Clinical Research Group, Health & Medical Equipment Business, Samsung Electronics, Suwon, Korea.
Department of Radiology, Chung-Ang University Hospital, Seoul, Korea.
PLoS One. 2020 Feb 21;15(2):e0228609. doi: 10.1371/journal.pone.0228609. eCollection 2020.
To evaluate the image quality of low-dose chest digital radiographic images obtained with a new spatial noise reduction algorithm, compared to a conventional de-noising technique.
In 69 patients, the dose reduction protocol was divided into A, B, and C test groups- 60% (n = 22), 50% (n = 23), and 40% (n = 24) of the baseline dose. In each patient, baseline dose radiographs were obtained with conventional image processing while low-dose images were acquired with new image processing. A set of baseline and low-dose radiographic images per patient was evaluated and scored on a 5-point scale over seven anatomical landmarks (radiolucency of unobscured lung, pulmonary vascularity, trachea, edge of rib, heart border, intervertebral disc space, and pulmonary vessels in the retrocardiac area) and three representative abnormal findings (nodule, consolidation, and interstitial marking) by two thoracic radiologists. A comparison of paired baseline and low-dose images was statistically analyzed using a non-inferiority test based on the paired t-test or the Wilcoxon signed-rank test.
In A, B, and C test groups, the mean dose reduction rate of the baseline radiation dose was 63.4%, 53.9%, and 47.8%, respectively. In all test groups, the upper limit of the 95% confidence interval was less than the non-inferiority margin of 0.5 every seven anatomical landmarks and three representative abnormal findings, which suggested that the image quality of the low-dose image was not inferior to that of the baseline dose image even if the maximum average dose reduction rate was reduced to 47.8% of the baseline dose.
In our study, an image processing technique integrating a new noise reduction algorithm achieved dose reductions of approximately half without compromising image quality for abnormal lung findings and anatomical landmarks seen on chest radiographs. This feature-preserving, noise reduction algorithm adopted in the proposed engine enables a lower radiation dose boundary for the sake of patient's and radiography technologist's radiation safety in routine clinical practice, in compliance with regulatory guidelines.
评估使用新的空间降噪算法获得的低剂量胸部数字射线照相图像的图像质量，与传统的去噪技术相比。
在 69 名患者中，剂量减少方案分为 A、B 和 C 测试组-分别为基线剂量的 60%（n=22）、50%（n=23）和 40%（n=24）。在每个患者中，使用常规图像处理获得基线剂量射线照相，而使用新图像处理获得低剂量图像。对每位患者的一组基线和低剂量射线照相进行评估，并对七个解剖标志（未遮挡肺的透亮性、肺血管、气管、肋骨边缘、心脏边界、椎间空间和心脏后区的肺血管）和三个代表性异常发现（结节、实变和间质标记）进行五分制评分由两名胸部放射科医生进行。使用基于配对 t 检验或 Wilcoxon 符号秩检验的非劣效性检验对配对基线和低剂量图像进行统计学分析。
在 A、B 和 C 测试组中，基线辐射剂量的平均剂量减少率分别为 63.4%、53.9%和 47.8%。在所有测试组中，95%置信区间的上限均小于非劣效性边界 0.5，每个七个解剖标志和三个代表性异常发现，这表明低剂量图像的图像质量即使最大平均剂量减少率降低至基线剂量的 47.8%，也不劣于基线剂量图像。
在我们的研究中，一种集成新降噪算法的图像处理技术可在不影响异常肺部发现和胸部射线照相解剖标志的图像质量的情况下，将剂量减少约一半。该提议引擎采用的这种具有保留特征、降低噪声的算法，在常规临床实践中，为了患者和放射技师的辐射安全，可以将辐射剂量降低到更低的水平，符合监管指南。
