Flavius D Raslau, MD, is associate professor.
All authors work for the University of Kentucky in Lexington.
Radiol Technol. 2022 May-Jun;93(5):462-472.
To investigate the potential of iterative reconstruction in radiation dose reduction during head computed tomography (CT) examinations and to evaluate the relationship between the parameters milliampere second (mAs), kilovoltage (kV), and iterative reconstruction strength using a live ovine (sheep) model.
A sheep was scanned on a SOMATOM Force (Siemens Healthineers) CT scanner at 12 mAs and 3 kV. Images were reconstructed with filtered back projection (FBP) and the Advanced Modeled Iterative Reconstruction (ADMIRE; Siemens Healthineers) strengths 1 to 5. Images with 216 combinations of varying doses, kVs, and reconstructions were rated by 2 neuroradiologists for low-contrast detectability (ie, gray-white matter differentiation) and image texture.
Using only gray-white matter differentiation, maximum dose reduction was 75% at 100 kV with ADMIRE-3, and using only image texture, maximum dose reduction was 75% at 120 kV (and 140 kV) with ADMIRE-5. When these 2 metrics were combined, maximum dose reduction was 50% at 120 kV with ADMIRE-3. Other kV levels and higher iterative reconstruction strengths did not offer superior results.
Although artificial intelligence algorithms are certainly gaining momentum, iterative reconstruction technology likely will remain more accessible to most hospitals and imaging centers. Dose reduction with preservation of image quality (ie, gray-white differentiation and image texture) can be achieved when complemented by appropriate iterative reconstruction strength. However, the effect of iterative reconstruction strength on gray-white differentiation and image texture does not necessarily converge on the same pattern.
Maximum dose reduction was 50% at 120 kV with ADMIRE-3, which confirms the potential for dose reduction with appropriately chosen iterative reconstruction strength and reveals a preference for 120 kV, as well as a limit to dose reduction by further increasing iterative reconstruction strength. A better understanding of dose-voltage-reconstruction relationships in iterative reconstruction might allow for greater dose reductions than current practices allow.
在头部 CT 检查中，研究迭代重建降低放射剂量的潜力，并使用活体绵羊模型评估毫安秒（mAs）、千伏（kV）和迭代重建强度之间的关系。
将一只绵羊在 SOMATOM Force（西门子医疗）CT 扫描仪上以 12 mAs 和 3 kV 进行扫描。使用滤波反投影（FBP）和高级模型迭代重建（ADMIRE；西门子医疗）强度 1 至 5 对图像进行重建。对具有 216 种不同剂量、kV 和重建组合的图像，由 2 位神经放射科医生进行低对比度可检测性（即灰白质分化）和图像纹理的评分。
仅使用灰度-白质分化，使用 ADMIRE-3 可将最大剂量降低 75%，在 100 kV；仅使用图像纹理，使用 ADMIRE-5 可将最大剂量降低 75%，在 120 kV（和 140 kV）。当这 2 个指标结合使用时，使用 ADMIRE-3 可在 120 kV 将最大剂量降低 50%。其他 kV 水平和更高的迭代重建强度没有提供更好的结果。
尽管人工智能算法肯定在不断发展，但迭代重建技术可能仍然更容易被大多数医院和影像中心所接受。通过适当的迭代重建强度，在保持图像质量（即灰度-白质分化和图像纹理）的同时，可以实现剂量降低。然而，迭代重建强度对灰度-白质分化和图像纹理的影响不一定会收敛于相同的模式。
在 ADMIRE-3 下，最大剂量降低 50%，在 120 kV，这证实了通过适当选择迭代重建强度降低剂量的潜力，并揭示了对 120 kV 的偏好，以及通过进一步增加迭代重建强度来降低剂量的限制。对迭代重建中剂量-电压-重建关系的更好理解可能允许比当前实践允许的更大的剂量降低。
