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开发并验证一种半自动测量工具,用于计算描述青少年特发性脊柱侧凸美容效果的一致且可靠的表面指标。

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

机构信息

Biomechanics and Spine Research Group (BSRG), Centre for Biomedical Technologies (CBT) at the Centre for Children's Health Research (CCHR), School of Mechanical Medical and Process Engineering, Queensland University of Technology, Brisbane, Australia.

Orthopaedics Department, Queensland Children's Hospital (QCH), Brisbane, Australia.

出版信息

Sci Rep. 2023 Apr 5;13(1):5574. doi: 10.1038/s41598-023-32614-4.

Abstract

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.

摘要

青少年特发性脊柱侧凸(AIS)是一种三维脊柱畸形,也会导致胸廓和躯干变形。虽然临床指标对于监测疾病进展很重要,但患者通常最关心的是他们的美容效果。本研究旨在实现 AIS 美容指标的自动量化,这些指标可以从患者特定的三维表面扫描(3DSS)中可靠地测量。使用昆士兰儿童医院接受治疗的术前 AIS 患者的现有 3DSS 数据库,创建了 30 个校准的 3D 虚拟模型。在 Rhino-Grasshopper 软件上开发了一种模块化生成设计算法,用于从这些模型中测量五个关键的 AIS 美容指标-肩膀、肩胛骨和臀部不对称、躯干旋转和头骨盆移位。从 Grasshopper 图形界面上用户选择的输入中计算了重复的美容测量。使用组内相关系数(ICC)来确定内部和用户之间的可靠性。躯干旋转和头骨盆移位测量值显示出极好的可靠性(>0.9),肩膀不对称测量值显示出良好到极好的可靠性(>0.7),肩胛骨和臀部不对称测量值显示出良好到中等的可靠性(>0.5)。ICC 结果表明,可靠地测量肩膀不对称、躯干旋转和头骨盆移位不需要 AIS 经验,但对于其他指标则需要。这种新的半自动工作流程可靠地描述了外部躯干畸形,减少了对手动解剖标志的依赖,并且不需要庞大/昂贵的设备。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d991/10076386/ed81f74a48cc/41598_2023_32614_Fig1_HTML.jpg

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