Prognostic Role Of Computed Tomography Textural Features In Early-Stage Non-Small Cell Lung Cancer Patients Receiving Stereotactic Body Radiotherapy
Prognostic Role Of Computed Tomography Textural Features In Early-Stage Non-Small Cell Lung Cancer Patients Receiving Stereotactic Body Radiotherapy
复制标题
计算机断层扫描纹理特征对接受立体定向放射治疗的早期非小细胞肺癌患者的预后作用
DOI：
10.2147/cmar.s220587
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发表时间：
2019-11
影响因子：
3.3
通讯作者：
Xing Ligang
中科院分区：
文献类型：
--
作者：
Zhang Ran;Wang Changbin;Cui Kai;Chen Yicong;Sun Fenghao;Sun Xiaorong;Xing Ligang
目的了解早期非小细胞肺癌（NSCLC）立体定向体部放疗（SBRT）患者的影像学特征，为制定治疗方案提供依据。本研究的目的是预测SBRT的临床结果从预处理的计算机断层扫描（CT）图像的纹理特征。患者和方法41例接受SBRT的早期NSCLC患者纳入本回顾性研究。总共从预处理对比增强CT图像中提取了72个纹理特征。生存分析用于确定无进展生存期（PFS）和疾病特异性生存期（DSS）的高风险组。采用受试者工作特征曲线（ROC）分析评价纹理参数的诊断能力。进行单变量和多变量考克斯回归分析，以评价PFS和DSS的预测因素。结果熵（P=0.003）、二阶矩（P=0.04）、高强度长期加重（P=0.046）和长期加重（P=0.042）4个参数是PFS的重要预后指标。此外，对比度（P=0.008），粗糙度（P=0.017），低强度区域强调（LIZE）（P=0.01）和大量强调（LNE）（P=0.046）是DSS的重要预后因素。ROC曲线分析中，局部复发（LR）的粗糙度曲线下面积（AUC）为0.722（0.528-0.916），淋巴结转移（LNM）的熵曲线下面积（AUC）为0.771（0.556-0.987）。远处转移（DM）的4个最高AUC分别为LNE 0.885（0.784-0.985）、SAM 0.846（0.733-0.959）、LRE 0.731（0.500-0.961）和造影剂0.731（0.585-0.876）。在多变量分析中，吸烟和熵是PFS的独立预后因素。结论术前CT图像的纹理特征对SBRT治疗的早期NSCLC患者有预后价值。
Purpose The imaging features of patients with early-stage non-small cell lung cancer (NSCLC) receiving stereotactic body radiotherapy (SBRT) are crucial for the decision-making process to establish a treatment plan. The purpose of this study was to predict the clinical outcomes of SBRT from the textural features of pretreatment computed tomography (CT) images. Patients and methods Forty-one early-stage NSCLC patients who received SBRT were included in this retrospective study. In total, 72 textural features were extracted from the pretreatment contrast-enhanced CT images. Survival analysis was used to identify high-risk groups for progression-free survival (PFS) and disease-specific survival (DSS). Receiver operating characteristic (ROC) curve analysis was utilized to estimate the diagnostic abilities of the textural parameters. Univariable and multivariable Cox regression analyses were performed to evaluate the predictors of PFS and DSS. Results Four parameters, including entropy (P=0.003), second angular moment (SAM) (P=0.04), high-intensity long-run emphasis (HILRE) (P=0.046) and long-run emphasis (LRE) (P=0.042), were significant prognostic features for PFS. In addition, contrast (P=0.008), coarseness (P=0.017), low-intensity zone emphasis (LIZE) (P=0.01) and large number emphasis (LNE) (P=0.046) were significant prognostic factors for DSS. In the ROC analysis, the area under the curve (AUC) of coarseness for local recurrence (LR) was 0.722 (0.528–0.916), and the AUC of entropy for lymph node metastasis (LNM) was 0.771 (0.556–0.987). The four highest AUCs for distant metastasis (DM) were 0.885 (0.784–0.985) for LNE, 0.846 (0.733–0.959) for SAM, 0.731 (0.500–0.961) for LRE and 0.731 (0.585–0.876) for contrast. In the multivariable analysis, smoking and entropy were independent prognostic factors for PFS. Conclusion This exploratory study reveals that textual features derived from pretreatment CT scans have prognostic value in early-stage NSCLC patients treated with SBRT.
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DOI：
10.1177/107327480100800403
发表时间：
2001-07
期刊：
Cancer control : journal of the Moffitt Cancer Center
影响因子：
--
作者：
W. Smythe
通讯作者：
W. Smythe
影响因子：
5.7
作者：
Huynh, Elizabeth;Coroller, Thibaud P.;Aerts, Hugo J. W. L.
通讯作者：
Aerts, Hugo J. W. L.
DOI：
10.1111/ajco.12128
发表时间：
2016-03
期刊：
Asia‐Pacific Journal of Clinical Oncology
影响因子：
--
作者：
Hidekazu Tanaka;S. Hayashi;H. Hoshi
通讯作者：
Hidekazu Tanaka;S. Hayashi;H. Hoshi
影响因子：
5.7
作者：
Huang, Kitty;Senthi, Sashendra;Senan, Suresh
通讯作者：
Senan, Suresh
DOI：
10.1007/s00259-009-1291-x
发表时间：
2010-04
影响因子：
9.1
作者：
Agarwal, Mohit;Brahmanday, Govinda;Bajaj, Sunil K.;Ravikrishnan, K. P.;Wong, Ching-Yee Oliver
通讯作者：
Wong, Ching-Yee Oliver