肺结节的生长动态:对肺癌筛查分类的影响。

IF 3.5 2区 医学 Q2 ONCOLOGY Cancer Imaging Pub Date : 2024-08-26 DOI:10.1186/s40644-024-00755-y
Beatriz Ocaña-Tienda, Alba Eroles-Simó, Julián Pérez-Beteta, Estanislao Arana, Víctor M Pérez-García
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引用次数: 0

摘要

背景:在癌症筛查中观察到的肺结节被认为是呈指数增长的,其相关的体积倍增时间(VDT)已被提出用于结节分类。这项回顾性研究旨在阐明肺结节的生长动态,并确定良性或恶性结节的最佳分类:方法:分析了 180 名参加 I-ELCAP 筛查计划(140 名原发性肺癌患者和 40 名良性患者)的患者(73.7% 为男性)的数据,这些患者在切除术前每年接受三次或三次以上的 CT 检查。作为分类方法,对衰减、体积、质量和生长模式(减速、线性、亚指数、指数和加速)进行了评估和比较:结果:大多数肺癌(83/140)和少数良性结节(11/40)表现出加速生长模式,快于指数生长模式。一半(50%)的良性结节和 26.4% 的恶性结节呈减速生长。通过生长模式的差异可以对结节的恶性程度进行分类,最有效的个体变量是两年间隔扫描之间体积的增加(ROC-AUC = 0.871)。前两次随访的相同指标的 AUC 值为 0.769。进一步分为实性、部分实性或非实性后,结果有所改善(第一年的ROC-AUC为0.813,第二年为0.897):结论:在我们的数据集中,与良性肿瘤相比,大多数肺癌都表现出加速生长。通过测量体积增长可以区分良性和恶性结节。如果增加有关结节紧密度的信息,其分类能力就会增强。将这两个有意义且容易获得的变量结合起来,可用于评估肺癌结节的恶性程度。
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Growth dynamics of lung nodules: implications for classification in lung cancer screening.

Background: Lung nodules observed in cancer screening are believed to grow exponentially, and their associated volume doubling time (VDT) has been proposed for nodule classification. This retrospective study aimed to elucidate the growth dynamics of lung nodules and determine the best classification as either benign or malignant.

Methods: Data were analyzed from 180 participants (73.7% male) enrolled in the I-ELCAP screening program (140 primary lung cancer and 40 benign) with three or more annual CT examinations before resection. Attenuation, volume, mass and growth patterns (decelerated, linear, subexponential, exponential and accelerated) were assessed and compared as classification methods.

Results: Most lung cancers (83/140) and few benign nodules (11/40) exhibited an accelerated, faster than exponential, growth pattern. Half (50%) of the benign nodules versus 26.4% of the malignant ones displayed decelerated growth. Differences in growth patterns allowed nodule malignancy to be classified, the most effective individual variable being the increase in volume between two-year-interval scans (ROC-AUC = 0.871). The same metric on the first two follow-ups yielded an AUC value of 0.769. Further classification into solid, part-solid or non-solid, improved results (ROC-AUC of 0.813 in the first year and 0.897 in the second year).

Conclusions: In our dataset, most lung cancers exhibited accelerated growth in contrast to their benign counterparts. A measure of volumetric growth allowed discrimination between benign and malignant nodules. Its classification power increased when adding information on nodule compactness. The combination of these two meaningful and easily obtained variables could be used to assess malignancy of lung cancer nodules.

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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
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