Severity Of Scoliosis Research Articles

Genome-wide methylation association study in monozygotic twins discordant for curve severity of adolescent idiopathic scoliosis

Background contextEmerging evidence suggests that abnormal DNA methylation patterns may play a role in the progression of adolescent idiopathic scoliosis (AIS). However, the mechanisms underlying the influence of DNA methylation on curve severity remain largely unknown. PurposeTo characterize the DNA methylation profiles associated with the curve severity of AIS. Study designRetrospective study with prospectively collected clinical data and blood samples. MethodsA total of 7 AIS monozygotic twin pairs discordant for curve severity were included. Genome-wide methylation profile from blood samples were quantified by Illumina Infinium MethylationEPIC BeadChip (850K chip). Cell type composition of the samples was estimated by RefbaseEWAS method. Differentially methylated CpG sites were identified through comparison between patients with low and high Cobb angle. We also performed a gene-based collapsing analysis using mCSEA by aggregating the CpG sites based on promoter region. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using clusterProfiler package. ResultsGenome-wide DNA methylation analysis identified multiple differentially methylated positions across the genome. Gene-based collapsing analysis identified 212 differentially methylated genes (FDR adjusted p<0.05), most of which (186/212) were hypermethylated in the group with high Cobb angle. Some of the identified genes were well-documented in AIS literature, such as TBX1, PAX3 and LBX1. Functional enrichment analysis revealed that the differentially methylated genes (DMGs) were involved in pattern specification process, skeletal development, muscle function, neurotransmission and several signaling pathways (cAMP, Wnt and prolactin). ConclusionsThe study represents the largest systematic epigenomic analyses of monozygotic twins discordant for curve severity and supports the important role of altered DNA methylation in AIS. Clinical significanceThe identified CpG sites provide insight into novel biomarkers predicting curve progression of AIS. Furthermore, the differentially methylated genes and enriched pathways may serve as interventional therapy target for AIS patients.

Deep learning prediction of curve severity from rasterstereographic back images in adolescent idiopathic scoliosis.

Radiation-free systems based on dorsal surface topography can potentially represent an alternative to radiographic examination for early screening of scoliosis, based on the ability of recognizing the presence of deformity or classifying its severity. This study aims to assess the effectiveness of a deep learning model based on convolutional neural networks in directly predicting the Cobb angle from rasterstereographic images of the back surface in subjects with adolescent idiopathic scoliosis. Two datasets, comprising a total of 900 individuals, were utilized for model training (720 samples) and testing (180). Rasterstereographic scans were performed using the Formetric4D device. The true Cobb angle was obtained from radiographic examination. The best model configuration was identified by comparing different network architectures and hyperparameters through cross-validation in the training set. The performance of the developed model in predicting the Cobb angle was assessed on the test set. The accuracy in classifying scoliosis severity (non-scoliotic, mild, and moderate category) based on Cobb angle was evaluated as well. The mean absolute error in predicting the Cobb angle was 6.1° ± 5.0°. Moderate correlation (r = 0.68) and a root-mean-square error of 8° between the predicted and true values was reported. The overall accuracy in classifying scoliosis severity was 59%. Despite some improvement over previous approaches that relied on spine shape reconstruction, the performance of the present fully automatic application is below that of radiographic evaluation performed by human operators. The study confirms that rasterstereography cannot be considered a valid non-invasive alternative to radiographic examination for clinical purposes.

Superior performance of a center-point AI model over VFLDNet in automated cobb angle estimation for scoliosis assessment.

Aims to establish the superiority of our proposed model over the state-of-the-art vertebra-focused landmark detection network (VFLDNet) in automating Cobb angle estimation from spinal radiographs. Utilizing a private dataset for external validation, we compared the performance of our center-point detection-based vertebra localization and tilt estimation network (VLTENet) with the key-point detection-based VFLDNet. Both models' Cobb angle predictions were rigorously evaluated against manual consensus score using metrics such as mean absolute error (MAE), correlation coefficient, intraclass correlation coefficient (ICC), Fleiss' kappa, Bland-Altman analysis, and classification metrics [sensitivity (SN), specificity, accuracy] focusing on major curve estimation and scoliosis severity classification. A retrospective analysis of 118 cases with 342 Cobb angle measurements revealed that our model achieved a MAE of 2.15° for total Cobb angles and 1.89° for the major curve, significantly outperforming VFLDNet's MAE of 2.80°and 2.57°, respectively. Both models demonstrated robust correlation and ICC, but our model excelled in classification consistency, particularly in predicting major curve magnitude (ours: kappa = 0.83; VFLDNet: kappa = 0.67). In subgroup analyses by scoliosis severity, our model consistently surpassed VFLDNet, displaying superior mean (SD) differences, narrower limits of agreement, and higher SN, specificity, and accuracy, most notably in moderate (ours: SN = 86.84%; VFLDNet: SN = 83.16%) to severe (ours: SN = 92.86%; VFLDNet: SN = 85.71%) scoliosis. Our model emerges as the superior choice for automated Cobb angle estimation, particularly in assessing major curve and moderate to severe scoliosis, underscoring its potential to revolutionize clinical workflows and enhance patient care.

MGScoliosis: Multi-grained scoliosis detection with joint ordinal regression from natural image

Scoliosis is among the most prevalent diseases affecting teenagers. However, traditional scoliosis screening methods often resort to physical examination or radiographic imaging. The two ways both rely on experts with high costs, which are not suitable for wide-range screening. Besides, estimating Cobb angle level only using natural images are challenging. To tackle these issues, we propose a multi-grained scoliosis detection framework by jointly estimating severity level and Cobb angle level of scoliosis from a natural image instead of a radiographic image, which has not been explored before. Specifically, we regard scoliosis estimation as an ordinal regression problem, and transform it into a series of binary classification sub-problems. Besides, we adopt the visual attention network with large kernel attention as the backbone for feature learning, which can model local and global correlations with efficient computations. The feature learning and the ordinal regression is put into an end-to-end framework, in which the two tasks of scoliosis severity level estimation and scoliosis angle level estimation are jointly learned and can contribute to each other. Extensive experiments demonstrate that our approach outperforms state-of-the-art methods as well as human performance, which provides a promising and economical solution to wide-range scoliosis screening. Particularly, our approach achieves accuracies of 94.90% and 79.62% in estimating severity level and Cobb angle level, improving large margins of 4.90% and 12.15% over existing natural image based scoliosis detection performance, respectively. The code is available at https://github.com/RuiChen-stack/MGScoliosis.

Effects of a Long-Term Supervised Schroth Exercise Program on the Severity of Scoliosis and Quality of Life in Individuals with Adolescent Idiopathic Scoliosis: A Randomized Clinical Trial Study.

Background and Objectives: Adolescent Idiopathic Scoliosis (AIS) affects individuals aged 10-18 years and is characterized by spinal deformity, three-dimensional axis deformation, and vertebral rotation. Schroth method exercises and braces have been shown to reduce the Cobb angle and halt spinal deformity progression. The aim of this study was to investigate the impact of a 12-month, supervised Schroth exercise program on scoliosis severity and quality of life in adolescents with AIS. Materials and Methods: Eighty adolescents with AIS (aged 10-17 years) were prescribed a brace and were divided into two groups. The intervention group followed a supervised Schroth exercise program three times a week for 12 months in addition to wearing a brace. The control group used only the brace. Outcomes included the Cobb angle of the main curvature and the sum of curves using radiography, the maximum angle of trunk rotation (ATR maximum, using a scoliometer), and quality of life with the Scoliosis Research Society-22 (SRS-22) questionnaire. Evaluations were conducted at baseline, after 12 months, and 6 months post-intervention. A multivariate analysis of covariance (MANCOVA) was used for statistical analysis (p-Value < 0.05). Results: The intervention group showed statistically significant improvement compared to the control group in the 12th month in Cobb angle (mean differences, 95% CI: -3.65 (-5.81, -1.53), p-Value < 0.001, Cohen's d = 0.30), ATR maximum (mean differences, 95% CI: -3.05 (-3.86, -2.23), p-Value < 0.001, Cohen's d = 0.74), and SRS-22 score (mean differences, 95% CI: 0.87 (0.60, 1.13), p-Value < 0.001, Cohen's d = 0.58). Differences in ATR maximum and SRS-22 score remained significant at the 18-month measurement. No significant differences were found between groups in the sum of curves (p-Value > 0.05). Conclusions: A 12-month supervised Schroth exercise program in AIS patients undergoing brace treatment significantly improves scoliosis severity (Cobb angle and ATR maximum) and quality of life. Improvements were greater than those in shorter-duration studies, suggesting a linear dose-response relationship. Further clinical studies are needed to clarify the impact of long-term Schroth programs.

Association between Changes in Menarcheal Age and Adolescent Idiopathic Scoliosis: An Analysis of 38,879 Patients over 20 Years.

Menarche has a significant impact on the progression of adolescent idiopathic scoliosis (AIS); however, studies in this area are insufficient. This study used large-scale school screening data to investigate the relationship between menarcheal age and AIS, especially the severity of scoliosis. Of 2,326,577 students who participated in school screening for scoliosis (SSS) in South Korea from 2001 to 2021, 38,879 girls with AIS, who experienced menarche, were included. Data including the patient's demographics, such as menarcheal age, Cobb angle, Risser stage, and the interval between menarche and the time of screening were retrieved from the SSS database. Pearson correlation coefficient was used to identify the changes in menarcheal age according to the birth year and to investigate the relationship between menarcheal age and each variable of interest. Based on the birth year, the mean menarcheal ages in girls with AIS from 1988 to 2008 demonstrated a steadily decreasing trend over time (r = -0.857, p < 0.001). Girls with AIS and late menarche demonstrated a higher Cobb angle at the time of screening (r = 0.095, p < 0.001). Other variables did not significantly correlate with menarcheal age. Based on the SSS, a large-scale school screening dataset, menarcheal age in girls with AIS demonstrated an ongoing downward trend in the recent 20 years in South Korea. Notably, girls with AIS and late menarche had a higher Cobb angle at screening. Our findings indicate the need for earlier screening of AIS in girls who have not undergone menarche.

Asymmetric Osteopenia in Adolescent Idiopathic Scoliosis Based on Hounsfield Unit of Computed Tomography.

To characterize the asymmetrical loss of bone mass and identify the association between scoliosis and osteopenia in patients with adolescent idiopathic scoliosis (AIS). Demographic information, Cobb angle, and Hounsfield unit (HU) of the neutral vertebra (NV) and apical vertebra (apex) of the major curve were collected retrospectively in 54 AIS patients. For 84 control subjects, HU values were measured at T12 and L5. Propensity score matching was performed to balance the interference of age and BMI. In the AIS group, the concave and convex lateral HU of the NV and the convex lateral HU of the apex were negatively correlated with the Cobb angle. The AIS patients had lower bilateral HU. The mean HU and the apex-convex HU were also lower in the AIS group, while the apex-concave HU was slightly higher. After matching, the apex-convex HU of the AIS group remained lower, while the apex-concave HU was higher. Patients with AIS exhibit osteopenia, particularly on the convex side. The severity of scoliosis was found to be directly proportional to the severity of bone loss and the degree of bilateral osteopenia asymmetry. Appropriate intervention for bone loss may be able to curb the progression of scoliosis.

Conditional generative adversarial network-assisted system for radiation-free evaluation of scoliosis using a single smartphone photograph: a model development and validation study

Adolescent idiopathic scoliosis (AIS) is the most common spinal disorder in children, characterized by insidious onset and rapid progression, which can lead to severe consequences if not detected in a timely manner. Currently, the diagnosis of AIS primarily relies on X-ray imaging. However, due to limitations in healthcare access and concerns over radiation exposure, this diagnostic method cannot be widely adopted. Therefore, we have developed and validated a screening system using deep learning technology, capable of generating virtual X-ray images (VXI) from two-dimensional Red Green Blue (2D-RGB) images captured by a smartphone or camera to assist spine surgeons in the rapid, accurate, and non-invasive assessment of AIS. We included 2397 patients with AIS and 48 potential patients with AIS who visited four medical institutions in mainland China from June 11th 2014 to November 28th 2023. Participants data included standing full-spine X-ray images captured by radiology technicians and 2D-RGB images taken by spine surgeons using a camera. We developed a deep learning model based on conditional generative adversarial networks (cGAN) called Swin-pix2pix to generate VXI on retrospective training (n=1842) and validation (n=100) dataset, then validated the performance of VXI in quantifying the curve type and severity of AIS on retrospective internal (n=100), external (n=135), and prospective test datasets (n=268). The prospective test dataset included 268 participants treated in Nanjing, China, from April 19th, 2023, to November 28th, 2023, comprising 220 patients with AIS and 48 potential patients with AIS. Their data underwent strict quality control to ensure optimal data quality and consistency. Our Swin-pix2pix model generated realistic VXI, with the mean absolute error (MAE) for predicting the main and secondary Cobb angles of AIS significantly lower than other baseline cGAN models, at 3.2° and 3.1° on prospective test dataset. The diagnostic accuracy for scoliosis severity grading exceeded that of two spine surgery experts, with accuracy of 0.93 (95% CI [0.91, 0.95]) in main curve and 0.89 (95% CI [0.87, 0.91]) in secondary curve. For main curve position and curve classification, the predictive accuracy of the Swin-pix2pix model also surpassed that of the baseline cGAN models, with accuracy of 0.93 (95% CI [0.90, 0.95]) for thoracic curve and 0.97 (95% CI [0.96, 0.98]), achieving satisfactory results on three external datasets as well. Our developed Swin-pix2pix model holds promise for using a single photo taken with a smartphone or camera to rapidly assess AIS curve type and severity without radiation, enabling large-scale screening. However, limited data quality and quantity, a homogeneous participant population, and rotational errors during imaging may affect the applicability and accuracy of the system, requiring further improvement in the future. National Key R&D Program of China, Natural Science Foundation of Jiangsu Province, China Postdoctoral Science Foundation, Nanjing Medical Science and Technology Development Foundation, Jiangsu Provincial Key Research and Development Program, and Jiangsu Provincial Medical Innovation Centre of Orthopedic Surgery.

Automated Cobb Angle Measurements for Scoliosis Diagnosis and Assessment: AI Applications and Accuracy Enhancement Through Image Processing Techniques.

Introduction Scoliosis is characterized by an abnormal curvature of the spine in the coronal plane. Idiopathic scoliosis is the most prevalent type, though specific causes are sometimes identifiable. Genetic factors significantly influence adolescent idiopathic scoliosis (AIS), which is diagnosed through clinical and radiographic evaluations, primarily using the Cobb angle to measure curvature severity. The classification of scoliosis severity ranges from mild scoliosis, where sometimes the absence of pain is encountered, to moderate and severe, which is usually associated with lancinating pain. Early onset and high progression rates in idiopathic scoliosis are indicative of poorer prognoses. Methods The study analyzed 197 radiographic images from a private clinic database between December 2023 and April 2024. Inclusion criteria focused on anteroposterior images of the thorax and abdomen, excluding unclear and non-spinal images. Manual Cobb angle measurements were performed using RadiAnt DICOM Viewer 2020.2, followed by automated measurements using the Cobb Angle Calculator software. Discrepancies led to further image processing with enhanced color contrast for improved visualization. Data were analyzed using GraphPad InStat to assess error margins between manual and automated measurements. Results Initial results indicated discrepancies between manual and automated Cobb angle measurements. Enhanced image processing improved accuracy, demonstrating the efficacy of both manual and automated techniques in evaluating spinal deformities. Statistical analysis revealed significant error margins, prompting a refined approach for minimizing measurement errors. Discussion The study highlights the importance of accurate Cobb angle measurement in diagnosing and classifying scoliosis. Manual measurements, while reliable, are time-consuming and prone to human error. Automated methods, particularly those enhanced by machine learning algorithms, offer promising accuracy and efficiency. The integration of image processing techniques further enhances the reliability of scoliosis evaluation. Conclusion Accurate assessment of scoliosis through Cobb angle measurement is crucial for effective diagnosis and treatment planning. The study demonstrates that combining manual techniques with advanced automated methods and image processing significantly improves measurement accuracy. Such an approach is intended to support better clinical outcomes. Future research should focus on refining these technologies for broader clinical applications.

Prevalence of scoliosis in children and adolescents: a systematic review and meta-analysis.

The understanding of the prevalence and early predictive factors of scoliosis in children and adolescents is limited, which poses challenges to developing preventative strategies. This systematic review and meta-analysis aimed to clarify the prevalence and predictors of scoliosis among children and adolescents. We conducted a comprehensive search in PubMed, Cochrane, Embase, and Web of Science through October 2023. The quality of included studies was evaluated using the Joanna Briggs Institute scale or the Newcastle-Ottawa Scale. Subgroup analyses were performed to examine different types of scoliosis and specific demographic groups. From 32 studies encompassing 55,635,351 children and adolescents, we identified 284,114 cases of scoliosis, resulting in a prevalence rate of 3.1% (95% CI: 1.5%-5.2%). This rate varied by gender, degrees of scoliosis severity, and between idiopathic vs. congenital forms. Notable predictors included gender, age, Body Mass Index (BMI), race, environmental factors, and lifestyle choices. Scoliosis is a significant condition affecting a minority of children and adolescents, particularly adolescent girls and individuals who are overweight. It is recommended that guardians and schools enhance educational efforts towards its prevention. https://www.crd.york.ac.uk/, Identifier CRD42023476498.

Assessing the Accuracy of Artificial Intelligence Models in Scoliosis Classification and Suggested Therapeutic Approaches.

Background: Open-source artificial intelligence models (OSAIMs) are increasingly being applied in various fields, including IT and medicine, offering promising solutions for diagnostic and therapeutic interventions. In response to the growing interest in AI for clinical diagnostics, we evaluated several OSAIMs-such as ChatGPT 4, Microsoft Copilot, Gemini, PopAi, You Chat, Claude, and the specialized PMC-LLaMA 13B-assessing their abilities to classify scoliosis severity and recommend treatments based on radiological descriptions from AP radiographs. Methods: Our study employed a two-stage methodology, where descriptions of single-curve scoliosis were analyzed by AI models following their evaluation by two independent neurosurgeons. Statistical analysis involved the Shapiro-Wilk test for normality, with non-normal distributions described using medians and interquartile ranges. Inter-rater reliability was assessed using Fleiss' kappa, and performance metrics, like accuracy, sensitivity, specificity, and F1 scores, were used to evaluate the AI systems' classification accuracy. Results: The analysis indicated that although some AI systems, like ChatGPT 4, Copilot, and PopAi, accurately reflected the recommended Cobb angle ranges for disease severity and treatment, others, such as Gemini and Claude, required further calibration. Particularly, PMC-LLaMA 13B expanded the classification range for moderate scoliosis, potentially influencing clinical decisions and delaying interventions. Conclusions: These findings highlight the need for the continuous refinement of AI models to enhance their clinical applicability.

Relationship between inflammatory laboratory parameters and severity of adolescent idiopathic scoliosis: A pilot study.

Adolescent idiopathic scoliosis is a complex condition whose pathogenesis may include inflammation and signs of joint and bone degeneration. The main objective of this study is to evaluate the relationship between the severity of adolescent idiopathic scoliosis and inflammatory blood parameters. The study recruited patients with adolescent idiopathic scoliosis who attended the Rehabilitation Center of the Apostolo Foundation in Merate (LC). The scoliosis curve (Cobb's angle) was used as a severity index to compare with inflammatory blood parameters (white blood cells subpopulations, immunoglobulins, protein electrophoresis). In addition, the study used an overall severity grading called "Scoliosis Score" which includes all spine angles and Risser's score (bone development index). Thirty-four subjects were recruited (mean age 14years, 2months), 30females and 2males. A significant correlation was found between Cobb's angle and the percentage values of beta-2 globulins in a directly proportional manner (r= 0.42, p= 0.01), and gamma globulins in an inversely proportional manner (r=-0.366, p= 0.04). However, no significant correlation between Cobb's angle and the absolute values of white blood cells and percentage subpopulations was found (r= 0.0821 p= 0.655). A moderate, inverse correlation was found between the Scoliosis Score and the percentage of neutrophils (r=-0.385, p= 0.02), a direct correlation was found between the Scoliosis Score and the percentage of lymphocytes (r= 0.404, p= 0.02). In addition, there was a strong correlation of the Scoliosis Score with alpha-2 globulin (r= 0.564, p= 0.0012), beta-1 globulin (r= 0.478, p= 0.0074), and beta-2 globulin (r= 0.370, p= 0.044) and an inverse relationship with gamma globulin (r=-0.625, p= 0.0002). The main correlations were confirmed by regression analysis. The correlation between beta-2 globulins and gamma globulins with Cobb's angle and the Scoliosis Score suggests a link between spinal curvature and inflammation in scoliosis patients, This link may indicate the significance of these parameters for diagnosing, staging the disease, and monitoring therapies.

Unraveling the Link of Altered TGFβ Signaling with Scoliotic Vertebral Malformations in Osteogenesis Imperfecta: A Comprehensive Review.

Osteogenesis Imperfecta (OI) is a genetic disorder caused by mutations in genes responsible for collagen synthesis or polypeptides involved in the formation of collagen fibers. Its predominant skeletal complication is scoliosis, impacting 25 to 80% of OI patients. Vertebral deformities of the scoliotic curves in OI include a variety of malformations such as codfish, wedged-shaped vertebrae or platyspondyly, craniocervical junction abnormalities, and lumbosacral spondylolysis and spondylolisthesis. Although the precise pathophysiology of these spinal deformities remains unclear, anomalies in bone metabolism have been implicated in the progression of scoliotic curves. Bone Mineral Density (BMD) measurements have demonstrated a significant reduction in the Z-score, indicating osteoporosis and a correlation with the advancement of scoliosis. Factors such as increased mechanical strains, joint hypermobility, lower leg length discrepancy, pelvic obliquity, spinal ligament hypermobility, or vertebrae microfractures may also contribute to the severity of scoliosis. Histological vertebral analysis has confirmed that changes in trabecular microarchitecture, associated with inadequate bone turnover, indicate generalized bone metabolic defects in OI. At the molecular level, the upregulation of Transforming Growth factor-β (TGFβ) signaling in OI can lead to disturbed bone turnover and changes in muscle mass and strength. Understanding the relationship between spinal clinical features and molecular pathways could unveil TGFβ -related molecular targets, paving the way for novel therapeutic approaches in OI.

Impact of Wheelchair Seating Systems on Scoliosis Progression for Children With Neurologic and Neuromuscular Disorders: A Retrospective Study of Custom-Contoured Wheelchair Seating and Modular Wheelchair Seating

ObjectivesTo retrospectively evaluate the comparative effect of 2 wheelchair seating systems, Custom-Contoured Wheelchair Seating (CCS) and Modular Wheelchair Seating (MWS), on scoliosis progression in children with neuromuscular and neurologic disorders and to determine any predictors for scoliosis progression. DesignLongitudinal, retrospective cohort study. SettingA national health service regional posture and mobility service. ParticipantsNonambulant pediatric wheelchair users with neuromuscular and neurologic disorders (N=75; 36 men, 39 women; mean age at seating intervention, 10.50±3.97y) issued CCS and MWS by the South Wales Posture and Mobility Service from 2012-2022. InterventionsTwo specialized wheelchair seating systems, CCS and MWS. Main Outcome MeasuresA generalized least squares model was used to estimate the effect of seat type on Cobb angle over time. ResultsOf the 75 participants enrolled, 51% had cerebral palsy. Fifty were issued CCS and 25 were issued MWS. Baseline Cobb angle was 32.9±18.9° for the MWS group and 48.0±31.0° for the CCS group. The generalized least squares model demonstrated that time since seating intervention (χ2=122, P<.0001), seating type (χ2=52.5, P<.0001), and baseline scoliosis severity (χ2=41.6, P<.0001) were predictive of scoliosis progression. Condition was not a strong predictor (χ2=9.96, P =.0069), and sex (χ2=5.67, P=.13) and age at intervention (χ2=4.47, P=.35) were not predictive. Estimated contrasts of medical condition with seat type over time demonstrated smaller differences between MWS and CCS over time. Predicted scoliosis velocity was found to attenuate with use of CCS over time compared with MWS, although scoliosis deteriorated regardless of intervention. ConclusionsOur findings showed pediatric wheelchair users with neurologic and neuromuscular disorders prescribed CCS showed greater mitigation of scoliosis progression over time compared with those issued MWS.

Quantitative analysis of paravertebral muscle asymmetry and its correlation with spinal deformity in patients with degenerative lumbar scoliosis: a retrospective case-control study.

The degeneration and functional decline of paravertebral muscles (PVMs) are reported to be closely linked to the incidence of degenerative lumbar scoliosis (DLS), a spinal deformity of the mature skeleton. However, the functional role and degeneration of PVMs and their relationship to the development of spinal deformities remain controversial. Therefore, the present study analyzed the morphological changes in the PVMs of patients with DLS, and explored the relationship between PVM degeneration and spinal osseous parameters. In this retrospective case-control study, we evaluated the PVM parameters of patients with DLS (n=120) and compared them with patients free of DLS (control group, n=120). The cross-sectional area (CSA) and computed tomography (CT) values of the PVM at the lumbar vertebra 1-5 levels were measured. Further, the lumbar scoliosis Cobb, lumbar lordotic, and apical vertebral rotation angles were measured on CT and radiographs in the DLS group, and the relationship between PVM changes and these factors was analyzed. In the control group, the PVM CSA and CT values differed insignificantly between the bilateral sides at all levels (P>0.05). In the DLS group, the CSAs of the multifidus (MF) and erector spinae (ES) were larger on the convex side than the concave side (P>0.05), whereas that of the psoas major (PM) was smaller on the convex side than the concave side (P<0.05). The CT value of the PVM was lower on the convex side at all levels (P<0.05). The CSA and CT values on both sides of the patients were lower in the DLS group than the control group at all levels (P<0.05). Further, the degree of PVM asymmetry at the apical vertebral level was positively correlated with the lumbar scoliosis (P<0.01) and apical vertebral rotation angles (P<0.05), but negatively correlated with the lumbar lordotic angle (P<0.05). Asymmetric degeneration of the PVM was observed bilaterally in DLS patients, and the degeneration was more pronounced on the concave side than the convex side. This asymmetrical degeneration was closely associated with the severity of lumbar scoliosis, vertebral rotation, and loss of lumbar lordosis, and a stronger correlation was observed with the MF and ES than with the PM.

Using Photogrammetry to Analyze Anatomical Changes in the Nipple in Juvenile and Adolescent Scoliosis Patients

BackgroundThe need for an objective set of anterior trunk measurements, such as nipple and clavicular shoulder joints, is essential to quantify the anterior asymmetry present in scoliosis. This study aims to characterize breast asymmetry (BA) in young individuals with scoliosis using photogrammetry.MethodsDigital photographs of the anterior trunk of the 51 scoliosis patients aged 4–20 years were taken from an anterior perspective. These images were then transferred to a computer. Ten parameters were measured using the ImageJ software. The positions of patients’ nipples were classified into 6 types based on ratios on the x-axis.ResultsThe majority of patients had a right breast that was larger, intensifying the apparent BA due to trunk rotation. The apical vertebra level in patients was found at T8 in 23.6% and T9 in 45.1%. In 92.5% of the patients, the right breast was consistently larger. The lengths between the lateral boundaries and nipples of the right and left breasts and between the medial boundary and nipple of the right breast were statistically significantly higher in males than in females (p < 0.05). Significant differences were found when comparing the values of the lengths between the medial boundaries and nipples of the right and left breasts, the difference in length between the right and left acromioclavicular joint lines, and the angles of the nipple and acromioclavicular joint with the degrees of scoliosis in juvenile and adolescents (p < 0.05). Pearson regression analysis revealed a significant correlation between BA differences and the Cobb angle with a correlation coefficient of 0.901. Factors related to breast aesthetics, like differences in the height of nipples and the distance from the sternal notch to the nipple, represent 30% of the overall score.ConclusionThe study concluded that there is a significant correlation between the severity of scoliosis and BA differences. Augmentation mammaplasty for BA not only decreased the breast difference but also leveled the nipple disparities. Photogrammetry is considered to be an alternative to other methods and is believed to contribute to the follow-up of BA.Level of Evidence IVThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

Application of System Nursing in the Prevention of Postoperative Nonstructural Scoliosis in Patients With Ear Reconstruction.

To evaluate whether early systematic nursing can reduce the occurrence of postoperative nonstructural scoliosis in patients undergoing ear reconstruction. A total of 136 patients with congenital microtia who underwent ear reconstruction surgery at the Department of Plastic Surgery, Chinese Academy of Medical Sciences from, January 2022 to July 2022 were included as study subjects. They were randomly divided into a routine nursing group and a systematic nursing group. After preoperative and postoperative education, as well as continuous follow-up intervention after surgery, spinal CT three-dimensional imaging examination was performed 6 months later to measure the Cobb angle and observe the occurrence of spinal scoliosis. Compared with the routine nursing group, the incidence and severity of postoperative nonstructural scoliosis were significantly reduced in patients who received systematic nursing. Systematic nursing intervention for patients undergoing ear reconstruction can help prevent the occurrence of postoperative nonstructural scoliosis and has a positive effect on improving patient prognosis. It is worth promoting in clinical treatment.

Correlative Assessment of Machine Learning-Based Cobb Angle Measurements and Human-Based Measurements in Adolescent Idiopathic and Congenital Scoliosis.

Purpose: Scoliosis is a complex spine deformity with direct functional and cosmetic impacts on the individual. The reference standard for assessing scoliosis severity is the Cobb angle which is measured on radiographs by human specialists, carrying interobserver variability and inaccuracy of measurements. These limitations may result in lack of timely referral for management at a time the scoliotic deformity progression can be saved from surgery. We aimed to create a machine learning (ML) model for automatic calculation of Cobb angles on 3-foot standing spine radiographs of children and adolescents with clinical suspicion of scoliosis across 2 clinical scenarios (idiopathic, group 1 and congenital scoliosis, group 2). Methods: We retrospectively measured Cobb angles of 130 patients who had a 3-foot spine radiograph for scoliosis within a 10-year period for either idiopathic or congenital anomaly scoliosis. Cobb angles were measured both manually by radiologists and by an ML pipeline (segmentation-based approach-Augmented U-Net model with non-square kernels). Results: Our Augmented U-Net architecture achieved a Symmetric Mean Absolute Percentage Error (SMAPE) of 11.82% amongst a combined idiopathic and congenital scoliosis cohort. When stratifying for idiopathic and congenital scoliosis individually a SMAPE of 13.02% and 11.90% were achieved, respectively. Conclusion: The ML model used in this study is promising at providing automated Cobb angle measurement in both idiopathic scoliosis and congenital scoliosis. Nevertheless, larger studies are needed in the future to confirm the results of this study prior to translation of this ML algorithm into clinical practice.

Treatment of Symptomatic Spinal Muscular Atrophy with Nusinersen: A Prospective Longitudinal Study on Scoliosis Progression.

Nusinersen treatment has demonstrated efficacy in improving clinical outcomes for spinal muscular atrophy (SMA), yet its impact on scoliosis progression remains unclear. This study aimed to assess the progression of scoliosis in pediatric patients with SMA undergoing nusinersen treatment. In this prospective study, data were systematically collected from Hong Kong pediatric SMA patients receiving nusinersen between 2018 and 2023. All patients had longitudinal radiographic studies pre-nusinersen, and at half-yearly or yearly intervals during treatment based on the scoliosis severity. Motor function evaluations were conducted pre-nusinersen, and after starting treatment at 6- and 12-month intervals. Twenty-three patients ((SMA type 1 (SMA1) = 8, SMA type 2 (SMA2) = 7, SMA type 3 (SMA3) = 8)) with a median age of 5.8 years (range: 0.4-17.5 years) at nusinersen initiation, and median follow-up duration of 3.4 years (range: 1.1-5.2 years) were included. During the study period, motor scores remained stable or improved in 83% of patients. However, scoliosis progressed across all subtypes, with mean annual progression rates of 5.2, 11.9, and 3.6 degrees in SMA1, SMA2, and SMA3 respectively. Patients initiating nusinersen between ages 5 and 11 years exhibited the most rapid progression, with rates of 11.8, 16.5, and 7.3 degrees per year in SMA1, SMA2, and SMA3 respectively. Positive correlations were observed between the difference in CHOP-INTEND score post-nusinersen and scoliosis progression in SMA1 (rs = 0.741, p = 0.041). Conversely, negative correlations were found between the difference in HFMSE score post-nusinersen and scoliosis progression in SMA2 (rs =-0.890, p = 0.012) and SMA3 (rs =-0.777, p = 0.028). This study reveals that nusinersen treatment in symptomatic pediatric SMA patients with motor improvement is linked to increased scoliosis progression in SMA1, whereas it is associated with decreased progression in SMA2 and SMA3. Age, baseline Cobb angle, and motor milestone improvement are influential factors in scoliosis progression.

The Pathophysiology of Scoliosis Across the Spectrum of Human Physiological Systems

Scoliosis is a medical condition characterized by an abnormal lateral curvature of the spine. It can lead to various health issues, affecting mobility, respiratory function, and overall quality of life. There are several types of scoliosis, including idiopathic, congenital, neuromuscular, degenerative, and functional. The severity of scoliosis is measured by the degree of spinal curvature, typically expressed in degrees through a system known as the Cobb angle. Early detection and intervention are fundamental in managing scoliosis, as more severe forms may necessitate bracing or surgical intervention. Healthcare professionals must understand the different types of scoliosis and their unique characteristics to tailor appropriate treatment plans.Scoliosis can significantly impact various physiological systems, including the circulatory, digestive, endocrine, integumentary, lymphatic, muscular, nervous, and respiratory systems. In the circulatory system, scoliosis can cause hemodynamic changes, impaired venous return, cardiac strain, and pulmonary complications. In the digestive system, scoliosis can lead to gastric displacement, impaired intra-abdominal pressure, gastroesophageal reflux, and nutritional implications. The endocrine system can be affected by scoliosis, leading to neuroendocrine dysregulation, growth hormone abnormalities, cortisol dysregulation, and impact on thyroid function. Scoliosis can also affect the integumentary system, leading to pressure ulcers, altered skin sensation, and hygiene challenges. In the lymphatic system, scoliosis can cause lymphatic obstruction, impaired immune response, altered inflammatory responses, fibrosis, and secondary lymphedema. Scoliosis can affect the muscular system, leading to muscle imbalance, myofascial pain, respiratory muscle weakness, and mobility issues. The nervous system can also be impacted by scoliosis, leading to neural compression, central nervous system impact, neurological dysfunction, and coordination challenges. In the respiratory system, scoliosis can cause thoracic deformities, reduced lung compliance, ventilation-perfusion mismatch, respiratory muscle weakness, increased work of breathing (WOB), and an increased risk of respiratory infections.Recognizing and addressing the interplay between scoliosis and these physiological systems is integral for healthcare professionals to provide comprehensive care to individuals with scoliosis.Current research on scoliosis has made progress in diagnostic tools and techniques, including the use of imaging methods like MRI and X-ray, wearable sensors, and 3D reconstruction techniques for better evaluation of spinal motion and function, along with treatment strategies like Schroth exercises and braces, and management measures for respiratory and circulatory problems. However, there are limitations to current studies, such as the heterogeneity of scoliosis, compartmentalized approaches, limited longitudinal studies, reliance on retrospective data, and the need for standardized measures and diagnostic criteria. Future research prospects include advancements in genetic research, biomechanics, artificial intelligence and machine learning, longitudinal studies, non-invasive treatments, and multidisciplinary collaborations among researchers, clinicians, and technologists.