Risk assessment and stepwise management framework for pulmonary nodules_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

TANG Lang ^1,2 , CHEN Xiaoke ² , TANG Jie ² , JIANG Jin ² , FANG Xinnan ² , LIU Sikun ² , YE Zeguang ² , JIN Jiamei ² , ZHANG Canglei ² , ZHONG Wenzhao ³ , WANG Haibo ⁴ , HU Yi ⁵ , ZHANG Hao ⁶ , DAI Jigang ⁷ , QIAO Guibin ⁸ ,  FAN Junqiang ²

1. Bengbu Medical University, Bengbu, 233030, Anhui, P. R. China;
2. Department of Thoracic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, P. R. China;
3. Department of Thoracic Surgery, Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, P. R. China;
4. Center for Medical Big Data and Artificial Intelligence, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, P. R. China;
5. Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, 100039, P. R. China;
6. Department of Thoracic Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, P. R. China;
7. Department of Thoracic Surgery, The Second Affiliated Hospital of Third Military Medical University, Chongqing, 630037, P. R. China;
8. Department of Thoracic Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, P. R. China;

Corresponding?author：

FAN Junqiang, Email: zrxwk@zju.edu.cn

Keywords：

Pulmonary nodule; risk assessment; stepwise management; multidisciplinary collaboration; clinical decision-making

DOI：

10.7507/1007-4848.202608010

Video：

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Abstract Full text Figures/Tables Video References Cited by

Objective To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

Citation： TANG Lang, CHEN Xiaoke, TANG Jie, JIANG Jin, FANG Xinnan, LIU Sikun, YE Zeguang, JIN Jiamei, ZHANG Canglei, ZHONG Wenzhao, WANG Haibo, HU Yi, ZHANG Hao, DAI Jigang, QIAO Guibin, FAN Junqiang. Risk assessment and stepwise management framework for pulmonary nodules. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2026, 33(10): 1544-1552. doi: 10.7507/1007-4848.202608010 Copy

1.	中華醫學會呼吸病學分會, 中國肺癌防治聯盟. 肺結節診治中國專家共識(2024年版)[J]. 中華結核和呼吸雜志, 2024, 47(8): 716-729.Chinese Thoracic Society, Chinese Medical Association; Chinese Alliance Against Lung Cancer Expert Group. Chinese expert consensus on the diagnosis and treatment of pulmonary nodules (2024 edition)[J]. Chin J Tuberc Respir Dis, 2024, 47(8): 716-729.
2.	MacMahon H, Naidich DP, Goo JM, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017[J]. Radiology, 2017, 284(1): 228-243.
3.	Callister MEJ, Baldwin DR, Akram AR, et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules[J]. Thorax, 2015, 70(Suppl 2): ii1-ii54.
4.	中華醫學會健康管理學分會, 中華醫學會放射學分會, 《中華健康管理學雜志》編輯委員會. 肺癌篩查及肺結節健康管理專家共識(2025版)[J]. 中華健康管理學雜志, 2025, 19(10): 759-769.Chinese Medical Association Health Management Branch, Chinese Medical Association Radiology Branch, Editorial Board of Chinese Journal of Health Management. Expert consensus on lung cancer screening and pulmonary nodule health management (2025 Edition)[J]. Chin J Health Manage, 2025, 19(10): 759-769.
5.	Christensen J, Prosper AE, Wu CC, et al. ACR Lung-RADS v2022: assessment categories and management recommendations[J]. Chest, 2024, 165(3): 738-753.
6.	Swensen SJ, Silverstein MD, Ilstrup DM, et al. The probability of malignancy in solitary pulmonary nodules: application to small radiologically indeterminate nodules[J]. Arch Intern Med, 1997, 157(8): 849-855.
7.	Wu H, Chen X, Feng X, et al. Efficacy of three lung cancer prediction models in diagnosing benign and malignant pulmonary nodules[J]. Transl Cancer Res, 2025, 14(4): 2410-2420.
8.	Wang C, Shao J, He Y, et al. Data-driven risk stratification and precision management of pulmonary nodules detected on chest computed tomography[J]. Nat Med, 2024, 30(11): 3184-3195.
9.	Chen S, Lin WL, Liu WT, et al. Pulmonary nodule malignancy probability: a meta-analysis of the Brock model[J/OL]. Clin Radiol, 2025, 82: 106788. DOI: 10.1016/j.crad.2025.106788.
10.	Izawa A, Hara Y, Horita N, et al. Improved diagnostic accuracy with three lung tumor markers compared to six-marker panel[J]. Transl Lung Cancer Res, 2024, 13(3): 503-511.
11.	Gould MK, Donington J, Lynch WR, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines[J/OL]. Chest, 2013, 143(5 Suppl): e93S-e120S. DOI: 10.1378/chest.12-2355.
12.	Zhang W, Cui X, Wang J, et al. The study of plain CT combined with contrast-enhanced CT-based models in predicting malignancy of solitary solid pulmonary nodules[J/OL]. Sci Rep, 2024, 14: 21871. DOI: 10.1038/s41598-024-72345-6.
13.	Machado DI, Brito-Rocha T, Salta S, et al. Circulating cell-free DNA methylation as biomarker for lung cancer detection: a systematic review and meta-analysis of diagnostic studies[J/OL]. Syst Rev, 2025, 14: 120. DOI: 10.1186/s13643-025-02789-6.
14.	Guo Q, Deng C, Pan X, et al. A noninvasive circulating tumor DNA methylation classifier to identify benign pulmonary nodules[J]. Clin Cancer Res, 2026, 32(16): 3629-3640.
15.	Wang H, Huang H, Li F, et al. Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study (DECIPHER-NODL)[J/OL]. Lancet Reg Health West Pac, 2025, 64: 101730. DOI: 10.1016/j.lanwpc.2025.101730.
16.	He J, Wang H, Feng Y, et al. Integrative fragmentomic and mutational signature profile of plasma cfDNA for early lung cancer detection[J/OL]. NPJ Precis Oncol, 2026, 10(1): 307. DOI: 10.1038/s41698-026-01416-y.
17.	Meng R, Gao Y, Peng Z, et al. Development and validation of a small extracellular vesicle-derived RNA signature for early diagnosis of lung adenocarcinoma and prognosis in advanced stages[J]. Mol Cancer, 2026, 25: 7.
18.	Wang Y, Duan Y, Guo D, et al. Value of circulating tumor cell assisting low-dose computed tomography in screening pulmonary nodules based on existing liquid biopsy techniques: a systematic review with meta-analysis and trial sequential analysis[J]. Clin Transl Oncol, 2024, 26(12): 3252-3263.
19.	Guo H, Zhao W, Li C, et al. The diagnostic efficacy of seven autoantibodies in early detection of ground-glass nodular lung adenocarcinoma[J/OL]. Front Oncol, 2024, 14: 1499140. DOI: 10.3389/fonc.2024.1499140.
20.	Filis P, Markozannes G, Salgkamis D, et al. Integrating liquid biopsies and artificial intelligence for early cancer detection: a systematic review and meta-analysis[J/OL]. Eur J Cancer, 2026, 239: 116699. DOI: 10.1016/j.ejca.2025.116699.
21.	Panagiotou E, Vathiotis IA, Makrythanasis P, et al. Biological and therapeutic implications of the cancer-related germline mutation landscape in lung cancer[J]. Lancet Respir Med, 2024, 12(12): 997-1005.
22.	Mucci LA, Hjelmborg JB, Harris JR, et al. Familial risk and heritability of cancer among twins in Nordic countries[J]. JAMA, 2016, 315(1): 68-76.
23.	McKay JD, Hung RJ, Han Y, et al. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes[J]. Nat Genet, 2017, 49(7): 1126-1132.
24.	Govindan R, Navo K, Huang M, et al. Germline alterations in patients with lung cancer[J]. Ann Oncol, 2026, 37(5): 701-711.
25.	Arrieta O, Caballe-Perez E, Hernandez-Pedro N, et al. Prevalence of pathogenic or likely pathogenic germline variants in cancer predisposition genes among selected patients with lung adenocarcinoma: the GERMLUNG study[J/OL]. Lung Cancer, 2024, 194: 107864. DOI: 10.1016/j.lungcan.2024.107864.
26.	Mukherjee S, Bandlamudi C, Hellmann MD, et al. Germline pathogenic variants impact clinicopathology of advanced lung cancer[J]. Cancer Epidemiol Biomarkers Prev, 2022, 31(7): 1450-1459.
27.	Zurera M, Laguna JC, Mezquita L, et al. Germline mutation analysis and real-world impact in a selected cohort of patients with non-small cell lung cancer: INHERITY LC study[J]. Clin Lung Cancer, 2026, 27(3): 144-152. e4.
28.	Agrawal A, Chitikela SD, Rastogi A, et al. Germline variants in Indian non-small cell lung cancer patients with familial aggregation: a prospective cohort study[J]. Clin Lung Cancer, 2026, 27(1): 15-23.
29.	Oxnard GR, Chen R, Pharr JR, et al. Germline EGFR mutations and familial lung cancer[J]. J Clin Oncol, 2023, 41(34): 5274-5284.
30.	Saridaki Z, Fountzilas E, Alexopoulos A, et al. Inherited rare epidermal growth factor receptor mutation and somatic mutations in patients with non-small cell lung cancer: a case report[J]. BMC Med Genomics, 2025, 18: 51.
31.	中華醫學會腫瘤學分會. 中華醫學會肺癌臨床診療指南(2025版)[J]. 中華醫學雜志, 2025, 105(34): 2918-2959.Oncology Society of Chinese Medical Association. Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2025 edition)[J]. Natl Med J China, 2025, 105(34): 2918-2959.
32.	胡堅, 支修益, 劉倫旭, 等. 直徑≤2 cm肺結節胸外科合理診療中國專家共識(2024)[J]. 中國胸心血管外科臨床雜志, 2024, 31(8): 1077-1089.Hu J, Zhi XY, Liu LX, et al. Chinese thoracic surgery expert consensus on rational diagnosis and treatment of pulmonary nodules with a diameter ≤2 cm (2024)[J]. Chin J Clin Thorac Cardiovasc Surg, 2024, 31(8): 1077-1089.
33.	Balasubramanian P, Abia-Trujillo D, Barrios-Ruiz A, et al. Diagnostic yield and safety of diagnostic techniques for pulmonary lesions: systematic review, meta-analysis and network meta-analysis[J/OL]. Eur Respir Rev, 2024, 33: 240046. DOI: 10.1183/16000617.0046-2024.
34.	Altorki N, Wang X, Kozono D, et al. Lobar or sublobar resection for peripheral stage ⅠA non-small-cell lung cancer[J]. N Engl J Med, 2023, 388(6): 489-498.
35.	Bankier AA, MacMahon H, Colby TV, et al. Fleischner Society: glossary of terms for thoracic imaging—2024 update[J/OL]. Radiology, 2024, 310(2): e232558. DOI: 10.1148/radiol.232558.
36.	Jiang B, Han D, van der Aalst CM, et al. Lung cancer volume doubling time by computed tomography: a systematic review and meta-analysis[J/OL]. Eur J Cancer, 2024, 212: 114339. DOI: 10.1016/j.ejca.2024.114339.
37.	Prokop M, Schaefer-Prokop C, Jacobs C, et al. Aggressiveness-guided nodule management for lung cancer screening in Europe—justification for follow-up intervals and definition of growth[J]. Eur Radiol, 2026, 36(1): 122-134.
38.	Li TZ, Xu K, Krishnan A, et al. Performance of lung cancer prediction models for screening-detected, incidental, and biopsied pulmonary nodules[J/OL]. Radiol Artif Intell, 2025, 7(2): e230506. DOI: 10.1148/ryai.230506.
39.	Antonissen N, Venkadesh KV, Dinnessen R, et al. External test of a deep learning algorithm for pulmonary nodule malignancy risk stratification using European screening data[J/OL]. Radiology, 2025, 316(3): e250874. DOI: 10.1148/radiol.250874.
40.	Zhao M, Xue G, He B, et al. Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer[J]. Nat Commun, 2025, 16: 84.
41.	McIntosh LJ. A new framework for pulmonary nodules: how terminology impacts management[J]. Eur Radiol, 2026, 36(6): 4354-4365.
42.	Gilyard S, Ahmed O, Kim CY, et al. ACR Appropriateness Criteria? radiologic management of pulmonary nodules and masses: update 2025[J]. J Am Coll Radiol, 2026, 23(5): 915-927.

1. 中華醫學會呼吸病學分會, 中國肺癌防治聯盟. 肺結節診治中國專家共識(2024年版)[J]. 中華結核和呼吸雜志, 2024, 47(8): 716-729.Chinese Thoracic Society, Chinese Medical Association; Chinese Alliance Against Lung Cancer Expert Group. Chinese expert consensus on the diagnosis and treatment of pulmonary nodules (2024 edition)[J]. Chin J Tuberc Respir Dis, 2024, 47(8): 716-729.
2. MacMahon H, Naidich DP, Goo JM, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017[J]. Radiology, 2017, 284(1): 228-243.
3. Callister MEJ, Baldwin DR, Akram AR, et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules[J]. Thorax, 2015, 70(Suppl 2): ii1-ii54.
4. 中華醫學會健康管理學分會, 中華醫學會放射學分會, 《中華健康管理學雜志》編輯委員會. 肺癌篩查及肺結節健康管理專家共識(2025版)[J]. 中華健康管理學雜志, 2025, 19(10): 759-769.Chinese Medical Association Health Management Branch, Chinese Medical Association Radiology Branch, Editorial Board of Chinese Journal of Health Management. Expert consensus on lung cancer screening and pulmonary nodule health management (2025 Edition)[J]. Chin J Health Manage, 2025, 19(10): 759-769.
5. Christensen J, Prosper AE, Wu CC, et al. ACR Lung-RADS v2022: assessment categories and management recommendations[J]. Chest, 2024, 165(3): 738-753.
6. Swensen SJ, Silverstein MD, Ilstrup DM, et al. The probability of malignancy in solitary pulmonary nodules: application to small radiologically indeterminate nodules[J]. Arch Intern Med, 1997, 157(8): 849-855.
7. Wu H, Chen X, Feng X, et al. Efficacy of three lung cancer prediction models in diagnosing benign and malignant pulmonary nodules[J]. Transl Cancer Res, 2025, 14(4): 2410-2420.
8. Wang C, Shao J, He Y, et al. Data-driven risk stratification and precision management of pulmonary nodules detected on chest computed tomography[J]. Nat Med, 2024, 30(11): 3184-3195.
9. Chen S, Lin WL, Liu WT, et al. Pulmonary nodule malignancy probability: a meta-analysis of the Brock model[J/OL]. Clin Radiol, 2025, 82: 106788. DOI: 10.1016/j.crad.2025.106788.
10. Izawa A, Hara Y, Horita N, et al. Improved diagnostic accuracy with three lung tumor markers compared to six-marker panel[J]. Transl Lung Cancer Res, 2024, 13(3): 503-511.
11. Gould MK, Donington J, Lynch WR, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines[J/OL]. Chest, 2013, 143(5 Suppl): e93S-e120S. DOI: 10.1378/chest.12-2355.
12. Zhang W, Cui X, Wang J, et al. The study of plain CT combined with contrast-enhanced CT-based models in predicting malignancy of solitary solid pulmonary nodules[J/OL]. Sci Rep, 2024, 14: 21871. DOI: 10.1038/s41598-024-72345-6.
13. Machado DI, Brito-Rocha T, Salta S, et al. Circulating cell-free DNA methylation as biomarker for lung cancer detection: a systematic review and meta-analysis of diagnostic studies[J/OL]. Syst Rev, 2025, 14: 120. DOI: 10.1186/s13643-025-02789-6.
14. Guo Q, Deng C, Pan X, et al. A noninvasive circulating tumor DNA methylation classifier to identify benign pulmonary nodules[J]. Clin Cancer Res, 2026, 32(16): 3629-3640.
15. Wang H, Huang H, Li F, et al. Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study (DECIPHER-NODL)[J/OL]. Lancet Reg Health West Pac, 2025, 64: 101730. DOI: 10.1016/j.lanwpc.2025.101730.
16. He J, Wang H, Feng Y, et al. Integrative fragmentomic and mutational signature profile of plasma cfDNA for early lung cancer detection[J/OL]. NPJ Precis Oncol, 2026, 10(1): 307. DOI: 10.1038/s41698-026-01416-y.
17. Meng R, Gao Y, Peng Z, et al. Development and validation of a small extracellular vesicle-derived RNA signature for early diagnosis of lung adenocarcinoma and prognosis in advanced stages[J]. Mol Cancer, 2026, 25: 7.
18. Wang Y, Duan Y, Guo D, et al. Value of circulating tumor cell assisting low-dose computed tomography in screening pulmonary nodules based on existing liquid biopsy techniques: a systematic review with meta-analysis and trial sequential analysis[J]. Clin Transl Oncol, 2024, 26(12): 3252-3263.
19. Guo H, Zhao W, Li C, et al. The diagnostic efficacy of seven autoantibodies in early detection of ground-glass nodular lung adenocarcinoma[J/OL]. Front Oncol, 2024, 14: 1499140. DOI: 10.3389/fonc.2024.1499140.
20. Filis P, Markozannes G, Salgkamis D, et al. Integrating liquid biopsies and artificial intelligence for early cancer detection: a systematic review and meta-analysis[J/OL]. Eur J Cancer, 2026, 239: 116699. DOI: 10.1016/j.ejca.2025.116699.
21. Panagiotou E, Vathiotis IA, Makrythanasis P, et al. Biological and therapeutic implications of the cancer-related germline mutation landscape in lung cancer[J]. Lancet Respir Med, 2024, 12(12): 997-1005.
22. Mucci LA, Hjelmborg JB, Harris JR, et al. Familial risk and heritability of cancer among twins in Nordic countries[J]. JAMA, 2016, 315(1): 68-76.
23. McKay JD, Hung RJ, Han Y, et al. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes[J]. Nat Genet, 2017, 49(7): 1126-1132.
24. Govindan R, Navo K, Huang M, et al. Germline alterations in patients with lung cancer[J]. Ann Oncol, 2026, 37(5): 701-711.
25. Arrieta O, Caballe-Perez E, Hernandez-Pedro N, et al. Prevalence of pathogenic or likely pathogenic germline variants in cancer predisposition genes among selected patients with lung adenocarcinoma: the GERMLUNG study[J/OL]. Lung Cancer, 2024, 194: 107864. DOI: 10.1016/j.lungcan.2024.107864.
26. Mukherjee S, Bandlamudi C, Hellmann MD, et al. Germline pathogenic variants impact clinicopathology of advanced lung cancer[J]. Cancer Epidemiol Biomarkers Prev, 2022, 31(7): 1450-1459.
27. Zurera M, Laguna JC, Mezquita L, et al. Germline mutation analysis and real-world impact in a selected cohort of patients with non-small cell lung cancer: INHERITY LC study[J]. Clin Lung Cancer, 2026, 27(3): 144-152. e4.
28. Agrawal A, Chitikela SD, Rastogi A, et al. Germline variants in Indian non-small cell lung cancer patients with familial aggregation: a prospective cohort study[J]. Clin Lung Cancer, 2026, 27(1): 15-23.
29. Oxnard GR, Chen R, Pharr JR, et al. Germline EGFR mutations and familial lung cancer[J]. J Clin Oncol, 2023, 41(34): 5274-5284.
30. Saridaki Z, Fountzilas E, Alexopoulos A, et al. Inherited rare epidermal growth factor receptor mutation and somatic mutations in patients with non-small cell lung cancer: a case report[J]. BMC Med Genomics, 2025, 18: 51.
31. 中華醫學會腫瘤學分會. 中華醫學會肺癌臨床診療指南(2025版)[J]. 中華醫學雜志, 2025, 105(34): 2918-2959.Oncology Society of Chinese Medical Association. Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2025 edition)[J]. Natl Med J China, 2025, 105(34): 2918-2959.
32. 胡堅, 支修益, 劉倫旭, 等. 直徑≤2 cm肺結節胸外科合理診療中國專家共識(2024)[J]. 中國胸心血管外科臨床雜志, 2024, 31(8): 1077-1089.Hu J, Zhi XY, Liu LX, et al. Chinese thoracic surgery expert consensus on rational diagnosis and treatment of pulmonary nodules with a diameter ≤2 cm (2024)[J]. Chin J Clin Thorac Cardiovasc Surg, 2024, 31(8): 1077-1089.
33. Balasubramanian P, Abia-Trujillo D, Barrios-Ruiz A, et al. Diagnostic yield and safety of diagnostic techniques for pulmonary lesions: systematic review, meta-analysis and network meta-analysis[J/OL]. Eur Respir Rev, 2024, 33: 240046. DOI: 10.1183/16000617.0046-2024.
34. Altorki N, Wang X, Kozono D, et al. Lobar or sublobar resection for peripheral stage ⅠA non-small-cell lung cancer[J]. N Engl J Med, 2023, 388(6): 489-498.
35. Bankier AA, MacMahon H, Colby TV, et al. Fleischner Society: glossary of terms for thoracic imaging—2024 update[J/OL]. Radiology, 2024, 310(2): e232558. DOI: 10.1148/radiol.232558.
36. Jiang B, Han D, van der Aalst CM, et al. Lung cancer volume doubling time by computed tomography: a systematic review and meta-analysis[J/OL]. Eur J Cancer, 2024, 212: 114339. DOI: 10.1016/j.ejca.2024.114339.
37. Prokop M, Schaefer-Prokop C, Jacobs C, et al. Aggressiveness-guided nodule management for lung cancer screening in Europe—justification for follow-up intervals and definition of growth[J]. Eur Radiol, 2026, 36(1): 122-134.
38. Li TZ, Xu K, Krishnan A, et al. Performance of lung cancer prediction models for screening-detected, incidental, and biopsied pulmonary nodules[J/OL]. Radiol Artif Intell, 2025, 7(2): e230506. DOI: 10.1148/ryai.230506.
39. Antonissen N, Venkadesh KV, Dinnessen R, et al. External test of a deep learning algorithm for pulmonary nodule malignancy risk stratification using European screening data[J/OL]. Radiology, 2025, 316(3): e250874. DOI: 10.1148/radiol.250874.
40. Zhao M, Xue G, He B, et al. Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer[J]. Nat Commun, 2025, 16: 84.
41. McIntosh LJ. A new framework for pulmonary nodules: how terminology impacts management[J]. Eur Radiol, 2026, 36(6): 4354-4365.
42. Gilyard S, Ahmed O, Kim CY, et al. ACR Appropriateness Criteria? radiologic management of pulmonary nodules and masses: update 2025[J]. J Am Coll Radiol, 2026, 23(5): 915-927.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Risk assessment and stepwise management framework for pulmonary nodules

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