Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer.
Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer.
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DOI：
10.1016/j.ijrobp.2014.07.020
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发表时间：
2014-11-15
影响因子：
7
通讯作者：
Court, Laurence E.
中科院分区：
文献类型：
--
作者：
Fried, David V.;Tucker, Susan L.;Zhou, Shouhao;Liao, Zhongxing;Mawlawi, Osama;Ibbott, Geoffrey;Court, Laurence E.
确定治疗前CT纹理特征是否可以改善III期非小细胞肺癌（NSCLC）患者的风险分层，超出常规预后因素（CPF）。我们回顾性分析了91例接受明确放化疗的III期NSCLC患者。所有患者均接受了治疗前诊断性对比增强CT（CE-CT），随后进行了4D-CT模拟治疗。我们使用4D-CT的平均（平均-CT）和呼气（T50-CT）图像以及CE-CT进行纹理提取。采用直方图、梯度、共生、灰度差分和滤波等技术进行纹理特征提取。采用实施交叉验证的惩罚性考克斯回归进行协变量选择和建模。将包含来自3种图像类型和CPF的纹理特征的模型与仅包含CPF的模型进行总生存率（OS）、局部区域控制（LRC）和无远处转移（FFDM）的比较。使用留一法交叉验证生成预测性Kaplan-Meier曲线。根据患者的预测结局高于/低于中位数对患者进行分层。纹理特征的再现性进行了评估，使用测试-重测扫描从独立的患者和量化的一致性相关系数（CCC）。我们比较了模型，将重复测试扫描上看到的再现性与我们的原始模型进行比较，并确定了分类再现性。结合纹理特征和CPF的模型显示，与仅使用CPF的模型相比，OS（p = 0.046）、LRC（p = 0.01）和FFDM（p = 0.005）的风险分层显著改善。从平均CT、T50-CT和CE-CT提取的纹理特征的平均CCC分别为0.89、0.91和0.67。在我们的模型中，在OS、LRC和FFDM方面的重复性分别为80.4%（SD = 3.7）、78.3%（SD = 4.0）和78.8%（SD = 3.9）。治疗前的肿瘤纹理可以提供超出CPF的预后信息。结合特征再现性的模型实现了~80%的分类率。将需要外部验证来建立纹理作为预后因素。
To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). We retrospectively reviewed 91 patients with stage III NSCLC treated with definitive chemoradiation. All patients underwent a pretreatment diagnostic contrast enhanced CT (CE-CT) followed by a 4D-CT for treatment simulation. We used the average (average-CT) and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray-tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation was used for covariate selection and modeling. Models incorporating texture features from the 3 image types and CPFs were compared to models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on their predicted outcome being above/below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (p=0.046), LRC (p=0.01), and FFDM (p=0.005). The average CCC was 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4 (SD=3.7), 78.3 (SD=4.0), and 78.8 (SD=3.9) percent classification reproducibility in terms of OS, LRC, and FFDM, respectively. Pretreatment tumor texture may provide prognostic information beyond what is obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ~80%. External validation would be required to establish texture as a prognostic factor.
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影响因子：
5.9
作者：
Ganeshan, Balaji;Panayiotou, Elleny;Miles, Ken
通讯作者：
Miles, Ken
影响因子：
11.5
作者：
Raz, Dan J.;Ray, M. Roshni;Jablons, David M.
通讯作者：
Jablons, David M.
影响因子：
254.7
作者：
Siegel, Rebecca;Naishadham, Deepa;Jemal, Ahmedin
通讯作者：
Jemal, Ahmedin
影响因子：
9.3
作者：
Cook, Gary J. R.;Yip, Connie;Landau, David
通讯作者：
Landau, David
DOI：
10.1109/tsmc.1973.4309314
发表时间：
1973-01-01
期刊：
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS
影响因子：
--
作者：
HARALICK, RM;SHANMUGAM, K;DINSTEIN, I
通讯作者：
DINSTEIN, I