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find Keyword "肺结节" 128 results
  • Research on pulmonary nodule recognition algorithm based on micro-variation amplification

    Objective To develop an innovative recognition algorithm that aids physicians in the identification of pulmonary nodules. MethodsPatients with pulmonary nodules who underwent thoracoscopic surgery at the Department of Thoracic Surgery, Affiliated Drum Tower Hospital of Nanjing University Medical School in December 2023, were enrolled in the study. Chest surface exploration data were collected at a rate of 60 frames per second and a resolution of 1 920×1 080. Frame images were saved at regular intervals for subsequent block processing. An algorithm database for lung nodule recognition was developed using the collected data. ResultsA total of 16 patients were enrolled, including 9 males and 7 females, with an average age of (54.9±14.9) years. In the optimized multi-topology convolutional network model, the test results demonstrated an accuracy rate of 94.39% for recognition tasks. Furthermore, the integration of micro-variation amplification technology into the convolutional network model enhanced the accuracy of lung nodule identification to 96.90%. A comprehensive evaluation of the performance of these two models yielded an overall recognition accuracy of 95.59%. Based on these findings, we conclude that the proposed network model is well-suited for the task of lung nodule recognition, with the convolutional network incorporating micro-variation amplification technology exhibiting superior accuracy. Conclusion Compared to traditional methods, our proposed technique significantly enhances the accuracy of lung nodule identification and localization, aiding surgeons in locating lung nodules during thoracoscopic surgery.

    Release date:2025-02-28 06:45 Export PDF Favorites Scan
  • Benign and Malignant Solitary Pulmonary Nodule: Analysis of Risk Factors

    Objective To investigate the risk factors, diagnosis and treatment of solitary pulmonary nodule (diameter≤3cm). Methods From Jan. 2001 to Dec. 2002, the clinical data of 297 patients with solitary pulmonary nodule were reviewed. Chi-square or t-test were used in univariate analysis of age, gender, symptom, smoking history, the size, location and radiological characteristics of nodule, and logistic regression in multivariate analysis. Results Univariate analysis revealed that malignancy was significantly associated with age (P=0. 000), smoking history (P=0. 001), the size (P=0. 000) and radiological characteristics (P=0. 000) of nodule. In multivariate analysis (logistic regression), it was significantly associated with age (OR = 1. 096), the size (OR = 2. 329) and radiological characteristics (OR=0. 167) of nodule. Conclusion Age and the size of nodule could be risk factors. Radiological findings could help distinguish from malignant nodules.

    Release date:2016-08-30 06:22 Export PDF Favorites Scan
  • 18F-FDG PET/CT combined with CT three-dimensional reconstruction in the differentiation of benign and malignant pulmonary nodules: A retrospective cohort study

    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.

    Release date:2024-02-20 04:11 Export PDF Favorites Scan
  • 主动脉瓣二尖瓣置换术同期右上肺叶切除术一例

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  • 第一届肺肿瘤精准诊疗论坛暨肺结节微创手术与精准消融学习班学术亮点

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  • A Review on the Research Progress of the Computer-Aided Detection of Pulmonary Nodule

    Computer-aided detection (CAD) of pulmonary nodule technology can effectively assist the radiologist to enhance lung nodule detection efficiency and accuracy rate, so it can lay the foundation for the early diagnosis of lung cancer. In order to provide reference for the scholars and to develop the CAD technology, we in this paper review the technology research and development of CAD of the pulmonary nodules which is based on CT image in recent years both home and abroad. At the same time, we also analyse the advantages and shortcomings of different methods. Then we present the improvement direction for reference. According to the literature in recent years, there still has been large development space in CAD technology for pulmonary nodules. The establishment and improvement of the CAD system in each step would be of great scientific value.

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  • Clinical application of 3D precise localization based on anatomical markers in the treatment of pulmonary nodules during thoracoscopic surgery

    ObjectiveTo explore the safety and feasibility of 3D precise localization based on anatomical markers in the treatment of pulmonary nodules during video-assisted thoracoscopic surgery (VATS).MethodsFrom June 2019 to April 2015, 27 patients with pulmonary nodules underwent VATS in our Hospital were collected in the study, including 3 males and 24 females aged 51.8±13.7 years. The surgical data were retrospectively reviewed and analyzed, such as localization time, localization accuracy rate, pathological results, complication rate and postoperative hospital stay.ResultsA total of 28 pulmonary nodules were localized via this method. All patients received surgery successfully. No mortality or major morbidity occurred. The general mean localization time was 17.6±5.8 min, with an accuracy of 96.4%. The mean diameter of pulmonary nodules was 14.0±8.0 mm with a mean distance from visceral pleura of 6.5±5.4 mm. There was no localization related complication. The mean postoperative hospital stay was 6.7±4.3 d. The routine pathological result showed that 78.6% of the pulmonary nodules were adenocarcinoma.Conclusion3D precise localization based on anatomical markers in the treatment of pulmonary nodules during thoracoscopic surgery is accurate, safe, effective, economical and practical, and it is easy to master with a short learning curve.

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  • Multidisciplinary Thoracic Tumor Board: Therapy for Pulmonary Nodule with Postoperation of Cervical Cancer——Tree Cases Report

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  • Short-term efficacy of CT-guided microwave ablation for solitary pulmonary nodules

    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.

    Release date:2021-07-28 10:22 Export PDF Favorites Scan
  • 人工智能平台下肺结节的三维可视化定位与手术规划专家共识

    Release date:2019-12-13 03:50 Export PDF Favorites Scan
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