Department of Clinical Radiology-Grosshadern, LMU Ludwig Maximilian University of Munich, Munich, Germany.
Invest Radiol. 2010 Apr;45(4):165-73. doi: 10.1097/RLI.0b013e3181cd74e2.
Oxygen-enhanced MRI (O2-MRI) is frequently based on a block paradigm consisting of a series of consecutive T1-weighted scans acquired during alternating blocks with inhalation of room air and of pure oxygen. This design results in a complex signal-time course for each pixel, which displays the oxygen wash-in and wash-out processes and provides spatially resolved information about the lung function. The purpose of the present study was to optimize the signal-time-course analysis to extract (pixelwise) the maximum amount of information from the acquired data, and to introduce an appropriate cross-correlation approach for data sets containing the oxygen wash-in and wash-out periods.
O2-MRI data of 11 healthy volunteers were acquired with a multislice inversion-recovery single-shot turbo-spin-echo sequence at 1.5 Tesla; lung and spleen were manually segmented on all 44 acquired slices. Six different model functions were pixelwise fitted to the data and compared using the Akaike information criterion. Four different reference functions were compared for cross-correlation analysis.
The optimal model function is a piecewise exponential function (median enhancement in lung/spleen: 16.3%/14.8%) with different time constants for wash-in (29.4 seconds/72.7 seconds) and wash-out (25.1 seconds/29.6 seconds). As a new parameter, it contains the delay between switching the gas supply and the onset of the signal change (4.8 seconds/24.5 seconds). Optimal cross-correlation results were obtained with a piecewise exponential reference function, which was temporally shifted to maximize the correlation, yielding median correlation coefficients of 0.694 and 0.878, median time delays of 7.5 seconds and 38.6 seconds, and median fractions of oxygen-activated pixels of 83.6% and 92.2% in the lung and the spleen, respectively.
It was demonstrated that the pixelwise assessment of O2-MRI data are optimally performed with piecewise exponential functions. Cross-correlation analysis with a piecewise exponential reference function results in significantly higher fractions of oxygen-activated pixels than with rectangular functions.
氧增强磁共振成像（O2-MRI）通常基于一个块范式，由一系列连续的 T1 加权扫描组成，这些扫描是在吸入室气和纯氧的交替块中获得的。这种设计导致每个像素的信号时间过程复杂，显示了氧气的冲洗和冲洗过程，并提供了关于肺功能的空间分辨信息。本研究的目的是优化信号时间过程分析，以从获得的数据中提取（像素）最大信息量，并引入一种合适的互相关方法，用于包含氧气冲洗和冲洗周期的数据。
在 1.5T 上使用多切片反转恢复单次涡轮自旋回波序列采集 11 名健康志愿者的 O2-MRI 数据；在所有 44 个采集切片上手动分割肺和脾脏。对数据进行了像素级拟合，并使用赤池信息量准则比较了六种不同的模型函数。比较了四种不同的参考函数进行互相关分析。
最优模型函数是分段指数函数（肺/脾增强中位数：16.3%/14.8%），其冲洗入和冲洗出的时间常数不同（29.4 秒/72.7 秒）和（25.1 秒/29.6 秒）。作为一个新参数，它包含了气体供应切换和信号变化开始之间的延迟（4.8 秒/24.5 秒）。使用分段指数参考函数获得了最佳的互相关结果，该参考函数在时间上进行了移位，以最大化相关性，得到了肺和脾脏的中位数相关系数分别为 0.694 和 0.878、中位数时间延迟分别为 7.5 秒和 38.6 秒以及中位数氧激活像素分数分别为 83.6%和 92.2%。
证明了分段指数函数可以最优地进行 O2-MRI 数据的像素级评估。与矩形函数相比，使用分段指数参考函数进行互相关分析可导致氧激活像素的分数显著更高。
