Department of Radiology, Yonsei University College of Medicine, Seoul 03722, Korea.
Korean J Radiol. 2018 Sep-Oct;19(5):957-964. doi: 10.3348/kjr.2018.19.5.957. Epub 2018 Aug 6.
The purpose of this study was to determine the diagnostic utility of low-dose CT with knowledge-based iterative model reconstruction (IMR) for the evaluation of parotid gland tumors.
This prospective study included 42 consecutive patients who had undergone low-dose contrast-enhanced CT for the evaluation of suspected parotid gland tumors. Prior or subsequent non-low-dose CT scans within 12 months were available in 10 of the participants. Background noise (BN), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between non-low-dose CT images and images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose; Philips Healthcare), and knowledge-based IMR. Subjective image quality was rated by two radiologists using five-point grading scales to assess the overall image quality, delineation of lesion contour, image sharpness, and noise.
With the IMR algorithm, background noise (IMR, 4.24 ± 3.77; iDose, 8.77 ± 3.85; FBP, 11.73 ± 4.06; = 0.037 [IMR vs. iDose] and < 0.001 [IMR vs. FBP]) was significantly lower and SNR (IMR, 23.93 ± 7.49; iDose, 10.20 ± 3.29; FBP, 7.33 ± 2.03; = 0.011 [IMR vs. iDose] and < 0.001 [IMR vs. FBP]) was significantly higher compared with the other two algorithms. The CNR was also significantly higher with the IMR compared with the FBP (25.76 ± 11.88 vs. 9.02 ± 3.18, < 0.001). There was no significant difference in BN, SNR, and CNR between low-dose CT with the IMR algorithm and non-low-dose CT. Subjective image analysis revealed that IMR-generated low-dose CT images showed significantly better overall image quality and delineation of lesion contour with lesser noise, compared with those generated using FBP by both reviewers 1 and 2 (4 vs. 3; 4 vs. 3; and 3-4 vs. 2; < 0.05 for all pairs), although there was no significant difference in subjective image quality scores between IMR-generated low-dose CT and non-low-dose CT images.
Iterative model reconstruction-generated low-dose CT is an alternative to standard non-low-dose CT without significantly affecting image quality for the evaluation of parotid gland tumors.
本研究旨在评估低剂量 CT 联合基于知识的迭代模型重建(IMR)在评估腮腺肿瘤中的诊断效能。
本前瞻性研究纳入了 42 例因疑似腮腺肿瘤行低剂量对比增强 CT 检查的患者。其中 10 例患者的检查时间在 12 个月内,其先前或随后的非低剂量 CT 扫描图像均可用。对比分析非低剂量 CT 图像与滤波反投影(filtered back projection,FBP)、混合迭代重建(hybrid iterative reconstruction,iDose;Philips Healthcare)和基于知识的 IMR 图像的背景噪声(background noise,BN)、信噪比(signal-to-noise ratio,SNR)和对比噪声比(contrast-to-noise ratio,CNR)。两位放射科医生采用五分制对整体图像质量、病灶轮廓勾画、图像锐利度和噪声进行主观图像质量评分。
与 iDose 和 FBP 相比,采用 IMR 算法时,背景噪声(IMR:4.24 ± 3.77;iDose:8.77 ± 3.85;FBP:11.73 ± 4.06; = 0.037 [IMR 与 iDose 相比]和 < 0.001 [IMR 与 FBP 相比])显著降低,而 SNR(IMR:23.93 ± 7.49;iDose:10.20 ± 3.29;FBP:7.33 ± 2.03; = 0.011 [IMR 与 iDose 相比]和 < 0.001 [IMR 与 FBP 相比])显著升高。与 FBP 相比,CNR 也显著升高(25.76 ± 11.88 vs. 9.02 ± 3.18, < 0.001)。采用 IMR 算法的低剂量 CT 与非低剂量 CT 之间的 BN、SNR 和 CNR 差异无统计学意义。主观图像分析显示,与 FBP 相比,采用 IMR 算法生成的低剂量 CT 图像的整体图像质量更好,病灶轮廓勾画更清晰,噪声更小,两位放射科医生的评分均为 4 分(4 分比 3 分;4 分比 3 分;3-4 分比 2 分;所有配对差异均有统计学意义, < 0.05),但 IMR 生成的低剂量 CT 与非低剂量 CT 图像的主观图像质量评分差异无统计学意义。
与标准非低剂量 CT 相比,迭代模型重建生成的低剂量 CT 是一种替代方法,对评估腮腺肿瘤的图像质量无明显影响。