Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development.
Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development.
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DOI：
10.1016/j.ijrobp.2014.11.030
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发表时间：
2015-04-01
影响因子：
7
通讯作者：
Al-Hallaq, Hania A.
中科院分区：
文献类型：
--
作者：
Cunliffe, Alexandra;Armato, Samuel G., III;Castillo, Richard;Ngoc Pham;Guerrero, Thomas;Al-Hallaq, Hania A.
评估辐射剂量与一组基于数学强度和纹理的特征变化之间的关系，并确定纹理分析识别患有放射性肺炎 (RP) 的患者的能力。经机构审查委员会批准，对总共 106 名接受食管癌放射治疗 (RT) 的患者进行了回顾性鉴定。对于每位患者，在放疗前（0-168 天）和放疗后（5-120 天）进行诊断性计算机断层扫描 (CT) 扫描，并获得带有相关剂量图的治疗计划 CT 扫描。在每次 RT 前扫描的肺部中随机识别 32 × 32 像素的感兴趣区域 (ROI)。随后通过使用可变形图像配准将 ROI 映射到 RT 后扫描和计划扫描剂量图。计算 RT 扫描 ROI 前后 20 个特征值 (ΔFV) 的变化。使用回归模型和方差分析来测试 ΔFV、平均 ROI 剂量和≥2 级 RP 发展之间的关系。计算受试者工作特征曲线下面积 (AUC)，以确定每个特征区分患有 RP 的患者和不患有 RP 的患者的能力。构建分类器以确定 2 个或 3 个特征组合是否可以提高 RP 区分度。对于所有 20 个特征，随着辐射剂量的增加，观察到显着的 ΔFV。 RP 患者有 12 项特征发生显着变化。个体纹理特征可以区分具有中等表现（AUC 为 0.49 至 0.78）的 RP 患者和无 RP 患者。在分类器中使用多个特征，AUC 显着增加 (0.59–0.84)。观察了剂量与一组基于图像的特征的变化之间的关系。对于 12 个特征，ΔFV 与 RP 开发显着相关。这项研究证明了放射组学能够对患者肺组织对 RT 的反应进行定量、个性化测量，并评估 RP 的发展。
To assess the relationship between radiation dose and change in a set of mathematical intensity- and texture-based features and to determine the ability of texture analysis to identify patients who develop radiation pneumonitis (RP). A total of 106 patients who received radiation therapy (RT) for esophageal cancer were retrospectively identified under institutional review board approval. For each patient, diagnostic computed tomography (CT) scans were acquired before (0–168 days) and after (5–120 days) RT, and a treatment planning CT scan with an associated dose map was obtained. 32- × 32-pixel regions of interest (ROIs) were randomly identified in the lungs of each pre-RT scan. ROIs were subsequently mapped to the post-RT scan and the planning scan dose map by using deformable image registration. The changes in 20 feature values (ΔFV) between pre- and post-RT scan ROIs were calculated. Regression modeling and analysis of variance were used to test the relationships between ΔFV, mean ROI dose, and development of grade ≥2 RP. Area under the receiver operating characteristic curve (AUC) was calculated to determine each feature’s ability to distinguish between patients with and those without RP. A classifier was constructed to determine whether 2- or 3-feature combinations could improve RP distinction. For all 20 features, a significant ΔFV was observed with increasing radiation dose. Twelve features changed significantly for patients with RP. Individual texture features could discriminate between patients with and those without RP with moderate performance (AUCs from 0.49 to 0.78). Using multiple features in a classifier, AUC increased significantly (0.59–0.84). A relationship between dose and change in a set of image-based features was observed. For 12 features, ΔFV was significantly related to RP development. This study demonstrated the ability of radiomics to provide a quantitative, individualized measurement of patient lung tissue reaction to RT and assess RP development.
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DOI：
10.1186/1748-717x-9-74
发表时间：
2014-03-13
期刊：
Radiation oncology (London, England)
影响因子：
--
作者：
Castillo R;Pham N;Ansari S;Meshkov D;Castillo S;Li M;Olanrewaju A;Hobbs B;Castillo E;Guerrero T
通讯作者：
Guerrero T
影响因子：
10.6
作者：
CHEN, CC;DAPONTE, JS;FOX, MD
通讯作者：
FOX, MD
影响因子：
3.8
作者：
Cunliffe, Alexandra R.;Contee, Clay;Al-Hallaq, Hania A.
通讯作者：
Al-Hallaq, Hania A.
影响因子：
3.8
作者：
Cunliffe, Alexandra R.;Al-Hallaq, Hania A.;Armato, Samuel G., III
通讯作者：
Armato, Samuel G., III
DOI：
10.1097/01.coc.0000260950.44761.74
发表时间：
2007-08-01
影响因子：
2.6
作者：
Hartsell, William F.;Scott, Charles B.;Weigensberg, Irving J.
通讯作者：
Weigensberg, Irving J.