肺结节MRI发展历程与展望

胡皓; 王宇博; 和正英; 丁志勇; 叶晓丹; 杨斌

doi:10.19732/j.cnki.2096-6210.2026.01.013

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肺结节MRI发展历程与展望

综述 | 更新时间：2026-03-25

- 肺结节MRI发展历程与展望
- Development and prospects of MRI in pulmonary nodule evaluation
- 肿瘤影像学 2026年35卷第1期页码：103-110
- 作者机构：
  
  1.昆明医科大学附属甘美医院医学影像中心，云南昆明650051
  2.昆明医科大学研究生院放射影像学专业，云南昆明650500
  3.迪庆藏族自治州人民医院影像中心，云南迪庆674400
  4.曲靖市妇幼保健院影像中心，云南曲靖655000
  5.复旦大学附属中山医院放射诊断科，上海200032
- 作者简介：
  
  胡　皓（ORCID：0009-0009-1807-9304），硕士研究生。
  杨　斌（ORCID：0000-0001-5518-7325），博士，主任医师，医学影像中心科室主任，E-mail：yyangbinapple@163.com。
- 基金信息：
  
  国家自然科学基金项目(82160348);云南省重大专项计划(202302AA310018-D-8);云南省“兴滇英才支持计划”青年人才专项(XDYC-QNRC-2022-0608);2024年度云南省医学学科带头人培养对象(D-202405);2023年度昆明市卫生科技人才培养项目（医学技术中心）［2023-SW（技术）-13］
- DOI：10.19732/j.cnki.2096-6210.2026.01.013
  中图分类号： R734.2;R445.2
- 收稿：2025-08-14，
  
  修回：2025-10-30，
  
  纸质出版：2026-02-28
- 稿件说明：
移动端阅览
胡　皓, 王宇博, 和正英, 等. 肺结节MRI发展历程与展望［J］. 肿瘤影像学, 2026, 35(1): 103-110.

HU H, WANG Y B, HE Z Y,Citation: et al. Development and prospects of MRI in pulmonary nodule evaluation［J］. Oncoradiology, 2026, 35(1): 103-110.
胡　皓, 王宇博, 和正英, 等. 肺结节MRI发展历程与展望［J］. 肿瘤影像学, 2026, 35(1): 103-110. DOI： 10.19732/j.cnki.2096-6210.2026.01.013.

HU H, WANG Y B, HE Z Y,Citation: et al. Development and prospects of MRI in pulmonary nodule evaluation［J］. Oncoradiology, 2026, 35(1): 103-110. DOI： 10.19732/j.cnki.2096-6210.2026.01.013.

摘要

肺癌是全球范围内导致癌症死亡的首要原因，由于早期症状隐匿，确诊时多已进展。低剂量或标准剂量计算机体层成像（computed tomography，CT）筛查虽提高了早期检出率，但电离辐射暴露问题促使磁共振成像（magnetic resonance imaging，MRI）作为无辐射成像手段受到关注。新型MRI序列在肺结节筛查中展现出优异的抗伪影、高分辨率与小结节识别能力。然而，这些序列在临床推广过程中仍面临标准化参数缺乏、设备依赖高、阅片经验不足等落地难点，限制了其真实世界应用。本文进一步聚焦于此类序列在肺结节早期筛查与定性诊断中的转化瓶颈，尝试构建“性能—适应性—解读”三位一体的评估框架。同时，文章还探讨MRI功能成像与人工智能（artificial intelligence，AI）诊断模型结合的可能性，指出当前AI模型在MRI数据处理上面临训练数据匮乏、序列异构性与特征迁移障碍等关键问题。综上，本文系统分析MRI在肺结节筛查与诊断中的技术进展，特别强调新序列落地难题及AI分析框架缺口，旨在为无辐射肺癌筛查路径提供有针对性的研究思路与实践启示。

Abstract

Lung cancer remains the leading cause of cancer-related mortality worldwide

and its insidious early symptoms often result in diagnosis at an advanced stage. Although low-dose or standard-dose computed tomography (CT) screening has improved early detection rates

concerns regarding ionizing radiation exposure have increased interest in magnetic resonance imaging (MRI) as a radiation-free alternative. Recent advances in novel MRI sequences have demonstrated promising performance in lung nodule screening

offering reduced susceptibility to artifacts

high spatial resolution

and improved detection of small nodules. However

their clinical implementation remains challenging due to the lack of standardized imaging parameters

strong equipment dependence

and limited reader experience

which restrict their real-world applicability. This review focused on the translational bottlenecks of these novel sequences in early lung nodule screening and qualitative diagnosis

and proposed an integrated evaluation framework encompassing performance

adaptability

and interpretability. Furthermore

the potential integration of MRI functional imaging with artificial intelligence (AI)-based diagnostic models is discussed

highlighting current challenges such as limited training datasets

sequence heterogeneity

and barriers to feature transferability. Overall

this review systematically summarized the technological advances of MRI in lung nodule screening and diagnosis

emphasizing the implementation challenges of emerging sequences and gaps in AI analytical frameworks

with the aim of providing targeted research directions and practical insights for radiation-free lung cancer screening strategies.

关键词

Keywords

references

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