To propose a deep learning framework \"SpineCurve-net\" for automated measuring the 3D Cobb angles from computed tomography (CT) images of presurgical scoliosis patients. A total of 116 scoliosis patients were analyzed, divided into a training set of 89 patients (average age 32.4 ± 24.5 years) and a validation set of 27 patients (average age 17.3 ± 5.8 years). Vertebral identification and curve fitting were achieved through U-net and NURBS-net and resulted in a Non-Uniform Rational B-Spline (NURBS) curve of the spine. The 3D Cobb angles were measured in two ways: the predicted 3D Cobb angle (PRED-3D-CA), which is the maximum value in the smoothed angle map derived from the NURBS curve, and the 2D mapping Cobb angle (MAP-2D-CA), which is the maximal angle formed by the tangent vectors along the projected 2D spinal curve. The model segmented spinal masks effectively, capturing easily missed vertebral bodies. Spoke kernel filtering distinguished vertebral regions, centralizing spinal curves. The SpineCurve Network method\'s Cobb angle (PRED-3D-CA and MAP-2D-CA) measurements correlated strongly with the surgeons\' annotated Cobb angle (ground truth, GT) based on 2D radiographs, revealing high Pearson correlation coefficients of 0.983 and 0.934, respectively. This paper proposed an automated technique for calculating the 3D Cobb angle in preoperative scoliosis patients, yielding results that are highly correlated with traditional 2D Cobb angle measurements. Given its capacity to accurately represent the three-dimensional nature of spinal deformities, this method shows potential in aiding physicians to develop more precise surgical strategies in upcoming cases.

Scoliosis often occurs in adolescents and seriously affects physical development and health. Traditionally, medical imaging is the most common means of evaluating the corrective effect of bracing during treatment. However, the imaging approach falls short in providing real-time feedback, and the optimal corrective force remains unclear, potentially slowing the patient\'s recovery progress. To tackle these challenges, an all-in-one integrated array of pressure sensors and sEMG electrodes based on hierarchical MXene/chitosan/polydimethylsiloxane (PDMS)/polyurethane sponge and MXene/polyimide (PI) is developed. Benefiting from the microstructured electrodes and the modulus enhancement of PDMS, the sensor demonstrates a high sensitivity of 444.3 kPa-1 and a broad linear detection range (up to 81.6 kPa). With the help of electrostatic attraction of chitosan and interface locking of PDMS, the pressure sensor achieves remarkable stability of over 100 000 cycles. Simultaneously, the sEMG electrodes offer exceptional stretchability and flexibility, functioning effectively at 60% strain, which ensures precise signal capture for various human motions. After integrating the developed all-in-one arrays into a commercial scoliosis brace, the system can accurately categorize human motion and predict Cobb angles aided by deep learning. This study provides real-time insights into brace effectiveness and patient progress, offering new ideas for improving the efficiency of scoliosis treatment.

OBJECTIVE: The accurate measurement of Cobb angles is crucial for the effective clinical management of patients with adolescent idiopathic scoliosis (AIS). The Lenke classification system plays a pivotal role in determining the appropriate fusion levels for treatment planning. However, the presence of interobserver variability and time-intensive procedures presents challenges for clinicians. The purpose of this study is to compare the measurement accuracy of our developed artificial intelligence measurement system for Cobb angles and Lenke classification in AIS patients with manual measurements to validate its feasibility.
METHODS: An artificial intelligence (AI) system measured the Cobb angle of AIS patients using convolutional neural networks, which identified the vertebral boundaries and sequences, recognized the upper and lower end vertebras, and estimated the Cobb angles of the proximal thoracic, main thoracic, and thoracolumbar/lumbar curves sequentially. Accordingly, the Lenke classifications of scoliosis were divided by oscillogram and defined by the AI system. Furthermore, a man-machine comparison (n = 300) was conducted for senior spine surgeons (n = 2), junior spine surgeons (n = 2), and the AI system for the image measurements of proximal thoracic (PT), main thoracic (MT), thoracolumbar/lumbar (TL/L), thoracic sagittal profile T5-T12, bending views PT, bending views MT, bending views TL/L, the Lenke classification system, the lumbar modifier, and sagittal thoracic alignment.
RESULTS: In the AI system, the calculation time for each patient\'s data was 0.2 s, while the measurement time for each surgeon was 23.6 min. The AI system showed high accuracy in the recognition of the Lenke classification and had high reliability compared to senior doctors (ICC 0.962).
CONCLUSIONS: The AI system has high reliability for the Lenke classification and is a potential auxiliary tool for spinal surgeons.

UNASSIGNED: Adolescent idiopathic scoliosis (AIS) is a prevalent spinal disorder that can potentially influence bone mineral density (BMD), thereby increasing the susceptibility to osteoporosis and fractures. Early identification of reduced bone mass in AIS patients is crucial for clinicians to develop effective preventive strategies against fractures. This study aims to elucidate the correlation between BMD, as measured by quantitative computed tomography (QCT), and various clinical parameters in AIS, including the Cobb angle, vertebral rotation, and the Risser sign. By revealing the potential influences of these factors on BMD, our findings aim to assist clinicians in making informed and timely decisions regarding AIS management, particularly in situations where QCT is unavailable.
UNASSIGNED: A cross-sectional study was conducted on 129 adolescents with AIS who were enrolled at The Third People\'s Hospital of Chengdu, Sichuan, China, between 2021 and 2023. QCT was employed to assess BMD and vertebral rotation. The Cobb angle and Risser sign were determined through radiographic evaluation, while anthropometric and biochemical data were also collected. Statistical analyses, including Pearson and Spearman rank correlation and regression models, were used to investigate the associations between BMD and clinical measures.
UNASSIGNED: A significant negative correlation was found between BMD and Cobb angle (coefficient =-0.663; P<0.001), as well as between BMD and vertebral rotation angle (coefficient =-0.442; P<0.001) in patients with AIS. BMD was positively correlated with increased height (coefficient =0.355; P<0.001) and BMI (coefficient =0.199; P=0.02). A significant association was detected between BMD and the Risser sign (P=0.002). No significant sex-based differences in BMD were observed (P=0.052). No significant correlations were observed between BMD and levels of potassium (K), calcium (Ca), inorganic phosphate (P), and iron (Fe) (P>0.05 all). The binary logistic regression analysis identified Cobb angle as a risk factor of lower BMD presence in AIS patients (coefficient =0.072; OR=1.075; P<0.001). Furthermore, the receiver operating characteristic (ROC) analysis of the combined model for predicting low BMD in AIS patients yielded an area under the curve (AUC) value of 0.900, with an optimal threshold determined as 0.398. The sensitivity and specificity were calculated as 0.816 and 0.900, respectively, indicating a robust predictive capacity.
UNASSIGNED: This study highlights the significant inverse correlation observed between BMD measured by QCT and both Cobb angle and vertebral rotation angle in patients with AIS. Furthermore, a notable variation in BMD was found across different Risser sign categories, with BMD values generally increasing as Risser sign levels increased. Additionally, our findings indicate that Cobb angle serves as a risk factor for low BMD presence. Moreover, a combined model was developed to predict the likelihood of low BMD occurrence in AIS patients.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) necessitates accurate spinal curvature assessment for effective clinical management. Traditional two-dimensional (2D) Cobb angle measurements have been the standard, but the emergence of three-dimensional (3D) automatic measurement techniques, such as those using weight-bearing 3D imaging (WR3D), presents an opportunity to enhance the accuracy and comprehensiveness of AIS evaluation.
OBJECTIVE: This study aimed to compare traditional 2D Cobb angle measurements with 3D automatic measurements utilizing the WR3D imaging technique in patients with AIS.
METHODS: A cohort of 53 AIS patients was recruited, encompassing 88 spinal curves, for comparative analysis.
METHODS: The patient sample consisted of 53 individuals diagnosed with AIS.
METHODS: Cobb angles were calculated using the conventional 2D method and three different 3D methods: the Analytical Method (AM), the Plane Intersecting Method (PIM), and the Plane Projection Method (PPM).
METHODS: The 2D cobb angle was manually measured by 3 experienced clinicians with 2D frontal whole-spine radiographs. For 3D cobb angle measurements, the spine and femoral heads were segmented from the WR3D images using a 3D-UNet deep-learning model, and the automatic calculations of the angles were performed with the 3D slicer software.
RESULTS: AM and PIM estimates were found to be significantly larger than 2D measurements. Conversely, PPM results showed no statistical difference compared to the 2D method. These findings were consistent in a subgroup analysis based on 2D Cobb angles.
CONCLUSIONS: Each 3D measurement method provides a unique assessment of spinal curvature, with PPM offering values closely resembling 2D measurements, while AM and PIM yield larger estimations. The utilization of WR3D technology alongside deep learning segmentation ensures accuracy and efficiency in comparative analyses. However, additional studies, particularly involving patients with severe curves, are required to validate and expand on these results. This study emphasizes the importance of selecting an appropriate measurement method considering the imaging modality and clinical context when assessing AIS, and it also underlines the need for continuous refinement of these techniques for optimal use in clinical decision-making and patient management.

BACKGROUND: Delayed extubation and transfer to the intensive care unit (ICU) in children undergoing major scoliosis surgery may increase postoperative complications, prolong hospital stay, and increase medical expenses; however, whether a child will require delayed extubation or transfer to the ICU after scoliosis orthopedic surgery is not fully understood. In this study, we reviewed the risk factors for delayed extubation and transfer to the ICU after scoliosis orthopedic surgery in children.
METHODS: The electronic medical records of pediatric patients (≤ 18 years) who underwent posterior spinal fusion surgery between January 2018 and November 2021 were reviewed and analyzed. Patient characteristics (age, sex, body mass index, American Society of Anesthesiologists, ASA, grade, preoperative lung function, and congenital heart disease), preoperative Cobb angle, scoliosis type, correction rate, vertebral fusion segments, pedicle screws, surgical osteotomy, intraoperative bleeding, intraoperative allogeneic transfusion, intraoperative hemoglobin changes, intraoperative mean arterial pressure changes, intraoperative tidal volume (ml/kg predicted body weight), surgical time, postoperative extubation, and transfer to the ICU were collected. The primary outcomes were delayed extubation and transfer to the ICU. Multivariate logistic regression models were used to determine the risk factors for delayed extubation and ICU transfer.
RESULTS: A total of 246 children who satisfied the inclusion criteria were enrolled in this study, of whom 23 (9.3%) had delayed extubation and 81 (32.9%) were transferred to the ICU after surgery. High ASA grade (odds ratio [OR] 5.42; 95% confidence interval [CI] 1.49-19.78; p = 0.010), high Cobb angle (OR 1.04; 95% CI 1.02-1.07; p < 0.001), moderate to severe pulmonary dysfunction (OR 10.9; 95% CI 2.00-59.08; p = 0.006) and prolonged surgical time (OR 1.01; 95% CI 1.00-1.03; p = 0.040) were risk factors for delayed extubation. A high Cobb angle (OR 1.02; 95% CI 1.01-1.04; p = 0.004), high intraoperative bleeding volume (OR 1.06; 95% CI 1.03-1.10; p = 0.001), allogeneic transfusion (OR 3.30; 95% CI 1.24-8.83; p = 0.017) and neuromuscular scoliosis (OR 5.38; 95% CI 1.59-18.25; p = 0.007) were risk factors for transfer to the ICU. A high Cobb angle was a risk factor for both delayed extubation and ICU transfer. Age, sex, body mass index, number of vertebral fusion segments, correction rate, and intraoperative tidal volume were not associated with delayed postoperative extubation and ICU transfer.
CONCLUSIONS: The most common risk factor for delayed extubation and ICU transfer in pediatric patients who underwent posterior spinal fusion was a high Cobb angle. Determining risk factors for a poor prognosis may help optimize perioperative respiratory management strategies and planning of postoperative care for children undergoing complicated spinal surgery.
UNASSIGNED: HINTERGRUND: Verzögerte Extubation und Verlegung auf die Intensivstation (ICU) bei Kindern, die sich einer größeren Skolioseoperation unterziehen, können postoperative Komplikationen erhöhen, den Krankenhausaufenthalt verlängern und die medizinischen Kosten steigern. Es ist jedoch nicht vollständig verstanden, ob ein Kind nach einer orthopädischen Skolioseoperation eine verzögerte Extubation oder Verlegung auf die ICU benötigen wird. In dieser Studie haben wir die Risikofaktoren für verzögerte Extubation und Verlegung auf die ICU nach orthopädischer Skolioseoperation bei Kindern überprüft.
UNASSIGNED: Die elektronischen Krankenakten pädiatrischer Patienten (≤ 18 Jahre), die sich zwischen Januar 2018 und November 2021 einer Spondylodese der hinteren Wirbelsäule unterzogen, wurden überprüft und analysiert. Die Patientenmerkmale (Alter, Geschlecht, Body-Mass-Index, ASA-Klassifikation der ASA [Amerikanischen Gesellschaft für Anästhesiologie], präoperative Lungenfunktion und angeborene Herzkrankheiten), präoperativer Cobb-Winkel, Skoliosetyp, Korrekturrate, fusionierte Wirbelsegmente, Pedikelschrauben, chirurgische Osteotomie, intraoperative Blutung, intraoperative allogene Transfusion, intraoperative Hämoglobinveränderungen, intraoperative mittlere arterielle Druckänderungen, intraoperatives Tidalvolumen (ml/kg prognostiziertes Körpergewicht), Operationsdauer, postoperative Extubation und Verlegung auf die Intensivstation wurden erfasst. Die primären Endpunkte waren verzögerte Extubation und Verlegung auf die Intensivstation. Multivariate logistische Regressionsmodelle wurden verwendet, um die Risikofaktoren für verzögerte Extubation und die Verlegung auf die Intensivstation zu ermitteln.
UNASSIGNED: Insgesamt wurden 246 Kinder, die die Einschlusskriterien erfüllten, in diese Studie eingeschlossen, von denen 23 (9,3 %) eine verzögerte Extubation hatten und 81 (32,9 %) nach der Operation auf die Intensivstation verlegt wurden. Ein hoher ASA-Grad (Odds-Ratio [OR] 5,42; 95 % Konfidenzintervall [KI] 1,49–19,78; p = 0,010), ein hoher Cobb-Winkel (OR 1,04; 95 % KI 1,02–1,07; p < 0,001), eine moderate bis schwere Lungenfunktionsstörung (OR 10,9; 95 % KI 2,00–59,08; p = 0,006) und eine verlängerte Operationsdauer (OR 1,01; 95 % KI 1,00–1,03; p = 0,040) waren Risikofaktoren für verzögerte Extubation. Ein hoher Cobb-Winkel (OR 1,02; 95 % KI 1,01–1,04; p = 0,004), ein hohes intraoperatives Blutungsvolumen (OR 1,06; 95 % KI 1,03–1,10; p = 0,001), allogene Transfusion (OR 3,30; 95 % KI 1,24–8,83; p = 0,017) und neuromuskuläre Skoliose (OR 5,38; 95 % KI 1,59–18,25; p = 0,007) waren Risikofaktoren für die Verlegung auf die Intensivstation. Ein hoher Cobb-Winkel war ein Risikofaktor sowohl für die verzögerte Extubation als auch für die Verlegung auf die Intensivstation. Alter, Geschlecht, Body-Mass-Index, Anzahl der fusionierten Wirbelsegmente, Korrekturrate und intraoperatives Tidalvolumen standen nicht im Zusammenhang mit der verzögerten postoperativen Extubation und der Verlegung auf die Intensivstation.
UNASSIGNED: Der häufigste Risikofaktor für eine verzögerte Extubation und die Verlegung auf die Intensivstation bei pädiatrischen Patienten, die sich einer Spondylodese der hinteren Wirbelsäule unterzogen haben, war ein hoher Cobb-Winkel. Die Identifizierung von Risikofaktoren für eine ungünstige Prognose kann dazu beitragen, die perioperative Atemwegsmanagementstrategie zu optimieren und die Planung der postoperativen Versorgung von Kindern mit komplexen Wirbelsäuleneingriffen zu verbessern.

BACKGROUND: Patients with idiopathic scoliosis commonly present with an imbalance of the paraspinal muscles. However, it is unclear whether this muscle imbalance is an underlying cause or a result of idiopathic scoliosis. This study aimed to investigate the role of paraspinal muscles in the development of idiopathic scoliosis based on surface electromyography (sEMG) and radiographic analyses.
METHODS: This was a single-center prospective study of 27 patients with single-curve idiopathic scoliosis. Posteroanterior whole-spine radiographs and sEMG activity of the erector spinae muscles were obtained for all patients in the habitual standing position (HSP), relaxed prone position (RPP), and prone extension position (PEP). The Cobb angle, symmetrical index (SI) of the sEMG activity (convex/concave), and correlation between the two factors were analyzed.
RESULTS: In the total cohort, the mean Cobb angle in the HSP was significantly greater than the mean Cobb angle in the RPP (RPP-Cobb) (p < 0.001), whereas the mean Cobb angle in the PEP (PEP-Cobb) did not differ from the RPP-Cobb. Thirteen patients had a PEP-Cobb that was significantly smaller than their RPP-Cobb (p = 0.007), while 14 patients had a PEP-Cobb that was significantly larger than their RPP-Cobb (p < 0.001). In the total cohort and two subgroups, the SI of sEMG activity at the apex vertebra (AVSI) in the PEP was significantly greater than 1, revealing significant asymmetry, and was also significantly larger than the AVSI in the RPP. In the RPP, the AVSI was close to 1 in the total cohort and two subgroups, revealing no significant asymmetry.
CONCLUSIONS: The coronal Cobb angle and the SI of paraspinal muscle activity in AIS patients vary with posture changes. Asymmetrical sEMG activity of the paraspinal muscles may be not an inherent feature of AIS patients, but is evident in the challenging tasks. The potential significance of asymmetric paraspinal muscle activity need to be explored in further research.

The current study aimed to assess and rank the comparative efficacy of different nonoperative treatments on Cobb angle, angle of trunk rotation, and quality of life for mild-to-moderate adolescent idiopathic scoliosis.
A comprehensive search of databases, including Medline, The Cochrane Library, PubMed, EMBASE, and Web of Science spanning all previous years up to January 1, 2024. The included studies were evaluated for literature quality according to Cochrane Handbook criteria, and a network meta-analysis was performed using STATA 14.0 statistical software.
Twenty randomized controlled trials met all inclusion criteria and were analyzed. Schroth exercise and scoliosis-specific exercise combined with brace treatments had a significant positive effect on Cobb angle and quality of life. For angle of trunk rotation, Schroth exercise and Schroth exercise combined with brace treatments prove more effective compared to the control group. On surface-under-the-cumulative-ranking-curve analysis, Schroth exercise combined with brace treatment had the highest likelihood for reducing Cobb angle (P-score = 0.899), angle of trunk rotation (0.82), and improving quality of life (0.828).
Although most conservative treatments had benefits for mild-to-moderate adolescent idiopathic scoliosis, the most optimal programs were those that included (1) at least 10 weeks of approximately 60-minute Schroth exercise sessions twice a week and (2) wearing the brace for 23 hours every day throughout the treatment period.

A recently developed deep-learning-based automatic evaluation model provides reliable and efficient Cobb angle measurements for scoliosis diagnosis. However, few studies have explored its clinical application, and external validation is lacking. Therefore, this study aimed to explore the value of automated assessment models in clinical practice by comparing deep-learning models with manual measurement methods.
The 481 spine radiographs from an open-source dataset were divided into training and validation sets, and 119 spine radiographs from a private dataset were used as the test set. The mean Cobb angle values assessed by three physicians in the hospital\'s PACS system served as the reference standard. The results of Seg4Reg, VFLDN, and manual measurement were statistically analyzed. The intra-class correlation coefficients (ICC) and the Pearson correlation coefficient (PCC) were used to compare their reliability and correlation. The Bland-Altman method was used to compare their agreement. The Kappa statistic was used to compare the consistency of Cobb angles at different severity levels.
The mean Cobb angle values measured were 35.89° ± 9.33° with Seg4Reg, 31.54° ± 9.78° with VFLDN, and 32.23° ± 9.28° with manual measurement. The ICCs for the reliability of Seg4Reg and VFLDN were 0.809 and 0.974, respectively. The PCC and MAD between Seg4Reg and manual measurements were 0.731 (p<0.001) and 6.51°, while those between VFLDN and manual measurements were 0.952 (p<0.001) and 2.36°. The Kappa statistic indicated VFLDN (k= 0.686, p< 0.001) was superior to Seg4Reg and manual measurements for Cobb angle severity classification.
The deep-learning-based automatic scoliosis Cobb angle assessment model is feasible in clinical practice. Specifically, the keypoint-based VFLDN is more valuable in actual clinical work with higher accuracy, transparency, and interpretability.

Scoliosis is a spinal deformation in which the spine takes a lateral curvature, generating an angle in the coronal plane. The conventional method for detecting scoliosis is measurement of the Cobb angle in spine images obtained by anterior X-ray scanning. Ultrasound imaging of the spine is found to be less ionising than traditional radiographic modalities. For posterior ultrasound scanning, alternate indices of the spinous process angle (SPA) and ultrasound curve angle (UCA) were developed and have proven comparable to those of the traditional Cobb angle. In SPA, the measurements are made using the spinous processes as an anatomical reference, leading to an underestimation of the traditionally used Cobb angles. Alternatively, in UCA, more lateral features of the spine are employed for measurement of the main thoracic and thoracolumbar angles; however, clear identification of bony features is required. The current practice of UCA angle measurement is manual. This research attempts to automate the process so that the errors related to human intervention can be avoided and the scalability of ultrasound scoliosis diagnosis can be improved. The key objective is to develop an automatic scoliosis diagnosis system using 3-D ultrasound imaging.
The novel diagnosis system is a three-step process: (i) finding the ultrasound spine image with the most visible lateral features using the convolutional RankNet algorithm; (ii) segmenting the bony features from the noisy ultrasound images using joint spine segmentation and noise removal; and (iii) calculating the UCA automatically using a newly developed centroid pairing and inscribed rectangle slope method.
The proposed method was evaluated on 109 patients with scoliosis of different severity. The results obtained had a good correlation with manually measured UCAs (R2=0.9784 for the main thoracic angle andR2=0.9671 for the thoracolumbar angle) and a clinically acceptable mean absolute difference of the main thoracic angle (2.82 ± 2.67°) and thoracolumbar angle (3.34 ± 2.83°).
The proposed method establishes a very promising approach for enabling the applications of economic 3-D ultrasound volume projection imaging for mass screening of scoliosis.