Hurtado-Aviles José, Roca-González Joaquín, Kurochka Konstantsin Sergeevich, Sanz-Mengibar Jose Manuel, Santonja-Medina Fernando
Faculty of Medicine, University of Murcia, Murcia, Spain.
Technical University of Cartagena (UPCT), Technical School of Industrial Engineering, Cartagena, Spain.
Radiol Res Pract. 2021 Feb 5;2021:5523775. doi: 10.1155/2021/5523775. eCollection 2021.
Axial vertebral rotation (AVR) is a basic parameter in the study of idiopathic scoliosis and on physical two-dimensional images. Raimondi's tables are the most used method in the quantification of AVR. The development of computing technologies has enabled the creation of computer-aided or automated diagnosis systems (CADx) with which measurement on medical images can be carried out more quickly, simply, and with less intra and interobserver variabilities than manual methods. Although there are several publications dealing with the measurement of AVR in CADx systems, none of them provides information on the equation or algorithm used for the measurement applying Raimondi's method. . The aim of this work is to perform a mathematical modelling of the data contained in Raimondi's tables that enable the Raimondi method to be used in digital medical images more precisely and in a more exact manner.
Data from Raimondi's tables were tabulated on a first step. After this, each column of Raimondi's tables containing values corresponding to vertebral body width () were adjusted to a curve determined by AVR = (). Third, representative values of each rotation divided by were obtained through the equation of each column . In a fourth step, a regression line was fitted to the data in each row, and from its equation, the mean value of the / distribution is calculated (value corresponding to the central column, = 45). Finally, a curve was adjusted to the obtained data using the least squares method. . Our mathematical equation allows the Raimondi method to be used in digital images of any format in a more accurate and simplified approach. This equation can be easily and freely implemented in any CADx system to quantify AVR, providing a more precise use of Raimondi's method, as well as being used in traditional manual measurement as it is performed with Raimondi tables.
椎体轴向旋转（AVR）是特发性脊柱侧凸研究以及二维体格检查中的一个基本参数。雷蒙迪表是AVR量化中最常用的方法。计算技术的发展使得计算机辅助或自动诊断系统（CADx）得以创建，借助该系统，医学图像测量能够比手动方法更快、更简便地进行，且观察者内和观察者间的变异性更小。尽管有几篇关于CADx系统中AVR测量的出版物，但它们均未提供关于应用雷蒙迪方法进行测量所使用的方程或算法的信息。本研究的目的是对雷蒙迪表中所包含的数据进行数学建模，以使雷蒙迪方法能够更精确、更准确地应用于数字医学图像。
第一步，将雷蒙迪表中的数据制成表格。此后，雷蒙迪表中每列包含对应椎体宽度（）值的数据被调整至由AVR = （）确定的曲线。第三步，通过每列的方程获得每个旋转除以 后的代表值。第四步，对每行数据拟合一条回归线，并根据其方程计算 / 分布的平均值（对应中心列的值， = 45）。最后，使用最小二乘法对所得数据拟合一条曲线。我们的数学方程允许以更准确和简化的方法将雷蒙迪方法应用于任何格式的数字图像。该方程可轻松、免费地在任何CADx系统中实现，以量化AVR，从而更精确地使用雷蒙迪方法，并且如同使用雷蒙迪表进行传统手动测量一样，也可用于传统手动测量。
