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Yoon DW, Kang D, Jeon YJ, Lee J, Shin S, Cho JH, Choi YS, Zo JI, Kim J, Shim YM, Cho J, Kim HK, Lee HY. Computed tomography characteristics of cN0 primary non-small cell lung cancer predict occult lymph node metastasis. Eur Radiol 2024:10.1007/s00330-024-10835-z. [PMID: 38850308 DOI: 10.1007/s00330-024-10835-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 04/23/2024] [Accepted: 05/10/2024] [Indexed: 06/10/2024]
Abstract
RATIONALE Occult lymph node metastasis (OLNM) is frequently found in patients with resectable non-small cell lung cancer (NSCLC), despite using diagnostic methods recommended by guidelines. OBJECTIVES To evaluate the risk of OLNM in NSCLC patients using the radiologic characteristics of the primary tumor on computed tomography (CT). METHODS We retrospectively reviewed clinicopathologic features of 2042 clinical T1-4N0 NSCLC patients undergoing curative intent pulmonary resection. Unique radiological features (i.e., air-bronchogram throughout the whole tumor, heterogeneous ground-glass opacity (GGO), mainly cystic appearance, endobronchial location), percentage of solid portion, and shape of tumor margin were analyzed via a stepwise approach. We used multivariable logistic regression to assess the relationship between OLNM and tumor characteristics. RESULTS Compared with the other unique features, endobronchial tumors were associated with the highest risk of OLNM (OR = 3.9, 95% confidence interval (CI) = 2.29-6.62), and heterogeneous GGO and mainly cystic tumors were associated with a low risk of OLNM. For tumors without unique features, the percentage of the solid portion was measured, and solid tumors were associated with OLNM (OR = 2.49, 95% CI = 1.86-3.35). Among part-solid tumors with solid proportion > 50%, spiculated margin, and peri-tumoral GGO were associated with OLNM. CONCLUSIONS The risk of OLNM could be assessed using radiologic characteristics on CT. This could allow us to adequately select optimal candidates for invasive nodal staging procedures (INSPs) and complete systematic lymph node dissection. CLINICAL RELEVANCE STATEMENT These data may be helpful for clinicians to select appropriate candidates for INSPs and complete surgical systematic lymph node dissection in NSCLC patients. KEY POINTS Lymph node metastasis status plays a key role in both prognostication and treatment planning. Solid tumors, particularly endobronchial tumors, were associated with occult lymph node metastasis (OLNM). The risk of OLNM can be assessed using radiologic characteristics acquired from CT images.
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Affiliation(s)
- Dong Woog Yoon
- Department of Thoracic and Cardiovascular Surgery, Chungang-University Hospital, Seoul, South Korea
| | - Danbee Kang
- Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul, South Korea
| | - Yeong Jeong Jeon
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Junghee Lee
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sumin Shin
- Department of Thoracic and Cardiovascular Surgery, School of Medicine, Ewha Womans University, Seoul, South Korea
| | - Jong Ho Cho
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yong Soo Choi
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jae Ill Zo
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jhingook Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Young Mog Shim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Juhee Cho
- Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul, South Korea
- Departments of Epidemiology and Health, Behavior, and Society, Baltimore, MD, USA
| | - Hong Kwan Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ho Yun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea.
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Jiang Y, Deng T, Huang Y, Ren B, He L, Pang M, Jiang L. Developing a multi-institutional nomogram for assessing lung cancer risk in patients with 5-30 mm pulmonary nodules: a retrospective analysis. PeerJ 2023; 11:e16539. [PMID: 38107565 PMCID: PMC10725170 DOI: 10.7717/peerj.16539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 11/08/2023] [Indexed: 12/19/2023] Open
Abstract
Background The diagnosis of benign and malignant solitary pulmonary nodules based on personal experience has several limitations. Therefore, this study aims to establish a nomogram for the diagnosis of benign and malignant solitary pulmonary nodules using clinical information and computed tomography (CT) results. Methods Retrospectively, we collected clinical and CT characteristics of 1,160 patients with pulmonary nodules in Guang'an People's Hospital and the hospital affiliated with North Sichuan Medical College between 2019 and 2021. Among these patients, data from 773 patients with pulmonary nodules were used as the training set. We used the least absolute shrinkage and selection operator (LASSO) to optimize clinical and imaging features and performed a multivariate logistic regression to identify features with independent predictive ability to develop the nomogram model. The area under the receiver operating characteristic curve (AUC), C-index, decision curve analysis, and calibration plot were used to evaluate the performance of the nomogram model in terms of predictive ability, discrimination, calibration, and clinical utility. Finally, data from 387 patients with pulmonary nodules were utilized for validation. Results In the training set, the predictors for the nomogram were gender, density of the nodule, nodule diameter, lobulation, calcification, vacuole, vascular convergence, bronchiole, and pleural traction, selected through LASSO and logistic regression analysis. The resulting model had a C-index of 0.842 (95% CI [0.812-0.872]) and AUCs of 0.842 (95% CI [0.812-0.872]). In the validation set, the C-index was 0.856 (95% CI [0.811-0.901]), and the AUCs were 0.844 (95% CI [0.797-0.891]). Results from the calibration curve and clinical decision curve analyses indicate that the nomogram has a high fit and clinical benefit in both the training and validation sets. Conclusion The establishment of a nomogram for predicting the benign or malignant diagnosis of solitary pulmonary nodules by this study has shown good efficacy. Such a nomogram may help to guide the diagnosis, follow-up, and treatment of patients.
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Affiliation(s)
- Yongjie Jiang
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Taibing Deng
- Department of Respiratory and Critical Care Medicine, Guang’an People’s Hospital, Guang’an, Sichuan, China
| | - Yuyan Huang
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Bi Ren
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Liping He
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Min Pang
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Li Jiang
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
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Xue M, Li R, Wang K, Liu W, Liu J, Li Z, Ma Z, Zhang H, Tian H, Tian Y. Nomogram combining clinical and radiological characteristics for predicting the malignant probability of solitary pulmonary nodules measuring ≤ 2 cm. Front Oncol 2023; 13:1196778. [PMID: 37795448 PMCID: PMC10545867 DOI: 10.3389/fonc.2023.1196778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 09/04/2023] [Indexed: 10/06/2023] Open
Abstract
Background At present, how to identify the benign or malignant nature of small (≤ 2 cm) solitary pulmonary nodules (SPN) are an urgent clinical challenge. This retrospective study aimed to develop a clinical prediction model combining clinical and radiological characteristics for assessing the probability of malignancy in SPNs measuring ≤ 2 cm. Method In this study, we included patients with SPNs measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to December 2021. Clinical features, preoperative biomarker results, and computed tomography characteristics were collected. The enrolled patients were randomized at a ratio of 7:3 into a training cohort of 775 and a validation cohort of 331. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. The receiver operating characteristic (ROC) curve was used to evaluate the identification ability of the model. The calibration power was evaluated using the Hosmer-Lemeshow test and calibration curve. The clinical utility of the nomogram was also assessed by decision curve analysis (DCA). Result A total of 1,106 patients were included in this study. Among them, the malignancy rate of SPNs was 85.08% (941/1,106). We finally identified the following six independent risk factors by logistic regression: age, carcinoembryonic antigen, nodule shape, calcification, maximum diameter, and consolidation-to-tumor ratio. The area under the ROC curve (AUC) for the training cohort was 0.764 (95% confidence interval [CI]: 0.714-0.814), and the AUC for the validation cohort was 0.729 (95% CI: 0.647-0.811), indicating that the prediction accuracy of nomogram was relatively good. The calibration curve of the predictive model also demonstrated a good calibration in both cohorts. DCA proved that the clinical prediction model was useful in clinical practice. Conclusion We developed and validated a predictive model and nomogram for estimating the probability of malignancy in SPNs measuring ≤ 2 cm. With the application of predictive models, thoracic surgeons can make more rational clinical decisions while avoiding overtreatment and wasting medical resources.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Hui Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Yu Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, China
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Radiomics based on enhanced CT for differentiating between pulmonary tuberculosis and pulmonary adenocarcinoma presenting as solid nodules or masses. J Cancer Res Clin Oncol 2022:10.1007/s00432-022-04256-y. [PMID: 35939114 DOI: 10.1007/s00432-022-04256-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/02/2022] [Indexed: 10/15/2022]
Abstract
PURPOSE To investigate the incremental value of enhanced CT-based radiomics in discriminating between pulmonary tuberculosis (PTB) and pulmonary adenocarcinoma (PAC) presenting as solid nodules or masses and to develop an optimal radiomics model. METHODS A total of 128 lesions (from 123 patients) from three hospitals were retrospectively analyzed and were randomly divided into training and test datasets at a ratio of 7:3. Independent predictors in subjective image features were used to develop the subjective image model (SIM). The plain CT-based and enhanced CT-based radiomics features were screened by the correlation coefficient method, univariate analysis, and the least absolute shrinkage and selection operator, then used to build the plain CT radiomics model (PRM) and enhanced CT radiomics model (ERM), respectively. Finally, the combined model (CM) combining PRM and ERM was established. In addition, the performance of three radiologists and one respiratory physician was evaluated. The areas under the receiver operating characteristic curve (AUCs) were used to assess the performance of each model. RESULTS The differential diagnostic capability of the ERM (training: AUC = 0.933; test: AUC = 0.881) was better than that of the PRM (training: AUC = 0.861; test: AUC = 0.756) and the SIM (training: AUC = 0.760; test: AUC = 0.611). The CM was optimal (training: AUC = 0.948; test: AUC = 0.917) and outperformed the respiratory physician and most radiologists. CONCLUSIONS The ERM was more helpful than the PRM for identifying PTB and PAC that present as solid nodules or masses, and the CM was the best.
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Sun J, Zhu C, Shen J. Editorial: Surgical Selection of Sublobar Resection and Scope of Lymph Node Dissection for Early-Stage Lung Cancer. Front Surg 2022; 9:915220. [PMID: 35647018 PMCID: PMC9130624 DOI: 10.3389/fsurg.2022.915220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 04/25/2022] [Indexed: 12/02/2022] Open
Affiliation(s)
| | - Chengchu Zhu
- Taizhou Hospital, Zhejiang University, Taizhou, China
| | - Jianfei Shen
- Taizhou Hospital, Zhejiang University, Taizhou, China
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