Semi-automated and automated glioma grading using dynamic susceptibility-weighted contrast-enhanced perfusion MRI relative cerebral blood volume measurements
Semi-automated and automated glioma grading using dynamic susceptibility-weighted contrast-enhanced perfusion MRI relative cerebral blood volume measurements
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DOI：
10.1259/bjr/13908936
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发表时间：
2012-12-01
影响因子：
2.6
通讯作者：
Hoggard, N.
中科院分区：
文献类型：
--
作者：
Friedman, S. N.;Bambrough, P. J.;Hoggard, N.
目的：尽管MRI在脑肿瘤诊断中的作用已经确立，但组织病理学评估仍然是临床使用的技术，尤其是对于神经胶质瘤组。相对脑血容量（rCBV）是一种动态磁共振成像（MRI）参数，已被证明与肿瘤分级相关，但评估需要专家，而且耗时。我们开发的分析软件，以确定胶质瘤分级灌注rCBV扫描的方式，是快速，简便，不需要一个专业operator.Methods：MRI灌注数据从47例不同组织病理学级别的胶质瘤进行了分析与定制设计的软件。半自动化分析由专家和非专家操作员分别确定与肿瘤对应的最大rCBV值。通过计算rCBV值的平均值、标准差、中位数、众数、偏度和峰度进行自动直方图分析。所有的值进行了比较，与组织病理学评估的肿瘤grade.Results：专家和非专家观察员测量之间的强相关性被发现。显着不同的值之间的肿瘤等级使用半自动化和自动化技术，与以前的结果一致。原始（未标准化）数据单像素最大rCBV半自动分析值与胶质瘤分级的相关性最强。标准偏差的原始数据有最强的相关性的automated analysis.Conclusion：半自动计算的原始最大rCBV值是肿瘤分级的最佳指标，并不需要一个专业operator.Advances的知识：半自动和自动MRI灌注技术提供了可行的非侵入性替代活检神经胶质瘤肿瘤分级。
Objective: Despite the established role of MRI in the diagnosis of brain tumours, histopathological assessment remains the clinically used technique, especially for the glioma group. Relative cerebral blood volume (rCBV) is a dynamic susceptibility-weighted contrast-enhanced perfusion MRI parameter that has been shown to correlate to tumour grade, but assessment requires a specialist and is time consuming. We developed analysis software to determine glioma gradings from perfusion rCBV scans in a manner that is quick, easy and does not require a specialist operator.Methods: MRI perfusion data from 47 patients with different histopathological grades of glioma were analysed with custom-designed software. Semi-automated analysis was performed with a specialist and non-specialist operator separately determining the maximum rCBV value corresponding to the tumour. Automated histogram analysis was performed by calculating the mean, standard deviation, median, mode, skewness and kurtosis of rCBV values. All values were compared with the histopathologically assessed tumour grade.Results: A strong correlation between specialist and non-specialist observer measurements was found. Significantly different values were obtained between tumour grades using both semi-automated and automated techniques, consistent with previous results. The raw (unnormalised) data single-pixel maximum rCBV semi-automated analysis value had the strongest correlation with glioma grade. Standard deviation of the raw data had the strongest correlation of the automated analysis.Conclusion: Semi-automated calculation of raw maximum rCBV value was the best indicator of tumour grade and does not require a specialist operator.Advances in knowledge: Both semi-automated and automated MRI perfusion techniques provide viable non-invasive alternatives to biopsy for glioma tumour grading.