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OBJECTIVE: The goal of this study is to discuss the transitional nature of idiopathic scoliosis and the variation in treatment and management across the spectrum of age presentation. METHODS: This is a review article that discusses the evaluation, management, and classification of idiopathic scoliosis. The authors searched PubMed/MEDLINE, Google Scholar, and the Cochrane database for articles published up to April 2024. Keywords and MeSH terms relevant to the topic were used, including adolescent idiopathic scoliosis (AIS), adult idiopathic scoliosis (AdIS), adult degenerative scoliosis, young adult idiopathic scoliosis, early-onset scoliosis (EOS), classification, management, follow-up, outcomes, natural history, Cobb angle, and transitional care. Reference lists of selected articles were also searched to identify further articles. Inclusion criteria included English language articles that summarized any type of study design, including randomized controlled trials, observational studies, case-control/series, or metaanalysis, with study populations ranging from infants to > 50-year-old patients. Inter-reviewer disagreement on inclusion of particular articles was resolved through discussion. Related information was analyzed, and relevant concepts related to the transitional period dilemma have been discussed. RESULTS: Each idiopathic scoliosis case needs independent assessment with regard to the age, degree of the curve, and patient-specific presentation. An accurate prediction of the curve progression by considering the patient's remaining growth potential is paramount to the treatment strategy. The classification system for EOS, AIS Lenke classification, AdIS classification, and the Scoliosis Research Society-Schwab classification are important for reliable communication between surgeons treating deformities. Untreated progressive idiopathic scoliosis warrants multidisciplinary management during the transition from EOS stage to AIS and then to AdIS. Also, surgical treatment of untreated AIS transitioning to AdIS is specific and nuanced. AdIS needs to be differentiated from adult degenerative scoliosis because the latter is associated with multiple comorbidities and anatomical differences. CONCLUSIONS: Idiopathic scoliosis presents across the age spectrum with specific age-related decisions that transition into adulthood. Integrated models of both surgical and nonsurgical treatment of idiopathic scoliosis are warranted.
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Escoliose , Humanos , Escoliose/terapia , Escoliose/cirurgia , Adolescente , Adulto , Cuidado Transicional , Adulto JovemRESUMO
STUDY DESIGN: Cross-sectional study. OBJECTIVES: Imaging classification of adolescent idiopathic scoliosis (AIS) is directly related to the surgical strategy, but the artificial classification is complex and depends on doctors' experience. This study investigated deep learning-based automated classification methods (DL group) for AIS and validated the consistency of machine classification and manual classification (M group). METHODS: A total of 506 cases (81 males and 425 females) and 1812 AIS full spine images in the anteroposterior (AP), lateral (LAT), left bending (LB) and right bending (RB) positions were retrospectively used for training. The mean age was 13.6 ± 1.8. The mean maximum Cobb angle was 46.8 ± 12.0. U-Net semantic segmentation neural network technology and deep learning methods were used to automatically segment and establish the alignment relationship between multiple views of the spine, and to extract spinal features such as the Cobb angle. The type of each test case was automatically calculated according to Lenke's rule. An additional 107 cases of adolescent idiopathic scoliosis imaging were prospectively used for testing. The consistency of the DL group and M group was compared. RESULTS: Automatic vertebral body segmentation and recognition, multi-view alignment of the spine and automatic Cobb angle measurement were implemented. Compare to the M group, the consistency of the DL group was significantly higher in 3 aspects: type of lateral convexity (0.989 vs 0.566), lumbar curvature modifier (0.932 vs 0.738), and sagittal plane modifier (0.987 vs 0.522). CONCLUSIONS: Deep learning enables automated Cobb angle measurement and automated Lenke classification of idiopathic scoliosis whole spine radiographs with higher consistency than manual measurement classification.
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OBJECTIVE: This systematic review and meta-analysis of randomized controlled trials (RCTs) and retrospective controlled studies (RCSs) aims to evaluate the efficacy and safety of high-dose tranexamic acid (TXA) in spinal correction surgery for adolescent idiopathic scoliosis (AIS) patients. METHODS: In March 2024, a comprehensive search was conducted in PubMed, Web of Science, Embase, and Cochrane databases to identify RCTs and RCSs comparing the effects of high-dose TXA on blood loss and transfusion requirements during spinal correction surgery. RESULTS: This meta-analysis included 10 clinical trials encompassing a total of 741 patients. The pooled results indicated that the use of high-dose TXA significantly reduced intraoperative blood loss [WMD = -519.83, 95% CI (-724.74, -314.92), P < 0.00001], transfusion rate [RR = 0.28, 95% CI (0.17, 0.45), P < 0.00001], total blood loss [WMD = -891.09, 95% CI (-1623.92, -158.26), P = 0.02], and postoperative blood loss [WMD = -105.91, 95% CI (-141.29, -70.52), P < 0.00001]. There was no significant difference in operative time [WMD = -18.96, 95% CI (-40.20, 2.28), P = 0.08] and blood loss per segment [WMD = -50.51, 95% CI (-102.19, 1.17), P = 0.06]. Both groups had a comparable incidence of thromboembolic events. CONCLUSION: Our meta-analysis suggests that the use of high-dose TXA reduces intraoperative blood loss, transfusion rate, total blood loss, and postoperative blood loss in spinal correction surgery for AIS patients. However, there were no significant differences in operative time and blood loss per segment.
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Spinal deformities, including adolescent idiopathic scoliosis (AIS) and adult spinal deformity (ASD), affect many patients. The measurement of the Cobb angle on coronal radiographs is essential for their diagnosis and treatment planning. To enhance the precision of Cobb angle measurements for both AIS and ASD, we developed three distinct artificial intelligence (AI) algorithms: AIS/ASD-trained AI (trained with both AIS and ASD cases); AIS-trained AI (trained solely on AIS cases); ASD-trained AI (trained solely on ASD cases). We used 1612 whole-spine radiographs, including 1029 AIS and 583 ASD cases with variable postures, as teaching data. We measured the major and two minor curves. To assess the accuracy, we used 285 radiographs (159 AIS and 126 ASD) as a test set and calculated the mean absolute error (MAE) and intraclass correlation coefficient (ICC) between each AI algorithm and the average of manual measurements by four spine experts. The AIS/ASD-trained AI showed the highest accuracy among the three AI algorithms. This result suggested that learning across multiple diseases rather than disease-specific training may be an efficient AI learning method. The presented AI algorithm has the potential to reduce errors in Cobb angle measurements and improve the quality of clinical practice.
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Algoritmos , Inteligência Artificial , Escoliose , Humanos , Escoliose/diagnóstico por imagem , Adolescente , Feminino , Masculino , Adulto , Coluna Vertebral/diagnóstico por imagem , Criança , Radiografia/métodos , Adulto JovemRESUMO
PURPOSE: We defined sagittal S-line tilt (SSLT) as the tilt of the line connecting the upper instrumented vertebra and the lower instrumented vertebra. This study aimed to: (1) examine the correlation between SSLT and proximal junctional angle (PJA) change values, and (2) determine the cut-off value of SSLT with respect to proximal junctional kyphosis (PJK) occurrence. METHODS: Eighty-six consecutive patients (81 female and 5 male; mean age: 15.8 years) with Lenke 5C AIS who underwent posterior selective spinal fusion. Pearson's correlation coefficients were used to examine the relationship between preoperative SSLT and changes in PJA from preoperative to 2 years postoperative. The impact of SSLT on PJK at 2 years after surgery was assessed using a receiver operating characteristic (ROC) curve. RESULTS: We observed a moderate positive correlation between preoperative SSLT and change in PJA (R = 0.541, P < 0.001). We identified 18 patients (21%) with PJK at 2 years postoperative. Mean preoperative SSLT in the PJK group and the non-PJK group differed significantly at 23.3 ± 4.1° and 16.1 ± 5.0°, respectively (P < 0.001). The cut-off value of preoperative SSLT for PJK at 2 years postoperative was 18° in ROC curve analysis, with a sensitivity of 94%, specificity of 68%, and area under the ROC curve of 0.868. CONCLUSION: In selective lumbar fusion for AIS Lenke type 5C curves, preoperative SSLT was significantly correlated with PJA change from preoperative to 2 years postoperative. SSLT was a predictor of PJK occurrence, with a cut-off value of 18°.
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This study aimed to elucidate the vertebral bone density variations associated with adolescent idiopathic scoliosis (AIS), specifically examining the impact of unilateral muscle paralysis using an integrated approach combining Frost's Mechanostat theory, a three-dimensional subject-specific finite element model and a musculoskeletal model of the L2 vertebra. The findings revealed a spectrum of bone density values ranging from 0.29 to 0.31 g/cm3, along with vertebral micro-strain levels spanning from 300 to 2200, consistent with existing literature. Furthermore, the ratio of maximum von Mises stress between the concave and convex side in the AIS model with intact muscles was approximately 1.08, which decreased by 4% due following unilateral paralysis of longissimus thoracis pars thoracic muscle. Overall, this investigation contributes to a deeper understanding of AIS biomechanics and lays the groundwork for future research endeavors aimed at optimizing clinical management approaches for individuals with this condition.
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Adolescent idiopathic scoliosis is the most common form of scoliosis, with severe cases leading to a decline in patients with worsening angulation of deformity. Technical nuances of spinal flexibility and cord type based on the extent of the deformity may impact operating safety and outcome, with risks including neurological loss during and after surgical intervention. Here we present a case of posterior osteotomy and correction of a patient with adolescent idiopathic scoliosis with a T2 - L3 fusion in which transcranial motor evoked potentials (TcMEPs) and somatosensory evoked potentials (SSEPs) were lost intraoperatively, thus requiring application of operative consensus guidelines for the loss of neuromonitoring data. Particularly, the discussion focuses on the decision-making process that resulted in the complete recovery of TcMEPs and SSEPs post-operatively.
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PURPOSE: The purpose of this study is to compare postoperative outcomes between selective and non-selective fusions longitudinally over the first five postoperative years. METHODS: Patient parameters were retrieved from a multicenter, prospective, database. Patients with Lenke 1-6, B and C deformities were included. Patients were stratified into 2 groups: selective fusion (SF), if the last instrumented vertebra (LIV) was at or cranial to the lumbar apex, or non-selective fusion (NSF). Differences in coronal and sagittal radiographic outcomes were assessed with generalized linear models (GLMs) at 1-, 2- and 5- year postoperative outcomes. Five-year postoperative categorical radiographic outcomes, flexibility, scoliosis research society scores (SRS), and reoperation rates were compared between groups. Matched cohorts were created for subgroup analysis. RESULTS: 416 (SF:261, NF:155) patients, including 353 females were included in this study. The mean preoperative thoracic and lumbar Cobb angles were 57.3 ± 8.9 and 45.3 ± 8.0, respectively. GLMs demonstrated greater postoperative coronal deformity in the SF group (p < 0.01); however, the difference between groups did not change overtime (p > 0.05) indicating a relatively stable postoperative deformity correction. The SF group had a greater incidence of lumbar Cobb ≥ 26 degrees (p < 0.01). The NSF group demonstrated worse forward and lateral flexibility at 5-year postoperative outcome (p < 0.05). There was no difference in postoperative SRS scores between the SF and NSF groups. Reoperation rates were similar between groups. CONCLUSION: Selective fusion results in greater coronal plane deformity; however, this deformity does not progress significantly over time compared to non-selective fusion. Selective spinal fusion may be a beneficial option for a larger subset of patients than previously identified. LEVEL OF EVIDENCE: III.
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Predicting curve progression during the initial visit is pivotal in the disease management of patients with adolescent idiopathic scoliosis (AIS)-identifying patients at high risk of progression is essential for timely and proactive interventions. Both radiological and clinical factors have been investigated as predictors of curve progression. With the evolution of machine learning technologies, the integration of multidimensional information now enables precise predictions of curve progression. This review focuses on the application of machine learning methods to predict AIS curve progression, analyzing 15 selected studies that utilize various machine learning models and the risk factors employed for predictions. Key findings indicate that machine learning models can provide higher precision in predictions compared to traditional methods, and their implementation could lead to more personalized patient management. However, due to the model interpretability and data complexity, more comprehensive and multi-center studies are needed to transition from research to clinical practice.
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Progressão da Doença , Aprendizado de Máquina , Escoliose , Escoliose/diagnóstico por imagem , Humanos , AdolescenteRESUMO
Background: The Cobb angle is critical in assessing adolescent idiopathic scoliosis (AIS) patients. This study aimed to evaluate the error in selecting the upper- and lower-end vertebrae on AIS digital X-rays by experienced and novice observers and its correlation with the error in measuring the Cobb angle and determining the length of the scoliotic curves. Methods: Using the TraumaMeter v.873 software, eight raters independently evaluated 68 scoliotic curves. Results: The error percentage in the upper-end vertebra selection was higher than for the lower-end vertebra (44.7%, CI95% 41.05-48.3 compared to 35%, CI95% 29.7-40.4). The mean bias error (MBE) was 0.45 (CI95% 0.38-0.52) for the upper-end vertebra and 0.35 (CI% 0.69-0.91) for the lower-end vertebra. The percentage of errors in the choice of the end vertebrae was lower for the experienced than for the novices. There was a positive correlation (r = 0.673, p = 0.000) between the error in selecting the end vertebrae and determining the length of the scoliotic curves. Conclusions: We can conclude that errors in selecting end vertebrae are common among experienced and novice observers, with a greater error frequency for the upper-end vertebrae. Contrary to the consensus, the accuracy of determining the length of the scoliotic curve is limited by the Cobb method's reliance on the correct selection of the end vertebrae.
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PURPOSE: To investigate the incidence, risk factors, and clinical impact of persistent coronal imbalance (PCI) in Lenke5C adolescent idiopathic scoliosis (AIS) undergoing posterior spinal fusion (PSF). METHODS: We analyzed the medical records of 112 Lenke5C AIS patients. They were grouped into PCI (+) group and PCI (-) group according to the occurrence of PCI at 2 years after surgery. Coronal and sagittal parameters were measured and compared between both groups preoperatively, immediately postoperatively, and 2 years postoperatively. Scoliosis Research Societyâ22 (SRSâ22) score was used to evaluate clinical outcomes. RESULTS: Of the 112 patients, 12 had coronal imbalance persisting 2 years after surgery. Logistic regression analysis indicated risk factors including older age [odds ratio(OR)= 1.841, 95% confidence interval (CI) 1.147-2.132, P = 0.001], lower preoperative flexibility main thoracic (MT) curve (OR = 1.308,95% CI: 1.041-2.015, P = 0.016), greater preoperative apical vertebral translation (AVT) of the thoracolumbar/lumbar (TL/L) curve (AVT-TL/L) (OR= 2.291, 95%CI: 1.120-4.719, P = 0.001), larger preoperative lowest instrumented vertebra tilt (LIV lilt) (OR = 2.141, 95% CI: 1.491-3.651, P = 0.011), postoperative immediate coronal imbalance (OR = 5.512, 95% CI: 4.531-6.891, P = 0.001). The satisfaction and total score of SRS-22 scale in PCI (+) group were lower than those in PCI (-) group at 2 years after surgery (P < 0.05). CONCLUSIONS: We found a 10.7% incidence of PCI in patients with Lenke5C AIS undergoing PSF. PCI adversely affects clinical outcomes. Risk factors of PCI included older age, reduced preoperative MT curve flexibility, increased preoperative AVT in the TL/L curve, greater preoperative LIV tilt, and immediate postoperative coronal imbalance.
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BACKGROUND CONTEXT: Pulmonary function in patients with scoliosis has been a topic of concern, with some reports of markedly decreased ventilatory function leading to disability and increased mortality in patients with severe scoliosis. Only limited data is available concerning pulmonary function in adult patients with scoliosis. PURPOSE: To report the long-term pulmonary function (PF) in patients diagnosed with idiopathic scoliosis (IS) compared with an age-matched population using extended pulmonary function testing (EPFT). STUDY DESIGN/SETTING: Retrospective clinical follow-up. PATIENT SAMPLE: A total of 177 patients seen at our institution from 1972 to 1983 for a pediatric spinal deformity were assessed for inclusion in the study. About 77/129 eligible patients with IS (60%) partook in a clinical examination including radiographs, and EPFT. OUTCOME MEASURES: The EPFT values included forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEV1/FVC ratio, vital capacity (VC), total lung capacity (TLC), residual volume (RV), RV/TLC ratio, diffusion capacity of carbon monoxide (DLco), carbon monoxide transfer coefficient (KCO) and alveolar volume (VA). Results were expressed with z-scores derived from height and arm span normative data. Z-scores were calculated as z-score=Measured PF-Predicted PF /Relative standard deviation (RSD). The limits of normal, are defined as the 5th and 95th percentile limits (z-score between -1.645 and 1.645), respectively. METHODS: Patients underwent a clinical examination with full spine standing radiographs and EFPT. The results were compared between patients with thoracic and thoracolumbar/lumbar (TL/L) main curves, and overall compared with a background population. Results were expressed with z-scores derived from height and arm span normative data. RESULTS: Of 77 included patients, 76 (99%) were females with a mean age of 54.6±2.5 years. The mean follow-up time was 40.8±2.8 years. Forty-four patients had thoracic main curves, and 33 had TL/L main curves. We found no pulmonary impairment based on z-scores in the total cohort or between groups, with only patients who were current or previous smokers, having z-scores below the normal limits Patients with main thoracic curves displayed significantly lower PF on mean absolute values and mean z-scores on FEV1, FVC, FEV1/FVC ratio, VC, TLC, and DLco compared with main TL/L curves. Patients with thoracic curves had significantly larger Cobb angles at follow-up; 52±17° compared with 40±22° (p-value <.05) in the TL/L group. We found no linear association between thoracic Cobb angle and degree of pulmonary impairment assessed with DLco, TLC, and FVC. Comparison of pulmonary z-scores based on arm span data, differed significantly on FVC and TLC, with the arm span measurements showing lower mean z-scores (p-value <.05). CONCLUSIONS: Using EPFT, no pulmonary impairment could be demonstrated compared to the age-matched population 40 years after a diagnosis of IS. However, patients with thoracic curves had decreased PF compared to patients with TL/L curves although within the normal range. Thus, when treated as current guidelines suggest, patients with idiopathic scoliosis can expect the same long-term pulmonary function as the general population.
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AIM: The aim of this study was to evaluate the effects of spinal mobilisation on curvature magnitude, angle of trunk rotation (ATR) and pulmonary function in adolescents with idiopathic scoliosis (AIS). METHODS: Conducted as a double-blind randomised controlled trial, the study included 40 patients with AIS (Cobb angles 10°-25°) randomised to experimental (n = 20; female = 12, male = 8; age = 12.9 ± 1.8 mean ± SD) and control (n = 20; female = 13, male = 7; age = 12.85 ± 1.81 mean ± SD) groups. The experimental group received spinal mobilisation for 30 min per session followed by 60 min of core stabilisation exercises (CSE), twice a week for 10 weeks. The control group received CSE only at the same frequency and duration. Evaluation of Cobb angle, ATR and pulmonary function tests (PEF: Peak Expiratory Flow, FEV1: Forced Expiratory Volume in 1 s, FVC: Forced Vital Capacity, and FEV1/FVC: Tiffeneau index) were performed at baseline and after the intervention. RESULTS: Both groups showed significant improvements in Cobb angle, ATR, PEF and FVC, with the experimental group showing significantly greater improvements in Cobb angle (-7.65 ± 3.17) and ATR (-2.5 ± 1.43) compared to the control group (P < 0.05). In addition, while the control group showed no change in FEV1, the experimental group showed improvement. There was no change in FEV1/FVC ratio in either group. CONCLUSION: These results indicate that adding spinal mobilisation to treatment sessions can effectively reduce the magnitude of curvature and improve scoliosis-related problems in the short term.
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PURPOSE: Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with varying progression, complicating treatment decisions. Artificial intelligence (AI) and machine learning (ML) are increasingly prominent in orthopedic care, aiding in diagnosis, risk-stratification, and treatment guidance. This scoping review outlines AI applications in AIS. METHODS: This study followed PRISMA-ScR guidelines and included articles that reported the development, use, or validation of AI models for treating, diagnosing, or predicting clinical outcomes in AIS. RESULTS: 40 full-text articles were included, with most studies published in the last 5 years (77.5%). Common ML techniques were convolutional neural networks (55%), decision trees and random forests (15%), and artificial neural networks (15%). Most AI applications in AIS were for imaging analysis (25/40; 62.5%), focusing on automatic measurement of Cobb angle, and axial vertebral rotation (13/25; 52%) and curve classification/severity (13/25; 52%). Prediction was the second most common application (15/40; 37.5%), with studies predicting curve progression (9/15; 60%), and Cobb angles (9/15; 60%). Only 15 studies (37.5%) reported clinical implementation guidelines for AI in AIS management. 52.5% of studies reported model accuracy, with an average of 85.4%. CONCLUSION: This review highlights the applications of AI in AIS care, notably including automatic radiographic analysis, curve type classification, prediction of curve progression, and AIS diagnosis. However, the current lack of clear clinical implementation guidelines, model transparency, and external validation of studied models limits clinician trust and the generalizability and applicability of AI in AIS management.
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PURPOSE: To report the accuracy and reliability of Cobb angle (CA), axial vertebral rotation (AVR), kyphotic and lordotic angles (KA and LA) measurements on using a new 3D ultrasound (US) system. METHODS: Forty participants (34 F, 6 M, aged 14.0 ± 2.3 years) were recruited. The first 20 participants were scanned by the validated US system and the new US system. The other 20 participants were scanned with the new US system only. Two raters (R1 and R2) performed the measurements: R1 has 10 years of experience in radiology but is new in ultrasound scoliosis, while R2 has 30 years of scoliosis experience. All US images were measured twice by R1, and once by R2. Forty posteroanterior and 30 lateral standing radiographs were obtained and measured once by R1. Statistical analysis consisted of mean absolute difference (MAD), intraclass correlation coefficient (ICC (2,1)), and Bland-Altman plots. RESULTS: R1 showed excellent intra-rater and inter-rater reliability for US measurements with ICCs(2,1) ≥ 0.91. The inter-method reliability was good between the two US systems for all parameters with ICCs(2,1) ≥ 0.85 and maximum MAD of 3.4°. The new US showed good reliability and accuracy compared to radiographs for CA, AVR and KA with ICCs(2,1) ≥ 0.81 and maximum MAD of 5.8°, but poor results for LA with ICCs(2,1) of 0.27-0.35 and MADs of 14.0°-15.4°. CONCLUSION: The new 3D US system showed good reliability and accuracy for CA, AVR and KA measurements, but a large measurement discrepancy on LA. A new measurement method for US LA may need to investigate.
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PURPOSE: The management of adolescent idiopathic scoliosis (AIS) curves between 40 and 50° is controversial. Here, we investigated the prognostic significance of simple radiographic rotational parameters to identify curves of this magnitude with accelerated deterioration following skeletal maturity. METHODS: Seventy-three patients were identified with AIS and Cobb angles of the major curve between 40 and 50° at skeletal maturity. We defined fast progressive curves as those increasing by ≥ 2° per year after skeletal maturity. From the apical vertebra of the major curve upon presentation and skeletal maturity, we determined the modified Nash-Moe index (×100), and from thoracic major curves, the Rib Index. T tests were performed to compare fast-progressive curves with those that deteriorated by < 2° per year. Receiver operator characteristic (ROC) curves were plotted to establish optimal cutoffs, sensitivity, and specificity measures for rotational parameters. RESULTS: The average duration of follow-up post was 11.8 ± 7.3 years. Thirteen out of seventy-three patients were fast progressors. The modified Nash-Moe index was similar between groups at presentation (p = 0.477) but significantly higher in fast progressors than non-fast progressors at maturity for major thoracic curves (25.40 ± 6.60 vs. 19.20 ± 4.40, p < 0.001). Rib Index values were also higher among fast progressors at skeletal maturity (2.50 ± 0.90 vs. 1.80 ± 0.60, p = 0.026). An ROC curve for a modified Nash-Moe index of 0.235 for thoracic curves achieved an area under the curve (AUC) of 0.76 for discriminating fast progressors. A threshold of 1.915 for Rib Index at maturity achieved an AUC of 0.72 for discriminating fast progressors. In combining both rotational parameters, an AUC of 0.81 was achieved. CONCLUSION: These simple rotational parameters may be useful to predict fast progression in 40-50° AIS curves following skeletal maturity indicated for early fusion, but further validation upon larger cohorts and non-thoracic major curves is required.
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BACKGROUND: Prior reviews investigating the impact of pregnancy on adolescent idiopathic scoliosis (AIS) have reached different conclusions and a meta-analysis of curve progression among pregnant females with AIS and its effects on clinical outcomes has not previously been performed. METHODS: A comprehensive search of major bibliographic databases (PubMed, Embase, and Scopus) was conducted for articles pertaining to spinal curve progression during pregnancy among patients with AIS. Patient demographics, scoliotic curve outcomes, and patient-reported quality of life measures were extracted. RESULTS: Ten studies, including 857 patients with a mean age of 28.7 years, were included. Before pregnancy, 42.1% had undergone spinal fusion and 59.0% had a thoracic curve. Based on pre-pregnancy and post-pregnancy radiographs, the curve increased from 33.9° to 38.5° and meta-analysis revealed a curve progression of 3.6° (range=-5.85--1.25, p=0.003), primarily arising from loss of correction in the unfused group (Unfused=-5.0, p=0.040; Fused=-3.0, p=0.070). At the same time, 45.9% patients reported increased low back pain and many reported a negative body self-image and limitations in sexual function. However, five studies noted that pregnancy and number of pregnancies were not associated with curve progression, and multiple studies identified similar quality of life-related changes in non-pregnant patients with AIS. CONCLUSIONS: Among unfused pregnant females with AIS, the spinal curvature increased significantly by 5.0° from before to after pregnancy. However, these changes may be independent of pregnancy status and occur with time. Such curve progression can contribute to a negative body self-image, low back pain, and functional limitations irrespective of pregnancy state.
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PURPOSE: Adolescent idiopathic scoliosis is a chronic disease that may require correction surgery. The finite element method (FEM) is a popular option to plan the outcome of surgery on a patient-based model. However, it requires considerable computing power and time, which may discourage its use. Machine learning (ML) models can be a helpful surrogate to the FEM, providing accurate real-time responses. This work implements ML algorithms to estimate post-operative spinal shapes. METHODS: The algorithms are trained using features from 6400 simulations generated using the FEM from spine geometries of 64 patients. The features are selected using an autoencoder and principal component analysis. The accuracy of the results is evaluated by calculating the root-mean-squared error and the angle between the reference and predicted position of each vertebra. The processing times are also reported. RESULTS: A combination of principal component analysis for dimensionality reduction, followed by the linear regression model, generated accurate results in real-time, with an average position error of 3.75 mm and orientation angle error below 2.74 degrees in all main 3D axes, within 3 ms. The prediction time is considerably faster than simulations based on the FEM alone, which require seconds to minutes. CONCLUSION: It is possible to predict post-operative spinal shapes of patients with AIS in real-time by using ML algorithms as a surrogate to the FEM. Clinicians can compare the response of the initial spine shape of a patient with AIS to various target shapes, which can be modified interactively. These benefits can encourage clinicians to use software tools for surgical planning of scoliosis.
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PURPOSE: Identification of adolescent idiopathic scoliosis (AIS) patients with mild curvatures who pose significant risk of progressing to severe levels of curvatures is of paramount importance for clinical care. This study aimed to compare segmental deformity changes in AIS sub-cohorts that are dichotomised by progression status. METHODS: Thirty-six female participants with Lenke 1 AIS curves were investigated with sequential MRIs during growth. Scans were reformatted to measure orthogonal segmental parameters, including sagittal/coronal wedging angles and axial rotation angles. Participants were dichotomised by progression. Two-tailed, independent sample t-tests were used to compare sub-cohort multi-segmental and segmental deformity parameters. Measurements were compared at each scan number and variable rates of change were determined using actual time between measures. RESULTS: AIS progression status sub-cohorts were comparable at scan 1 for multi-segmental deformity parameters (e.g. major thoracic curve angle, rib hump, kyphosis) (P > 0.05). However, apical measures of coronal IVD wedging, axial IVD rotation and axial vertebral rotation were segmental parameters at scan 1 which were larger for participants whose AIS would later go on to clinically progress (all P < 0.05). Measures of segmental hypokyphosis were comparable between groups. As development was tracked at each subsequent scan, coronal and axial plane differences between groups increased in both magnitude and number of differences. CONCLUSION: Initial disparity and then subsequent increasing magnitude of change of axial rotation may indicate a higher propensity to clinically progress in the future. This knowledge hopes to provide useful management information for AIS care providers and prognostic education for patients alike. LEVEL OF EVIDENCE: II.
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PURPOSE: The purpose of this study is to develop and apply an algorithm that automatically classifies spine radiographs of pediatric scoliosis patients. METHODS: Anterior-posterior (AP) and lateral spine radiographs were extracted from the institutional picture archive for patients with scoliosis. Overall, there were 7777 AP images and 5621 lateral images. Radiographs were manually classified into ten categories: two preoperative and three postoperative categories each for AP and lateral images. The images were split into training, validation, and testing sets (70:15:15 proportional split). A deep learning classifier using the EfficientNet B6 architecture was trained on the spine training set. Hyperparameters and model architecture were tuned against the performance of the models in the validation set. RESULTS: The trained classifiers had an overall accuracy on the test set of 1.00 on 1166 AP images and 1.00 on 843 lateral images. Precision ranged from 0.98 to 1.00 in the AP images, and from 0.91 to 1.00 on the lateral images. Lower performance was observed on classes with fewer than 100 images in the dataset. Final performance metrics were calculated on the assigned test set, including accuracy, precision, recall, and F1 score (the harmonic mean of precision and recall). CONCLUSIONS: A deep learning convolutional neural network classifier was trained to a high degree of accuracy to distinguish between 10 categories pre- and postoperative spine radiographs of patients with scoliosis. Observed performance was higher in more prevalent categories. These models represent an important step in developing an automatic system for data ingestion into large, labeled imaging registries.