Prognostic value of initial [18F]FDG PET/computed tomography volumetric and texture analysis-based parameters in patients with head and neck squamous cell carcinoma
Prognostic value of initial [18F]FDG PET/computed tomography volumetric and texture analysis-based parameters in patients with head and neck squamous cell carcinoma
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初始 [18F]FDG PET/计算机断层扫描基于体积和纹理分析的参数对头颈鳞状细胞癌患者的预后价值
DOI：
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发表时间：
2023
影响因子：
1.5
通讯作者：
Salwa Abd El
中科院分区：
文献类型：
--
作者：
Mai Amr Elahmadawy;Aya Ashraf;H. Moustafa;M. Kotb;Salwa Abd El
工作目的 确定初始 [18F]FDG PET/计算机断层扫描 (CT) 体积和放射组学分析对头颈鳞状细胞癌 (HNSCC) 患者的预测价值。方法 纳入 46 例经病理证实的 HNSCC 成年患者，并接受治疗前 [18F]FDG PET/CT。使用 LIFEx 6.73.3 软件进行半定量 PET 衍生体积分析 [（最大标准化摄取值 (SUVmax) 和平均 SUV (SUVmean)、总病灶糖酵解 (TLG) 和代谢肿瘤体积 (MTV)] 和放射组学分析。结果 在当前研究组中，受试者工作特征曲线标志着初级 MTV 的截止点为 21.105，曲线下面积 (AUC) 为0.727，敏感性为 62.5%，特异性为 86.8%（P 值为 0.041），可区分有反应者和无反应者，同时无法确定具有统计学显着性的主要 SUV 平均值或最大或主要 TLG 截止点，这也标志着初级 MTV 的生存预测截止点为 10.845，AUC 为 0.728，敏感性为 80%，特异性为 77.8%。 （P 值 0.026）。对 PET 衍生的体积和纹理特征显着参数的协同性能进行了测试，试图开发最准确和稳定的预测模型，因此，进行多变量逻辑回归分析来检测死亡率的独立预测因子，原发肿瘤 MTV 和纹理特征灰度共生矩阵相关性的组合提供了最准确的预测。结论 纹理特征指数是一种捕获肿瘤内异质性的非侵入性方法，在我们的研究中，成功生成了具有高特异性和准确性的 PET 衍生预测模型。
Aim of work To determine the predictive value of initial [18F]FDG PET/computed tomography (CT) volumetric and radiomics-derived analyses in patients with head and neck squamous cell carcinoma (HNSCC). Methods Forty-six adult patients had pathologically proven HNSCC and underwent pretherapy [18F]FDG PET/CT were enrolled. Semi-quantitative PET-derived volumetric [(maximum standardized uptake value (SUVmax) and mean SUV (SUVmean), total lesion glycolysis (TLG) and metabolic tumor volume (MTV)] and radiomics analyses using LIFEx 6.73.3 software were performed. Results In the current study group, the receiver operating characteristic curve marked a cutoff point of 21.105 for primary MTV with area under the curve (AUC) of 0.727, sensitivity of 62.5%, and specificity of 86.8% (P value 0.041) to distinguish responders from non-responders, while no statistically significant primary SUVmean or max or primary TLG cut off points could be determined. It also marked the cutoff point for survival prediction of 10.845 for primary MTV with AUC 0.728, sensitivity of 80%, and specificity of 77.8% (P value 0.026). A test of the synergistic performance of PET-derived volumetric and textural features significant parameters was conducted in an attempt to develop the most accurate and stable prediction model. Therefore, multivariate logistic regression analysis was performed to detect independent predictors of mortality. With a high specificity of 97.1% and an overall accuracy of 89.1%, the combination of primary tumor MTV and the textural feature gray-level co-occurrence matrix correlation provided the most accurate prediction of mortality (P value < 0.001). Conclusion Textural feature indices are a noninvasive method for capturing intra-tumoral heterogeneity. In our study, a PET-derived prediction model was successfully generated with high specificity and accuracy.
DOI：
10.1016/j.ijrobp.2008.10.060
发表时间：
2009-08-01
影响因子：
7
作者：
La, Trang H.;Filion, Edith J.;Turnbull, Brit B.;Chu, Jackie N.;Lee, Percy;Nguyen, Khoa;Maxim, Peter;Quon, Andy;Graves, Edward E.;Loo, Billy W., Jr.;Le, Quynh-Thu
通讯作者：
Le, Quynh-Thu
DOI：
10.2217/iim.12.60
发表时间：
2012-12
期刊：
Imaging in medicine
影响因子：
--
作者：
Paidpally V;Chirindel A;Lam S;Agrawal N;Quon H;Subramaniam RM
通讯作者：
Subramaniam RM