CT Predictors of Angiolymphatic Invasion in Non-Small Cell Lung Cancer 30 mm or Smaller.

IF 12.1 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Radiology Pub Date : 2025-01-01 DOI:10.1148/radiol.240599
Qi Sun, Pengfei Li, Jiafang Zhang, Rowena Yip, David F Yankelevitz, Claudia I Henschke
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Abstract

Background Angiolymphatic invasion (ALI) is an important prognostic indicator in non-small cell lung cancer (NSCLC). However, few studies focus on radiologic features for predicting ALI in patients with early-stage NSCLCs 30 mm or smaller. Purpose To identify radiologic features for predicting ALI in NSCLCs 30 mm or smaller in maximum diameter. Materials and Methods This study was a secondary review of pathologic and CT findings from an integrated health care system between January 2016 and November 2023 for participants in the prospective study Initiative for Early Lung Cancer Research on Treatment, or IELCART. Preoperative diagnostic radiologic features possibly related to ALI, volume doubling time (VDT), and PET maximum standardized uptake value were evaluated. Multivariable logistic regression analysis, adjusted for sex, age, nodule size, and smoking status, was used to determine predictors of ALI. Model performance was analyzed with the area under the receiver operating characteristic curve (AUC). Results Of 778 resected NSCLCs 30 mm or smaller (median patient age, 69 years [IQR, 63-76 years]; 458 female patients), 715 (92%) were solid, 41 (5%) were part-solid, and 22 (3%) were nonsolid. ALI was documented in 271 (35%) resected NSCLCs, all in solid NSCLCs, representing 37.9% (95% CI: 34.4, 41.5) of solid NSCLCs. None of the 63 subsolid NSCLCs had ALI (0% [95% CI: 0, 5.75]). For the 715 solid NSCLCs (median patient age, 69 years [IQR, 63-76 years]; 420 female patients), multivariable logistic regression analysis showed that lollipop sign (odds ratio [OR] = 4.12 [95% CI: 2.82, 6.04]; P < .001) and spiculation (OR = 2.05 [95% CI: 1.42, 2.97]; P < .001) were independent predictors of ALI (AUC = 0.77 [95% CI: 0.73, 0.80]). Considering only the 474 patients in whom VDT could be calculated based on CT scans, VDT was also an independent predictor for ALI (OR = 0.96 [95% CI: 0.94, 0.98]; P < .001). Incorporating VDT into the model improved ALI prediction (AUC = 0.82 [95% CI: 0.77, 0.86]; P < .001). Conclusion For patients with NSCLCs 30 mm or smaller, ALI was present in 37.9% of solid NSCLCs and none of the 63 subsolid NSCLCs. Among solid NSCLCs, lollipop sign, spiculation, and VDT were independent radiologic predictors of ALI. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Czum in this issue.

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30mm及以下非小细胞肺癌血管淋巴浸润的CT预测因素。
血管淋巴浸润(ALI)是非小细胞肺癌(NSCLC)的重要预后指标。然而,很少有研究关注于预测早期非小细胞肺癌30mm或更小患者ALI的影像学特征。目的探讨预测最大直径小于30mm的非小细胞肺癌ALI的影像学特征。材料和方法本研究是对2016年1月至2023年11月期间来自综合医疗保健系统的病理和CT结果的二次回顾,参与者是早期肺癌研究治疗前瞻性研究计划(IELCART)的参与者。评估术前可能与ALI、体积倍增时间(VDT)和PET最大标准化摄取值相关的诊断放射学特征。采用多变量logistic回归分析,调整性别、年龄、结节大小和吸烟状况,以确定ALI的预测因素。用接收机工作特性曲线下面积(AUC)对模型性能进行分析。结果778例30mm或更小的非小细胞肺癌(患者中位年龄69岁[IQR, 63-76岁];女性458例),实性715例(92%),半实性41例(5%),非实性22例(3%)。271例(35%)被切除的非小细胞肺癌记录了ALI,均为实性非小细胞肺癌,占实性非小细胞肺癌的37.9% (95% CI: 34.4, 41.5)。63例亚实性非小细胞肺癌均无ALI (0% [95% CI: 0,5.75])。715例实体性非小细胞肺癌(患者年龄中位数为69岁[IQR, 63-76岁];420例女性患者),多变量logistic回归分析显示棒棒糖体征(优势比[OR] = 4.12 [95% CI: 2.82, 6.04];P < .001)和棘刺(OR = 2.05 [95% CI: 1.42, 2.97];P < 0.001)是ALI的独立预测因子(AUC = 0.77 [95% CI: 0.73, 0.80])。考虑到只有474例患者可以通过CT扫描计算VDT, VDT也是ALI的独立预测因子(OR = 0.96 [95% CI: 0.94, 0.98];P < 0.001)。将VDT纳入模型可改善ALI预测(AUC = 0.82 [95% CI: 0.77, 0.86];P < 0.001)。结论对于30mm及以下的nsclc患者,37.9%的实性nsclc存在ALI, 63例亚实性nsclc中无ALI。在实性非小细胞肺癌中,棒棒糖征、针状突起和VDT是ALI的独立放射学预测因子。©RSNA, 2025本文可获得补充材料。参见Czum在本期的社论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Radiology
Radiology 医学-核医学
CiteScore
35.20
自引率
3.00%
发文量
596
审稿时长
3.6 months
期刊介绍: Published regularly since 1923 by the Radiological Society of North America (RSNA), Radiology has long been recognized as the authoritative reference for the most current, clinically relevant and highest quality research in the field of radiology. Each month the journal publishes approximately 240 pages of peer-reviewed original research, authoritative reviews, well-balanced commentary on significant articles, and expert opinion on new techniques and technologies. Radiology publishes cutting edge and impactful imaging research articles in radiology and medical imaging in order to help improve human health.
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