Reduced Chest Computed Tomography Scan Length for Patients Positive for Coronavirus Disease 2019: Dose Reduction and Impact on Diagnostic Utility.
Reduced Chest Computed Tomography Scan Length for Patients Positive for Coronavirus Disease 2019: Dose Reduction and Impact on Diagnostic Utility.
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DOI：
10.1097/rct.0000000000001312
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发表时间：
2022-07-01
影响因子：
1.3
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中科院分区：
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这项工作旨在回顾性评估通过减少COVID-19阳性患者的纵向扫描长度来降低胸部CT检查剂量的潜力。本研究使用CT剂量个性化快速估计（PREDICT）工具从CT图像数据中估计患者特定器官剂量。PREDICT是一种研究工具，将用于辐射剂量图生成的线性玻尔兹曼传输方程求解器与用于器官轮廓绘制的深度学习算法相结合。分析了MIDRC-RICORD数据集中74名受试者的CT图像（COVID-19阳性成人患者的胸部CT），其中包括专家注释，包括“感染性混浊”。首先，评价CT图像数据集的完整z扫描长度。然后，从左半膈到主动脉弓顶部减少z扫描长度。计算基于剂量长度乘积（DLP）的一般剂量减少和患者特异性器官剂量减少。从减少的z扫描长度中排除的感染性混浊的百分比用于量化对诊断效用的影响。基于DLP，通用剂量减少率为69%。器官剂量减少范围为18%（乳房）和164%（骨表面和骨髓）。平均而言，每例患者有12.4%的感染性混浊未包括在减少的z覆盖范围内，其中5.1%位于足弓顶部上方，7.5%位于左半膈下方。限制胸部CT的z扫描长度可减少辐射剂量，而不会显著影响COVID-19患者的诊断效用。PREDICT表明，患者特异性器官剂量降低与基于DLP的通用剂量降低不同。
This work aims to retrospectively evaluate the potential of dose reduction on chest CT examinations by reducing the longitudinal scan-length for patients positive for COVID-19. This study used the Personalized Rapid Estimation of Dose In CT (PREDICT) tool to estimate patient-specific organ doses from CT image data. PREDICT is a research tool that combines a linear Boltzmann transport equation solver for radiation dose map generation with deep learning algorithms for organ contouring. CT images from 74 subjects in the MIDRC-RICORD dataset (chest CT of adult patients positive for COVID-19) which included expert annotations including “infectious opacities” were analyzed. First, the full z-scan-length of the CT image dataset was evaluated. Next, the z-scan-length was reduced from the left hemidiaphragm to the top of the aortic arch. Generic dose reduction based on dose-length-product (DLP) and patient-specific organ dose reductions were calculated. The percentage of infectious opacities excluded from the reduced z-scan-length was used to quantify the effect on diagnostic utility. Generic dose reduction, based on DLP, was 69%. The organ dose reduction ranged from ≈18% (breasts) and ≈64% (bone surface and bone marrow). On average, 12.4% of the infectious opacities were not included in the reduced z-coverage, per patient, of which 5.1% were above the top of the arch and 7.5% below the left hemidiaphragm. Limiting z-scan-length of chest CTs reduced radiation dose without significantly compromising diagnostic utility in COVID-19 patients. PREDICT demonstrated that patient-specific organ dose reductions varied from generic dose reduction based on DLP.