Schaller Frank, Sedlmair Martin, Raupach Rainer, Uder Michael, Lell Michael
Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-University-Erlangen-Nuremberg, Maximiliansplatz 1, D 91054, Erlangen, Germany.
Siemens Healthcare, CT, Forchheim, Germany.
Acad Radiol. 2016 Oct;23(10):1230-8. doi: 10.1016/j.acra.2016.05.016. Epub 2016 Jun 16.
The study aimed to compare image quality of filtered back projection (FBP) and iterative reconstruction (advanced modeled iterative reconstruction, ADMIRE) in contrast-enhanced computed tomography (CT) of the abdomen, and to assess the differences of reconstructions according to these methods. It also aimed to investigate the potential for noise reduction of ADMIRE for different reconstructed slice thicknesses.
CT data of the abdomen and pelvis were acquired using a 128-slice single-source CT system using automated kV selection and tube current adaption based on patients' anatomy. Raw data sets from patients scanned at 100 kV were selected, and images were reconstructed with slice thicknesses of 1 mm, 3 mm, and 5 mm, both with FBP and ADMIRE. Filter strength F1, F3, and F5 of the ADMIRE algorithm and the corresponding reconstruction kernels were used. In total, 58 raw data sets from 17 patients were used to reconstruct from the same raw data FBP and ADMIRE images, representing identical body regions. Identical regions of interest were placed at the same position of up to four images and image noise was measured. Differences of reconstructed images and detail preservation were tested using an image subtraction technique, and subjective image quality was assessed using a 5-point Likert scale.
On average, for 1-mm slice thickness, noise reduction was 9.15% ± 2.4% with filter strength level F1, 30.2% ± 3.4% with F3, and 54.4% ± 7.0% with F5 as compared to FBP. For a slice thickness of 3 mm, noise reduction was 8.5% ± 3.7% with F1, 28.6% ± 3.9% with F3, and 52.2% ± 9.1% with F5. For 5 mm, the corresponding values are 8.9% ± 2.7%, 31.4% ± 2.8%, and 52.7% ± 7.7%. On subtraction images, edge information of tissue classes with a high attenuation gradient was found, but structures with small differences in attenuation were not detectable on subtraction images, confirming that no relevant details were lost in the iterative reconstruction process.
ADMIRE is able to reduce image noise considerably (up to 50%) without any obvious negative impact on lesion depiction as assessed visually. Noise reduction of ADMIRE seems to be independent of slice thickness.
本研究旨在比较腹部增强计算机断层扫描（CT）中滤波反投影（FBP）和迭代重建（高级建模迭代重建，ADMIRE）的图像质量，并评估根据这些方法进行重建的差异。它还旨在研究ADMIRE对不同重建层厚的降噪潜力。
使用128层单源CT系统采集腹部和骨盆的CT数据，该系统基于患者解剖结构自动选择千伏值和调整管电流。选择在100 kV下扫描患者的原始数据集，并使用FBP和ADMIRE两种方法以1 mm、3 mm和5 mm的层厚重建图像。使用ADMIRE算法的滤波强度F1、F3和F5以及相应的重建内核。总共使用了来自17名患者的58个原始数据集，从相同的原始数据重建FBP和ADMIRE图像，代表相同的身体区域。在多达四张图像的相同位置放置相同的感兴趣区域，并测量图像噪声。使用图像减法技术测试重建图像的差异和细节保留情况，并使用5点李克特量表评估主观图像质量。
平均而言，对于1 mm层厚，与FBP相比，滤波强度水平F1时降噪9.15%±2.4%，F3时为30.2%±3.4%，F5时为54.4%±7.0%。对于3 mm层厚，F1时降噪8.5%±3.7%，F3时为28.6%±3.9%，F5时为52.2%±9.1%。对于5 mm层厚，相应的值分别为8.9%±2.7%、31.4%±2.8%和52.7%±7.7%。在减法图像上，发现了具有高衰减梯度的组织类别的边缘信息，但在减法图像上无法检测到衰减差异小的结构，这证实了在迭代重建过程中没有丢失相关细节。
ADMIRE能够显著降低图像噪声（高达50%），且在视觉评估中对病变显示没有明显负面影响。ADMIRE的降噪似乎与层厚无关。
