Association between age and lung cancer risk: evidence from lung lobar radiomics.

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Yuwei Li, Chengting Lin, Lei Cui, Chao Huang, Liting Shi, Shiyang Huang, Yue Yu, Xianglan Zhou, Qian Zhou, Kun Chen, Lei Shi
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引用次数: 0

Abstract

Background: Previous studies have highlighted the prominent role of age in lung cancer risk, with signs of lung aging visible in computed tomography (CT) imaging. This study aims to characterize lung aging using quantitative radiomic features extracted from five delineated lung lobes and explore how age contributes to lung cancer development through these features.

Methods: We analyzed baseline CT scans from the Wenling lung cancer screening cohort, consisting of 29,810 participants. Deep learning-based segmentation method was used to delineate lung lobes. A total of 1,470 features were extracted from each lobe. The minimum redundancy maximum relevance algorithm was applied to identify the top 10 age-related radiomic features among 13,137 never smokers. Multiple regression analyses were used to adjust for confounders in the association of age, lung lobar radiomic features, and lung cancer. Linear, Cox proportional hazards, and parametric accelerated failure time models were applied as appropriate. Mediation analyses were conducted to evaluate whether lobar radiomic features mediate the relationship between age and lung cancer risk.

Results: Age was significantly associated with an increased lung cancer risk, particularly among current smokers (hazard ratio = 1.07, P = 2.81 × 10- 13). Age-related radiomic features exhibited distinct effects across lung lobes. Specifically, the first order mean (mean attenuation value) filtered by wavelet in the right upper lobe increased with age (β = 0.019, P = 2.41 × 10- 276), whereas it decreased in the right lower lobe (β = -0.028, P = 7.83 × 10- 277). Three features, namely wavelet_HL_firstorder_Mean of the right upper lobe, wavelet_LH_firstorder_Mean of the right lower lobe, and original_shape_MinorAxisLength of the left upper lobe, were independently associated with lung cancer risk at Bonferroni-adjusted P value. Mediation analyses revealed that density and shape features partially mediated the relationship between age and lung cancer risk while a suppression effect was observed in the wavelet first order mean of right upper lobe.

Conclusions: The study reveals lobe-specific heterogeneity in lung aging patterns through radiomics and their associations with lung cancer risk. These findings may contribute to identify new approaches for early intervention in lung cancer related to aging.

Clinical trial number: Not applicable.

年龄与肺癌风险之间的关系:来自肺叶放射组学的证据。
背景:先前的研究强调了年龄在肺癌风险中的重要作用,在计算机断层扫描(CT)成像中可以看到肺衰老的迹象。本研究旨在利用从五个肺叶中提取的定量放射学特征来表征肺衰老,并通过这些特征探讨年龄如何影响肺癌的发展。方法:我们分析了温岭市肺癌筛查队列的基线CT扫描,包括29,810名参与者。采用基于深度学习的分割方法对肺叶进行分割。每个叶共提取1470个特征。应用最小冗余最大相关算法在13137名从不吸烟者中识别出与年龄相关的前10个放射性特征。使用多元回归分析来调整混杂因素与年龄、肺叶放射学特征和肺癌的关系。适当地应用线性、Cox比例风险和参数加速失效时间模型。进行中介分析以评估大叶放射学特征是否介导年龄与肺癌风险之间的关系。结果:年龄与肺癌风险增加显著相关,特别是在当前吸烟者中(危险比= 1.07,P = 2.81 × 10- 13)。年龄相关的放射学特征在肺叶上表现出明显的影响。其中,右上叶一阶均值(平均衰减值)随年龄增大而增大(β = 0.019, P = 2.41 × 10- 276),右下叶一阶均值随年龄减小(β = -0.028, P = 7.83 × 10- 277)。右上肺叶的wavet_hl_firstorder_mean、右下肺叶的wavet_lh_firstorder_mean、左上肺叶的original_shape_MinorAxisLength三个特征在bonferroni校正P值下与肺癌风险独立相关。中介分析发现,密度和形状特征在年龄与肺癌风险之间有部分中介作用,右上肺叶小波一阶均值存在抑制作用。结论:该研究通过放射组学揭示了肺衰老模式的肺叶特异性异质性及其与肺癌风险的关系。这些发现可能有助于确定与衰老相关的肺癌早期干预的新方法。临床试验号:不适用。
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
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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