背景:统计形状模型的测量误差的程度尚不清楚,该模型基于关节盂高度预测天然关节盂宽度,以随后确定关节盂前骨丢失的量。因此,本研究的目的是(1)建立基于三维计算机断层扫描(3D-CT)测量的关节盂高度和宽度的统计形状模型,并通过测量误差确定准确性;(2)确定现有3D-CT统计形状模型的测量误差.
方法:一项回顾性横断面研究包括2007年至2022年在东北大学医院和附属医院接受创伤性肩关节前脱位初次手术治疗之前接受CT成像的所有连续患者。如果不稳定是单侧的,并且可以对受伤和对侧未受伤的肩膀进行CT扫描,则包括患者。创建3D分割并测量受伤侧和对侧未受伤侧的关节盂高度和宽度(金标准)。通过测量误差确定精度,定义为与天然关节盂宽度(对侧未损伤的关节盂)的百分比误差偏差,计算如下:测量误差=[(用统计形状模型估计的关节盂宽度-天然关节盂宽度)/天然关节盂宽度]×100%。根据公式进行线性回归分析以创建基于关节盂高度的统计形状模型:天然关节盂宽度=a×关节盂高度+b。
结果:诊断和程序代码确定了105名患者,其中69人(66%)符合入选条件。关节盂高度与天然关节盂宽度有很强的相关性(r=0.80)。基于该队列的线性回归公式如下:天然关节盂宽度=0.75×关节盂高度-0.61,并且其显示绝对平均测量误差为5%±4%。Giles等人的公式,Chen等人和Rayes等人的绝对平均测量误差为10%±7%,6%±5%,9%±6%,分别。
结论:基于关节盂高度估计天然关节盂宽度的统计形状模型显示出不可接受的测量误差,尽管相关性很高。因此,在使用这些模型确定关节盂骨丢失百分比时,建议非常谨慎.为了最大限度地减少由形态差异引起的错误,首选使用对侧作为参考的方法。
BACKGROUND: The extent of measurement errors of statistical shape models that predict native glenoid width based on glenoid height to subsequently determine the amount of anterior glenoid bone loss is unclear. Therefore, the aim of this
study was to (1) create a statistical shape model based on glenoid height and width measured on 3-dimensional computed tomography (3D-CT) and determine the accuracy through measurement errors and (2) determine measurement errors of existing 3D-CT statistical shape models.
METHODS: A retrospective cross-sectional
study included all consecutive patients who underwent CT imaging before undergoing primary surgical treatment of traumatic anterior shoulder dislocation between 2007 and 2022 at the Tohoku University Hospital and affiliated hospitals. Patients were included when instability was unilateral and CT scans of both the injured and contralateral uninjured shoulder were available. 3D segmentations were created and glenoid height and width of the injured and contralateral uninjured side (gold standard) were measured. Accuracy was determined through measurement errors, which were defined as a percentage error deviation from native glenoid width (contralateral uninjured glenoid), calculated as follows: measurement error = [(estimated glenoid width with a statistical shape model - native glenoid width) / native glenoid width] × 100%. A linear regression analysis was performed to create a statistical shape model based on glenoid height according to the formula: native glenoid width = a × glenoid height + b.
RESULTS: The diagnosis and procedure codes identified 105 patients, of which 69 (66%) were eligible for inclusion. Glenoid height demonstrated a very strong correlation (r = 0.80) with native glenoid width. The linear regression formula based on this cohort was as follows: native glenoid width = 0.75 × glenoid height - 0.61, and it demonstrated an absolute average measurement error of 5% ± 4%. The formulas by Giles et al, Chen et al and Rayes et al demonstrated absolute average measurement errors of 10% ± 7%, 6% ± 5%, and 9% ± 6%, respectively.
CONCLUSIONS: Statistical shape models that estimate native glenoid width based on glenoid height demonstrate unacceptable measurement errors, despite a high correlation. Therefore, great caution is advised when using these models to determine glenoid bone loss percentage. To minimize errors caused by morphologic differences, preference goes to methods that use the contralateral side as reference.