Assessment of the reliability of hand-held surface scanner in the evaluation of adolescent idiopathic scoliosis

Assessment of reliability and validity of a handheld surface spine scanner for measuring trunk rotation in adolescent idiopathic scoliosis

PURPOSE

To assess the reliability and validity of a handheld scanner (SpineScan3D) for trunk rotation measurement in adolescent idiopathic scoliosis (AIS) subjects, as compared with Scoliometer.

METHODS

This was a cross-sectional study with AIS subjects recruited. Biplanar spine radiographs were performed using an EOS imaging system with coronal Cobb angle (CCA) determined. The angle of trunk rotation (ATR) was measured using Scoliometer. SpineScan3D was employed to assess the axial rotation of subjects' back at forward bending, recorded as surface tilt angle (STA). Intra- and inter-examiner repeats were conducted to evaluate the reliability of SpineScan3D.

RESULTS

97 AIS patients were recruited. Intra- and inter-examiner reliability of STA measures were good to excellent in major thoracic and lumbar curves (p < 0.001). A strong correlation was found between STA and ATR measures in both curve types (p < 0.001) with a standard error of the ATR estimate of between 1 and 2 degrees from linear regression models (R squared: 0.8-0.9, p < 0.001). A similar correlation with CCA was found for STA and ATR measures (r: 0.5-0.6, p < 0.002), which also demonstrated a similar sensitivity (72%-74%) and specificity (62%-77%) for diagnosing moderate to severe curves.

CONCLUSION

SpineScan3D is a handheld surface scanner with a potential of wide applications in subjects with AIS. The current study indicated that SpineScan3D is reliable and valid for measuring trunk rotation in AIS subjects, comparable to Scoliometer. Further studies are planned to investigate its measurements in coronal and sagittal planes and the potential of this device as a screening and monitoring tool.

TRIAL REGISTRATION NUMBER (DATE OF REGISTRATION)

HKUCTR-2288 (06 Dec 2017).

LEVEL OF EVIDENCE

Level III.

Spine Deformity Assessment for Scoliosis Diagnostics Utilizing Image Processing Techniques: A Systematic Review

Spinal deformity refers to a range of disorders that are defined by anomalous curvature of the spine and may be classified as scoliosis, hypo/hyperlordosis, or hypo/hyperkyphosis. Among these, scoliosis stands out as the most common type of spinal deformity in human beings, and it can be distinguished by abnormal lateral spine curvature accompanied by axial rotation. Accurate identification of spinal deformity is crucial for a person’s diagnosis, and numerous assessment methods have been developed by researchers. Therefore, the present study aims to systematically review the recent works on spinal deformity assessment for scoliosis diagnosis utilizing image processing techniques. To gather relevant studies, a search strategy was conducted on three electronic databases (Scopus, ScienceDirect, and PubMed) between 2012 and 2022 using specific keywords and focusing on scoliosis cases. A total of 17 papers fully satisfied the established criteria and were extensively evaluated. Despite variations in methodological designs across the studies, all reviewed articles obtained quality ratings higher than satisfactory. Various diagnostic approaches have been employed, including artificial intelligence mechanisms, image processing, and scoliosis diagnosis systems. These approaches have the potential to save time and, more significantly, can reduce the incidence of human error. While all assessment methods have potential in scoliosis diagnosis, they possess several limitations that can be ameliorated in forthcoming studies. Therefore, the findings of this study may serve as guidelines for the development of a more accurate spinal deformity assessment method that can aid medical personnel in the real diagnosis of scoliosis.

Development and validation of a semi-automated measurement tool for calculating consistent and reliable surface metrics describing cosmesis in Adolescent Idiopathic Scoliosis

Adolescent Idiopathic Scoliosis (AIS) is a 3D spine deformity that also causes ribcage and torso distortion. While clinical metrics are important for monitoring disorder progression, patients are often most concerned about their cosmesis. The aim of this study was to automate the quantification of AIS cosmesis metrics, which can be measured reliably from patient-specific 3D surface scans (3DSS). An existing database of 3DSS for pre-operative AIS patients treated at the Queensland Children's Hospital was used to create 30 calibrated 3D virtual models. A modular generative design algorithm was developed on the Rhino-Grasshopper software to measure five key AIS cosmesis metrics from these models-shoulder, scapula and hip asymmetry, torso rotation and head-pelvis shift. Repeat cosmetic measurements were calculated from user-selected input on the Grasshopper graphical interface. InterClass-correlation (ICC) was used to determine intra- and inter-user reliability. Torso rotation and head-pelvis shift measurements showed excellent reliability (> 0.9), shoulder asymmetry measurements showed good to excellent reliability (> 0.7) and scapula and hip asymmetry measurements showed good to moderate reliability (> 0.5). The ICC results indicated that experience with AIS was not required to reliably measure shoulder asymmetry, torso rotation and head-pelvis shift, but was necessary for the other metrics. This new semi-automated workflow reliably characterises external torso deformity, reduces the dependence on manual anatomical landmarking, and does not require bulky/expensive equipment.

Predicting spinal column profile from surface topography via 3D non-contact surface scanning

INTRODUCTION

3D Non-Contact surface scanning (3DSS) is used in both biomechanical and clinical studies to capture accurate 3D images of the human torso, and to better understand the shape and posture of the spine-both healthy and pathological. This study sought to determine the efficacy and accuracy of using 3DSS of the posterior torso, to determine the curvature of the spinal column in the lateral lying position.

METHODS

A cohort of 50 healthy adults underwent 3DSS and Magnetic Resonance Imaging (MRI) to correlate the contours of the external spine surface with the internal spinal column. The correlation analysis was composed of two phases: (1) MRI vertebral points vs MRI external spine surface markers; and (2) MRI external spine surface markers vs 3DSS external spine surface markers. The first phase compared the profiles of fiducial markers (vitamin capsules) adhered to the skin surface over the spinous processes against the coordinates of the spinous processes-assessing the linear distance between the profiles, and similarity of curvature, in the sagittal and coronal planes. The second phase compared 3DSS external spine surface markers with the MRI external spine surface markers in both planes, with further qualitative assessment for postural changes.

RESULTS

The distance between the MRI vertebral points and MRI external spine surface markers showed strong statistically significant correlation with BMI in both sagittal and coronal planes. Kolmogorov-Smirnov (KS) tests showed similar no significant difference in curvature, k, in almost all participants on both planes. In the second phase, the coronal 3DSS external spine surface profiles were statistically different to the MRI external spine surface markers in 44% of participants. Qualitative assessment showed postural changes between MRI and 3DSS measurements in these participants.

CONCLUSION

These study findings demonstrate the utility and accuracy of using anatomical landmarks overlaid on the spinous processes, to identify the position of the spinal bones using 3DSS. Using this method, it will be possible to predict the internal spinal curvature from surface topography, provided that the thickness of the overlaying subcutaneous adipose layer is considered, thus enabling postural analysis of spinal shape and curvature to be carried out in biomechanical and clinical studies without the need for radiographic imaging.

Reliability and Validity of Scoliosis Measurements Obtained with Surface Topography Techniques: A Systematic Review

BACKGROUND

Surface topography (ST) is one of the methods in scoliosis assessment. This study aimed to systematically review the reliability and validity of the ST measurements for assessing scoliosis.

METHODS

A literature search of four databases was performed and is reported following PRISMA guidelines. The methodological quality was evaluated using Brink and Louw appraisal tool and data extraction was performed. The results were analyzed and synthesized qualitatively using the level of evidence method.

RESULTS

Eighteen studies were included and analyzed. Four were evaluated for reliability, six for validity, and eight for reliability and validity. The methodological quality of fourteen studies was high. Good to excellent intra-investigator reliability was shown on asymmetry, sagittal, horizontal, and most frontal ST measurements (evidence level: strong). Asymmetry and most frontal, sagittal, horizontal ST measurements showed good to excellent inter-investigator reliability (evidence level: moderate). When comparing corresponding ST and radiological measurements, good to strong validity was shown on most frontal, sagittal, and asymmetry measurements (evidence level: strong). Formetric measurements had good intra-investigator reliability and validity (evidence level: strong).

CONCLUSIONS

Most asymmetry, sagittal, and frontal ST measurements showed satisfactory reliability and validity. Horizontal ST measurements showed good reliability and poor validity. The ST technique may have great potential in assessing scoliosis, especially in reducing radiation exposure and performing cosmetic assessments.

Precision of a Hand-Held 3D Surface Scanner in Dry and Wet Skeletal Surfaces: An Ex Vivo Study

Three-dimensional surface scans of skeletal structures have various clinical and research applications in medicine, anthropology, and other relevant fields. The aim of this study was to test the precision of a widely used hand-held surface scanner and the associated software's 3D model generation-error in both dry and wet skeletal surfaces. Ten human dry skulls and ten mandibles (dry and wet conditions) were scanned twice with an industrial scanner (Artec Space Spider) by one operator. Following a best-fit superimposition of corresponding surface model pairs, the mean absolute distance (MAD) between them was calculated on ten anatomical regions on the skulls and six on the mandibles. The software's 3D model generation process was repeated for the same scan of four dry skulls and four mandibles (wet and dry conditions), and the results were compared in a similar manner. The median scanner precision was 31 μm for the skulls and 25 μm for the mandibles in dry conditions, whereas in wet conditions it was slightly lower at 40 μm for the mandibles. The 3D model generation-error was negligible (range: 5-10 μm). The Artec Space Spider scanner exhibits very high precision in the scanning of dry and wet skeletal surfaces.

Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation

Background

This study evaluates the conformity of using a computer vision-based posture analysis system as a screening assessment for postural deformity detection in the spine that is easily applicable to clinical practice.

Methods

One hundred forty participants were enrolled for screening of the postural deformation. Factors that determine the presence or absence of spinal deformation, such as shoulder height difference (SHD), pelvic height difference (PHD), and leg length mismatch (LLD), were used as parameters for the clinical decision support system (CDSS) using a commercial computer vision-based posture analysis system. For conformity analysis, the probability of postural deformation provided by CDSS, the Cobb angle, the PHD, and the SHD was compared and analyzed between the system and radiographic parameters. A principal component analysis (PCA) of the CDSS and correlation analysis were conducted.

Results

The Cobb angles of the 140 participants ranged from 0° to 61°, with an average of 6.16° ± 8.50°. The postural deformation of CDSS showed 94% conformity correlated with radiographic assessment. The conformity assessment results were more accurate in the participants of postural deformation with normal (0–9°) and mild (10–25°) ranges of scoliosis. The referenced SHD and the SHD of the CDSS showed statistical significance (p < 0.001) on a paired t-test. SHD and PHD for PCA were the predominant factors (PC1 SHD for 79.97%, PC2 PHD for 19.86%).

Conclusion

The CDSS showed 94% conformity for the screening of postural spinal deformity. The main factors determining diagnostic suitability were two main variables: SHD and PHD. In conclusion, a computer vision-based posture analysis system can be utilized as a safe, efficient, and convenient CDSS for early diagnosis of spinal posture deformation, including scoliosis.