Objective: The study aimed to evaluate the application value of computed tomography (CT) three-dimensional (3D) reconstruction technology in identifying benign and malignant lung nodules and characterizing the distribution of the nodules.
Methods: CT 3D reconstruction was performed for lung nodules. Pathological results were used as the gold standard to compare the detection rates of various lung nodule signs between conventional chest CT scanning and CT 3D reconstruction techniques. Additionally, the differences in mean diffusion coefficient values and partial anisotropy index values between male and female patients were analyzed.
Results: Pathologic confirmation identified 30 patients with benign lesions and 45 patients with malignant lesions. CT 3D reconstruction demonstrated higher diagnostic accuracy for lung nodule imaging signs compared to conventional CT scanning (P < 0.05). The mean diffusion coefficient values and partial anisotropy index values were lower in female patients compared to male patients in the lung nodule lesion area, lung perinodular edema area, and normal lung tissue (P < 0.05). Conventional CT scanning showed a benign accuracy rate of 63.33% and a malignant accuracy rate of 60.00%, whereas CT 3D imaging achieved a benign and malignant accuracy rate of 86.67% for both. The accuracy rates for CT 3D imaging were significantly higher than those for conventional CT scanning (P < 0.05).
Conclusion: CT 3D imaging technology demonstrates high diagnostic accuracy in differentiating benign from malignant lung nodules.
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http://dx.doi.org/10.1186/s12880-024-01505-z | DOI Listing |
Respir Med Res
December 2024
Department of Thoracic Oncology, Pleural Diseases and Interventional Pulmonology, Marseille, France.
Background: CT-guided trans-thoracic lung biopsy (CT-TTLB) is efficient and widely used to diagnose pulmonary nodules. After pneumothorax, the second most frequent complication is hemoptysis, which can be life-threatening. These patients often have comorbidities and are on acetylsalicylic-acid (ASA) therapy.
View Article and Find Full Text PDFBest Pract Res Clin Anaesthesiol
March 2024
1400 Holcombe Blvd, FC 13.2000, Houston, TX, 77030, USA. Electronic address:
Lung cancer is among one of the most commonly diagnosed malignancies and is the leading cause of cancer-related mortality in both men and women globally, with an estimated 1.8 million deaths annually. Moreover, it is also the leading cause of cancer related deaths in the United States (U.
View Article and Find Full Text PDFFront Oncol
December 2024
Honorary Research Associate, Department of Operations and Quality Management, Durban University of Technology, Durban, South Africa.
Introduction: Lung cancer is one of the main causes of the rising death rate among the expanding population. For patients with lung cancer to have a higher chance of survival and fewer deaths, early categorization is essential. The goal of thisresearch is to enhance machine learning to increase the precision and quality of lung cancer classification.
View Article and Find Full Text PDFJ Cardiothorac Surg
January 2025
Department of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Background: The intricate anatomical variations in lung structure often perplex thoracic surgeons, and the accurate identification of these variations is closely associated with favorable surgical outcomes.
Case Presentation: A 53-year-old female patient who underwent computed tomography (CT) examination due to chest discomfort, revealing the presence of a partial solid nodule highly suspected of early-stage lung cancer, measuring approximately 2.8 × 2.
BMC Med Imaging
January 2025
Department of Radiology, The First Affiliated Hospital of Yangtze University, No. 40 Jinlong Road, Shashi District, Jingzhou, Hubei, 434000, China.
Objective: The study aimed to evaluate the application value of computed tomography (CT) three-dimensional (3D) reconstruction technology in identifying benign and malignant lung nodules and characterizing the distribution of the nodules.
Methods: CT 3D reconstruction was performed for lung nodules. Pathological results were used as the gold standard to compare the detection rates of various lung nodule signs between conventional chest CT scanning and CT 3D reconstruction techniques.
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