| [1] |
李祥天,温小晖,王若琳,等. 机械拉伸载荷调控肺癌细胞行为的分子机制[J]. 中国临床解剖学杂志,2025,43(4):444-449.doi:10.13418/j.issn.1001-165x.2025.4.13 .
doi: 10.13418/j.issn.1001-165x.2025.4.13
|
| [2] |
KANZAKI R, REID S, BOLIVAR P,et al. FHL2 expression by cancer-associated fibroblasts promotes metastasis and angiogenesis in lung adenocarcinoma[J]. Int J Cancer,2025,156(2):431-446.doi: 10.1002/ijc.35174 .
doi: 10.1002/ijc.35174
|
| [3] |
YIN X, LU Y, CUI Y,et al. CT-based radiomics-deep learning model predicts occult lymph node metastasis in early-stage lung adenocarcinoma patients: A multicenter study[J]. Chin J Cancer Res,2025,37(1):12-27.doi: 10.21147/j.issn.1000-9604.2025. 01.02 .
doi: 10.21147/j.issn.1000-9604.2025. 01.02
|
| [4] |
LIU J, LI Y, LONG Y,et al. Predicting High-risk Lung Adenocarcinoma in Solid and Part-solid Nodules on Low-dose CT: A Multicenter Study[J]. Acad Radiol,2025,32(5): 2966-2976.doi: 10.1016/j.acra.2024.11.059 .
doi: 10.1016/j.acra.2024.11.059
|
| [5] |
ZOU P L, MA C H, LI X,et al. Early Lung Adenocarcinoma Manifesting as Irregular Subsolid Nodules: Clinical and CT Characteristics[J]. Acad Radiol,2025,32(4): 2320- 2329.doi: 10.1016/j.acra.2024.12.010 .
doi: 10.1016/j.acra.2024.12.010
|
| [6] |
石琴,张依凡,杨易,等. 18F-FDG PET/CT预测浸润性肺腺癌WHO(2021)组织学分级[J]. 中国医学影像学杂志,2025,33(2):171-176.doi: 10.3969/j.issn.1005-5185. 2025.02.012 .
doi: 10.3969/j.issn.1005-5185. 2025.02.012
|
| [7] |
WU L H, CHEN L, WANG Q Y,et al. Correlation between HRCT signs and levels of CA125, SCCA, and NSE for different pathological types of lung cancer[J]. Eur Rev Med Pharmacol Sci,2023,27(9):4162-4168.doi: 10.26355/eurrev_202305_32325 .
doi: 10.26355/eurrev_202305_32325
|
| [8] |
ZHANG G, SHANG L, LI S,et al. Non-enhanced CT deep learning model for differentiating lung adenocarcinoma from tuberculoma: A multicenter diagnostic study[J]. Eur Radiol,2025,35(12):8116-8125.doi: 10.1007/s00330-025-11721-y .
doi: 10.1007/s00330-025-11721-y
|
| [9] |
AZUMA Y, SAKAMOTO S, HOMMA S,et al. Impact of accurate diagnosis of interstitial lung diseases on postoperative outcomes in lung cancer[J]. Gen Thorac Cardiovasc Surg,2023,71(2):129-137.doi: 10.1007/s11748-022-01868-6 .
doi: 10.1007/s11748-022-01868-6
|
| [10] |
中国医疗保健国际交流促进会肿瘤内科学分会,中国医师协会肿瘤医师分会. Ⅳ期原发性肺癌中国治疗指南(2024版)[J].中华肿瘤杂志,2024,46(7):595-636. doi:10.3760/cma.j.cn112152-20240311-00104 .
doi: 10.3760/cma.j.cn112152-20240311-00104
|
| [11] |
SASAKI T, KUNO H, HIYAMA T,et al. 2021 WHO Classification of Lung Cancer: Molecular Biology Research and Radiologic-Pathologic Correlation[J]. Radiographics, 2024,44(3):1-36.doi: 10.1148/rg.230136 .
doi: 10.1148/rg.230136
|
| [12] |
王春,王晓娣,张海涛,等. 人工智能量化参数联合256层螺旋CT扫描对肺磨玻璃结节浸润程度的预测[J]. 实用医学杂志,2025,41(19):3106-3111. doi:10.3969/j.issn.1006-5725.2025. 19.022 .
doi: 10.3969/j.issn.1006-5725.2025. 19.022
|
| [13] |
CHEN L, SU Y, HUANG Y,et al. Predicting lymphovascular invasion in stage IA lung adenocarcinoma: A CT-based classification and regression tree model[J]. Eur Radiol,2025,35(10):6357-6368.doi: 10.1007/s00330-025-11593-2 .
doi: 10.1007/s00330-025-11593-2
|
| [14] |
古明宇, 郑翔匀, 马吉尔, 等. 干细胞治疗在肺移植领域中的应用现状[J]. 器官移植, 2026, 17(2): 311-318. doi: 10.12464/ j.issn.1674-7445.2025233 .
doi: 10.12464/ j.issn.1674-7445.2025233
|
| [15] |
XU P, YAO F, XU Y,et al. Habitat Radiomics and Deep Learning Features Based on CT for Predicting Lymphovascular Invasion in T1-stage Lung Adenocarcinoma: A Multicenter Study[J]. Acad Radiol,2025,32(8):4860-4870.doi: 10.1016/j.acra.2025. 04.005 .
doi: 10.1016/j.acra.2025. 04.005
|
| [16] |
HUANG L, XU L, WANG X,et al. Prediction of EGFR Mutations in Lung Adenocarcinoma via CT Images: A Comparative Study of Intratumoral and Peritumoral Radiomics, Deep Learning, and Fusion Models[J]. Acad Radiol, 2025,32(8):4880-4892.doi: 10.1016/j.acra.2025.04.029 .
doi: 10.1016/j.acra.2025.04.029
|
| [17] |
汪琼,王之悦,雍千叶,等. 肺结节圆度在HRCT多平面重建图像上对纯磨玻璃结节的浸润性预测优于常规横断位[J]. 中国CT和MRI杂志,2025,23(9): 44-46, 93.doi: 10.3969/j.issn.1 672-5131.2025.09.013 .
doi: 10.3969/j.issn.1 672-5131.2025.09.013
|
| [18] |
武国华,伏平友,邢璐,宋方. 51例单发炎性肺磨玻璃结节患者HRCT特异征象分析[J]. 医学影像学杂志,2025,35(9):65-67.doi: 10.20258/j.cnki.1006-9011.2025. 09.015 .
doi: 10.20258/j.cnki.1006-9011.2025. 09.015
|
| [19] |
张利霞,刘海霞,陈玮,等. 纯磨玻璃结节的HRCT征象对非附壁型浸润性肺腺癌的诊断价值[J]. 河北医学,2023,29(1):112-115.doi: 10.3969/j.issn.1006-6233. 2023. 01.021 .
doi: 10.3969/j.issn.1006-6233. 2023. 01.021
|
| [20] |
刘江勇,黄文才,薛阳,等. 基于HRCT浸润性肺腺癌异质性分析及其与肿瘤倍增时间的相关性[J]. 放射学实践,2023,38(8):990-995.doi: 10.13609/j.cnki.1000-0313. 2023.08.006 .
doi: 10.13609/j.cnki.1000-0313. 2023.08.006
|
| [21] |
CHEN X, QI H, ZOU Y,et al. Predicting the spread through air spaces in lung adenocarcinoma from preoperative 18 F-FDG PET/CT radiomics[J]. Nucl Med Commun,2025,46(6):570-578.doi: 10.1097/MNM.0000000000001975 .
doi: 10.1097/MNM.0000000000001975
|
| [22] |
SATO J, YANAGAWA M, NISHIGAKI D,et al. Radiologists Versus AI-Based Software: Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma From CT Under Various Image Display Conditions[J]. Clin Lung Cancer,2025,26(1): 58-71.doi: 10.1016/j.cllc.2024.10.015 .
doi: 10.1016/j.cllc.2024.10.015
|
| [23] |
DING X, ZHOU W, ZHONG G,et al. One-year mortality risk prediction model for patients with interstitial lung disease and lung cancer[J]. Transl Lung Cancer Res,2025, 14(5):1786-1803.doi: 10.21037/tlcr-2025-235 .
doi: 10.21037/tlcr-2025-235
|
| [24] |
KUDO Y, SAITO A, HORIUCHI T,et al. Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology[J]. Surg Today, 2025,55(1):18-28.doi: 10.1007/s00595-024-02869-z .
doi: 10.1007/s00595-024-02869-z
|
| [25] |
CHEN S, WANG X, LIN X,et al. CT-based radiomics predictive model for spread through air space of IA stage lung adenocarcinoma[J]. Acta Radiol,2025,66(5): 477- 486.doi: 10.1177/02841851241305737 .
doi: 10.1177/02841851241305737
|
| [26] |
MORI S, HASEGAWA M, SAKAI F,et al. Incidence of and predictive factors for lung cancer in patients with rheumatoid arthritis: A retrospective long-term follow-up study[J]. Mod Rheumatol,2025,35(2):240-248.doi: 10.1093/mr/roae084 .
doi: 10.1093/mr/roae084
|
| [27] |
邓琦,徐志锋,周涛,等. 基于人工智能CT定量分析对长径≤10 mm肺磨玻璃结节浸润程度的预测价值[J].实用放射学杂志,2023,39(7):1088-1092.doi: 10.3969/j.issn.1002-1671. 2023.07.010 .
doi: 10.3969/j.issn.1002-1671. 2023.07.010
|