Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Department of Oncology, University College London Hospital NHS Foundation Trust, London, United Kingdom.
Phys Med Biol. 2021 May 4;66(10):105005. doi: 10.1088/1361-6560/abf010.
Reducing radiation-induced side effects is one of the most important challenges in paediatric cancer treatment. Recently, there has been growing interest in using spatial normalisation to enable voxel-based analysis of radiation-induced toxicities in a variety of patient groups. The need to consider three-dimensional distribution of doses, rather than dose-volume histograms, is desirable but not yet explored in paediatric populations. In this paper, we investigate the feasibility of atlas construction and spatial normalisation in paediatric radiotherapy. We used planning computed tomography (CT) scans from twenty paediatric patients historically treated with craniospinal irradiation to generate a template CT that is suitable for spatial normalisation. This childhood cancer population representative template was constructed using groupwise image registration. An independent set of 53 subjects from a variety of childhood malignancies was then used to assess the quality of the propagation of new subjects to this common reference space using deformable image registration (i.e. spatial normalisation). The method was evaluated in terms of overall image similarity metrics, contour similarity and preservation of dose-volume properties. After spatial normalisation, we report a dice similarity coefficient of 0.95 ± 0.05, 0.85 ± 0.04, 0.96 ± 0.01, 0.91 ± 0.03, 0.83 ± 0.06 and 0.65 ± 0.16 for brain and spinal canal, ocular globes, lungs, liver, kidneys and bladder. We then demonstrated the potential advantages of an atlas-based approach to study the risk of second malignant neoplasms after radiotherapy. Our findings indicate satisfactory mapping between a heterogeneous group of patients and the template CT. The poorest performance was for organs in the abdominal and pelvic region, likely due to respiratory and physiological motion and to the highly deformable nature of abdominal organs. More specialised algorithms should be explored in the future to improve mapping in these regions. This study is the first step toward voxel-based analysis in radiation-induced toxicities following paediatric radiotherapy.
降低放射性副作用是儿科癌症治疗中最重要的挑战之一。最近,人们越来越关注使用空间归一化来实现各种患者群体中放射性毒性的体素分析。需要考虑剂量的三维分布,而不是剂量-体积直方图,这在儿科人群中是可取的,但尚未探索。在本文中,我们研究了在儿科放射治疗中构建图谱和进行空间归一化的可行性。我们使用历史上接受颅脊髓照射治疗的二十名儿科患者的计划计算机断层扫描(CT)扫描生成适用于空间归一化的模板 CT。使用分组图像配准构建了这个儿童癌症人群代表性模板。然后,使用一组来自各种儿童恶性肿瘤的 53 个独立个体来评估使用可变形图像配准(即空间归一化)将新个体传播到这个通用参考空间的质量。该方法的评估基于总体图像相似性指标、轮廓相似性和剂量-体积特性的保留。归一化后,我们报告了大脑和脊髓、眼球、肺、肝、肾和膀胱的整体图像相似性系数分别为 0.95±0.05、0.85±0.04、0.96±0.01、0.91±0.03、0.83±0.06 和 0.65±0.16。然后,我们展示了基于图谱的方法研究放疗后第二恶性肿瘤风险的潜在优势。我们的发现表明,在一组异质患者和模板 CT 之间存在令人满意的映射。表现最差的是腹部和盆腔器官,这可能是由于呼吸和生理运动以及腹部器官的高度可变形性所致。未来应探索更专业的算法来改善这些区域的映射。这项研究是儿科放射治疗后放射性毒性的体素分析的第一步。