Contour and Angle-Function Based Scoliosis Monitoring: Relaxing the Requirement on Image Quality in the Measurement of Spinal Curvature

Institution-wide shape analysis of 3D spinal curvature and global alignment parameters

The spine is an articulated, 3D structure with 6 degrees of translational and rotational freedom. Clinical studies have shown spinal deformities are associated with pain and functional disability in both adult and pediatric populations. Clinical decision making relies on accurate characterization of the spinal deformity and monitoring of its progression over time. However, Cobb angle measurements are time-consuming, are limited by interobserver variability, and represent a simplified 2D view of a 3D structure. Instead, spine deformities can be described by 3D shape parameters, addressing the limitations of current measurement methods. To this end, we develop and validate a deep learning algorithm to automatically extract the vertebral midline (from the upper endplate of S1 to the lower endplate of C7) for frontal and lateral radiographs. Our results demonstrate robust performance across datasets and patient populations. Approximations of 3D spines are reconstructed from the unit normalized midline curves of 20,118 pairs of full spine radiographs belonging to 15,378 patients acquired at our institution between 2008 and 2020. The resulting 3D dataset is used to describe global imbalance parameters in the patient population and to build a statistical shape model to describe global spine shape variations in preoperative deformity patients via eight interpretable shape parameters. The developed method can identify patient subgroups with similar shape characteristics without relying on an existing shape classification system.

Radiographic scoliosis angle estimation: spline-based measurement reveals superior reliability compared to traditional COBB method

INTRODUCTION AND OBJECTIVE

Although being standard for scoliosis curve size estimation, COBB angle measurement is well known to be inaccurate, due to a high interobserver variance in end vertebra selection and end plate contour delineation. We propose a stepwise improvement by using a spline constructed from vertebra centroids to resemble spinal curve characteristics more closely. To enhance precision even further, a neural net was trained to detect the centroids automatically.

MATERIALS & METHODS

Vertebra centroids in AP spinal X-ray images of varying quality from 551 scoliosis patients were manually labeled by 4 investigators. With these inputs, splines were generated and the computed curve sizes were compared to the manually measured COBB angles and to the curve estimation obtained from the neural net.

RESULTS

Splines achieved a higher interobserver correlation of 0.92-0.95 compared to manual COBB measurements (0.83-0.92) and showed 1.5-2 times less variance, depending on the anatomic region. This translates into an average of 1° of interobserver measurement deviation for spline-based curve estimation compared to 3°-8° for COBB measurements. The neural net was even more precise and achieved mean deviations below 0.5°.

CONCLUSION

In conclusion, our data suggest an advantage of spline-based automated measuring systems, so further investigations are warranted to abandon manual COBB measurements.

Mobile Applications for Assessing Human Posture: A Systematic Literature Review

Smartphones are increasingly incorporated with features such as sensors and high resolution cameras that empower their capabilities, enabling their use for varied activities including human posture assessments. Previous reviews have discussed methods used in postural assessment but none of them focused exclusively on mobile applications. This paper systematically reviews mobile applications proposed for analyzing human posture based on alignment of the body in the sagittal and coronal plane. The main digital libraries were searched, 26 articles published between 2010 and 2020 were selected, and 13 mobile applications were identified, classified and discussed. Results showed that the use of mobile applications to assist with posture assessment have been demonstrated to be reliable, and this can contribute to clinical practice of health professionals, especially the assessment and reassessment phases of treatments, despite some variations when compared to traditional methods. Moreover, in the case of image-based applications, we highlight the advantage that measurements can be taken with the assessor at a certain distance with respect to the patient’s position, which is an important function for assessments performed in pandemic times such as the outbreak of COVID-19.

Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays

OBJECTIVES

To automatically measure the Cobb angle and diagnose scoliosis on chest X-rays, a computer-aided method was proposed and the reliability and accuracy were evaluated.

METHODS

Two Mask R-CNN models as the core of a computer-aided method were used to separately detect and segment the spine and all vertebral bodies on chest X-rays, and the Cobb angle of the spinal curve was measured from the output of the Mask R-CNN models. To evaluate the reliability and accuracy of the computer-aided method, the Cobb angles on 248 chest X-rays from lung cancer screening were measured automatically using a computer-aided method, and two experienced radiologists used a manual method to separately measure Cobb angles on the aforementioned chest X-rays.

RESULTS

For manual measurement of the Cobb angle on chest X-rays, the intraclass correlation coefficients (ICC) of intra- and inter-observer reliability analysis was 0.941 and 0.887, respectively, and the mean absolute differences were < 3.5°. The ICC between the computer-aided and manual methods for Cobb angle measurement was 0.854, and the mean absolute difference was 3.32°. These results indicated that the computer-aided method had good reliability for Cobb angle measurement on chest X-rays. Using the mean value of Cobb angles in manual measurements > 10° as a reference standard for scoliosis, the computer-aided method achieved a high level of sensitivity (89.59%) and a relatively low level of specificity (70.37%) for diagnosing scoliosis on chest X-rays.

CONCLUSION

The computer-aided method has potential for automatic Cobb angle measurement and scoliosis diagnosis on chest X-rays. These slides can be retrieved under Electronic Supplementary Material.

The Duration of the correction loss after removing cheneau brace in patients with adolescent idiopathic scoliosis

OBJECTIVE

The aim of the study was to evaluate the loss of truncal rotation over 54 hours after removing Chêneau brace.

METHODS

The studied groups consisted of 39 girls aged 10-18 years old, diagnosed with adolescent idiopathic scoliosis (AIS) and treated with Chêneau brace (CAST) and 20 AIS girls aged 10-18 years old, not treated with bracing. Posterior-anterior radiographs were obtained from the clinical assessment of all subjects and were subsequently used to determine Cobb angles. The measurements of the angle of trunk rotation (ATR) were taken with the Scoliometer® and back-contour device during Adams forward bending test by the two evaluators. The changes in ATRs during 54 hours of observation were performed after the brace had been taken off (0, 2, 24, 30, 48 and 54 hours after debracing). This was described using VATR variable, defined as the change in the absolute Scoliometer® readings in the time intervals against the time interval Δt between the measurements. During back-contour assessment the differential factor (kra) has been used for the digital analysis. The changes in kra over 54 hours of observation were expressed as Vkra factor, defined as the difference in the absolute value of the amplitude differential factor (kra) in the time intervals against the time interval Δt between the measurements.

RESULTS

The highest changes were observed in the thoracic as well as in lumbar spine in patients with Cobb angle ≥30°, axial rotation of the apical vertebrae within 5-15°, Risser sign 0-2. The biggest change in the trunk rotation after Chêneau brace had been taken off was noted within the first two hours of observation.

CONCLUSION

The patients should be advised to take the brace off for a minimum of two hours before the scheduled x-ray, to allow full relaxation of the trunk in order to obtain reliable radiological images of the deformation.

LEVEL OF EVIDENCE

Level III Therapeutic study.

Computer Assisted Cobb Angle Measurements: A novel algorithm

BACKGROUND

The standard for evaluating scoliosis is PA radiographs using Cobb angle to measure curve magnitude. Newer PACS systems allow easier Cobb angle calculations, but have not improved inter/intra observer precision of measurement. Cobb angle and its progression are important to determine treatment; therefore, angle variability is not optimal. This study seeks to demonstrate that a performance equivalent to that achieved in the manual method is possible using a novel computer algorithm with limited user input. The authors compared Cobb angles from predetermined spinal levels in the average attending score versus the computer assisted approach.

METHODS

Retrospective analysis of PA radiographs from 58 patients previously evaluated for scoliosis was collected. Predesignated spinal levels (e.g., T2-T10) were assigned for different curves and calculated by Cobb method. Four spine surgeons evaluated these Cobb angles. Their average scores were measured and compared to formulated values using the novel computer-based algorithm. Literature reports inter-observer reliability is 6.3-7.2degrees. Limits of accuracy were set at 5 degrees of average orthopedic surgeons' score.

RESULTS

The computer-based algorithm calculated Cobb angles within 5 degrees of orthopedic surgeons' average with a standard deviation of 3.2 degrees. This result was based on a 95% confidence interval with p values <0.001. The computer algorithm was plotted against average angle determined by the surgeons, with individual determinations and linear regression (r² =0.90). The average difference between surgeons' measures and computer algorithm was 0.4 degrees(SD= 3.2degrees, n=79). There was a tendency for the computer algorithm program to overestimate the angle at larger angles, but difference was small with r² = 0.09.

CONCLUSIONS

Our study showed the novel computer based algorithm was an efficient and reliable method to assess scoliotic curvature in the coronal plane with the possibility of expediting clinic visits, ensuring reliability of calculation and decreasing patient exposure to radiation. Level of Evidence: III.