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技术说明:ROdiomiX:一种经过验证的用于放射肿瘤学中医学图像放射组学分析的软件。

Technical Note: ROdiomiX: A validated software for radiomics analysis of medical images in radiation oncology.

作者信息

Bagher-Ebadian Hassan, Chetty Indrin J

机构信息

Department of Radiation Oncology, Henry Ford Health System, 2799 West Grand Blvd, Detroit, MI, 48202, USA.

出版信息

Med Phys. 2021 Jan;48(1):354-365. doi: 10.1002/mp.14590. Epub 2020 Dec 4.

Abstract

PURPOSE

This study introduces an in-house-designed software platform (ROdiomiX) for the radiomics analysis of medical images in radiation oncology. ROdiomiX is a MATLAB-based framework for the computation of radiomic features and feature aggregation techniques in compliance with the Image-Biomarker-Standardization-Initiative (IBSI) guidelines, which includes preprocessing protocols and quantitative benchmark results for analysis of computational phantom images.

METHODS AND MATERIALS

The ROdiomiX software system consists of a series of computation cores implemented on the basis of the guidelines proposed by the IBSI. It is capable of quantitative computation of the following 11 different feature categories: Local-Intensity, Intensity-Histogram, Intensity-Based-Statistical, Intensity-Volume-Histogram, Gray-Level-Co-occurrence, Gray-Level-Run-Length, Gray-Level-Size-Zone, Gray-Level-Distance-Zone, Neighborhood-Grey-Tone-Difference, Neighboring-Grey-Level-Dependence, and Morphological feature. ROdiomiX was validated against benchmark values for the IBSI 3D digital phantom, as well as one designed in-house (HFH). The intraclass correlation coefficient (ICC) for estimating the degree of absolute agreement between ROdiomiX computation and benchmark values for different features at the 95% confidence level (CL) was used for comparison.

RESULTS

Among the 11 feature categories with 149 total features including 10 different feature aggregation methods (following the IBSI guidelines), the percent difference between absolute feature values computed by the ROdiomiX software and benchmark values reported for IBSI and HFH digital phantoms were 0.14% + 0.43% and 0.11% + 0.27%, respectively. The ICC values were >0.997 for all ten feature categories for both the IBSI and HFH digital phantoms.

CONCLUSION

The authors successfully developed a platform for computation of quantitative radiomic features. The image preprocessing and computational software cores were designed following the procedures specified by the IBSI. Benchmarking testing was in excellent agreement against the IBSI- and HFH-designed computational phantoms.

摘要

目的

本研究介绍了一种内部设计的软件平台(ROdiomiX),用于放射肿瘤学中医学图像的放射组学分析。ROdiomiX是一个基于MATLAB的框架,用于计算放射组学特征和特征聚合技术,符合图像生物标志物标准化倡议(IBSI)指南,其中包括用于分析计算体模图像的预处理协议和定量基准结果。

方法和材料

ROdiomiX软件系统由一系列根据IBSI提出的指南实现的计算核心组成。它能够对以下11种不同的特征类别进行定量计算:局部强度、强度直方图、基于强度的统计、强度体积直方图、灰度共生矩阵、灰度行程长度、灰度大小区域、灰度距离区域、邻域灰度差异、相邻灰度级依赖性和形态学特征。ROdiomiX针对IBSI 3D数字体模以及内部设计的一个体模(HFH)的基准值进行了验证。使用类内相关系数(ICC)来估计ROdiomiX计算与不同特征在95%置信水平(CL)下的基准值之间的绝对一致性程度,以进行比较。

结果

在包括10种不同特征聚合方法(遵循IBSI指南)的总共149个特征的11个特征类别中,ROdiomiX软件计算的绝对特征值与IBSI和HFH数字体模报告的基准值之间的百分比差异分别为0.14%±0.43%和0.11%±0.27%。IBSI和HFH数字体模的所有十个特征类别的ICC值均>0.997。

结论

作者成功开发了一个用于计算定量放射组学特征的平台。图像预处理和计算软件核心是按照IBSI规定的程序设计的。基准测试与IBSI和HFH设计的计算体模高度一致。

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