Accurate staging is the fundamental basis for the treatment and prognosis of non-small cell lung cancer (NSCLC), and whether the tumor involves the pleura or chest wall is a critical aspect in assessing the staging of peripheral lung cancer. Imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and positron emission tomography (PET) are widely used to determine pleural invasion in NSCLC. There has been an increasing number of studies evaluating whether NSCLC invades the pleura and the extent of such invasion. This article provides a review of the staging and the imaging diagnostic criteria of pleural invasion, aiming to offer references for peers in the precise diagnosis of pleural or chest wall invasion.
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Humans ; Carcinoma, Non-Small-Cell Lung/diagnosis* ; Lung Neoplasms/diagnosis* ; Thoracic Wall/diagnostic imaging* ; Pleura/diagnostic imaging* ; Neoplasm Invasiveness ; Tomography, X-Ray Computed

OBJECTIVES: Non-small cell lung cancer (NSCLC) is associated with poor prognosis, with 30% of patients diagnosed at an advanced stage. Mutations in the EGFR and KRAS genes are important prognostic factors for NSCLC, and targeted therapies can significantly improve survival in these patients. Although tissue biopsy remains the gold standard for detecting gene mutations, it has limitations, including invasiveness, sampling errors due to tumor heterogeneity, and poor reproducibility. This study aims to develop machine learning models based on radiomic features to predict EGFR and KRAS gene mutation status in NSCLC patients, thereby providing a reference for precision oncology. METHODS: Imaging and mutation data from eligible NSCLC patients were obtained from the publicly available Lung-PET-CT-Dx dataset in The Cancer Imaging Archive (TCIA). A three-dimensional-convolutional neural network (3D-CNN) was used to extract imaging features from the regions of interest (ROI). The LightGBM algorithm was employed to build classification models for predicting EGFR and KRAS gene mutation status. Model performance was evaluated using 5-fold cross-validation, with receiver operator characteristic (ROC) curves, area under the curve (AUC), accuracy, sensitivity, and specificity used for validation. RESULTS: The models effectively predicted EGFR and KRAS mutations in NSCLC patients, achieving an AUC of 0.95 for EGFR mutations and 0.90 for KRAS. The models also demonstrated high accuracy (EGFR 89.66%; KRAS 87.10%), sensitivity (EGFR 93.33%; KRAS 87.50%), and specificity (EGFR 85.71%; KRAS 86.67%). CONCLUSIONS A radiogenomics-machine learning predictive model can serve as a non-invasive tool for anticipating EGFR and KRAS gene mutation status in NSCLC patients.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Lung Neoplasms/diagnostic imaging* ; Mutation ; Proto-Oncogene Proteins p21(ras)/genetics* ; ErbB Receptors/genetics* ; Machine Learning ; Positron Emission Tomography Computed Tomography ; Female ; Male ; Neural Networks, Computer ; Middle Aged ; Aged

Non-small cell lung cancer (NSCLC) can be detected with enlarged lymph nodes on imaging, but their benignity and malignancy are difficult to determine directly, making it difficult to stage the tumor and design radiotherapy target volumes. The clinical diagnosis of malignant lymph nodes is often based on the short diameter of lymph nodes ≥1 cm or the maximum standard uptake value ≥2.5, but the sensitivity and specificity of these criteria are too low to meet the clinical needs. In recent years, many advances have been made in diagnosing benign and malignant lymph nodes using other imaging parameters, and with the development of radiomics, deep learning and other technologies, models of mining the image information of enlarged lymph node regions further improve the diagnostic accuracy. The purpose of this paper is to review recent advances in imaging-based diagnosis of benign and malignant enlarged lymph nodes in NSCLC for more accurate and noninvasive assessment of lymph node status in clinical practice.
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Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Diagnostic Imaging ; Lung Neoplasms/pathology* ; Lymph Nodes/pathology* ; Sensitivity and Specificity

Because of the unobvious early symptoms and low 5-year survival rate, the early diagnosis and treatment is of great significance for patients with non-small cell lung cancer. Glucose transporter-1 is the most widely distributed glucose transporters in various tissue cells in the human body, whose expression in non-small cell lung cancer is closely related to the histological types, lymph node metastasis, degree of differentiation, progression and prognosis.
Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Fluorodeoxyglucose F18 ; Glucose Transport Proteins, Facilitative ; Glucose Transporter Type 1 ; Humans ; Lung Neoplasms/diagnostic imaging* ; Positron Emission Tomography Computed Tomography ; Positron-Emission Tomography ; Radiopharmaceuticals

OBJECTIVE: To validate the value of dual energy CT (DECT) in the differentiation of mediastinal metastatic lymph nodes from non-metastatic lymph nodes in non-small cell lung cancer (NSCLC). METHODS: In the study, 57 surgically confirmed NSCLC patients who underwent enhanced DECT scan within 2 weeks before operation were enrolled. Two radiologists analyzed the CT images before operation. All mediastinal lymph nodes with short diameter≥5 mm on axial images were included in this study. The morphological parameters [long-axis diameter (L), short-axis diameter (S) and S/L of lymph nodes] and the DECT parameters [iodine concentration (IC), normalized iodine concentration (NIC), slope of spectral hounsfield unit curve (λHU) and effective atomic number (Zeff) in arterial and venous phase] were measured. The differences of morphological parameters and DECT parameters between metastatic and non-metastatic lymph nodes were compared. The parameters with significant difference were analyzed by the Logistic regression model, then a new predictive variable was established. Receiver operator characteristic (ROC) analyses were performed for S, NIC in venous phase and the new predictive variable. RESULTS: In 57 patients, 49 metastatic lymph nodes and 938 non-metastatic lymph nodes were confirmed by surgical pathology. A total of 163 mediastinal lymph nodes (49 metastatic, 114 non-metastatic) with S≥5 mm were detected on axial CT images. The S, L and S/L of metastatic lymph nodes were significantly higher than those of non-metastatic lymph nodes (P < 0.05). The DECT parameters of metastatic lymph nodes were significantly lower than those of non-metastatic lymph nodes (P < 0.05). The best single morphological parameter for differentiation between metastatic and nonmetastatic lymph nodes was S (AUC, 0.752; threshold, 8.5 mm; sensitivity, 67.4%; specificity, 73.7%; accuracy, 71.8%). The best single DECT parameter for differentiation between metastatic and nonmetastatic lymph nodes was NIC in venous phase (AUC, 0.861; threshold, 0.53; sensitivity, 95.9%; specificity, 70.2%; accuracy, 77.9%). Multivariate analysis showed that S and NIC were independent predictors of lymph node metastasis. The AUC of combined S and NIC in the venous phase was 0.895(sensitivity, 79.6%; specificity, 87.7%; accuracy, 85.3%), which were significantly higher than that of S (P < 0.001) and NIC (P=0.037). CONCLUSIONS The ability of quantitative DECT parameters to distinguish mediastinal lymph node metastasis in NSCLC patients is better than that of morphological parameters. Combined S and NIC in venous phase can be used to improve preoperative diagnostic accuracy of metastatic lymph nodes.
Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Humans ; Lung Neoplasms/diagnostic imaging* ; Lymph Nodes ; Lymphatic Metastasis ; Mediastinum ; Tomography, X-Ray Computed

Tyrosine kinase inhibitor (TKI) have been proved to be effective in the treatment of advanced non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) sensitive mutation, which is superior to chemotherapy. However, there are still some patients with sensitive mutations have primary drug resistance. It may be related to the coexistence of susceptible and resistant mutations of EGFR gene, downstream mutations of EGFR pathway, MET amplification and BIM deletion polymorphism. We present 2 cases of primary drug resistance and analyze the reasons.
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Carcinoma, Non-Small-Cell Lung ; diagnostic imaging ; drug therapy ; genetics ; Disease Progression ; Drug Resistance, Neoplasm ; drug effects ; genetics ; ErbB Receptors ; antagonists & inhibitors ; genetics ; Fatal Outcome ; Humans ; Lung Neoplasms ; diagnostic imaging ; drug therapy ; genetics ; Male ; Middle Aged ; Mutation ; Protein Kinase Inhibitors ; therapeutic use ; Treatment Outcome

Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancer, with a 5-year survival rate of less than 15%-19%, and more than 80% of the patients with lung cancer have progressed to advanced stage (Stage IIIb-IV) when they are clearly diagnosed. The comprehensive treatment mainly based on chemotherapy as the primary form is now considered as the major therapy method for advanced NSCLC without actionable driver gene mutations. Pemetrexed plus platinum doublet as well as single-agent pemetrexed are respectively the first-line major regimens recommended by guidelines and the second-line optional regimens. Yet the third-line treatment or beyond in advanced NSCLC is not evidence-based but conducted based on patients' previous medications, which is one of the most commonly used clinical methods. As pemetrexed is a multi-target chemotherapy drug with high efficiency but low toxicity, pemetrexed re-challenge strategy in advanced NSCLC is also a reasonable choice. We report one effective individual case that adopted pemetrexed re-challenge strategy in advanced NSCLC for three times, and at the same time conduct the relevant literature review.
Carcinoma, Non-Small-Cell Lung ; diagnostic imaging ; drug therapy ; Female ; Humans ; Lung Neoplasms ; diagnostic imaging ; drug therapy ; Middle Aged ; Pemetrexed ; administration & dosage ; Positron Emission Tomography Computed Tomography

Lung cancer is the most common cause of cancer-related death worldwide. There are two classes of lung cancer: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC represents approximately 85% of all lung cancer cases. Immune checkpoint inhibitors (ICIPs) are a class of inhibitors of programmed death-1 and programmed death-ligand 1. Preclinical studies have shown that ICIPs have shown good clinical efficacy and durable response in diverse cancers. Among them, atezolizumab (MPDL3280), an anti-PD-L1 monoclonal antibody, is being investigated as a potential therapy against solid tumors and hematologic malignancies in humans. Pseudoprogression is reported as one of the unique phenomena with immune therapeutic agents. Here we report case of a person with advanced NSCLC who developed pseudoprogression after receiving immunotherapy. We hope this case could help clinicians to make appropriate decision when assessing therapeutic effects of immunotherapy.
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Antibodies, Monoclonal ; administration & dosage ; Antineoplastic Agents, Immunological ; administration & dosage ; Carcinoma, Non-Small-Cell Lung ; diagnostic imaging ; drug therapy ; Humans ; Immunotherapy ; Lung Neoplasms ; diagnostic imaging ; drug therapy ; Male ; Middle Aged

Tumor-node-metastasis (TNM) staging system is the most important basis for making therapeutic decisions and predicting prognosis of lung cancer patients. The metabolic parameters including standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) measured by ¹⁸F-fluorodeoxyglucose-positron emission tomography (¹⁸F-FDG PET/CT) associate with tumor aggressiveness and can provide additional prognostic information. A new staging methodology combines the conventional cTNM with the metabolic tumor burden quantified from the PET images is a better predictor of overall survival with superior stratifying power may help oncologists to make better treatment plans. ¹⁸F-FDG PET/CT image texture analysis, as an emerging research tool, is used to quantify the spatial heterogeneity of radioactive uptake in tumors, thereby to explore the biological characteristics of the tumor. This article reviews developments in evaluating the ¹⁸F-FDG PET/CT metabolic parameters and its role as a prognostic factor for non-small cell lung cancer.
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Carcinoma, Non-Small-Cell Lung ; diagnostic imaging ; metabolism ; Fluorodeoxyglucose F18 ; Humans ; Image Processing, Computer-Assisted ; Lung Neoplasms ; diagnostic imaging ; metabolism ; Positron Emission Tomography Computed Tomography ; methods ; Prognosis

BACKGROUND: The preferred therapy for patients with pulmonary nodules which highly suspected as lung cancer by low-dose spiral computed tomography (CT) is surgery, but the best screening method of whole body is not clear yet. The aim of this study is to investigate the differences in the progression-free survival (PFS) of patients with Ia stage non-small cell lung cancer after screening of positron emission computed tomography (PET)-CT and conventional imaging (B-ultrasound/CT/MRI/ECT, BCME). METHODS: A total of 300 cases of Ia stage non-small cell lung cancer were collected, of which 170 cases were performed PET-CT and 130 cases were performed BCME before operation. The basic characteristics of the two groups were analyzed by propensity score matching (PSM), and 114 cases of each group were included in the study. The survival analysis was carried out by the Kaplan-Meier survival curve and the Cox regression analysis. RESULTS: There was no significant difference between each group analyzed by PSM. The PFS of PET-CT and BCME were (44.9±27.2) months and (44.1±33.1) months (χ2=1.284, P=0.257). Both of the method ssucceed in screening. It is not the PFS influence factors. The false positive of PET-CT and BCME were 10 cases and 8 cases (χ2=0.241, P=0.623). CONCLUSIONS Both PET-CT and BCME can be used as a screening method for Ia stage non-small cell lung cancer according to individualized choice of patients.
Adult ; Aged ; Carcinoma, Non-Small-Cell Lung ; diagnostic imaging ; pathology ; surgery ; Disease-Free Survival ; Early Detection of Cancer ; methods ; Female ; Fluorodeoxyglucose F18 ; Humans ; Lung Neoplasms ; diagnostic imaging ; pathology ; surgery ; Male ; Middle Aged ; Neoplasm Staging ; Positron Emission Tomography Computed Tomography ; Preoperative Period