Placidi Lorenzo, Gioscio Eliana, Garibaldi Cristina, Rancati Tiziana, Fanizzi Annarita, Maestri Davide, Massafra Raffaella, Menghi Enrico, Mirandola Alfredo, Reggiori Giacomo, Sghedoni Roberto, Tamborra Pasquale, Comi Stefania, Lenkowicz Jacopo, Boldrini Luca, Avanzo Michele
Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Roma, Italy.
Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale Tumori, 20133 Milano, Italy.
Cancers (Basel). 2021 Jul 30;13(15):3835. doi: 10.3390/cancers13153835.
Dosiomics is a texture analysis method to produce dose features that encode the spatial 3D distribution of radiotherapy dose. Dosiomic studies, in a multicentre setting, require assessing the features' stability to dose calculation settings and the features' capability in distinguishing different dose distributions. Dose distributions were generated by eight Italian centres on a shared image dataset acquired on a dedicated phantom. Treatment planning protocols, in terms of planning target volume coverage and dose-volume constraints to the organs at risk, were shared among the centres to produce comparable dose distributions for measuring reproducibility/stability and sensitivity of dosiomic features. In addition, coefficient of variation (CV) was employed to evaluate the dosiomic features' variation. We extracted 38,160 features from 30 different dose distributions from six regions of interest, grouped by four features' families. A selected group of features (CV < 3 for the reproducibility/stability studies, CV > 1 for the sensitivity studies) were identified to support future multicentre studies, assuring both stable features when dose distributions variation is minimal and sensitive features when dose distribution variations need to be clearly identified. Dosiomic is a promising tool that could support multicentre studies, especially for predictive models, and encode the spatial and statistical characteristics of the 3D dose distribution.
剂量组学是一种纹理分析方法，用于生成编码放射治疗剂量空间三维分布的剂量特征。在多中心环境下进行的剂量组学研究，需要评估特征对剂量计算设置的稳定性以及特征区分不同剂量分布的能力。八个意大利中心在一个专用体模上采集的共享图像数据集上生成了剂量分布。各中心共享了在计划靶区覆盖范围和危及器官的剂量体积约束方面的治疗计划方案，以生成可比较的剂量分布，用于测量剂量组学特征的再现性/稳定性和敏感性。此外，采用变异系数（CV）来评估剂量组学特征的变异情况。我们从六个感兴趣区域的30种不同剂量分布中提取了38160个特征，按四个特征类别进行分组。确定了一组选定的特征（用于再现性/稳定性研究时CV<3，用于敏感性研究时CV>1），以支持未来的多中心研究，确保在剂量分布变化最小时特征稳定，在需要清晰识别剂量分布变化时特征敏感。剂量组学是一种很有前景的工具，可以支持多中心研究，特别是对于预测模型，并编码三维剂量分布的空间和统计特征。
