Department of Radiology, University of California Davis, Sacramento, California, USA.
Department of Radiology, University of California Los Angeles, Los Angeles, California, USA.
Med Phys. 2023 Apr;50(4):2037-2048. doi: 10.1002/mp.16194. Epub 2023 Jan 12.
Accurate detection and grading of atheromatous stenotic lesions within the cardiac, renal, and intracranial vasculature is imperative for early recognition of disease and guiding treatment strategies.
In this work, a stenotic lesion phantom was used to compare high resolution and normal resolution modes on the same CT scanner in terms of detection and size discrimination performance.
The phantom is comprised of three acrylic cylinders (each 15.0 cm in diameter and 1.3 cm thick) with a matching array of holes in each module. The outer two modules contain holes that are slightly larger than the corresponding hole in the central module to simulate stenotic narrowing in vasculature. The stack of modules was submerged in an iodine solution simulating contrast-enhanced stenotic lesions with a range of lumen diameters (1.32-10.08 mm) and stenosis severity (0%, 50%, 60%, 70%, and 80%). The phantom was imaged on the Canon Aquilion Precision high-resolution CT scanner in high-resolution (HR) mode (0.25 mm × 0.50 mm detector element size) and normal-resolution (NR) mode (0.50 mm × 0.50 mm) using 120 kV and two dose levels (14 and 21 mGy SSDE) with 30 repeat scans acquired for each combination Filtered back-projection (FBP) and a hybrid-iterative reconstruction (AIDR) were used with the FC18 kernel, as well as a deep learning algorithm (AiCE) which is only available for HR. A non-prewhitening model observer with an eye filter was implemented to quantify performance for detection and size discrimination tasks in the axial plane.
Detection performance improved with increasing diameter, dose, and for AIDR in comparison to FBP for a fixed resolution mode. Performance in the HR mode was generally higher than NR for the smaller lumen diameters (1-5 mm) with decreasing differences as the diameter increased. Performance in NR mode surpassed HR mode for lumen diameters greater than ∼4 mm and ∼5 mm for 14 mGy and 21 mGy, respectively. AiCE provided consistently higher detection performance compared with AIDR-FC18 (48% higher for a 6 mm lumen diameter). Discrimination performance increased with increasing nominal diameter, dose, and for larger differences in stenosis severity. When comparing discrimination performance in HR to NR modes, the largest relative differences occur at the smallest nominal diameters and smallest differences in stenosis severity. The AiCE reconstruction algorithm produced the highest overall discrimination performance values, and these were significantly higher than AIDR-FC18 for nominal diameters of 7.14 and 10.08 mm.
HR mode outperforms NR for detection up to a specific diameter and the results improve with AiCE and for higher dose levels. For the task of size discrimination, HR mode consistently outperforms NR if AIDR-FC18 is used for dose levels of at least 21 mGy, and the results improve with AiCE and for the smallest differences in stenosis severity investigated (50% vs. 60%). High-resolution CT appears to be beneficial for detecting smaller simulated lumen diameters (<5 mm) and is generally advantageous for discrimination tasks related to stenotic lesions, which inherently contain information at higher frequencies, given the right reconstruction algorithm and dose level.
准确检测和分级心脏、肾脏和颅内血管中的动脉粥样硬化狭窄病变对于早期发现疾病和指导治疗策略至关重要。
本研究使用狭窄病变体模比较了同一 CT 扫描仪上的高分辨率和常规分辨率模式在检测和大小判别性能方面的表现。
该体模由三个丙烯酸圆柱体(直径均为 15.0 厘米,厚 1.3 厘米)组成,每个模块都有一个匹配的孔阵列。外两个模块中的孔略大于中央模块中的孔,以模拟血管中的狭窄变窄。将模块堆叠浸入碘溶液中,模拟具有不同管腔直径(1.32-10.08 毫米)和狭窄严重程度(0%、50%、60%、70%和 80%)的增强狭窄病变。该体模在佳能 Aquilion Precision 高分辨率 CT 扫描仪上以高分辨率(HR)模式(0.25 毫米×0.50 毫米探测器元素大小)和常规分辨率(NR)模式(0.50 毫米×0.50 毫米)进行成像,使用 120 kV 和两种剂量水平(14 和 21 mGy SSDE),每种组合采集 30 次重复扫描。使用 FC18 内核的滤波反投影(FBP)和混合迭代重建(AIDR)以及仅在 HR 模式下可用的深度学习算法(AiCE)。实现了无预白化模型观察者与眼部滤波器,以量化轴向平面中检测和大小判别任务的性能。
与 FBP 相比,随着直径、剂量的增加,以及对于固定分辨率模式下的 AIDR,检测性能得到提高。与 HR 模式相比,在较小的管腔直径(1-5 毫米)下,NR 模式的性能通常更高,随着直径的增加,差异逐渐减小。在管腔直径大于约 4 毫米和约 5 毫米时,NR 模式的性能超过 HR 模式,分别为 14 mGy 和 21 mGy。与 AIDR-FC18 相比,AiCE 提供了更高的检测性能(6 毫米管腔直径时提高了 48%)。随着名义直径、剂量的增加,以及狭窄严重程度的差异增大,判别性能得到提高。在将 HR 模式与 NR 模式的判别性能进行比较时,在最小名义直径和最小狭窄严重程度差异下,最大的相对差异出现。AiCE 重建算法产生了最高的整体判别性能值,与 AIDR-FC18 相比,7.14 和 10.08 毫米的名义直径显著更高。
在特定直径下,HR 模式优于 NR 模式进行检测,并且随着 AiCE 和更高剂量水平的使用,结果会得到改善。对于大小判别任务,如果使用 AIDR-FC18 进行至少 21 mGy 的剂量水平,则 HR 模式始终优于 NR 模式,如果使用 AiCE 并且狭窄严重程度的差异最小(50%比 60%),则结果会得到改善。高分辨率 CT 似乎有利于检测较小的模拟管腔直径(<5 毫米),并且对于与狭窄病变相关的判别任务通常是有利的,因为固有地包含更高频率的信息,给定正确的重建算法和剂量水平。