IRCCS SDN, Naples, Italy.
Institute of Biostructures and Bioimaging, National Research Council (CNR), Naples, Italy.
Sci Rep. 2017 Aug 3;7(1):7220. doi: 10.1038/s41598-017-07586-x.
The risk of radiation-induced toxicity in patients treated for head and neck (HN) cancer with radiation therapy (RT) is traditionally estimated by condensing the 3D dose distribution into a monodimensional cumulative dose-volume histogram which disregards information on dose localization. We hypothesized that a voxel-based approach would identify correlations between radiation-induced morbidity and local dose release, thus providing a new insight into spatial signature of radiation sensitivity in composite regions like the HN district. This methodology was applied to a cohort of HN cancer patients treated with RT at risk of radiation-induced acute dysphagia (RIAD). We implemented an inter-patient elastic image registration framework that proved robust enough to match even the most elusive HN structures and to provide accurate dose warping. A voxel-based statistical analysis was then performed to test regional dosimetric differences between patients with and without RIAD. We identified a significantly higher dose delivered to RIAD patients in two voxel clusters in correspondence of the cricopharyngeus muscle and cervical esophagus. Our study goes beyond the well-established organ-based philosophy exploring the relationship between radiation-induced morbidity and local dose differences in the HN region. This approach is generally applicable to different HN toxicity endpoints and is not specific to RIAD.
接受放射治疗的头颈部 (HN) 癌症患者的放射性毒性风险传统上是通过将 3D 剂量分布浓缩为一维累积剂量-体积直方图来估计的，这种方法忽略了剂量定位的信息。我们假设基于体素的方法将确定放射性发病率与局部剂量释放之间的相关性，从而为 HN 等复合区域的放射敏感性的空间特征提供新的见解。该方法应用于一组接受放射治疗、有发生放射性急性吞咽困难 (RIAD) 风险的 HN 癌症患者。我们实施了一种患者间弹性图像配准框架，该框架足够稳健，可以匹配即使是最难以捉摸的 HN 结构，并提供准确的剂量变形。然后进行基于体素的统计分析，以测试 RIAD 患者与无 RIAD 患者之间的区域剂量差异。我们在环状软骨肌和颈食管对应位置的两个体素簇中发现 RIAD 患者接受的剂量明显更高。我们的研究超越了传统的基于器官的理念，探索了 HN 区域放射性发病率与局部剂量差异之间的关系。这种方法通常适用于不同的 HN 毒性终点，并且不仅限于 RIAD。
