EA 2415, Department of Radiology, Medical Imaging Group Nîmes, University of Montpellier, CHU Nîmes, boulevard du Professeur Robert Debré, 30029 Nîmes cedex, France.
EA 2415, Department of Radiology, Medical Imaging Group Nîmes, University of Montpellier, CHU Nîmes, boulevard du Professeur Robert Debré, 30029 Nîmes cedex, France.
Diagn Interv Imaging. 2019 Dec;100(12):763-770. doi: 10.1016/j.diii.2019.08.003. Epub 2019 Aug 28.
To compare the noise-magnitude and noise-texture obtained using strong kernel across two generations of iterative reconstruction (IR) algorithms proposed by three manufacturers.
Five computed tomography (CT) systems equipped with two generations of IR algorithm (hybrid/statistical IR [H/SIR] or full/partial model-based IR [MBIR]) were compared. Acquisitions on Catphan 600 phantom were performed at 120kV and three dose levels (CTDI: 3, 7 and 12mGy). Raw data were reconstructed using standard "bone" kernel for filtered back projection and one iterative level of two generations of IR algorithms. Contrast-to-noise ratio (CNR) was computed using three regions of interest placed semi-automatically: two placed in the low-density polyethylene and Teflon inserts and another placed on the solid water. Noise power spectrum (NPS) was computed to assess the NPS-peak and noise-texture.
CNR was significantly greater in MBIR compared to H/SIR algorithms for all CT systems (P<0.01). CNR were improved on average from H/SIR to MBIR of 36±14% [SD] (range: 24-57%) for GE-Healthcare, 109±19 [SD] % (range: 89-139%) for Philips Healthcare and 42±5 [SD] % (range: 36-47%) for Siemens Healthineers. The mean NPS peak decreased from H/SIR to MBIR by -41±6 [SD] % (range: -47--35%) for GE Healthcare, -79±3 [SD] % (range: -82--76%) for Philips Healthcare and -52±2 [SD] % (range: -54--51%) for Siemens Healthineers systems. NPS spatial frequencies were greater with MBIR than with H/SIR for Philips Healthcare (20 ± 2 [SD] %; range: 19-22%) and for Siemens Healthineers (9±5 [SD] %; range: 4-14%) but lower for GE Healthcare (-17±3 [SD] %; range: -14--20%).
Using bone kernel with recent MBIR algorithms reduces the noise-magnitude for all CT systems assessed. Noise texture shifted towards high frequency for Siemens Healthineers and Philips Healthcare but the opposite for GE Healthcare.
比较三种制造商提出的两代迭代重建（IR）算法中使用强核获得的噪声幅度和噪声纹理。
比较了配备两代 IR 算法（混合/统计 IR [H/SIR]或全/部分基于模型的 IR [MBIR]）的五台 CT 系统。在 120kV 和三个剂量水平（CTDI：3、7 和 12mGy）下对 Catphan 600 体模进行采集。使用标准“骨”核对滤波反投影和两代 IR 算法的一个迭代级别的原始数据进行重建。使用三个半自动放置的感兴趣区域计算对比噪声比（CNR）：两个放置在低密度聚乙烯和特氟隆插塞中，另一个放置在固体水中。计算噪声功率谱（NPS）以评估 NPS 峰值和噪声纹理。
对于所有 CT 系统，MBIR 算法的 CNR 明显大于 H/SIR 算法（P<0.01）。与 H/SIR 相比，GE-Healthcare 的平均 CNR 提高了 36±14%[SD]（范围：24-57%），Philips Healthcare 的平均 CNR 提高了 109±19%[SD]（范围：89-139%），而 Siemens Healthineers 的平均 CNR 提高了 42±5%[SD]（范围：36-47%）。从 H/SIR 到 MBIR，GE-Healthcare 的平均 NPS 峰值下降了-41±6%[SD]（范围：-47--35%），Philips Healthcare 的平均 NPS 峰值下降了-79±3%[SD]（范围：-82--76%），Siemens Healthineers 的平均 NPS 峰值下降了-52±2%[SD]（范围：-54--51%）。与 H/SIR 相比，MBIR 算法的 NPS 空间频率在 Philips Healthcare 系统中更高（20 ± 2 [SD]%；范围：19-22%），在 Siemens Healthineers 系统中更高（9 ± 5 [SD]%；范围：4-14%），但在 GE Healthcare 系统中更低（-17±3 [SD]%；范围：-14--20%）。
对于所有评估的 CT 系统，使用最近的 MBIR 算法和骨核都会降低噪声幅度。对于 Siemens Healthineers 和 Philips Healthcare，噪声纹理向高频转移，但对于 GE Healthcare 则相反。
