Functional classification of patients with idiopathic scoliosis assessed by the Quantec system: a discriminant functional analysis to determine patient curve magnitude

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

PURPOSE

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.

METHODS

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.

RESULTS

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%.

CONCLUSION

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.

A preliminary study in classification of the severity of spine deformation in adolescents with lumbar/thoracolumbar idiopathic scoliosis using machine learning algorithms based on lumbosacral joint efforts during gait

To assess the severity and progression of adolescents with idiopathic scoliosis (AIS), radiography with X-rays is usually used. The methods based on statistical observations have been developed from 3D reconstruction of the trunk or topography. Machine learning has shown great potential to classify the severity of scoliosis on imaging data, generally on X-ray measurements. It is also known that AIS leads to the development of gait disorder. To our knowledge, machine learning has never been tested on spine intervertebral efforts during gait as a radiation-free method to classify the severity of spinal deformity in AIS. Develop automated machine learning algorithms in lumbar/thoracolumbar scoliosis to classify the severity of spinal deformity of AIS based on the lumbosacral joint (L5-S1) efforts during gait. The lumbosacral joint efforts of 30 individuals with lumbar/thoracolumbar AIS were used as distinctive features fed to the machine learning algorithms. Several tests were run using various classification algorithms. The labeling consisted of three classes reflecting the severity of scoliosis i.e. mild, moderate and severe. The ensemble classifier algorithm including k-nearest neighbors, support vector machine, random forest and multilayer perceptron achieved the most promising results, with accuracy scores of 91.4%. This preliminary study shows lumbosacral joint efforts can be used to classify the severity of spinal deformity in lumbar/thoracolumbar AIS. This method showed the potential of being used as an assessment tool to follow-up the progression of AIS as a radiation-free method, alternative to radiography. Future studies should be performed to test the method on other categories of AIS.

A Survey of Methods and Technologies Used for Diagnosis of Scoliosis

The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis in the form of a brief review. This article aims to point out the advantages of select methods. This article focuses on general issues without elaborating on problems strictly related to physiotherapy and treatment methods, which may be the subject of further discussions. By outlining and categorizing each method, we summarize relevant publications that may not only help introduce other researchers to the field but also be a valuable source for studying existing methods, developing new ones or choosing evaluation strategies.

Development and validation of deep learning algorithms for scoliosis screening using back images

Adolescent idiopathic scoliosis is the most common spinal disorder in adolescents with a prevalence of 0.5-5.2% worldwide. The traditional methods for scoliosis screening are easily accessible but require unnecessary referrals and radiography exposure due to their low positive predictive values. The application of deep learning algorithms has the potential to reduce unnecessary referrals and costs in scoliosis screening. Here, we developed and validated deep learning algorithms for automated scoliosis screening using unclothed back images. The accuracies of the algorithms were superior to those of human specialists in detecting scoliosis, detecting cases with a curve ≥20°, and severity grading for both binary classifications and the four-class classification. Our approach can be potentially applied in routine scoliosis screening and periodic follow-ups of pretreatment cases without radiation exposure.

Anatomical reference marks, evaluation parameters and reproducibility of surface topography for evaluating the adolescent idiopathic scoliosis: a systematic review with meta-analysis

BACKGROUND

Surface topography is a radiation-free examination that provides relevant information for the evaluation of patients with Adolescent Idiopathic Scoliosis (AIS). However, its usage is not standardized, which restricts the applicability of this instrument.

RESEARCH QUESTIONS

(a) To identify the anatomical reference markers used on surface topography; (b) to identify the parameters used on surface topography; and (c) to pool correlation and reproducibility results.

METHODS

Systematic searches were conducted following MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines. The methodological quality was assessed according to Brink & Louw appraisal tool.

RESULTS

Twenty-three studies were included for the qualitative synthesis. The most commonly used anatomical reference markers were: the prominent vertebra (C7 or T1), the posterior superior iliac spines (PSISs) and the sacrum (S1). The parameters for the evaluation of the AIS by surface topography are: spinal inclination angle (analogous to Cobb), gibbosity, thoracic kyphosis angle, lumbar lordosis angle, pelvic obliquity, spine length, apex of the curve, C7-S1 distance (frontal plane), and C7-S1 displacement (sagittal plane). Data from eleven studies were metanalyzed and evidenced the correlation of the surface topography with X-ray exams and the reproducibility of the surface topography in the sagittal and frontal planes.

SIGNIFICANCE

The findings of this study recommend the use of a protocol for the application of the equipment. The analyzed studies predict the use of only four markers for anatomical reference. The evaluation of the AIS can be carried out observing nine parameters. Surface topography correlates with radiography when the spinal inclination angle (Cobb angle), thoracic kyphosis angle and lumbar lordosis angle are compared. Also, surface topography presents inter and intra-rater reproducibility in the sagittal plane and intra-rater reproducibility in the frontal plane.

Surface Topography Classification Trees for Assessing Severity and Monitoring Progression in Adolescent Idiopathic Scoliosis

STUDY DESIGN

A validation study.

OBJECTIVE

The aim of this study was to independently validate the diagnostic accuracy of surface topography (ST) classification trees to identify curve severity and progression using a new sample of data in participants with adolescent idiopathic scoliosis (AIS).

SUMMARY OF BACKGROUND DATA

Radiographs for diagnosing and monitoring AIS involve harmful radiation exposure repeated at successive clinical visits. Classification trees using a novel ST technique have been proposed to determine curve severity and progression noninvasively that could be used to monitor scoliosis.

METHODS

Forty-five adolescents with AIS treated nonoperatively, with ST scans and radiographs at baseline and follow-up (1 year later), were recruited from a scoliosis clinic. The Cobb angle (CA) from radiographs determined curve severity as mild (10° < CA < 25°) or moderate/severe (CA ≥ 25°) and progression as an increase >5°.ST scans were analyzed to calculate the best plane of symmetry and associated deviation color map. Root mean squares and maximum deviation were calculated for each area of asymmetry. ST measurements were analyzed using two published decision trees developed to maximize sensitivity and negative predictive value. Curves were classified as mild or moderate/severe and curve progression was predicted. Accuracy statistics were calculated to evaluate performance.

RESULTS

For curve severity, sensitivity and specificity were 95% and 35%, respectively. Negative and positive predictive values were 90% and 53%, respectively, with an accuracy of 61%. For curve progression, sensitivity and specificity were 73% and 44%, respectively. Negative and positive predictive values were 83% and 30%, respectively, with an accuracy of 51%. Assuming that mild and nonprogressive curves would not require an x-ray, the use of ST decision trees could eliminate 31% of x-rays.

CONCLUSION

Decision trees showed strong negative predictive values and sensitivity suggesting it may be possible to safely use ST asymmetry analysis with validated decision trees to reduce x-rays in patients with mild and nonprogressive curves.

LEVEL OF EVIDENCE

2.

Quantification of topographic changes in the surface of back of young patients monitored for idiopathic scoliosis: correlation with radiographic variables

Idiopathic scoliosis requires a close follow-up while the patient is skeletally immature to detect early progression. Patients who are monitored by radiographs are exposed to high doses of ionizing radiation. The purpose of this study is to evaluate if an optic noninvasive method of back surface topography based on structured light would be clinically useful in the follow-up of young patients with idiopathic scoliosis. This could reduce the number of radiographs made on these children. Thirty-one patients with idiopathic scoliosis were submitted twice to radiograph and our topographic method at intervals of 6 months to 1 year. Three topographical variables were applied horizontal plane deformity index (DHOPI), posterior trunk symmetry index (POTSI), and columnar profile (PC). A statistically significant correlation was found between variations of Cobb angle with DHOPI (r=0.720, p<0.01) and POTSI (r=0.753, p<0.01) during the monitoring period. Hence, this topographic method could be useful in clinical practice as an objective adjuvant tool in routine follow-up of scoliosis.

Bracing and exercise-based treatment for idiopathic scoliosis

BACKGROUND

Various conservative therapies are available for treating adolescent idiopathic scoliosis (AIS), however, the disparities between them and the evidence of their efficacy and effectiveness is still unclear.

OBJECTIVES

To evaluate the effectiveness of different conservative treatments on AIS.

METHODS

A literature-based narrative review of the English language medical literature.

RESULTS AND CONCLUSIONS

The most appropriate treatment for each patient should be chosen individually and based on various parameters. Bracing has been found to be a most effective conservative treatment for AIS. There is limited evidence that specific physical exercises also an effective intervention for AIS. Exercise-based physical therapy, if correctly administered, can prevent a worsening of the curve and may decrease need for bracing. In addition, physical exercises were found to be the only treatment improving respiratory function. Combining bracing with exercise increases treatment efficacy compared with a single treatment. Additional, well-designed and good quality studies are required to assess the effectiveness of different conservative methods in treating AIS.

Monitoring for idiopathic scoliosis curve progression using surface topography asymmetry analysis of the torso in adolescents

BACKGROUND CONTEXT

At first visit and each clinical follow-up session, patients with adolescent idiopathic scoliosis (AIS) undergo radiographic examination, from which the Cobb angle is measured. The cumulative exposure to X-ray radiation justifies efforts in developing noninvasive methods for scoliosis monitoring.

PURPOSE

To determine the capability of the three-dimensional markerless surface topography (ST) asymmetry analysis to detect ≥5° progression in the spinal curvature in patients with AIS over 1-year follow-up interval.

STUDY DESIGN/SETTING

Cross-sectional study in a specialized scoliosis clinic.

PATIENT SAMPLE

In this study, baseline and 1-year follow-up full torso ST scans of 100 patients with AIS were analyzed using three-dimensional markerless asymmetry analysis.

OUTCOME MEASURES

Patients with ΔCobb≥5° and ΔCobb<5° were categorized into progression and nonprogression groups, respectively.

METHODS

The ST scan of each full torso was analyzed to calculate the best plane of symmetry by minimizing the distances between the torso and its reflection about the plane of symmetry. Distance between the torso and its reflection was measured and displayed as deviation color maps. The difference of ST measurements between two successive acquisitions was used to determine if the scoliosis has progressed at least 5° or not. The classification tree technique was implemented using the local deformity of the torso in the thoracic-thoracolumbar (T-TL) and lumbar (L) regions to categorize curves into progression and nonprogression groups. The change in maximum deviation and root mean square of the deviations in the torso were the parameters effective in capturing the curve progression. Funding for this research is provided by the Scoliosis Research Society, and Women and Children's Health Research Institute.

RESULTS

The classification model detected 85.7% of the progression and 71.6% of the nonprogression cases. The resulting false-negative rate of 4% for T-TL curves, representing the proportion of undetected progressions, confirmed that the technique shows promise to monitor the progression of T-TL scoliosis curves. Although 100% L curves with progression were detected using the deviation color maps of the torsos, because of the small number of analyzed L curves, further research is needed before the efficiency of the method in capturing the L curves with progression is confirmed.

CONCLUSIONS

Using the developed classification tree for the patients analyzed in this study, 43% of nonprogression cases between two visits would not have to undergo an X-ray examination.

Surface topography asymmetry maps categorizing external deformity in scoliosis

BACKGROUND CONTEXT

Adolescent idiopathic scoliosis (AIS) affects 2% to 4% of the population and predominantly affects female individuals. The scoliosis researchers and clinical communities use the "Cobb angle" obtained from anterior-posterior radiographs as the standard assessment tool for scoliosis. However, excessive radiation exposure over consecutive visits during the growing years increases the risk of cancer in young patients with AIS. Surface topography (ST) is a noninvasive method that is being investigated as an alternative tool for scoliosis assessment. The necessity of applying markers by skilled operators, which is time consuming and a potential area for errors, is one of the main limitations of these methods.

PURPOSE

This study introduces a three-dimensional markerless analysis technique for assessing torso asymmetry in AIS and a system for classifying patients based on this technique. The intra/interobserver and test-retest reliability and validity of the classification system was assessed.

STUDY DESIGN

A novel three-dimensional analysis technique of ST data of patients with scoliosis and its clinical applications.

METHODS

Full-torso ST scans of 46 patients with AIS (Cobb angle: 34±15°, curve types: Lenke 1, 3, and 5) and five healthy subjects were used for analysis. The best plane of symmetry, dividing the torso into left and right, was calculated for each scan. The deviation between the original torso and its reflection with respect to the best plane of symmetry was illustrated using deviation contour maps. The subjects were visually classified into three main groups and six subgroups based on the number and location of the asymmetry contours. A second baseline scan and a 1-year follow-up scan were analyzed for 15 subjects and reliability of the method was assessed using kappa coefficients. Funding for this research is provided by the Scoliosis Research Society, Women and Children's Health Research Institute, and the Natural Sciences and Engineering Research Council of Canada.

RESULTS

The intraobserver reliability of the group classification demonstrated excellent agreement with mean kappa coefficient of 0.85. The multiobserver kappa value of 0.62 was attained in the interobserver reliability test conducted among four observers classifying 46 subjects in three groups. The test-retest reliability of the method was assessed. Mean kappa values of 0.99 and 0.83 were achieved for group (three groups) and subgroup (six subgroups) classifications, respectively. The classification system showed good reliability when five observers classified the first baseline and the 1-year follow-up scans.

CONCLUSIONS

A novel method to examine torso asymmetry in patients with AIS is presented, using noninvasive ST scans and a visually intuitive asymmetry map. Distinct patterns of asymmetry were identified allowing patients to be classified into three groups, with six subgroups based on their asymmetry map with very good to excellent reliability. The presented technique shows promise to provide a noninvasive tool for assessment and monitoring of AIS.

SOSORT 2012 consensus paper: reducing x-ray exposure in pediatric patients with scoliosis

This 2012 Consensus paper reviews the literature on side effects of x-ray exposure in the pediatric population as it relates to scoliosis evaluation and treatment. Alternative methods of spinal assessment and imaging are reviewed, and strategies for reducing the number of radiographs are developed. Using the Delphi technique, SOSORT members developed consensus statements that describe how often radiographs should be taken in each of the pediatric and adolescent sub-populations.

Development of a 3-Dimensional Back Contour Imaging System for Monitoring Scoliosis Progression in Children

STUDY DESIGN

Control study.

OBJECTIVES

To present a new surface topography system capable of taking 3-dimensional (3D) spine measurements, to establish baseline values for the measured parameters in a typically developing population, and to determine the intra-rater and inter-rater reproducibility of these parameters.

SUMMARY OF BACKGROUND DATA

Cumulative exposure to radiation from diagnostic radiographs increases patient risk for cancer development. There is a need for noninvasive and non-radiographic tools to accurately and reproducibly measure spine deformity and track scoliosis progression.

METHODS

We measured 10 typically developing subjects with the new Milwaukee Topography System, which is composed of 2 electromagnetic markers, an electronic processing unit, a handheld laser scanner, a software package, and a desktop computer. Two investigators separately scanned the same subjects multiple times, yielding a total of 4 scans per subject per investigator. We measured 17 3D back parameters in each scan. We performed a multivariate analysis of variances to test the hypothesis of no difference for all variables, measured intra-rater and inter-investigator reliability with intra-class correlation (ICC) coefficients, and calculated mean values.

RESULTS

There were highly reproducible ICC values between investigators for 6 parameters (ICC > 0.75), moderate ICC values for 8 parameters (0.75 > ICC > 0.4), and poor ICC values for 3 parameters (ICC < 0.4), all at p < .05. Intra-investigator ICCs were moderate to excellent for almost all parameters.

CONCLUSIONS

The Milwaukee Topography System can be used to monitor and measure 3D back contours in children. The 3D back parameters values measured in the typically developing population can be considered baseline values that can be compared with parameters measured in children with idiopathic scoliosis.

ScolioMedIS: web-oriented information system for idiopathic scoliosis visualization and monitoring

Adolescent idiopathic scoliosis is the most common type of abnormal curvature observed in spine and it progresses rapidly during the puberty period. The most followed clinical way of assessing the spinal deformity is subjective by measuring the characteristic angles of spinal curve from a set of radiographic images. This paper presents a web-based information system (called ScolioMedIS) based on parameterized 3D anatomical models of the spine to quantitatively assess the deformity and to minimize the amount of radiation exposure by reducing the number of radiographs required. The main components of the system are 3D parametric solid model of spine, back surfaces, relevant clinical information and scoliosis ontology. The patient-specific spine model is regenerated from the parametric model and surface data using anatomical information extracted from radiographic images. The system is designed to take inherent advantage of Web for facilitating multi-center data collection and collaborative clinical decisions. The preliminary analysis of patient data showed promising results, which involve improved documentation standard, clinical decision knowledge base record, facilitated exchange and retrieval of medical data between institutions in multi-center clinical studies, 3D visualization of spinal deformity, and permanent monitoring of treatments.

Non invasive clinical assessment of trunk deformities associated with scoliosis

Besides the spinal deformity, scoliosis modifies notably the general appearance of the trunk resulting in trunk rotation, imbalance and asymmetries which constitutes patients' major concern. Existing classifications of scoliosis, based on the type of spinal curve as depicted on radiographs, are currently used to guide treatment strategies. Unfortunately, even though a perfect correction of the spinal curve is achieved, some trunk deformities remain, making patients dissatisfied with the treatment received. The purpose of this study is to identify possible shape patterns of trunk surface deformity associated with scoliosis. First, trunk surface is represented by a multivariate functional trunk shape descriptor based on 3D clinical measurements computed on cross sections of the trunk. Then, the classical formulation of hierarchical clustering is adapted to the case of multivariate functional data and applied to a set of 236 trunk surface 3D reconstructions. The highest internal validity is obtained when considering 11 clusters that explain up to 65% of the variance in our dataset. Our clustering result shows a concordance with the radiographic classification of spinal curves in 68% of the cases. As opposed to radiographic evaluation, the trunk descriptor is three-dimensional and its functional nature offers a compact and elegant description of not only the type, but also the severity and extent of the trunk surface deformity along the trunk length. In future work, new management strategies based on the resulting trunk shape patterns could be thought of in order to improve the esthetic outcome after treatment, and thus patients satisfaction.

Non invasive classification system of scoliosis curve types using least-squares support vector machines

OBJECTIVE

To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data.

METHODS

Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images.

RESULTS

The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively.

CONCLUSION

This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

Reproducibility of newly developed spinal topography measurements for scoliosis

Objective:

In an effort to limit exposure to ionizing radiation and fully characterize three dimensional changes in the spine of patients with scoliosis reliable non-invasive methods of spinal back contour analysis (Milwaukee Topographic Scanner) (MTS) have been developed.

Study Design:

The current study compares spinal topography measurements among different subject positions and evaluates the reproducibility of the system for both inter-rater and intra-rater reliability.

Methods:

A dummy cast (plastic cast) of one patient with adolescent idiopathic scoliosis was created in order to test the reliability of the MTS. The dummy cast was positioned and rotated in 3D while scanned by two investigators using the MTS. A total of twelve parameters including Q-angle (an analog to X-ray’s Cobb angle) were extracted.

Results:

All measurements of intra-rater and inter-rater reliability were excellent (Intraclass Correlation Coefficients ranging from 0.89 to 0.99) with the exception of Pelvic Tilt (intra-rater ICC is 0.61) and lordosis angle (inter-rater ICC is 0.82). No significant variability among investigators was observed for all tested metrics. No significant variability due to position was observed for the majority of back contour measurements but there were significant changes in the T1-S1 angle, T1-S1 deviation, T1-NC angle, T1-NC deviation, and Back Height metric (p< 0.05).

Conclusions:

The MTS is a reliable method of raster stereography in the measurement of the back contour, which will help monitor the progression of children with idiopathic scoliosis and reduce the use of X-rays.

No effect of osteopathic treatment on trunk morphology and spine flexibility in young women with adolescent idiopathic scoliosis

INTRODUCTION

Brace treatment is the gold standard for patients with mild adolescent idiopathic scoliosis (Cobb angle 20°-40°). However, negative psychosocial impacts, physical constraints and incompliance cause many patients and parents to seek for so-called holistic and apparently less harmful approaches within the field of complementary and alternative medicine (CAM). Osteopathy-manual interventions on the viscera and locomotor system-is widely used for scoliosis. There is, however, a complete lack of evidence regarding its efficacy. We, therefore, tested the hypothesis that osteopathy alters trunk morphology, a prerequisite to unload the concave side of the scoliosis, and that it halts curve progression.

METHODS

This was a prospective, controlled trial of 20 post-pubertal young women (20°-40° idiopathic scoliosis) randomly allocated to an observation (group 0) or osteopathic treatment (group 1). The latter comprised three sessions (5 weeks). Trunk morphology (clinical examination, video rasterstereography) and spine flexibility (MediMouse(®)) were assessed at a pre- and post-intervention with a 3-month interval (blinded examiner). We chose scoliometer measurement (rib hump, lumbar prominence) as the main outcome parameter.

RESULTS

Two patients in the treatment group refused further treatment and the final examination, as they felt no benefit after two osteopathic treatments. Regression analysis for repeat measurements (independent statistician) revealed no therapeutic effect on rib hump, lumbar prominence, plumb line, sagittal profile and global spinal flexibility.

CONCLUSIONS

We found no evidence to support osteopathy in the treatment of mild adolescent idiopathic scoliosis. Therefore, we caution against abandoning the conventional standard of care for mild idiopathic scoliosis. As for other CAM therapies, the use of osteopathy as a treatment option for scoliosis still needs to be clearly defined.

How to improve aesthetics in patients with Adolescent Idiopathic Scoliosis (AIS): a SPoRT brace treatment according to SOSORT management criteria

BACKGROUND

Aesthetics is a main goal of both conservative and surgical treatments in adolescent idiopathic scoliosis (AIS). Previously, we developed and validated a clinical scale - the Aesthetic Index (AI)--in order to measure aesthetic impairment and changes during treatment.

AIM

To verify the efficacy of bracing on aesthetics in AIS.

STUDY DESIGN

Prospective Cohort Study.

POPULATION

Thirty-four consecutive patients, age 13.2 +/- 3.7, initial Cobb Angle 32 +/- 12 degrees , ATR 10 +/- 4 degrees Bunnel, 11 males.

METHODS

Patients with AI scores of at least 5/6 were included. Each of them had a brace prescription (18 to 23 hours per day), according to the SPoRT concept. AI was measured again after six months and at the end of treatment, and then the pre- and post-treatment scores compared. The Wilcoxon test was performed.

RESULTS

Twenty-nine patients out of the 34 included completed the treatment and had six-month and final results; four patients were lost during the treatment, and one was fused. At baseline, median AI was 6 (95% IC 5-6) but the score decreased to 3 (95% IC 0-5; p < 0.05) after six months with brace, and this value was maintained in the 29 who completed the treatment (95% IC 1-6; p < 0.05 with respect to the baseline).

CONCLUSION

Aesthetics can be improved in a clinically significant way when the brace treatment is performed according to the SPoRT concept and by following the SOSORT management criteria. This is a relevant result for patients and a major goal of scoliosis treatment, be it conservative or surgical. The use of a more sensitive tool like TRACE could more easily detect the clinical changes; nevertheless, AI proved sensible enough that its use in everyday clinical practice can be suggested.

Range data pre-processing for the evaluation of torso shape and symmetry in scoliosis

Pre-processing range scans of the human torso for evaluating shape and symmetry changes in scoliosis are non-trivial. First, stray points from surrounding artefacts are often arbitrarily positioned and not amenable to automatic removal. Second, the asymmetrical alignment of the arms and neck makes cropping them difficult. Third, despite a plethora of methods, removal of holes by surface approximation for this niche application remains a challenge particularly in obscure regions like the sides and armpits. This paper proposes a novel surface approximation method and incorporates it into an integrated procedure for pre-processing range scans of the torso that includes interactive tools for cropping stray points and extremities. The new method, spline-fitted moving least squares (MLS), makes use of the Bezier curve and MLS algorithms. Numeric and clinical tests on scans of 30 volunteers, with and without scoliosis, show that the proposed method outperforms its constituent methods and a commercially available graphics package for this application.

TRACE (Trunk Aesthetic Clinical Evaluation), a routine clinical tool to evaluate aesthetics in scoliosis patients: development from the Aesthetic Index (AI) and repeatability

Background

Aesthetic appearance is of primary importance in the treatment of adolescent idiopathic scoliosis (AIS), but to date tools for routine clinical practice have not become available. The aim of the present study is to develop such a tool and to verify its repeatability.

Methods

Instrumentation: At first we developed the Aesthetic Index (AI), based on a three-point scale for asymmetry of the shoulders, scapulae and waist that we tested for 5 years. From this experience we developed another tool we called TRACE, the acronym of Trunk Aesthetic Clinical Evaluation; TRACE is a 12-point scale based on four sub-scales, shoulders (0–3), scapulae (0–2), hemi-thorax (0–2) and waist (0–4).

Population: Posterior-anterior (PA) photographs of one hundred-sixty AIS patients

Procedures: Each photograph was scored in two independent tests by four observers using AI, and subsequently TRACE.

Data analysis: Kappa statistical analysis and 95% level of agreement were used; we also identified the minimum significant change (95% confidence level).

Results

We found the intra- and inter-raters repeatability of AI to be fair. Three points out of seven was the minimum significant change between two different evaluations. For TRACE, intra-rater repeatability was fair and inter-raters poor; but the minimum significant change was three (intra-rater), or four (inter-raters) out of twelve points.

Conclusion

Widening the scale from 7 (AI) to 12 points (TRACE) increased the clinical sensitivity to changes of the aesthetic scale, even if TRACE has only a fair repeatability. TRACE is a no-cost tool for routine clinical practice in AIS patients. Due to the absence of other comparable validated tools, once the inherent measurement error is known and understood, its routine clinical use by physicians is advised.

Clinical monitoring of torso deformities in scoliosis using structured splines models

This paper describes the use of structured splines indices for the clinical monitoring of torso deformity in scoliosis. Structured splines indices are computed from the distribution of points of maximal curvature (dominant points) of an object. The suitability and robustness of the indices for this application is assessed by ascertaining their robustness to inevitable torso shape variations due to sway and breathing and the variability in their values relative to existing clinical measures of deformity. To assess the consistency of these indices with other indices in use for this application, they were used to assess the relative information contents of the front and back of the torso. Results show that structured splines indices are more robust than existing clinical measures for monitoring torso deformity in scoliosis. Results also show that the scoliosis information content ratio of the back torso to the front torso is three to one.

Smart garment for trunk posture monitoring: A preliminary study

Background

Poor postures of the spine have been considered in association with a number of spinal musculoskeletal disorders, including structural deformity of the spine and back pain. Improper posturing for the patients with spinal disorders may further deteriorate their pain and deformities. Therefore, posture training has been proposed and its rationale is to use the patient's own back muscles to keep the spine within the natural curvature. A posture training device may help to facilitate this therapeutic approach by providing continuous posture monitoring and feedback signals to the patient when "poor" posture is detected. In addition, the users of the device may learn good postural habits that could carry over into their whole life.

Methods

A smart garment with integrated accelerometers and gyroscopes, which can detect postural changes in terms of curvature variation of the spine in the sagittal and coronal planes, has been developed with intention to facilitate posture training. The smart garment was evaluated in laboratory tests and with 5 normal subjects during their daily activities.

Results

Laboratory tests verified that the accuracy of the system is < 1° and < 1.5° in static and dynamic tilting measurements respectively. The results showed that the smart garment could facilitate subjects to prevent prolonged poor postures of the spine, especially the posture of the lumbar spine in which at least 40% of the time in poor posture were reduced.

Conclusion

The smart garment has been developed to be a portable and user-friendly trunk posture monitoring system and it could be used for collection of the trunk posture information and provision of instant feedback to the user if necessary for posture training purpose. The current pilot study demonstrated that the posture of normal subjects could be monitored and trained via this smart garment. With further clinical investigations, this system could be considered in some flexible spinal deformities such as scoliosis and kyphosis.

Validating an imaging and analysis system for assessing torso deformities

We present the results of the numeric and functional validation of an imaging and analysis system used for assessing human torsos for deformities such as scoliosis. The system comprises of image acquisition, image reconstruction, and shape analysis components. The numeric validation procedure consists of assessing the accuracy of reconstruction of the system using inanimate models (a calibration box and a mannequin). The functional validation involves determining the system's response to variations in shape caused by sway and breathing, and evaluating the variability of a clinically relevant index, the Cosmetic Score, from multiple scans of scoliosis and non-scoliosis volunteers. Results show that the reconstruction accuracy of the system is 1.16+/-1.04 mm. This is better than the required accuracy for monitoring scoliosis of 2 mm. The system is robust to shape variations caused by sway and breathing and shows limited variability to the Cosmetic Score.

SOSORT consensus paper: school screening for scoliosis. Where are we today?

This report is the SOSORT Consensus Paper on School Screening for Scoliosis discussed at the 4th International Conference on Conservative Management of Spinal Deformities, presented by SOSORT, on May 2007. The objectives were numerous, 1) the inclusion of the existing information on the issue, 2) the analysis and discussion of the responses by the meeting attendees to the twenty six questions of the questionnaire, 3) the impact of screening on frequency of surgical treatment and of its discontinuation, 4) the reasons why these programs must be continued, 5) the evolving aim of School Screening for Scoliosis and 6) recommendations for improvement of the procedure.

Reliability of trunk shape measurements based on 3-D surface reconstructions

This study aimed to estimate the reliability of 3-D trunk surface measurements for the characterization of external asymmetry associated with scoliosis. Repeated trunk surface acquisitions using the Inspeck system (Inspeck Inc., Montreal, Canada), with two different postures A (anatomical position) and B (''clavicle'' position), were obtained from patients attending a scoliosis clinic. For each acquisition, a 3-D model of the patient's trunk was built and a series of measurements was computed. For each measure and posture, intraclass correlation coefficients (ICC) were obtained using a bivariate analysis of variance, and the smallest detectable difference was calculated. For posture A, reliability was fair to excellent with ICC from 0.91 to 0.99 (0.85 to 0.99 for the lower bound of the 95% confidence interval). For posture B, the ICC was 0.85 to 0.98 (0.74 to 0.99 for the lower bound of the 95% confidence interval). The smallest statistically significant differences for the maximal back surface rotation was 2.5 and 1.5 degrees for the maximal trunk rotation. Apparent global asymmetry and axial trunk rotation indices were relatively robust to changes in arm posture, both in terms of mean values and within-subject variations, and also showed a good reliability. Computing measurements from cross-sectional analysis enabled a reduction in errors compared to the measurements based on markers' position. Although not yet sensitive enough to detect small changes for monitoring of curve natural progression, trunk surface analysis can help to document the external asymmetry associated with different types of spinal curves as well as the cosmetic improvement obtained after surgical interventions. The anatomical posture is slightly more reliable as it allows a better coverage of the trunk surface by the digitizing system.

Reliability of a functional classification system in the monitoring of patients with idiopathic scoliosis

STUDY DESIGN

Patients with scoliosis from 1999 to 2001 were monitored using radiographs and the Quantec Spinal Imaging System (Quantec) to validate the Functional Classification System (FCS) developed at Children's Hospital of Wisconsin (CHW).

OBJECTIVE

To determine the accuracy of the FCS.

SUMMARY OF BACKGROUND DATA

The authors evaluated different noninvasive ways of evaluating the scoliotic spine. The FCS was developed as a means to predict the degree of scoliotic curve.

METHODS

Consecutive scoliosis visits (543) seen at CHW between 1999 and 2001 for initial or follow-up examination were investigated; of them, 157 had an radiograph within 6 months of Quantec. Subjects were placed into groups based on Cobb Angles. FCS classifications were compared to Cobb angle groupings and calculated sensitivity and specificity. Pearson's correlation coefficient was calculated for 39 subjects.

RESULTS

Sensitivity of the FCS for single curve groups ranged from 0.50 to 0.63 and specificity from 0.64 to 0.86. For double curve, both sensitivity and specificity ranged from 0.48 to 0.81. Pearson's correlation was statistically significant (r = 0.45, P < 0.05).

CONCLUSIONS

Sensitivity, specificity, and Pearson's correlation coefficient reflect the reliability of the Quantec method. Therefore, the FCS can be considered as a reliable tool for monitoring the progression of scoliosis with reduced need of radiographs.

Classifying torso deformity in scoliosis using orthogonal maps of the torso

Analysis of three-dimensional (3D) images of human torsos for torso deformities such as scoliosis requires classifying torso distortion. Assessing torso distortion from 3D images is not trivial as actual torsos are non-symmetric and show an outstanding range of variations leading to high classification errors. As the degree of spinal deformity (and classification of torso shape) influences scoliosis treatment options, the development of more accurate classification procedures is desirable. This paper presents a technique for assessing torso shape and classifying scoliosis into mild, moderate and severe categories using two indices, 'twist' and 'bend', obtained from orthogonally transformed images of the complete torso surface called orthogonal maps. Four transforms (axial line, unfolded cylinder, enclosing cylinder and subtracting cylinder) were used. Blind tests on 361 computer models with known deformation parameter values show 100% classification accuracy. Tests on eight volunteers without scoliosis validated the system and tests on 22 torso images of volunteers with scoliosis showed up to 95.5% classification accuracy. In addition to classifying scoliosis, orthogonal maps present the entire torso in one view and are viable for use in scoliosis clinics for monitoring the progression of scoliosis.

Clinical impact of optical imaging with 3-D reconstruction of torso topography in common anterior chest wall anomalies

BACKGROUND

Standard modalities to assist in determining the extent of chest wall developmental deformities in patients include x-ray and computed tomography (CT). The purpose of this study is to describe an optical imaging technique that provides accurate cross-sectional images of the chest, and to compare these with standard CT-derived images of chest wall abnormalities.

PATIENTS AND METHODS

Ten patients (5 pectus excavatum and 5 pectus carinatum) underwent imaging that included limited CT and optical cross-sectional imaging. Severity indices of the deformity using the standard Haller index (HI) were calculated from CT scans. A similar severity measurement of deformity was derived from the outline of torso cross sections (ie, from skin to skin measurements) obtained from optical images. To assess the severity of carinatum defects, a modified pectus index was derived, which measures the anterior chest protrusion from the central chord of the chest cross section. We performed regression analyses, comparing the indices obtained from CT and optical imaging methodologies.

RESULTS

Optical measures of cross-sectional deformities correlated well with standard HI (r2 = 0.94) and even better with the modified pectus index (r2 = 0.96). Adaptation of the HI for pectus carinatum deformity evaluation was effective, and consistent with the torso surface deformity measures.

CONCLUSIONS

Torso models from optical imaging offer 3-D images of the chest wall deformity with no radiation exposure. This preliminary study showed promising results for the use of torso surface measurement as an alternative index of pectus deformities; if validated in larger studies, these measures may be useful for following chest wall abnormalities, using repeated studies in patients.

Clinical applications of sensors for human posture and movement analysis: a review

Measurement of human posture and movement is an important area of research in the bioengineering and rehabilitation fields. Various attempts have been initiated for different clinical application goals, such as diagnosis of pathological posture and movements, assessment of pre- and post-treatment efficacy and comparison of different treatment protocols. Image-based methods for measurements of human posture and movements have been developed, such as the photogrammetry, optoelectric technique and video analysis. However, it is found that these methods are complicated to set up, time-consuming to operate and could only be applied in laboratory environments. Electronic sensors and systems with advanced technology, namely accelerometer, gyroscope, flexible angular sensor, electromagnetic tracking system and sensing fabrics, have been developed and applied to solve the relevant application problems of the image-based methods. Nonetheless, other problems for using these electronic sensors emerged, including the environment influence and signal extraction difficulties. Further development of these electronic sensors and measurement methods could enhance their clinical applications in institutional as well as community levels. This article reviews the possible applications of these electronic sensors and systems, and precautions of their applications in analysis of human posture and movement. Such information would help researchers and clinicians in selecting and developing the most appropriate measurement techniques of using the electronic sensors for clinical applications of human posture and movement analysis.

Why do we treat adolescent idiopathic scoliosis? What we want to obtain and to avoid for our patients. SOSORT 2005 Consensus paper

Background

Medicine is a scientific art: once science is not clear, choices are made according to individual and collective beliefs that should be better understood. This is particularly true in a field like adolescent idiopathic scoliosis, where currently does not exist definitive scientific evidence on the efficacy either of conservative or of surgical treatments.

Aim of the study

To verify the philosophical choices on the final outcome of a group of people believing and engaged in a conservative treatment of idiopathic scoliosis.

Methods

We performed a multifaceted study that included a bibliometric analysis, a questionnaire, and a careful Consensus reaching procedure between experts in the conservative treatment of scoliosis (SOSORT members).

Results

The Consensus reaching procedure has shown to be useful: answers changed in a statistically significant way, and 9 new outcome criteria were included. The most important final outcomes were considered Aesthetics (100%), Quality of life and Disability (more than 90%), while more than 80% of preferences went to Back Pain, Psychological well-being, Progression in adulthood, Breathing function, Scoliosis Cobb degrees (radiographic lateral flexion), Needs of further treatments in adulthood.

Discussion

In the literature prevail outcome criteria driven by the contingent treatment needs or the possibility to have measurement systems (even if it seems that usual clinical and radiographic methods are given much more importance than more complex Disability or Quality of Life instruments). SOSORT members give importance to a wide range of outcome criteria, in which clinical and radiographic issues have the lowest importance.

Conclusion

We treat our patients for what they need for their future (Breathing function, Needs of further treatments in adulthood, Progression in adulthood), and their present too (Aesthetics, Disability, Quality of life). Technical matters, such as rib hump or radiographic lateral alignment and rotation, but not lateral flexion, are secondary outcomes and only instrumental to previously reported primary outcomes. We advocate a multidimensional, comprehensive evaluation of scoliosis patients, to gather all necessary data for a complete therapeutic approach, that goes beyond x-rays to reach the person and the family.

A support vector machines classifier to assess the severity of idiopathic scoliosis from surface topography

A support vector machines (SVM) classifier was used to assess the severity of idiopathic scoliosis (IS) based on surface topographic images of human backs. Scoliosis is a condition that involves abnormal lateral curvature and rotation of the spine that usually causes noticeable trunk deformities. Based on the hypothesis that combining surface topography and clinical data using a SVM would produce better assessment results, we conducted a study using a dataset of 111 IS patients. Twelve surface and clinical indicators were obtained for each patient. The result of testing on the dataset showed that the system achieved 69-85% accuracy in testing. It outperformed a linear discriminant function classifier and a decision tree classifier on the dataset.