Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA.
Med Phys. 2011 Oct;38(10):5612-29. doi: 10.1118/1.3633937.
This work applies a cascaded systems model for cone-beam CT imaging performance to the design and optimization of a system for musculoskeletal extremity imaging. The model provides a quantitative guide to the selection of system geometry, source and detector components, acquisition techniques, and reconstruction parameters.
The model is based on cascaded systems analysis of the 3D noise-power spectrum (NPS) and noise-equivalent quanta (NEQ) combined with factors of system geometry (magnification, focal spot size, and scatter-to-primary ratio) and anatomical background clutter. The model was extended to task-based analysis of detectability index (d') for tasks ranging in contrast and frequency content, and d' was computed as a function of system magnification, detector pixel size, focal spot size, kVp, dose, electronic noise, voxel size, and reconstruction filter to examine trade-offs and optima among such factors in multivariate analysis. The model was tested quantitatively versus the measured NPS and qualitatively in cadaver images as a function of kVp, dose, pixel size, and reconstruction filter under conditions corresponding to the proposed scanner.
The analysis quantified trade-offs among factors of spatial resolution, noise, and dose. System magnification (M) was a critical design parameter with strong effect on spatial resolution, dose, and x-ray scatter, and a fairly robust optimum was identified at M ∼ 1.3 for the imaging tasks considered. The results suggested kVp selection in the range of ∼65-90 kVp, the lower end (65 kVp) maximizing subject contrast and the upper end maximizing NEQ (90 kVp). The analysis quantified fairly intuitive results-e.g., ∼0.1-0.2 mm pixel size (and a sharp reconstruction filter) optimal for high-frequency tasks (bone detail) compared to ∼0.4 mm pixel size (and a smooth reconstruction filter) for low-frequency (soft-tissue) tasks. This result suggests a specific protocol for 1 × 1 (full-resolution) projection data acquisition followed by full-resolution reconstruction with a sharp filter for high-frequency tasks along with 2 × 2 binning reconstruction with a smooth filter for low-frequency tasks. The analysis guided selection of specific source and detector components implemented on the proposed scanner. The analysis also quantified the potential benefits and points of diminishing return in focal spot size, reduced electronic noise, finer detector pixels, and low-dose limits of detectability. Theoretical results agreed quantitatively with the measured NPS and qualitatively with evaluation of cadaver images by a musculoskeletal radiologist.
A fairly comprehensive model for 3D imaging performance in cone-beam CT combines factors of quantum noise, system geometry, anatomical background, and imaging task. The analysis provided a valuable, quantitative guide to design, optimization, and technique selection for a musculoskeletal extremities imaging system under development.
本研究将锥形束 CT 成像性能级联系统模型应用于肌肉骨骼系统的设计和优化。该模型为系统几何形状、源和探测器组件、采集技术以及重建参数的选择提供了定量指导。
该模型基于 3D 噪声功率谱（NPS）和噪声等效量子（NEQ）的级联系统分析，结合系统几何形状（放大率、焦点尺寸和散射与初级射线的比率）和解剖背景杂波的因素。该模型扩展到基于任务的检测能力指数（d'）分析，用于对比度和频率内容不同的任务，并且 d'作为系统放大率、探测器像素大小、焦点尺寸、kVp、剂量、电子噪声、体素大小和重建滤波器的函数进行计算，以在多变量分析中检查这些因素之间的权衡和最佳值。该模型通过对提出的扫描仪对应的条件下的尸体图像进行测量的 NPS 进行定量测试，并对不同 kVp、剂量、像素大小和重建滤波器下的尸体图像进行定性测试。
该分析量化了空间分辨率、噪声和剂量因素之间的权衡。系统放大率（M）是一个关键的设计参数，对空间分辨率、剂量和 X 射线散射有很强的影响，并确定了一个相当稳健的最佳值，即在考虑到的成像任务中，M 约为 1.3。结果表明，kVp 的选择范围在 65-90 kVp 之间，下限（65 kVp）使对象对比度最大化，上限（90 kVp）使 NEQ 最大化。该分析量化了相当直观的结果，例如，与低频（软组织）任务相比，对于高频任务（骨骼细节），约 0.1-0.2 mm 的像素大小（和锐化重建滤波器）是最优的，而对于低频任务，约 0.4 mm 的像素大小（和平滑重建滤波器）是最优的。这一结果表明，对于 1×1（全分辨率）投影数据采集，应采用特定协议，然后使用锐化滤波器进行全分辨率重建，对于高频任务，采用 2×2 -bin 重建并使用平滑滤波器进行低频任务。该分析指导了特定源和探测器组件的选择，这些组件已在提出的扫描仪上实现。该分析还量化了焦点尺寸、降低电子噪声、更精细的探测器像素和低剂量检测能力的潜在好处和收益递减点。理论结果与测量的 NPS 定量一致，并与肌肉骨骼放射科医生对尸体图像的评估定性一致。
三维成像性能的级联系统模型较为全面，结合了量子噪声、系统几何形状、解剖背景和成像任务等因素。该分析为正在开发的肌肉骨骼系统成像系统的设计、优化和技术选择提供了有价值的、定量的指导。
