Droege R T, Wiener S N, Rzeszotarski M S
Radiology. 1984 Nov;153(2):425-33. doi: 10.1148/radiology.153.2.6484175.
A semi-empirical model was used to identify specific pulse sequences that cause most lesions to appear distinctly brighter than normal tissues in magnetic resonance (MR) images of the head. Clinical trials confirm the utility of these sequences for patient screening. As a result, a strategy for effective and efficient MR imaging of the head is proposed. The previously described gray-scale model has been modified to account for the effect of image noise. By means of computer simulation, 13,800 different hypothetical cerebral lesions were imaged with a variety of pulse sequences. A number of conclusions resulted. First, two sequences are expected to be sufficient to visualize most intracranial lesions, a "diagonal" SE sequence (e.g., SE 2500/80) and an IR sequence with a short inversion time (e.g., IR 1800/200). These sequences are orthogonal, i.e., lesions missed by one are likely to be detected by the other. Second, signal averaging the screening sequences is expected to be more effective than optimized sequences when lesion tissue parameters differ little from brain. Finally, the effectiveness of unaveraged screening sequences suggests that improved signal-to-noise ratio (SNR) is not necessary for the detection of most large lesions. Therefore, the increased SNR achievable through signal averaging or increased field strength might best be utilized to improve spatial resolution so that smaller lesions can be detected.
使用半经验模型来识别特定的脉冲序列,这些序列能使头部磁共振(MR)图像中的大多数病变比正常组织明显更亮。临床试验证实了这些序列在患者筛查中的实用性。因此,提出了一种用于头部有效且高效的MR成像策略。对先前描述的灰度模型进行了修改,以考虑图像噪声的影响。通过计算机模拟,用各种脉冲序列对13800个不同的假设性脑病变进行成像。得出了一些结论。首先,预计两个序列足以显示大多数颅内病变,一个“对角线”SE序列(例如,SE 2500/80)和一个具有短反转时间的IR序列(例如,IR 1800/200)。这些序列是正交的,即一个序列遗漏的病变很可能会被另一个序列检测到。其次,当病变组织参数与脑的差异不大时,对筛查序列进行信号平均预计比优化序列更有效。最后,未平均的筛查序列的有效性表明,检测大多数大病变不需要提高信噪比(SNR)。因此,通过信号平均或增加场强可实现的更高SNR最好用于提高空间分辨率,以便能够检测到更小的病变。