Table_1_Assessment and Prognostic Value of Immediate Changes in Post-Ablation Intratumor Density Heterogeneity of Pulmonary Tumors via Radiomics-Based Computed Tomography Features.docx

ObjectivesTo retrospectively observe the instantaneous changes in intratumor density heterogeneity after microwave ablation (MWA) of lung tumors and to determine their prognostic value in predicting treatment response and local tumor progression (LTP).
MethodsPre- and post-MWA computed tomography (CT) images of 50 patients (37-males; 13-females; mean-age 65.9 ± 9.7y, 39 primary and 11 metastasis) were analyzed to evaluate changes in intratumor density. Global, regional, and local scale radiomics features were extracted to assess intratumor density heterogeneity. In four to six weeks, chest enhanced CT was used as the baseline evaluation of treatment response. The correlations between the parametric variation immediately after ablation and the visual score of ablation response (Rvisu) were analyzed by nonparametric Spearman correlation analysis. The 1-year LTP discrimination power was assessed using the area under the receiver operating characteristic (ROC) curves. A Cox proportional hazards regression model was used to identify the independent prognostic features.
ResultsAlthough no significant volume changes were observed after ablation, the radiomics parameters changed in different directions and degrees. The mean intensity value from baseline CT image was 30.3 ± 23.2, and the post-MWA CT image was -60.9 ± 89.8. The ratio of values change was then calculated by a unified formulation. The largest increase (522.3%) was observed for cluster prominence, while the mean CT value showed the largest decline (321.4%). The pulmonary tumors had a mean diameter of 3.4 ± 0.8 cm. Complete ablation was documented in 36 patients. Significant correlations were observed between Rvisu and quantitative features. The highest correlations were observed for changes in local features after MWA, with r ranging from 0.594 to 0.782. LTP developed in 22 patients. The Cox regression model revealed Δcontrast% and response score as independent predictors (Δcontrast%: odds ratio [OR]=5.61, p=0.001; Rvisu: OR=1.73, p=0019). ROC curve analysis showed that Δcontrast% was a better predictor of 1-year LTP. with higher sensitivity (83.5% vs. 71.2%) and specificity (87.1% vs. 76.8%) than those for Rvisu.
ConclusionsThe changes in intratumor density heterogeneity after MWA could be characterized by analysis of radiomics features. Real-time density changes could predict treatment response and LTP in patients with pulmonary tumors earlier, especially for tumors with larger diameters.

研究目的
本研究旨在回顾性观察肺肿瘤微波消融（Microwave Ablation, MWA）后肿瘤内密度异质性的瞬时变化，并明确其在预测治疗应答与局部肿瘤进展（Local Tumor Progression, LTP）中的预后价值。

研究方法
本研究纳入50例肺肿瘤患者（男性37例，女性13例；平均年龄65.9±9.7岁，其中原发性肿瘤39例，转移性肿瘤11例），对其微波消融前后的计算机断层扫描（Computed Tomography, CT）影像进行分析，以评估肿瘤内密度变化。提取全局、区域及局部尺度的放射组学（radiomics）特征，用以评价肿瘤内密度异质性。于消融后4至6周行胸部增强CT作为治疗应答的基线评估。采用非参数Spearman相关分析，探究消融后即刻的参数变化与消融应答视觉评分（Rvisu）之间的相关性。采用受试者工作特征（Receiver Operating Characteristic, ROC）曲线下面积评估1年局部肿瘤进展（LTP）的鉴别效能。采用Cox比例风险回归模型筛选独立预后特征。

研究结果
尽管消融后未观察到明显的体积变化，但放射组学参数的变化方向与程度各不相同。基线CT图像的平均强度值为30.3±23.2，微波消融后CT图像的平均强度值为-60.9±89.8。随后通过统一公式计算数值变化率。其中聚类显著性（cluster prominence）的增幅最大，达522.3%，而平均CT值的降幅最大，达321.4%。本研究纳入的肺肿瘤平均直径为3.4±0.8 cm。36例患者实现完全消融。Rvisu与定量特征之间存在显著相关性。其中，消融后局部特征的变化相关性最高，相关系数r介于0.594至0.782之间。22例患者出现局部肿瘤进展（LTP）。Cox回归模型显示，Δ对比度百分比（Δcontrast%）与应答评分均为独立预测因子（Δcontrast%：优势比[OR]=5.61，P=0.001；Rvisu：OR=1.73，P=0.019）。ROC曲线分析显示，Δcontrast%对1年LTP的预测效能更佳，其灵敏度（83.5% vs 71.2%）与特异度（87.1% vs 76.8%）均高于Rvisu。

研究结论
微波消融后肿瘤内密度异质性的变化可通过放射组学特征分析进行表征。实时密度变化可较早预测肺肿瘤患者的治疗应答与局部肿瘤进展，对于直径较大的肿瘤尤为如此。