CT-based Radiogenomic Analysis of Clinical Stage I Lung Adenocarcinoma with Histopathologic Features and Oncologic Outcomes
CT-based Radiogenomic Analysis of Clinical Stage I Lung Adenocarcinoma with Histopathologic Features and Oncologic Outcomes
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DOI：
10.1148/radiol.211582
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发表时间：
2022-06-01
期刊：
影响因子：
19.7
通讯作者：
Jones, David R.
中科院分区：
文献类型：
--
作者：
Perez-Johnston, Rocio;Araujo-Filho, Jose A.;Jones, David R.
背景资料：需要一个术前预测模型，用于识别肺腺癌（LUAD）患者复发或转移的高风险。目的：研究I期LUAD基于CT的放射组学一致聚类与临床病理特征、基因组数据和患者预后之间的关系。材料和方法：回顾性确定了2014年4月至2017年12月期间接受LUAD完全手术切除的患者，术前CT和下一代测序数据。对术前CT图像进行了全面的放射组学分析;肿瘤被分类为实性、毛玻璃样或混合性。使用共识聚类法，根据患者的放射组学特征将其分组，并将聚类与肿瘤基因组改变、组织病理学特征和复发特异性生存率进行比较（Kruskal-Wallis检验用于连续数据，卡方（2）或Fisher精确检验用于分类数据，对数秩检验用于复发特异性生存率）。对整个队列和实性、磨玻璃样和混合性病变亚组进行聚类分析。结果：总共有219例患者被纳入研究（中位年龄68岁;四分位距63-74岁; 150例[68%]女性）。确定了四个放射组簇。第1组与麻风、腺泡和乳头亚型相关（76/90 [84%]）;第2组（13/50 [26%]）和第4组（13/45 [29%]）与实体和微乳头亚型相关（P <0.001）。EGFR改变在第1组中最高（38/90 [42%]，P = .004）。第2、3和4组与淋巴管浸润有关（分别为50例中的19例[38%]、34例中的14例[41%]和45例中的28例[62%]; P < .001）和肿瘤通过空气间隙扩散（分别为50例中的32例[64%]、34例中的21例[62%]和45例中的31例[69%]; P < .001）。STK 11改变（14/45 [31%]; P = .006），磷酸肌醇3-激酶通路改变（22/45 [49%]，P < .001），复发风险（对数秩P < .001）在第4组中最高。CT-基于放射组学一致性聚类的放射组学特征与临床病理学和基因组学特征之间的相关性识别，临床I期肺腺癌患者的结局。(C)RSNA，2022
Background: A preoperative predictive model is needed that can be used to identify patients with lung adenocarcinoma (LUAD) who have a higher risk of recurrence or metastasis.Purpose: To investigate associations between CT-based radiomic consensus clustering of stage I LUAD and clinical-pathologic features, genomic data, and patient outcomes.Materials and Methods: Patients who underwent complete surgical resection for LUAD from April 2014 to December 2017 with preoperative CT and next-generation sequencing data were retrospectively identified. Comprehensive radiomic analysis was performed on preoperative CT images; tumors were classified as solid, ground glass, or mixed. Patients were clustered into groups based on their radiomics features using consensus clustering, and clusters were compared with tumor genomic alterations, histopathologic features, and recurrence-specific survival (Kruskal-Wallis test for continuous data, chi(2) or Fisher exact test for categorical data, and log-rank test for recurrence-specific survival). Cluster analysis was performed on the entire cohort and on the solid, ground-glass, and mixed lesion subgroups.Results: In total, 219 patients were included in the study (median age, 68 years; interquartile range, 63-74 years; 150 [68%] women). Four radiomic clusters were identified. Cluster 1 was associated with lepidic, acinar, and papillary subtypes (76 of 90 [84%]); clusters 2 (13 of 50 [26%]) and 4 (13 of 45 [29%]) were associated with solid and micropapillary subtypes (P < .001). The EGFR alterations were highest in cluster 1 (38 of 90 [42%], P = .004). Clusters 2, 3, and 4 were associated with lymphovascular invasion (19 of 50 [38%], 14 of 34 [41%], and 28 of 45 [62%], respectively; P < .001) and tumor spread through air spaces (32 of 50 [64%], 21 of 34 [62%], and 31 of 45 [69%], respectively; P < .001). STK11 alterations (14 of 45 [31%]; P = .006), phosphoinositide 3-kinase pathway alterations (22 of 45 [49%], P < .001), and risk of recurrence (log-rank P < .001) were highest in cluster 4.Conclusion: CT-based radiomic consensus clustering enabled identification of associations between radiomic features and clinicalpathologic and genomic features and outcomes in patients with clinical stage I lung adenocarcinoma. (C) RSNA, 2022