Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.
Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.
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DOI：
10.1002/mrm.26860
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发表时间：
2018-04
影响因子：
3.3
通讯作者：
Parker GJM
中科院分区：
文献类型：
--
作者：
Featherstone AK;O'Connor JPB;Little RA;Watson Y;Cheung S;Babur M;Williams KJ;Matthews JC;Parker GJM
以前的工作表明，结合动态对比增强（DCE）-MRI和氧增强（OE）-MRI二元增强图可以识别肿瘤缺氧。目前的工作提出了一种基于聚类DCE/OE-MRI数据的新型数据驱动方法，用于映射组织氧合和灌注异质性。对9例U87（胶质母细胞瘤）和7例Calu 6（非小细胞肺癌）小鼠异种移植瘤进行了DCE-MRI和OE-MRI。曲线下面积和主成分分析特征分别使用高斯混合模型计算和聚类。计算评估指标以确定最佳特征集和聚类数。将输出与先前的非数据驱动方法进行定量比较。最佳方法在数据中定位了六个鲁棒可识别的聚类，产生了边缘核心结构中空间连续区域的肿瘤区域图，表明了生物学基础。平均簇内增强曲线显示生理上不同的、直观的增强动力学。定位了DCE/OE-MRI增强不匹配的区域，体素分类与之前的非数据驱动方法一致（Cohen kappa = 0.61，比例一致性= 0.75）。所提出的方法定位了与先前发表的DCE/OE-MRI增强二值化方法相似的区域，但对肿瘤内氧合和灌注进行了更精细的分割。这可能有助于了解肿瘤微环境及其异质性。Magn Reson Med 79：2236-2245，2018。© 2017 The Authors Magnetic Resonance in Medicine出版由Wiley Periodicals，Inc.国际医学磁共振学会（International Society for Magnetic Resonance in Medicine）这是一个开放获取的条款下的知识共享署名许可证，允许使用，分发和复制在任何媒体上，只要原始作品是适当的引用。
Previous work has shown that combining dynamic contrast‐enhanced (DCE)‐MRI and oxygen‐enhanced (OE)‐MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data‐driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE‐MRI data. DCE‐MRI and OE‐MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non‐small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data‐driven approach. The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim‐core structure, suggesting a biological basis. Mean within‐cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE‐MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data‐driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75). The proposed method locates similar regions to the previous published method of binarization of DCE/OE‐MRI enhancement, but renders a finer segmentation of intra‐tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236–2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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DOI：
10.1158/1078-0432.ccr-14-0990
发表时间：
2015-01-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
O'Connor JP;Rose CJ;Waterton JC;Carano RA;Parker GJ;Jackson A
通讯作者：
Jackson A
影响因子：
3.3
作者：
Beeman SC;Shui YB;Perez-Torres CJ;Engelbach JA;Ackerman JJ;Garbow JR
通讯作者：
Garbow JR
影响因子：
3.3
作者：
Henning, Erica C.;Azuma, Chieko;Helmer, Karl G.
通讯作者：
Helmer, Karl G.
影响因子：
4.4
作者：
Burrell, Jake S.;Walker-Samuel, Simon;Robinson, Simon P.
通讯作者：
Robinson, Simon P.
影响因子：
3.3
作者：
Hallac, Rami R.;Zhou, Heling;Pidikiti, Rajesh;Song, Kwang;Stojadinovic, Strahinja;Zhao, Dawen;Solberg, Timothy;Peschke, Peter;Mason, Ralph P.
通讯作者：
Mason, Ralph P.