Schick Rafael C, Bast Henriette, Frank Manuela, Urban Theresa, Koehler Thomas, Gassert Florian T, Sauter Andreas P, Renger Bernhard, Fingerle Alexander A, Karrer Alexandra, Makowski Marcus R, Pfeiffer Daniela, Pfeiffer Franz
Chair of Biomedical Physics, Department of Physics & School of Natural Sciences, Technical University of Munich, Garching bei München, Germany.
Munich Institute of Biomedical Engineering, Technical University of Munich, Garching bei München, Germany.
PLoS One. 2024 Dec 27;19(12):e0316104. doi: 10.1371/journal.pone.0316104. eCollection 2024.
Dark-field radiography has been proven to be a promising tool for the assessment of various lung diseases.
To evaluate the potential of dose reduction in dark-field chest radiography for the detection of the Coronavirus SARS-CoV-2 (COVID-19) pneumonia.
Patients aged at least 18 years with a medically indicated chest computed tomography scan (CT scan) were screened for participation in a prospective study between October 2018 and December 2020. Patients were included if they had a CO-RADS (COVID-19 Reporting and Data System) score ≥ 4 (COVID-19 group) or if they had no pathologic lung changes (controls). A total of 89 participants with a median age of 60 years (interquartile range 48 to 68 yrs.) were included in this study. Dark-field and attenuation-based radiographs were simultaneously obtained by using a prototype system for dark-field radiography. By modifying the image reconstruction algorithm, low-dose radiographs were simulated based on real participant images. The simulated radiographs corresponded to 50%, 25%, and 13% of the full dose (41.9 μSv, median value). Four experienced radiologists served as blinded readers assessing both image modalities, displayed side by side in random order. The presence of COVID-19-associated lung changes was rated on a scale from 1 to 6. The readers' diagnostic performance was evaluated by analyzing the area under the receiver operating characteristic curves (AUC) using Obuchowski's method. Also, the dark-field images were analyzed quantitatively by comparing the dark-field coefficients within and between the COVID-19 and the control group.
The readers' diagnostic performance in the image evaluation, as described by the AUC value (where a value of 1 corresponds to perfect diagnostic accuracy), did not differ significantly between the full dose images (AUC = 0.86) and the simulated images at 50% (AUC = 0.86) and 25% of the full dose(AUC = 0.84) (p>0.050), but was slightly lower at 13% dose (AUC = 0.82) (p = 0.038). For all four radiation dose levels, the median dark-field coefficients within groups were identical but different significantly by 15% between the controls and the COVID-19 pneumonia group (p<0.001).
Dark-field imaging can be used to diagnose the Coronavirus SARS-CoV-2 (COVID-19) pneumonia with a median dose of 10.5 μSv, which corresponds to 25% of the original dose used for dark-field chest imaging.
暗场射线照相术已被证明是评估各种肺部疾病的一种很有前景的工具。
评估暗场胸部射线照相术中降低剂量对检测冠状病毒SARS-CoV-2（COVID-19）肺炎的潜力。
对2018年10月至2020年12月期间因医学指征需要进行胸部计算机断层扫描（CT扫描）的18岁及以上患者进行筛查，以参与一项前瞻性研究。如果患者的CO-RADS（COVID-19报告和数据系统）评分≥4（COVID-19组）或没有病理性肺部改变（对照组），则将其纳入研究。本研究共纳入89名参与者，中位年龄为60岁（四分位间距48至68岁）。使用暗场射线照相术的原型系统同时获取暗场和基于衰减的射线照片。通过修改图像重建算法，基于真实参与者图像模拟低剂量射线照片。模拟射线照片相当于全剂量（41.9μSv，中位值）的50%、25%和13%。四位经验丰富的放射科医生作为盲法阅片者，对两种图像模式进行评估，两种图像模式并排随机显示。根据1至6分的量表对COVID-19相关肺部改变的存在情况进行评分。使用奥布霍夫斯基方法通过分析受试者操作特征曲线（AUC）下的面积来评估阅片者的诊断性能。此外，通过比较COVID-19组和对照组内部及之间的暗场系数，对暗场图像进行定量分析。
阅片者在图像评估中的诊断性能，用AUC值表示（其中值1对应完美诊断准确性），在全剂量图像（AUC = 0.86）与全剂量的50%（AUC = 0.86）和25%的模拟图像（AUC = 0.84）之间无显著差异（p>0.050），但在13%剂量时略低（AUC = 0.82）（p = 0.038）。对于所有四个辐射剂量水平，组内暗场系数中位数相同，但对照组和COVID-19肺炎组之间相差15%，差异有统计学意义（p<0.001）。
暗场成像可用于诊断冠状病毒SARS-CoV-2（COVID-19）肺炎，中位剂量为10.5μSv，相当于暗场胸部成像所用原始剂量的25%。
