Automated Voxel Placement: A Linux-based Suite of Tools for Accurate and Reliable Single Voxel Coregistration.
Automated Voxel Placement: A Linux-based Suite of Tools for Accurate and Reliable Single Voxel Coregistration.
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DOI：
10.17756/jnpn.2018-020
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发表时间：
2018
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影响因子：
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通讯作者：
Stanley JA
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文献类型：
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作者：
Woodcock EA;Arshad M;Khatib D;Stanley JA
单体素质子磁共振波谱 (1H MRS) 是研究体内神经化学的强大技术，但有一个经常被忽视的误差方差来源：扫描之间体素位置不一致。我们开发并评估了自动体素放置 (AVP) 程序，以实现准确可靠的 1H MRS 体素处方。 AVP 是一套基于 Linux 的程序，可促进自动化模板驱动的单体素配准。进行了三项研究来评估 AVP 对一个体素（左背外侧前额叶皮层）处方的影响。首先，我们评估了 AVP 对于扫描仪头部线圈内“极端”受试者头部位置/角度的鲁棒性。其次，招募受试者（N = 13）并进行 MR 扫描。手动体素处方 (n = 5) 与 AVP (n = 8) 进行对比。 AVP 受试者的子集 (n = 4) 完成了第二次扫描。第三，持续的数据收集（n = 16；招募用于一项单独的研究）有助于评估 AVP。体素放置精度被量化为每个受试者体素和模板体素之间的 3D 几何体素重叠百分比。可靠性被量化为每个时间点受试者之间以及完成两次扫描的受试者内的 3D 几何体素重叠百分比。结果表明，AVP 对于“极端”头部位置具有鲁棒性（与模板体素重叠 97.5% - 97.9%）。 AVP 比手动体素放置（67.7% ± 22.8% 重叠；ps<.05）明显更准确（基线和随访：96.2% ± 3.0% 和 97.6% ± 1.4% 重叠）。 AVP 在受试者内部（97.9%）和受试者之间（分别为 94.2% 和 97.2% 重叠；基线和随访）是可靠的。最后，持续的数据收集表明 AVP 是准确的 (96.0%)。这些试点研究表明，AVP 是自动化单体素配准的可行、准确且可靠的方法。
Single-voxel proton magnetic resonance spectroscopy (1H MRS) is a powerful technique for studying in vivo neurochemistry, but has an often-overlooked source of error variance: inconsistent voxel placement between scans. We developed and evaluated an Automated Voxel Placement (AVP) procedure for accurate and reliable 1H MRS voxel prescription. AVP is a suite of Linux-based programs that facilitate automated template-driven single-voxel coregistration. Three studies were conducted to evaluate AVP for prescription of one voxel: left dorsolateral prefrontal cortex. First, we evaluated how robust AVP was to ‘extreme’ subject head positions/angulations within the scanner head coil. Second, subjects (N = 13) were recruited and underwent MR scans. Manual voxel prescription (n = 5) was contrasted with AVP (n = 8). A subset of AVP subjects (n = 4) completed a second scan. Third, ongoing data collection (n = 16; recruited for a separate study) helped evaluate AVP. Voxel placement accuracy was quantified as 3D geometric voxel overlap percentage between each subject’s voxel and the template voxel. Reliability was quantified as 3D geometric voxel overlap percentage across subjects at each time point and within subjects who completed two scans. Results demonstrated that AVP was robust to ‘extreme’ head positions (97.5% - 97.9% overlap with the template voxel). AVP was significantly more accurate (baseline and follow-up: 96.2% ± 3.0% and 97.6% ± 1.4% overlap) than manual voxel placement (67.7% ± 22.8% overlap; ps<.05). AVP was reliable within- (97.9%) and between-subjects (94.2% and 97.2% overlap; baseline and follow-up; respectively). Finally, ongoing data collection indicates AVP is accurate (96.0%). These pilot studies demonstrated that AVP was feasible, accurate, and reliable method for automated single voxel coregistration.