Samei Ehsan, Tian Xiaoyu, Segars W Paul
Carl E. Ravin Advanced Imaging Laboratories, Departments of Radiology, Biomedical Engineering, Physics, and Electrical Engineering, Duke University, 2424 Erwin Road, Suite 302, Durham, NC, 27705, USA,
Pediatr Radiol. 2014 Oct;44 Suppl 3:460-7. doi: 10.1007/s00247-014-3117-7. Epub 2014 Oct 11.
Among the various metrics to quantify CT radiation dose, organ dose is generally regarded as one of the best to reflect patient radiation burden. Organ dose is dependent on two main factors, namely patient anatomy and irradiation field. An accurate estimation of organ dose requires detailed modeling of both factors. The modeling of patient anatomy needs to reflect the anatomical diversity and complexity across the population so that the attributes of a given clinical patient can be properly accounted for. The modeling of the irradiation field needs to accurately reflect the CT system condition, especially the tube current modulation (TCM) technique. We present an atlas-based method to model patient anatomy via a library of computational phantoms with representative ages, sizes and genders. A clinical patient is matched with a corresponding computational phantom to obtain a representation of patient anatomy. The irradiation field of the CT system is modeled using a validated Monte Carlo simulation program. The tube current modulation profiles are simulated using a manufacturer-generalizable ray-tracing algorithm. Combining the patient model, Monte Carlo results, and TCM profile, organ doses are obtained by multiplying organ dose values from a fixed mA scan (normalized to CTDIvol-normalized, denoted as h organ ) and an adjustment factor that reflects the specific irradiation of each organ. The accuracy of the proposed method was quantified by simulating clinical abdominopelvic examinations of 58 patients. The predicted organ doses showed good agreement with simulated organ dose across all organs and modulation schemes. For an average CTDIvol of a CT exam of 10 mGy, the absolute median error across all organs was 0.64 mGy (-0.21 and 0.97 for 25th and 75th percentiles, respectively). The percentage differences were within 15%. The study demonstrates that it is feasible to estimate organ doses in clinical CT examinations for protocols without and with tube current modulation. The methodology can be used for both prospective and retrospective estimation of organ dose.
在用于量化CT辐射剂量的各种指标中，器官剂量通常被认为是反映患者辐射负担的最佳指标之一。器官剂量取决于两个主要因素，即患者解剖结构和照射野。准确估计器官剂量需要对这两个因素进行详细建模。患者解剖结构的建模需要反映人群中的解剖多样性和复杂性，以便能够恰当地考虑特定临床患者的特征。照射野的建模需要准确反映CT系统状况，尤其是管电流调制（TCM）技术。我们提出了一种基于图谱的方法，通过具有代表性年龄、体型和性别的计算体模库来对患者解剖结构进行建模。将临床患者与相应的计算体模进行匹配，以获得患者解剖结构的表征。使用经过验证的蒙特卡罗模拟程序对CT系统的照射野进行建模。使用可推广到制造商的光线追踪算法模拟管电流调制曲线。结合患者模型、蒙特卡罗结果和TCM曲线，通过将固定毫安扫描的器官剂量值（归一化为CTDIvol归一化，记为h器官）与反映每个器官特定照射情况的调整因子相乘来获得器官剂量。通过模拟58例患者的临床腹部盆腔检查来量化所提出方法的准确性。预测的器官剂量在所有器官和调制方案中与模拟器官剂量显示出良好的一致性。对于CT检查平均CTDIvol为10 mGy的情况，所有器官的绝对中位数误差为0.64 mGy（第25和第75百分位数分别为-0.21和0.97）。百分比差异在15%以内。该研究表明，对于有无管电流调制的方案，在临床CT检查中估计器官剂量是可行的。该方法可用于器官剂量的前瞻性和回顾性估计。
