, calculating joints’ reactions in maintaining assigned spine configuration, was performed with AnyBody software. Reaction forces were computed to quantify intervertebral loads, and correlation with the patient anatomical parameters was then checked. Preliminary validation was performed comparing the model outcomes with that obtained from other authors in previous modeling works and from in vivo measurements. The comparison with previous modeling works and in vivo studies partially fulfilled the preliminary validation purpose. However, minor incongruities were pointed out that need further investigations. The subjects’ intervertebral loads were found significantly correlated with the anatomical parameters in the sagittal and axial planes. Despite preliminary encouraging results that support model suitability, future investigations to consolidate the proposed approach are necessary. Nonetheless, the present method appears to be a promising tool that once fully validated could allow the subject-specific non-invasive evaluation of a deformed spine, providing supplementary information to the routine clinical examination and surgical intervention planning.