Wang Mengting, Qin Tian, Fan Yihan, Xie Zongyu, Liang Baohui
School of Medical Imaging, Bengbu Medical University, Bengbu, China.
Department of Oncology, the Second Hospital of Anhui Medical University, Hefei, China.
Quant Imaging Med Surg. 2025 May 1;15(5):3849-3860. doi: 10.21037/qims-24-2061. Epub 2025 Apr 28.
The rapid advancement of computed tomography (CT) has greatly improved clinical diagnosis but has also introduced new challenges in radiation protection. This study aimed to evaluate the relationship between organ doses from Monte Carlo (MC) simulations and CT dose metrics for head CT exams with organ dose modulation (ODM), and to develop a simplified method for estimating individual organ doses.
A CT source model including the X-ray energy spectrum, bowtie filter, fan beam shape, and rotational motion of the tube was constructed and validated. The modeling was divided into two different exposure regions based on the ODM technical principles: the 100° range on the anterior side of the skull (tube current reduction region) and the remaining 260° (tube current constant region). The source model was validated by comparing the error between the MC-simulated weighted CT dose index (CTDI) and the measured CTDI. A total of 40 patients were retrospectively collected, and each patient's voxelized head models were constructed and used for MC simulation to calculate organ doses. The global volume CTDI (CTDI), regional CTDI, size-specific dose estimate (SSDE), and organ-specific SSDE were derived based on the exposure (mAs) and water-equivalent diameters of each slice image. Linear regression fitting was used to explore the correlation between organ doses (including the brain, the eyeballs, the eye lens, and the salivary glands) and the four CT dose metrics mentioned above.
Comparison results for CTDI showed that the simulated source model error was within 5%, and the ODM model's error was below 0.05%. Organ doses correlated strongly with organ-specific SSDE (The R between each organ dose and corresponding organ-specific SSDE were 0.92 for the brain, 0.91 for eyeballs, 0.90 for the eye lens, and 0.90 for the salivary gland). Estimation coefficients for estimating organ doses of the brain, eyeballs, eye lens, and salivary glands from organ-specific SSDE were 0.34, 0.59, 0.48, and 0.26, respectively, as a mean across all patients.
There is a strong correlation between organ dose and organ-specific SSDE in ODM head CT examinations. However, activating the ODM results in significant differences in estimation coefficients for head CT exams with a fixed tube current, which provides a practical way to determine organ doses for individual patients undergoing head CT scans.
计算机断层扫描（CT）的快速发展极大地改善了临床诊断，但也给辐射防护带来了新的挑战。本研究旨在评估蒙特卡洛（MC）模拟得到的器官剂量与采用器官剂量调制（ODM）的头部CT检查的CT剂量指标之间的关系，并开发一种估算个体器官剂量的简化方法。
构建并验证了一个包括X射线能谱、蝴蝶结滤波器、扇形束形状和球管旋转运动的CT源模型。根据ODM技术原理，将建模分为两个不同的曝光区域：颅骨前侧100°范围（管电流降低区域）和其余260°（管电流恒定区域）。通过比较MC模拟的加权CT剂量指数（CTDI）与测量的CTDI之间的误差来验证源模型。回顾性收集了40例患者，构建了每位患者的体素化头部模型并用于MC模拟以计算器官剂量。基于每个切片图像的曝光量（mAs）和水等效直径得出总体积CTDI、区域CTDI、尺寸特异性剂量估计值（SSDE）和器官特异性SSDE。采用线性回归拟合来探究器官剂量（包括脑、眼球、晶状体和唾液腺）与上述四个CT剂量指标之间的相关性。
CTDI的比较结果表明，模拟源模型误差在5%以内，ODM模型误差低于0.05%。器官剂量与器官特异性SSDE密切相关（脑的每个器官剂量与相应器官特异性SSDE之间的R为0.92，眼球为0.91，晶状体为0.90，唾液腺为0.90）。作为所有患者的平均值，从器官特异性SSDE估算脑、眼球、晶状体和唾液腺器官剂量的估算系数分别为0.34、0.59、0.48和0.26。
ODM头部CT检查中，器官剂量与器官特异性SSDE之间存在很强的相关性。然而，激活ODM会导致固定管电流的头部CT检查的估算系数存在显著差异，这为确定接受头部CT扫描的个体患者的器官剂量提供了一种实用方法。
