Department of Radiology, Tokyo Women's Medical University Medical Center East, 2-1-10 Nishiogu, Arakawa-ku, Tokyo 116-8567, Japan.
AJR Am J Roentgenol. 2013 Feb;200(2):442-6. doi: 10.2214/AJR.11.7826.
The purpose of this study was to investigate the utility of model-based iterative reconstruction (MBIR) for improving delineation of the anterior spinal artery (ASA) during routine-dose CT angiography.
For imaging of 10 patients (six men, four women; mean age, 73.9 ± 7.5 years) consecutively undergoing CT angiography of the whole aorta with a 12-HU noise index, we used filtered back projection with a standard kernel, adaptive statistical iterative reconstruction of 40% with a detail kernel, and MBIR to reconstruct axial and oblique coronal multiplanar reformation images to delineate the ASA. We measured objective noise in the spinal cord and contrast-to-noise ratio (CNR) between the aorta and spinal cord on axial images at the T12 level. Two radiologists independently graded subjective noise and ASA delineation on the multiplanar reformation images from 1 (poor) to 4 (excellent). We compared results among the three reconstructions using one-way analysis of variance and Tukey-Kramer significance tests.
Objective noise, CNR, and subjective image noise and ASA delineation improved significantly with MBIR. Image noise was 18.4 ± 3.6 HU and CNR, 23.4 ± 8.6 (reader 1 scores, 3.9 ± 0.3 and 3.7 ± 0.5; reader 2, 3.9 ± 0.3 and 3.5 ± 0.7). With filtered back projection, image noise was 34.7 ± 8.3 HU and CNR 12.1 ± 4.0 (reader 1 scores, 2.0 ± 0.0 and 2.2 ± 0.4; reader 2, 2.2 ± 0.4 and 2.5 ± 0.7), and with ASIR, 33.0 ± 8.1 HU and 12.7 ± 4.3 (reader 1 scores, 2.0 ± 0.0 and 2.2 ± 0.4; reader 2, 2.2 ± 0.4 and 2.5 ± 0.7) (p < 0.05). Results between filtered back projection and adaptive statistical iterative reconstruction were comparable.
Use of MBIR can improve delineation of the ASA during CT angiography.
本研究旨在探讨基于模型的迭代重建（MBIR）在常规剂量 CT 血管造影中改善脊髓前动脉（ASA）勾画的作用。
对 10 例患者（男 6 例，女 4 例；平均年龄 73.9±7.5 岁）行 12-HU 噪声指数全主动脉 CT 血管造影，分别采用滤波反投影标准算法、自适应统计迭代重建 40%细节算法和 MBIR 重建轴位及斜冠状多平面重组图像，以勾画 ASA。于 T12 层面轴位图像上测量脊髓的客观噪声和主动脉与脊髓的对比噪声比（CNR）。两位放射科医生分别对多平面重组图像上的主观噪声和 ASA 勾画进行评分（1 分：差；4 分：优）。采用单因素方差分析和 Tukey-Kramer 显著性检验比较三种重建方法的结果。
MBIR 可显著降低客观噪声，提高 CNR，改善图像噪声和 ASA 勾画。MBIR 的客观噪声为 18.4±3.6HU，CNR 为 23.4±8.6（两位观察者评分分别为 3.9±0.3 和 3.7±0.5；ASIR 为 33.0±8.1HU，CNR 为 12.7±4.3（两位观察者评分分别为 3.9±0.3 和 3.7±0.5）；ASIR 为 33.0±8.1HU，CNR 为 12.7±4.3（两位观察者评分分别为 2.0±0.0 和 2.2±0.4；2.2±0.4 和 2.5±0.7），差异均有统计学意义（p<0.05）。滤波反投影和自适应统计迭代重建之间的结果具有可比性。
MBIR 可改善 CT 血管造影中 ASA 的勾画。
