ObjectiveTo explore the influencing factors for Hook-wire precise positioning under CT guidance, determine the best positioning management strategy, and develop Nomogram prediction model. Methods Patients who underwent CT-guided Hook-wire puncture positioning in our hospital from July 2018 to November 2022 were selected. They were randomly divided into a training set and a validation set with a ratio of 7 : 3. Clinical data of the patients were analyzed, and the logistic analysis was used to screen out the risk factors that affected CT-guided Hook-wire precise positioning for the training set. The Nomogram prediction model was constructed according to the risk factors, and the goodness of fit test and clinical decision curve analysis were performed. ResultsA total of 199 patients with CT-guided Hook-wire puncture were included in this study, including 72 males and 127 females, aged 25-83 years. There were 139 patients in the training set and 60 patients in the validation set. In the training set, 70 patients were accurately located, with an incidence of 50.36%. Logistic regression analysis showed that height [OR=3.46, 95%CI (1.44, 8.35), P=0.006], locating needle perpendicular to the horizontal plane [OR=3.40, 95%CI (1.37, 8.43), P=0.008], locating needle perpendicular to the tangent line of skin surface [OR=6.01, 95%CI (2.38, 15.20), P＜0.001], CT scanning times [OR=3.03, 95%CI (1.25, 7.33), P=0.014], occlusion [OR=10.56, 95%CI (1.98, 56.48), P=0.006] were independent risk factors for CT-guided Hook-wire precise localization. The verification results of the Nomogram prediction model based on these independent risk factors showed that the area under the receiver operating characteristic curve (AUC) was 0.843 [95%CI (0.776, 0.910)], and the predicted value of the correction curve was basically consistent with the measured value. The AUC of the model in the validation set was 0.854 [95%CI (0.759, 0.950)]. The decision curves showed that when the threshold probability was within the range of 8%-85% in the training set and 18%-99% in the validation set, there was a high net benefit value. Conclusion Height, the locating needle perpendicular to the horizontal plane, the locating needle perpendicular to the tangent line of skin surface, number of CT scans, and occlusion are independent risk factors for CT-guided Hook-wire accurate localization. The Nomogram model established based on the above risk factors can accurately assess and quantify the risk of CT-guided Hook-wire accurate localization.
The widespread application of low-dose computed tomography (LDCT) has significantly increased the detection of pulmonary small nodules, while accurate prediction of their growth patterns is crucial to avoid overdiagnosis or underdiagnosis. This article reviews recent research advances in predicting pulmonary nodule growth based on CT imaging, with a focus on summarizing key factors influencing nodule growth, such as baseline morphological parameters, dynamic indicators, and clinical characteristics, traditional prediction models (exponential and Gompertzian models), and the applications and limitations of radiomics-based and deep learning models. Although existing studies have achieved certain progress in predicting nodule growth, challenges such as small sample sizes and lack of external validation persist. Future research should prioritize the development of personalized and visualized prediction models integrated with larger-scale datasets to enhance predictive accuracy and clinical applicability.
ObjectiveTo reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. MethodsPublications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. ResultsA marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. ConclusionOver the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.
ObjectiveTo evaluate the clinical feasibility and safety of CT-guided percutaneous microwave ablation for peripheral solitary pulmonary nodules.MethodsThe imaging and clinical data of 33 patients with pulmonary nodule less than 3 cm in diameter treated by CT-guided microwave ablation treatment (PMAT) in our hospital from July 2018 to December 2019 were retrospectively analyzed. There were 21 males and 12 females aged 38-90 (67.6±13.4) years. Among them, 26 patients were confirmed with lung cancer by biopsy and 7 patients were clinically considered as partial malignant lesions. The average diameter of 33 nodules was 0.6-3.0 (1.8±0.6) cm. The 3- and 6-month follow-up CT was performed to evaluate the therapy method by comparing the diameter and enhancement degree of lesions with 1-month CT manifestation. Short-term treatment analysis including complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD) was calculated according to the WHO modified response evaluation criteria in solid tumor (mRECIST) for short-term efficacy evaluation. Eventually the result of response rate (RR) was calculated. Progression-free survival was obtained by Kaplan–Meier analysis.ResultsCT-guided percutaneous microwave ablation was successfully conducted in all patients. Three patients suffered slight pneumothorax. There were 18 (54.5%) patients who achieved CR, 9 (27.3%) patients PR, 4 (12.1%) patients SD and 2 (6.1%) patients PD. The short-term follow-up effective rate was 81.8%. Logistic analysis demonstrated that primary and metastatic pulmonary nodules had no difference in progression-free time (log-rank P=0.624).ConclusionPMAT is of high success rate for the treatment of solitary pulmonary nodules without severe complications, which can be used as an effective alternative treatment for nonsurgical candidates.
ObjectiveTo evaluate the feasibility and clinical value of robot-assisted lung segmentectomy through anterior approach.MethodsWe retrospectively analyzed the clinical data of 77 patients who underwent robotic lung segmentectomy through anterior approach in our hospital between June 2018 to October 2019. There were 22 males and 55 females, aged 53 (30-71) years. Patients' symptoms, general conditions, preoperative imaging data, distribution of resected lung segments, operation time, bleeding volume, number of lymph node dissected, postoperative duration of chest tube insertion, drainage volume, postoperative hospital stay, postoperative complications, perioperative death and other indicators were analyzed.ResultsAll operations were successfully completed. There was no conversion to thoracotomy, serious complications or perioperative death. The postoperative pathology revealed early lung cancer in 48 patients, and benign tumors in 29 patients. The mean clinical parameters were following: the robot Docking time 1-30 (M=4) min, the operation time 30-170 (M=76) min, the blood loss 20-400 (M=30) mL, the drainage tube time 2-15 (M=4) days, the drainage fluid volume 200-3 980 (M=780) mL and the postoperative hospital time 3-19 (M=7) days.ConclusionRobotic lung segmentectomy through anterior approach is a safe and convenient operation method for pulmonary nodules.
Objective To investigate the accuracy of 18F-FDG positron emission tomography/computed tomography (PET/CT) combined with CT three-dimensional reconstruction (CT-3D) in the differential diagnosis of benign and malignant pulmonary nodules. Methods The clinical data of patients who underwent pulmonary nodule surgery in the Department of Thoracic Surgery, Northern Jiangsu People's Hospital from July 2020 to August 2021 were retrospectively analyzed. The preoperative 18F-FDG PET/CT and chest enhanced CT-3D and other imaging data were extracted. The parameters with diagnostic significance were screened by the area under the receiver operating characteristic (ROC) curve (AUC). Three prediction models, including PET/CT prediction model (MOD PET), CT-3D prediction model (MOD CT-3D), and PET/CT combined CT-3D prediction model (MOD combination), were established through binary logistic regression, and the diagnostic performance of the models were validated by ROC curve. Results A total of 125 patients were enrolled, including 57 males and 68 females, with an average age of 61.16±8.57 years. There were 46 patients with benign nodules, and 79 patients with malignant nodules. A total of 2 PET/CT parameters and 5 CT-3D parameters were extracted. Two PET/CT parameters, SUVmax≥1.5 (AUC=0.688) and abnormal uptake of hilar/mediastinal lymph node metabolism (AUC=0.671), were included in the regression model. Among the CT-3D parameters, CT value histogram peaks (AUC=0.694) and CT-3D morphology (AUC=0.652) were included in the regression model. Finally, the AUC of the MOD PET was verified to be 0.738 [95%CI (0.651, 0.824)], the sensitivity was 74.7%, and the specificity was 60.9%; the AUC of the MOD CT-3D was 0.762 [95%CI (0.677, 0.848)], the sensitivity was 51.9%, and the specificity was 87.0%; the AUC of the MOD combination was 0.857 [95%CI (0.789, 0.925)], the sensitivity was 77.2%, the specificity was 82.6%, and the differences were statistically significant (P<0.001). Conclusion 18F-FDG PET/CT combined with CT-3D can improve the diagnostic performance of pulmonary nodules, and its specificity and sensitivity are better than those of single imaging diagnosis method. The combined prediction model is of great significance for the selection of surgical timing and surgical methods for pulmonary nodules, and provides a theoretical basis for the application of artificial intelligence in the pulmonary nodule diagnosis.
With the increasing application of low-dose computed tomography and the rising public health awareness, the early detection of pulmonary nodules has become more prevalent. Pulmonary nodules, especially those with a diameter≤2 cm, pose a critical challenge in clinical practice due to the potential risk of progressing into malignant lung lesions. Guided by the principles of "avoiding both over-treatment and mistreatment", the goal is to standardize the clinical management of pulmonary nodules. The "Chinese thoracic surgery expert consensus on rational diagnosis and treatment of pulmonary nodules with a diameter≤2 cm (2024)" was developed after extensive consultation with nearly one hundred thoracic surgery experts in China, relying on large-scale clinical study data and referencing national and international guidelines and consensus. The consensus includes 29 recommendations, focusing on specific attributes such as the size, composition, and anatomical positioning of the nodules. It proposes targeted guidelines for screening, follow-up, diagnostic criteria, and recommendations for personalized treatment, surgical approaches, and protocols for rapid postoperative recovery.
ObjectiveBy combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. MethodsA retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). ResultsA total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. ConclusionThe combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.
As the popularity of thoracoscopic day surgery for pulmonary nodules increases, there is a growing demand among patients for information about the surgical approach, process, and recovery. To enhance patients’ understanding of the surgery, alleviate anxiety, facilitate postoperative recovery, and improve patient satisfaction, the Day Surgery Nursing Committee of Sichuan Tianfu New Area Medical Association has convened experts in the field to discuss the health education model and content for the perioperative period of thoracoscopic pulmonary nodule day surgery, reaching an expert consensus. The consensus underscores the importance of leveraging hospital intelligent information systems and integrating diverse educational methods to provide patients with comprehensive and individualized health education.
Surgical resection is the only radical method for the treatment of early-stage non-small cell lung cancer. Intraoperative frozen section (FS) has the advantages of high accuracy, wide applicability, few complications and real-time diagnosis of pulmonary nodules. It is one of the main means to guide surgical strategies for pulmonary nodules. Therefore, we searched PubMed, Web of Science, CNKI, Wanfang and other databases for nearly 30 years of relevant literature and research data, held 3 conferences, and formulated this consensus by using the Delphi method. A total of 6 consensus contents were proposed: (1) Rapid intraoperative FS diagnosis of benign and malignant diseases; (2) Diagnosis of lung cancer types including adenocarcinoma, squamous cell carcinoma, others, etc; (3) Diagnosis of lung adenocarcinoma infiltration degree; (4) Histological subtype diagnosis of invasive adenocarcinoma; (5) The treatment strategy of lung adenocarcinoma with inconsistent diagnosis on degree of invasion between intraoperative FS and postoperative paraffin diagnosis; (6) Intraoperative FS diagnosis of tumor spread through air space, visceral pleural invasion and lymphovascular invasion. Finally, we gave 11 recommendations in the above 6 consensus contents to provide a reference for diagnosis of pulmonary nodules and guiding surgical decision-making for peripheral non-small cell lung cancer using FS, and to further improve the level of individualized and precise diagnosis and treatment of early-stage lung cancer.