使用MRI分割技术监测脑肿瘤对治疗的反应。

Monitoring brain tumor response to therapy using MRI segmentation.

作者信息

Vaidyanathan M, Clarke L P, Hall L O, Heidtman C, Velthuizen R, Gosche K, Phuphanich S, Wagner H, Greenberg H, Silbiger M L

机构信息

Department of Radiology, University of South Florida, Tampa 33612, USA.

出版信息

Magn Reson Imaging. 1997;15(3):323-34. doi: 10.1016/s0730-725x(96)00386-4.

DOI:10.1016/s0730-725x(96)00386-4

PMID:9201680

Abstract

The performance evaluation of a semi-supervised fuzzy c-means (SFCM) clustering method for monitoring brain tumor volume changes during the course of routine clinical radiation-therapeutic and chemo-therapeutic regimens is presented. The tumor volume determined using the SFCM method was compared with the volume estimates obtained using three other methods: (a) a k nearest neighbor (kNN) classifier, b) a grey level thresholding and seed growing (ISG-SG) method and c) a manual pixel labeling (GT) method for ground truth estimation. The SFCM and kNN methods are applied to the multispectral, contrast enhanced T1, proton density, and T2 weighted, magnetic resonance images (MRI) whereas the ISG-SG and GT methods are applied only to the contrast enhanced T1 weighted image. Estimations of tumor volume were made on eight patient cases with follow-up MRI scans performed over a 32 week interval during treatment. The tumor cases studied include one meningioma, two brain metastases and five gliomas. Comparisons with manually labeled ground truth estimations showed that there is a limited agreement between the segmentation methods for absolute tumor volume measurements when using images of patients after treatment. The average intraobserver reproducibility for the SFCM, kNN and ISG-SG methods was found to be 5.8%, 6.6% and 8.9%, respectively. The average of the interobserver reproducibility of these methods was found to be 5.5%, 6.5% and 11.4%, respectively. For the measurement of relative change of tumor volume as required for the response assessment, the multi-spectral methods kNN and SFCM are therefore preferred over the seedgrowing method.

摘要

本文介绍了一种半监督模糊c均值（SFCM）聚类方法在常规临床放射治疗和化学治疗方案过程中监测脑肿瘤体积变化的性能评估。将使用SFCM方法确定的肿瘤体积与使用其他三种方法获得的体积估计值进行比较：（a）k最近邻（kNN）分类器，（b）灰度阈值化和种子生长（ISG-SG）方法，以及（c）用于地面真值估计的手动像素标记（GT）方法。SFCM和kNN方法应用于多光谱、对比增强T1、质子密度和T2加权磁共振图像（MRI），而ISG-SG和GT方法仅应用于对比增强T1加权图像。对8例患者进行了肿瘤体积估计，在治疗期间的32周间隔内进行了随访MRI扫描。研究的肿瘤病例包括1例脑膜瘤、2例脑转移瘤和5例胶质瘤。与手动标记的地面真值估计进行比较表明，在使用治疗后患者的图像进行绝对肿瘤体积测量时，分割方法之间的一致性有限。发现SFCM、kNN和ISG-SG方法的平均观察者内再现性分别为5.8%、6.6%和8.9%。这些方法的平均观察者间再现性分别为5.5%、6.5%和11.4%。因此，对于反应评估所需的肿瘤体积相对变化的测量，多光谱方法kNN和SFCM比种子生长方法更可取。