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骨转移患者骨髓放疗后改变的磁共振成像及图像分析

Magnetic resonance imaging and image analysis of post - radiation changes of bone marrow in patients with skeletal metastases.

作者信息

Romanos O, Solomou E, Georgiadis P, Kardamakis D, Siablis D

机构信息

University Hospital of Patras, Department of Clinical Radiology, MRI Unit, Rion - Patras, Greece.

出版信息

J BUON. 2013 Jul-Sep;18(3):788-94.

Abstract

PURPOSE

To evaluate the post-radiation lesions of the bone marrow with magnetic resonance imaging (MRI) and image analysis in patients with bone metastases undergoing radiation therapy (RT).

METHODS

Thirty-five patients with bone metastases were studied from June 2008 to December 2010. All patients had osseous metastases from various primary malignancies and underwent palliative RT. MRI was performed in a Philips Gyroscan Intera 1T scanner at the beginning of RT and 12-18 days later. T1-TSE, T2-TSE and short tau inversion recovery (STIR) sequences were used. All images obtained were evaluated for early post-radiation lesions. Additionally, 1st and 2nd order textural features were extracted from these images and were introduced into a probabilistic neural network (PNN) classifier in order to create an automated classification system for those lesions.

RESULTS

Changes of signal intensity in T1-TSE, T2-TSE and STIR sequences were evaluated for the presence of edema, fatty conversion of the bone marrow or areas of hemorrhage within the limits of the irradiated area. The automated classification system showed positive results in correctly discriminating the post-radiation lesions that MRI revealed. The overall classification accuracy for discriminating between pre-radiation and post-radiation lesions was 93.2%. Furthermore, the overall classification accuracy for discriminating between post-radiation lesions was 86.67%.

CONCLUSION

It seems that MRI can evaluate the degree of early therapy-induced bone marrow lesions observed during the first 18 days from the beginning of RT. The proposed neural network-based classification system might be used as an assisting tool for the characterization of these lesions.

摘要

目的

利用磁共振成像(MRI)及图像分析评估接受放射治疗(RT)的骨转移患者放疗后的骨髓损伤情况。

方法

对2008年6月至2010年12月期间的35例骨转移患者进行研究。所有患者均有来自各种原发性恶性肿瘤的骨转移,并接受了姑息性放疗。在放疗开始时及12 - 18天后,使用飞利浦Gyroscan Intera 1T扫描仪进行MRI检查。采用T1加权快速自旋回波(T1-TSE)、T2加权快速自旋回波(T2-TSE)和短tau反转恢复(STIR)序列。对所有获得的图像进行早期放疗后损伤评估。此外,从这些图像中提取一阶和二阶纹理特征,并将其引入概率神经网络(PNN)分类器,以创建针对这些损伤的自动分类系统。

结果

评估T1-TSE、T2-TSE和STIR序列中信号强度的变化,以确定照射区域内是否存在水肿、骨髓脂肪转化或出血区域。自动分类系统在正确区分MRI显示的放疗后损伤方面取得了积极结果。区分放疗前和放疗后损伤的总体分类准确率为93.2%。此外,区分放疗后损伤的总体分类准确率为86.67%。

结论

似乎MRI可以评估放疗开始后前18天内观察到的早期治疗引起的骨髓损伤程度。所提出的基于神经网络的分类系统可作为表征这些损伤的辅助工具。

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