Qu Shuiyin, Xie Tianwu, Giger Maryellen L, Mao Xianqing, Zaidi Habib
Institute, of Radiation Medicine, Fudan University, Shanghai, China.
Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.
Med Phys. 2023 Apr;50(4):2577-2589. doi: 10.1002/mp.15905. Epub 2022 Aug 23.
Accurate estimations of fetal absorbed dose and radiation risks are crucial for radiation protection and important for radiological imaging research owing to the high radiosensitivity of the fetus. Computational anthropomorphic models have been widely used in patient-specific radiation dosimetry calculations. In this work, we aim to build the first digital fetal library for more reliable and accurate radiation dosimetry studies.
Computed tomography (CT) images of abdominal and pelvic regions of 46 pregnant females were segmented by experienced medical physicists. The segmented tissues/organs include the body contour, skeleton, uterus, liver, kidney, intestine, stomach, lung, bladder, gall bladder, spleen, and pancreas for maternal body, and placenta, amniotic fluid, fetal body, fetal brain, and fetal skeleton. Nonuniform rational B-spline (NURBS) surfaces of each identified region was constructed manually using 3D modeling software. The Hounsfield unit values of each identified organs were gathered from CT images of pregnant patients and converted to tissue density. Organ volumes were further adjusted according to reference measurements for the developing fetus recommended by the World Health Organization (WHO) and International Commission on Radiological Protection. A series of anatomical parameters, including femur length, humerus length, biparietal diameter, abdominal circumference (FAC), and head circumference, were measured and compared with WHO recommendations.
The first fetal patient-specific model library was developed with the anatomical characteristics of each model derived from the corresponding patient whose gestational age varies between 8 and 35 weeks. Voxelized models are represented in the form of MCNP matrix input files representing the three-dimensional model of the fetus. The size distributions of each model are also provided in text files. All data are stored on Zenodo and are publicly accessible on the following link: https://zenodo.org/record/6471884.
The constructed fetal models and maternal anatomical characteristics are consistent with the corresponding patients. The resulting computational fetus could be used in radiation dosimetry studies to improve the reliability of fetal dosimetry and radiation risks assessment. The advantages of NURBS surfaces in terms of adapting fetal postures and positions enable us to adequately assess their impact on radiation dosimetry calculations.
由于胎儿具有高放射敏感性，准确估计胎儿吸收剂量和辐射风险对于辐射防护至关重要，且对放射影像学研究也很重要。计算人体模型已广泛应用于针对患者的辐射剂量学计算。在本研究中，我们旨在构建首个数字胎儿库，以进行更可靠、准确的辐射剂量学研究。
46名怀孕女性腹部和盆腔区域的计算机断层扫描（CT）图像由经验丰富的医学物理学家进行分割。分割的组织/器官包括母体身体的身体轮廓、骨骼、子宫、肝脏、肾脏、肠道、胃、肺、膀胱、胆囊、脾脏和胰腺，以及胎盘、羊水、胎儿身体、胎儿大脑和胎儿骨骼。使用3D建模软件手动构建每个识别区域的非均匀有理B样条（NURBS）曲面。从怀孕患者的CT图像中收集每个识别器官的亨氏单位值，并转换为组织密度。根据世界卫生组织（WHO）和国际放射防护委员会推荐的发育中胎儿的参考测量值，进一步调整器官体积。测量了一系列解剖学参数，包括股骨长度、肱骨长度、双顶径、腹围（FAC）和头围，并与WHO的建议进行了比较。
首个针对胎儿患者的模型库已开发完成，每个模型的解剖学特征源自相应孕周在8至35周之间的患者。体素化模型以表示胎儿三维模型的MCNP矩阵输入文件的形式呈现。每个模型的尺寸分布也在文本文件中提供。所有数据都存储在Zenodo上，可通过以下链接公开访问：https://zenodo.org/record/6471884。
构建的胎儿模型和母体解剖学特征与相应患者一致。由此产生的计算胎儿可用于辐射剂量学研究，以提高胎儿剂量学和辐射风险评估的可靠性。NURBS曲面在适应胎儿姿势和位置方面的优势使我们能够充分评估其对辐射剂量学计算的影响。
