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Hybrid constructs with sublaminar bands have recently regained popularity as an alternative to all-screw construct for correction of adolescent idiopathic scoliosis (AIS). The aim of this study is to evaluate the ability of hybrid constructs with sublaminar bands to achieve a tridimensional correction of the scoliotic deformity. Our hypothesis is that hybrid construct with sublaminar bands are able to achieve a substantial derotation of the apical vertebrae, while preserving the thoracic kyphosis.A prospective evaluation of 50 consecutive cases (41 F, 9 M, mean age 14.7 ± 2 years) of AIS correction with hybrid construct was performed. In all cases, sublaminar bands were used at the apex of the main curve on concave side. All patients underwent pre and postoperative X-rays with EOS System, with full 3D reconstruction. Spinopelvic parameters and axial rotation of the vertebrae were measured pre and postoperatively.2.7 ± 0.9 mean sublaminar bands were used per patient. Mean correction of deformity was 50 ± 9.5%. on the coronal plane. The mean axial rotation of the apical vertebra went from 18° ± 11.5° preoperatively to 9.4° ± 7.2° postoperatively (p 0.001) with a mean derotation of 47.7%. Thoracic kyphosis went from 32.1° ± 18° preoperatively to 37.3° ± 13.1° postoperatively (p 0.05). No intraoperative complications due to sublaminar bands were recorded.Hybrid construct with sublaminar band have been showed to be safe and effective in deformity correction and in maintaining or restoring thoracic kyphosis. This study showed that with sublaminar bands applied at the curve apex a substantial derotation of the apical vertebrae can be achieved.

In this work we propose to use Deep Learning to automatically calculate the coordinates of the vertebral corners in sagittal x-rays images of the thoracolumbar spine and, from those landmarks, to calculate relevant radiological parameters such as L1–L5 and L1–S1 lordosis and sacral slope. For this purpose, we used 10,193 images annotated with the landmarks coordinates as the ground truth. We realized a model that consists of 2 steps. In step 1, we trained 2 Convolutional Neural Networks to identify each vertebra in the image and calculate the landmarks coordinates respectively. In step 2, we refined the localization using cropped images of a single vertebra as input to another convolutional neural network and we used geometrical transformations to map the corners to the original image. For the localization tasks, we used a differentiable spatial to numerical transform (DSNT) as the top layer. We evaluated the model both qualitatively and quantitatively on a set of 195 test images. The median localization errors relative to the vertebrae dimensions were 1.98% and 1.68% for x and y coordinates respectively. All the predicted angles were highly correlated with the ground truth, despite non-negligible absolute median errors of 1.84°, 2.43° and 1.98° for L1–L5, L1–S1 and SS respectively. Our model is able to calculate with good accuracy the coordinates of the vertebral corners and has a large potential for improving the reliability and repeatability of measurements in clinical tasks.

Adolescent idiopathic scoliosis (AIS) is the most common spinal disorder in children. A severity index was recently proposed to identify the stable from the progressive scoliosis at the first standardized biplanar radiographic exam. The aim of this work was to extend the validation of the severity index and to determine if curve location influences its predictive capabilities. AIS patients with Cobb angle between 10° and 25°, Risser 0–2, and no previous treatment were included. They underwent standing biplanar radiography and 3D reconstruction of the spine and pelvis, which allowed to calculate their severity index. Patients were grouped by curve location (thoracic, thoracolumbar, lumbar). Patients were followed up until skeletal maturity (Risser ≥ 3) or brace prescription. Their outcome was compared to the prediction made by the severity index. In total, 205 AIS patients were included; 82% of them (155/189, 95% confidence interval [74–90%]) were correctly classified by the index, while 16 patients were unclassified. Positive predictive ratio was 78% and negative predictive ratio was 86%. Specificity (78%) was not significantly affected by curve location, while patients with thoracic and lumbar curves showed higher sensitivity (≥ 89%) than those with thoracolumbar curves (74%). In this multicentric cohort of 205 patients, the severity index was used to predict the risk of progression from mild to moderate scoliosis, with similar results of typical major curve types. This index represents a novel tool to aid the clinician and the patient in the modulation of the follow-up and, for progressive patients, their decision for brace treatment. • The severity index of adolescent idiopathic scoliosis has the potential to detect patients with progressive scoliosis as early as the first exam. • Out of 205 patients, 82% were correctly classified as either stable or progressive by the severity index. • The location of the main curve had small effect on the predictive capability of the index.

We developed and used a deep learning tool to process biplanar radiographs of 9,832 non-surgical patients suffering from spinal deformities, with the aim of reporting the statistical distribution of radiological parameters describing the spinal shape and the correlations and interdependencies between them. An existing tool able to automatically perform a three-dimensional reconstruction of the thoracolumbar spine has been improved and used to analyze a large set of biplanar radiographs of the trunk. For all patients, the following parameters were calculated: spinopelvic parameters; lumbar lordosis; mismatch between pelvic incidence and lumbar lordosis; thoracic kyphosis; maximal coronal Cobb angle; sagittal vertical axis; T1-pelvic angle; maximal vertebral rotation in the transverse plane. The radiological parameters describing the sagittal alignment were found to be highly interrelated with each other, as well as dependent on age, while sex had relatively minor but statistically significant importance. Lumbar lordosis was associated with thoracic kyphosis, pelvic incidence and sagittal vertical axis. The pelvic incidence-lumbar lordosis mismatch was found to be dependent on the pelvic incidence and on age. Scoliosis had a distinct association with the sagittal alignment in adolescent and adult subjects. The deep learning-based tool allowed for the analysis of a large imaging database which would not be reasonably feasible if performed by human operators. The large set of results will be valuable to trigger new research questions in the field of spinal deformities, as well as to challenge the current knowledge.

One of the most challenging tasks in non-invasive diagnosis of Adolescent Idiopathic Scoliosis (AIS) is to find the correlation between internal spinal deformity and external shape of the back and to create a model to predict internal curve from 3D scans of the back surfaces only. Consequently, X-ray imaging and analysis could be potentially reduced which lead to decreased cumulative dose to the patient and the risk for malignancy development later in life. We proposed a regression model that considers correlation between 3D coordinates of the ground-truth internal spinal curve and 3D coordinates of external asymmetry curve to predict internal spinal alignment close to the real one. With a limited number of samples used to create it, this model is able to provide an acceptable approximation of the spinal internal alignment particularly in sagittal plane, with a mean 3D displacement between predicted and real curve of around 10-12 mm. Quality of prediction could be significantly improved by simultaneously acquiring 3D scans of the back surface and X-ray scans of the patient, and adding to the model external features like scapulae or rib cage which are future steps towards improvement and clinical validation., ISSN:2158-8481, 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), ISBN:978-1-6654-4280-0, ISBN:978-1-6654-4281-7

The study aims to create a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome using a machine learning (ML) approach. A single spine surgery center retrospective review of prospectively collected data from January 2016 to December 2020 from the institutional registry (SpineREG) was performed. The inclusion criteria were age ≥ 18 years, both sexes, lumbar arthrodesis procedure, a complete follow up assessment (Oswestry Disability Index-ODI, SF-36 and COMI back) and the capability to read and understand the Italian language. A delta of improvement of the ODI higher than 12.7/100 was considered a "good early outcome". A combined target model of ODI (Δ ≥ 12.7/100), SF-36 PCS (Δ ≥ 6/100) and COMI back (Δ ≥ 2.2/10) was considered an "excellent early outcome". The performance of the ML models was evaluated in terms of sensitivity, i.e., True Positive Rate (TPR), specificity, i.e., True Negative Rate (TNR), accuracy and area under the receiver operating characteristic curve (AUC ROC). A total of 1243 patients were included in this study. The model for predicting ODI at 6 months' follow up showed a good balance between sensitivity (74.3%) and specificity (79.4%), while providing a good accuracy (75.8%) with ROC AUC = 0.842. The combined target model showed a sensitivity of 74.2% and specificity of 71.8%, with an accuracy of 72.8%, and an ROC AUC = 0.808. The results of our study suggest that a machine learning approach showed high performance in predicting early good to excellent clinical results. Conflict of interest statement: The authors declare that they have no competing interest.

The purpose of this review is to summarize the general knowledge about the biomechanics of the sacroiliac joint and sacropelvic fixation techniques. Additionally, this study aims to support biomechanical investigations in defining experimental protocols as well as numerical modeling of the sacropelvic structures. The sacroiliac joint is characterized by a large variability of shape and ranges of motion among individuals. Although the ligament network and the anatomical features strongly limit the joint movements, sacroiliac displacements and rotations are not negligible. Currently available treatments for sacroiliac joint dysfunction include physical therapy, steroid injections, Radio-frequency ablation of specific neural structures, and open or minimally invasive SIJ fusion. In long posterior construct, the most common solutions are the iliac screws and the S2 alar - iliac screws, whereas for the joint fixation alone, mini - invasive alternative system can be used. Several studies reported the clinical outcomes of the different techniques and investigated the biomechanical stability of the relative construct, but the effect of sacropelvic fixation techniques on the joint flexibility and on the stress generated into the bone is still unknown. In our opinion, more biomechanical analyses on the behavior of the sacroiliac joint may be performed in order to better predict the risk of failure or instability of the joint.

Study Design Basic science (finite element analysis). Objectives Pedicle subtraction osteotomy (PSO) at L5 is an effective treatment for sagittal imbalance, especially in select cases of patients showing kyphosis with the apex at L4-L5 but has been scarcely investigated. The aim of this study was to simulate various “high-demand” instrumentation approaches, including varying numbers of rods and sacropelvic implants, for the stabilization of a PSO at L5. Methods A finite element model of T10-pelvis was modified to simulate posterior fixation with pedicle screws and rods from T10 to S1, alone or in combination with an L5 PSO. Five additional configurations were then created by employing rods and novel porous fusion/fixation implants across the sacroiliac joints, in varying numbers. All models were loaded using pure moments of 7.5 Nm in flexion-extension, lateral bending, and axial rotation. Results The osteotomy resulted in a general increase in motion and stresses in posterior rods and S1 pedicle screws. When the number of rods was varied, three- and four-rod configurations were effective in limiting the maximal rod stresses; values approached those of posterior fixation with no osteotomy. Maximum stresses in the accessory rods were similar to or less than those observed in the primary rods. Multiple sacropelvic implants were effective in reducing range of motion, particularly of the SIJ. Conclusions Multi-rod constructs and sacropelvic fixation generally reduced maximal implant stresses and motion in comparison with standard posterior fixation, suggesting a reduced risk of rod breakage and increased joint stability, respectively, when a high-demand construct is utilized for the correction of sagittal imbalance.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity of the spine. Spine slenderness, which represents its potential instability to buckling under compressive loads, was shown to be higher in AIS patients than non-scoliotic subjects, but it is not clear at what stage of the progression this difference appeared, nor if slenderness could be used as an early sign of progression. In this study, we hypothesized that slenderness could be an early sign of progression. One-hundred thirty-eight patients and 93 non-scoliotic subjects were included. They underwent standing biplanar radiography and 3D reconstruction of the spine, which allowed computing vertebra and disc slenderness ratio. Then, patients were followed until progression of the deformity or skeletal maturity (stable patients). Vertebral slenderness ratio in AIS patients varied between 2.9 [2.7; 3.0] (T9) and 3.4 [3.2; 3.6] (T1), while disc slenderness ranged from 0.6 [0.6; 0.7] at T6-T7 to 1.2 [1.1; 1.3] at L4-L5. Slenderness ratio increased with age, while disc slenderness tended to decrease with age and Cobb angle. Slenderness was similar between progressive and stable patients, and also between patients and non-scoliotic subjects. In conclusion, spinal slenderness does not appear to be an early sign of progression. Further studies should analyse the development of slenderness during growth, and how it could be affected by non-operative treatment.

AimsTo create, using a machine learning (ML) approach, a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome.Patients and MethodsA single spine surgery center retrospective review of prospectively collected data from January 2016 to December 2020 from the institutional registry (SpineREG) was performed. The inclusion criteria were age ≥ 18 years, both sexes, lumbar arthrodesis procedure, a complete follow up assessment (ODI, SF-36 and COMI back) and the capability to read and understand the Italian language. A delta of improvement of the ODI higher than 12.7/100 was considered a “good early outcome”. A combined target model of ODI (Δ ≥ 12.7/100), SF-36 PCS (Δ ≥ 6/100) and COMI back (Δ ≥ 2.2/10) was considered an “excellent early outcome”. The performance of the ML models was evaluated in terms of sensitivity, i.e., True Positive Rate (TPR), specificity, i.e., True Negative Rate (TNR), accuracy and area under the receiver operating characteristic curve (AUC ROC).ResultsA total of 1243 patients were included in this study. The model for predicting ODI at 6 months follow up showed a good balance between sensitivity (74.3%) and specificity (79.4%), while providing a good accuracy (75.8%) with ROC AUC = 0.842. The combined target model showed a sensitivity of 74.2% and specificity of 71.8%, with an accuracy of 72.8%, and a ROC AUC = 0.808.ConclusionThe results of our study suggest that a machine learning approach showed high performance in predicting early good to excellent clinical results.

A major clinical challenge in adolescent idiopathic scoliosis (AIS) is the difficulty of predicting curve progression at initial presentation. The early detection of progressive curves can offer the opportunity to better target effective non-operative treatments, reducing the need for surgery and the risks of related complications. Predictive models for the detection of scoliosis progression in subjects before growth spurt have been developed. These models accounted for geometrical parameters of the global spine and local descriptors of the scoliotic curve, but neglected contributions from biomechanical measurements such as trunk muscle activation and intervertebral loading, which could provide advantageous information. The present study exploits a musculoskeletal model of the thoracolumbar spine, developed in AnyBody software and adapted and validated for the subject-specific characterization of mild scoliosis. A dataset of 100 AIS subjects with mild scoliosis and in pre-pubertal age at first examination, and recognized as stable (60) or progressive (40) after at least 6-months follow-up period was exploited. Anthropometrical data and geometrical parameters of the spine at first examination, as well as biomechanical parameters from musculoskeletal simulation replicating relaxed upright posture were accounted for as predictors of the scoliosis progression. Predicted height and weight were used for model scaling because not available in the original dataset. Robust procedure for obtaining such parameters from radiographic images was developed by exploiting a comparable dataset with real values. Six predictive modelling approaches based on different algorithms for the binary classification of stable and progressive cases were compared. The best fitting approaches were exploited to evaluate the effect of accounting for the biomechanical parameters on the prediction of scoliosis progression. The performance of two sets of predictors was compared: accounting for anthropometrical and geometrical parameters only; considering in addition the biomechanical ones. Median accuracy of the best fitting algorithms ranged from 0.76 to 0.78. No differences were found in the classification performance by including or neglecting the biomechanical parameters. Median sensitivity was 0.75, and that of specificity ranged from 0.75 to 0.83. In conclusion, accounting for biomechanical measures did not enhance the prediction of curve progression, thus not supporting a potential clinical application at this stage., Frontiers in Bioengineering and Biotechnology, 9, ISSN:2296-4185

Adolescent idiopathic scoliosis is a three-dimensional deformity of the spine which is frequently corrected with the implantation of instrumentation with generally good or excellent clinical results; mechanical post-operative complications such as implant loosening and breakage are however relatively frequent. The rate of complications is associated with a lack of consensus about the surgical decision-making process; choices about the instrumentation length, the anchoring implants and the degree of correction are indeed mostly based on personal views and previous experience of the surgeon. In this work, we performed an in silico clinical trial on a large number of subjects in order to clarify which factors have the highest importance in determining the risk of complications by quantitatively analysing the mechanical stresses and loads in the instrumentation after the correction maneuvers. The results of the simulations highlighted the fundamental role of the curve severity, also in its three-dimensional aspect, and of the instrumentation strategy, whereas the length of the fixation had a lower importance.

We present an automated method for extracting anatomical parameters from biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions, including sagittal and coronal deformities, degenerative phenomena as well as images acquired with different fields of view. The location of 78 landmarks (end plate centers, hip joint centers, and margins of the S1 end plate) was extracted from three-dimensional reconstructions of 493 spines of patients suffering from various disorders, including adolescent idiopathic scoliosis, adult deformities, and spinal stenosis. A fully convolutional neural network featuring an additional differentiable spatial to numerical (DSNT) layer was trained to predict the location of each landmark. The values of some parameters (T4–T12 kyphosis, L1–L5 lordosis, Cobb angle of scoliosis, pelvic incidence, sacral slope, and pelvic tilt) were then calculated based on the landmarks’ locations. A quantitative comparison between the predicted parameters and the ground truth was performed on a set of 50 patients. The spine shape predicted by the models was perceptually convincing in all cases. All predicted parameters were strongly correlated with the ground truth. However, the standard errors of the estimated parameters ranged from 2.7° (for the pelvic tilt) to 11.5° (for the L1–L5 lordosis). The proposed method is able to automatically determine the spine shape in biplanar radiographs and calculate anatomical and posture parameters in a wide scenario of clinical conditions with a very good visual performance, despite limitations highlighted by the statistical analysis of the results. These slides can be retrieved under Electronic Supplementary Material.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity of the spine, the aetiology and pathogenesis of which are poorly understood. Unfortunately, biomechanical data describing trunk muscle activation and intervertebral load, which can contribute to understanding the pathomechanics of the AIS spine, cannot be measured in vivo due to the invasiveness of the procedures. The present study provides the biomechanical characterization of the spinal loads in scoliotic subjects by exploiting musculoskeletal modelling approach, allowing for calculating biomechanical measures in an assigned posture. A spine model with articulated ribcage previously developed in AnyBody software was applied. The predicted outcomes were evaluated in the upright posture, depending on scoliosis severity and curve type, in a population of 132 scoliotic subjects with mild, moderate, and severe scoliosis. Radiographic-based three dimensional reconstruction of vertebral orientations and scaling of body segments and trunk muscle cross-section area guaranteed geometrical subject-specificity. Validation analysis supporting the application of the model was performed. Trunk muscles were found more activated in the convex side of the scoliotic curve, in agreement with reference in vivo measurements, with progressive increase with scoliosis severity. The intervertebral lateral shear was found positively correlated with the severity of the scoliosis, demonstrating that the transferred load is not a priori orthogonal to vertebral endplate in the frontal plane, and thus questioning the assumption of the 'follower load' approach in case of experimental or computational study on the scoliotic spine. The study opens the way for the subject-specific characterization of scoliosis in assigned loading and motion conditions.

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.

Musculoskeletal models provide a valuable insight to non-invasively investigate the relation between human motion and internal biomechanical loads. Through an inverse dynamic approach, this modeling technique allows to compute the intersegmental forces acting during the execution of imposed specific body motion and under the action of known external loads. When focusing on the characterization of human spine, musculoskeletal modeling can be accounted to evaluate lumbar loads during physiological activities (e.g. training, ergonomics and rehabilitation) and pathological scenarios (e.g. spine deformities and surgical fixation strategies). The results of the present work demonstrated the suitability of the AnyBody model in computing lumbar spine loads at L4L5 level. Specific caution needs to be taken only when considering postures characterized bylarge lateral displacements or high lateral loading. The present findings promote the AnyBody model as an appropriate tool to non-invasively evaluate lumbar loads in physiological activities. Future studies can be aimed at evaluating the use of AnyBody modeling in pathological conditions known altering spine alignment, such as spine deformities and fixation strategies.

Objective To mitigate the risk of iatrogenic instability, new posterior decompression techniques able to preserve musculoskeletal structures have been introduced but never extensively investigated from a biomechanical point of view. This study was aimed to investigate the impact on spinal flexibility caused by a unilateral laminotomy for bilateral decompression, in comparison to the intact condition and a laminectomy with preservation of a bony bridge at the vertebral arch. Secondary aims were to investigate the biomechanical effects of two-level decompression and the quantification of the restoration of stability after posterior fixation. Methods A universal spine tester was used to measure the flexibility of six L2-L5 human spine specimens in intact conditions and after decompression and fixation surgeries. An incremental damage protocol was applied : 1) unilateral laminotomy for bilateral decompression at L3-L4; 2) on three specimens, the unilateral laminotomy was extended to L4-L5; 3) laminectomy with preservation of a bony bridge at the vertebral arch (at L3-L4 in the first three specimens and at L4-L5 in the rest); and 4) pedicle screw fixation at the involved levels. Results Unilateral laminotomy for bilateral decompression had a minor influence on the lumbar flexibility. In flexion-extension, the median range of motion increased by 8%. The bone-preserving laminectomy did not cause major changes in spinal flexibility. Two-level decompression approximately induced a twofold destabilization compared to the single-level treatment, with greater effect on the lower level. Posterior fixation reduced the flexibility to values lower than in the intact conditions in all cases. Conclusion In vitro testing of human lumbar specimens revealed that unilateral laminotomy for bilateral decompression and bone-preserving laminectomy induced a minor destabilization at the operated level. In absence of other pathological factors (e.g., clinical instability, spondylolisthesis), both techniques appear to be safe from a biomechanical point of view.

Most patients suffering from Parkinson’s disease (PD) exhibit alterations in the posture, which can in several cases give rise to spine deformities, both in the sagittal and the coronal plane. In addition, degenerative disorders of the spine frequently associated to PD, such as spinal stenosis and sagittal instability, can further impact the quality of life of the patient. In recent years, spine surgery has been increasingly performed, with mixed results. The aim of this narrative review is to analyze the spinal disorders associated to PD, and the current evidence about their surgical treatment. Narrative review. Camptocormia, i.e., a pronounced flexible forward bending of the trunk with 7% prevalence, is the most reported sagittal disorder of the spine. Pisa syndrome and scoliosis are both common and frequently associated. Disorders to the spinopelvic alignment were not widely investigated, but a tendency toward a lower ability of PD patients to compensate the sagittal malalignment with respect to non-PD elderly subjects with imbalance seems to emerge. Spine surgery in PD patients showed high rates of complications and re-operations. Disorders of the posture and spinal alignment, both in the sagittal and in the coronal planes, are common in PD patients, and have a major impact on the quality of life. Outcomes of spine surgery are generally not satisfactory, likely mostly due to muscle dystonia and poor bone quality. Knowledge in this field needs to be consolidated by further clinical and basic science studies. These slides can be retrieved under Electronic Supplementary Material.

This paper describes new optical method and software tool developed to extract important intrinsic indicators of adolescent idiopathic scoliosis (AIS) non-invasively. Using optical digitalization, we scanned dorsal surfaces of 372 patients (141 males and 231 females) in a clinical environment from 2014–2017. Patient datasets were processed using our in-house “ScolioSIM” tool to generate key deformity indicators, along with 3D deformity visualizations. This method relies on a digitalized dorsal surface of AIS patient, on a multiscale and registerable 3D generic spinal model, CAD and KAx technologies. In this paper we focused our attention towards transpositions of intervertebral disks and their centroids in anteroposterior plane (AP). By knowing the exact transpositions values of all intervertebral centroids (L5/L4 to T1/C7) from the local spinal axis (DM-C7) it is possible to model 3D middle spinal alignment and to calculate the range of AIS curvature which is a basic for a new 3D classification scheme.

Proper statistical analysis is essential in the research studies. In particular, as regards the in vitro testing of the lumbar spine, the criteria for the standardization have been extensively discussed but the use of statistics has not been reviewed. Unfortunately, cadaveric testing is a very difficult and complex experimental field, in which many factors such as collection times, costs, funding, personnel and logistic issues, availability of implant components, can determinate low sample sizes, with impacts on the statistical evaluation. Moreover, as in any other field, some errors can be commonly made in the choice of the most appropriate statistical tests. The present tutorial article provides a comprehensive overview of the theoretical basics of the statistical approach, focusing on the experimental testing of the lumbar spine. Reference values about adequate sample size and statistical power were provided. The use of statistics was reviewed in a selection of 20 papers, chosen among the most cited and representative contributions for the in vitro study of the lumbar spine. Overall, only 7 in 20 papers applied fully corrected procedures. The achieved power, calculated for the medium conventional level of the effect size, ranged from 0.13 to 0.99 but overall was found rather poor, below 0.6. The study also revealed that applying incorrect statistical tests and having low sample size can impact p-value and power, respectively, with consequences on the identification of the significant outcomes. We emphasize that this review is not intended as a mere critical analysis from a statistical perspective, but as a constructive investigation aimed to support the researchers in the challenging field of cadaveric testing. It is worth noting that the provided recommendations and reference values can be also accounted for experimental scenarios testing the other spine regions, either in human or in animal models.

We trained a deep neural network for the three-dimensional estimation of the direction of the three anatomical axes (cranio-caudal, anteroposterior and laterolateral) of individual vertebrae from a single sagittal radiographic image acquired from an approximately lateral direction with large deviations from a perfect alignment up to 60 degrees. To this aim, we exploited computed tomography (CT), which can be used to create simulated radiographic projections with different orientations, for the creation of large training and validation datasets. In a set of 21 CT stacks, the location of 5 landmark points was manually determined for L2, L3 and L4, for a total of 63 vertebrae. For each vertebra, 200 simulated projections approximately aligned with sagittal plane but including random perturbations of the projection direction were built, resulting in 12,600 simulated radiographs with the corresponding local directions of the anatomical axes. These data were integrated by 1765 lateral images of vertebrae acquired with a biplanar radiographic imaging system, for which the orientation was calculated by means of three-dimensional reconstruction. The whole dataset was used to train a deep neural network, ResNet-101, customized for the estimation of the three-dimensional components of the axes. The accuracy of the network was qualitatively and quantitatively tested on a large group of simulated radiographic images as well as real lateral images acquired with a biplanar radiographic system for which the direction of the axes was known. Errors were lower than 3 degrees in 76% of the evaluations conducted on the simulated images, and in 86% for the real radiographs. The novel method will be useful to extract three-dimensional information from planar images even in clinical cases in which vertebrae are markedly rotated due to spinal deformities or to an imprecise alignment of the patient with respect to the detector.

BACKGROUND CONTEXT Sagittal plane alignment is of crucial importance for the treatment of spinal deformities. When planning corrective strategies, spine surgeons need to refer to normative parameters’ ranges which characterize the alignment in the asymptomatic population. Changes are known to occur with age. For the Caucasian population, the reference ranges are extensively documented for the young and middle-aged adults. In contrast, only a few studies have evaluated individuals in advanced age (>60 years) and in groups of limited numbers of subjects (less than 50). PURPOSE To describe the normative parameter ranges of sagittal spine alignment in a large population of asymptomatic elderly subjects. STUDY DESIGN/SETTING Monocentric, prospective, cross-sectional study. PATIENT SAMPLE One hundred sixty asymptomatic elderly volunteers (age>60 years, Caucasian heritage), consecutively enrolled. OUTCOME MEASURES Sagittal parameters of spine and pelvis: thoracic kyphosis (TK); lumbar lordosis (LL); sacral slope (SS); pelvic incidence (PI); pelvic tilt (PT); sagittal vertical axis (SVA); T1 pelvic angle (TPA); mismatch between PI and LL (PI-LL); Roussouly classification of the lumbopelvic profile. METHODS Each subject underwent one radiographic scan, performed in standing position with EOS low-dose system (EOS Imaging, Paris, France). The radiographic images were processed with sterEOS software allowing identification of the anatomical parameters and the presence of scoliosis. SVA, TPA, and the lumbopelvic profile were manually measured in the lateral images. The results were compared to previous studies describing younger adult populations. The study was supported by the Italian Ministry of Health in the amount of $15,000. The authors declare that there are no conflicts of interests. RESULTS Overall, the average values of the spinopelvic parameters were the followings: TK, 55±14°; LL, 57±12°; PI, 55±11°; SS, 38±10°; PT, 16±7°. The average PI-LL, SVA, and TPA was −3±11°, 25±32 mm, and 14.6±7.4°, respectively. TK, TPA, and SVA were found increasing with age. As for classification of the lumbopelvic profile, 16% of subjects were excluded because they were considered not to belong to any of the Roussouly types. In the classified subjects, the distribution was similar to that of younger adults. Asymptomatic scoliosis (average Cobb angle, 22±7°) was identified in 27% of individuals. CONCLUSIONS The ranges of values pointed out differences compared to younger adults and represent an important resource for spine surgeons in planning the surgical correction of spinal deformities. The characteristic changes occurring with age, as well as the observed presence of mild or moderate asymptomatic scoliosis, should be carefully taken into account. The classification of the lumbopelvic profile based on the Roussouly scheme revealed some limitations, although similar frequencies were identified compared to younger adults.