%0 Journal Article
%T 持续性亚实性肺结节的生长预测研究进展<br>Research Advances on Growth Prediction of Persistent Subsolid Nodules
%A 王雯琦
%A 李长毅
%J Advances in Clinical Medicine
%P 1244-1251
%@ 2161-8720
%D 2024
%I Hans Publishing
%R 10.12677/ACM.2024.141180
%X 随着全球肺癌筛查计划的实施，亚实性肺结节的高发现率越来越受到重视。持续存在的亚实性结节很有可能是前驱腺体病变或癌性病变。目前还不清楚需通过手术切除的持续性亚实性肺结节的特征，以及稳定的亚实性肺结节的随访年限。在过去的几年里，已经发布了许多肺结节的管理指南，但这些指南仍然存在争议。另外，随着放射组学、人工智能技术飞速发展，也建立了许多结节生长的预测模型。故本文就持续性亚实性结节的生长定义、生长影响因素、预测模型和分子生物学特征作一综述，旨在优化亚实性肺结节的随访管理和临床决策。<br />
With the implementation of the global lung cancer screening program, the high detection rate of pulmonary subsolid nodules has received more and more attention. Persistent subsolid nodules are likely to be prodromal or cancerous. The features of persistent subsolid pulmonary nodules requir-ing surgical resection and the follow-up period are unclear. Over the past few years, a number of guidelines have been issued for the management of pulmonary nodules, but these guidelines re-main controversial. In addition, with the rapid development of radiomics and artificial intelligence technology, many prediction models for nodule growth have been established. Therefore, this arti-cle reviews the growth definition, growth influencing factors, prediction models and molecular bi-ology characteristics of persistent subsolid pulmonary nodules, aiming to optimize the follow-up management and clinical decision-making of pulmonary subsolid nodules.
%K 亚实性结节，生长，放射组学，人工智能<br>Subsolid Nodules
%K Growth
%K Radiomics
%K Artificial Intelligence
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=79752