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Customized k-nearest neighbourhood analysis in the management of adolescent idiopathic scoliosis using 3D markerless asymmetry analysis.

Abstract：

:Adolescent Idiopathic Scoliosis (AIS) is a 3D spinal deformity characterized by curvature and rotation of the spine. Markerless surface topography (ST) analysis has been proposed for diagnosing and monitoring AIS to reduce the X-ray radiation exposure to patients. This method captures scans of the cosmetic deformity of the torso using visible, radiation-free light. The asymmetry analysis of the torso, represented as a deviation contour map with deviation patches outlining the areas of cosmetic asymmetries, has previously been shown to predict the severity and progression of the condition in comparison with radiographs, by using classification trees. While the classification results were promising, it was reported that some mild curves were erroneously diagnosed. Furthermore, this approach is highly sensitive to threshold values selected in the decision trees. Therefore, this study aims to define a custom Neighbourhood Classifier algorithm for AIS classification to improve the accuracy, sensitivity, and specificity of predicting curve severity and curve progression in AIS. Curve severity was predicted with 80% accuracy (sensitivity = 81%; specificity = 79%) for thoracic-thoracolumbar curves and 72% (sensitivity = 93%; specificity = 53%) for lumbar curves. This represents an improvement over the previous method with curve severity accuracies of 77% and 63% for thoracic-thoracolumbar and lumbar curves, respectively. Additionally, curve progression was predicted with 93% accuracy (sensitivity = 83%; specificity = 95%) representing a substantial improvement over the previous method with an accuracy of 59%. The current method has shown the potential to further reduce radiation exposure for AIS patients by avoiding X-rays for mild and non-progressive curves identified using ST analysis.

journal_name

Comput Methods Biomech Biomed Engin

journal_title

Computer methods in biomechanics and biomedical engineering

authors

Ghaneei M,Ekyalimpa R,Westover L,Parent EC,Adeeb S

doi

10.1080/10255842.2019.1584795

subject

Has Abstract

pub_date

2019-05-01 00:00:00

pages

696-705

issue

eissn

1025-5842

issn

1476-8259

journal_volume

pub_type

杂志文章

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Customized k-nearest neighbourhood analysis in the management of adolescent idiopathic scoliosis using 3D markerless asymmetry analysis.