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联合多种CT征象鉴别肺部病变良恶性的临床价值 被引量:3

The Clinical Value of Combining Multiple Features of CT in Discriminating Between Benign and Malignant Lung Lesions
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摘要 目的拟定一种联合多种CT征象对肺部病变良恶性进行初步判断的标准,并与病理结果进行对照研究,评价其临床应用价值。方法纳入2010年3~4月入住我科胸部CT检查有异常征象者,根据患者影像学改变,按制定的判断标准进行初步判定,并行纤支镜等检查,将判断的结果与病理结果进行对比分析。结果本组共纳入患者105例,其中病理明确诊断85例,以本研究制定的标准判断为恶性肿瘤者27例,良性者58例;判断为恶性者的27例中,病理诊断为恶性者22例,良性者5例;判断为良性者的58例中,病理诊断为恶性者3例,良性者55例;判断的准确率为90.59%,灵敏度为88.00%,特异度为91.67%。结论本研究制定的联合多种CT征象标准对于判断肺部病变良恶性有良好的临床应用价值。 Objecitve To develop a set of combined criteria of multiple features of chest CT for discriminating between benign and malignant lung lesions. Methods Patients whose chest CT showed abnormalities were recruited from the West China Hospital in March and April 2010. The patients were examined with bronchoscopy and the results of CT and pathology were compared. Results A total of 105 patients participated in this study and 85 had confirmed pathological results. The CT identified 27 cases of malignant lesions, 22 of which were confirmed by the pathology. The CT identified 58 cases of benign lesions, 55 of which were confirmed by the pathology. The set of combined criteria of multiple features of chest CT had an accuracy of 90.59%, a sensitivity of 88.00%, and a specificity of 91.67% in diagnosing benign and malignant lung lesions. Conclusion The combined criteria of multiple imaging signs of CT have good clinical values for diagnosing malignant lung lesions.
出处 《四川大学学报(医学版)》 CAS CSCD 北大核心 2013年第3期414-418,共5页 Journal of Sichuan University(Medical Sciences)
关键词 肺癌CT 纤支镜 病理 对照 Lung cancer Computed tomography Bronchoscopy Pathological Comparison
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  • 1Jermal A,Bray F,Center MM, et al. Global cancer statistics. CA Cancer J Clin,2011,61(2) :69 90.
  • 2Melamed MR, Flehinger BJ, Zaman MB, et al. Screening and early detection of lung cancer. Cancer J,2011,17(1) ,3-10.
  • 3Martini N, Bains MS, Burt ME, et al. Incidence of local recurrence and second primary tumors in resected stage I lung cancer. J Thoracic Cardiovasc Surg, 1995 , 109 (1) : 120- 129.
  • 4David O, Alan MF, Steven H, et al. The solitary pulmonary nodule. N Engl J Med, 2003 , 348 (10) : 2535-2542.
  • 5The International Early Lung Cancer Action Program Investigators, Henschke CI, Yankelevitz DF,et al. Survival of patients with Stage I lung cancer detected on CT screening. N Engl J Med,2008,355(17) :1763-1771.
  • 6Furuya H, Mwyama S, Soeda H,et al. New classification of small pulmonary nodules by margin characteristics on high resolution CT. Acta Radiol, 1999 ,40(5) :496-504.
  • 7de Hoop B, De Boo DW, Gietema HA,et al. Computer-aideddetection of lung cancer on chest radiographs: effect on observer performance. Radiology, 2010 ; 257 (2) : 532-540.
  • 8Takashima S, Sone S, Li F, et al. Small solitary pulmonary nodules (41 era) detected at population based CT screening for lung cancer: reliable high-resolution CT features of benign lesions. Am J Roentgenol,2003 ;180(4) :955-964.
  • 9Henschke CI, Yankelevitz DF, Mateescu I, et al. Neural networks for the analysis of small pulmonary nodules. Clin Imaging, 1997 ,21 (6) : 390-399.
  • 10Heber MM, John HM, Gordon G, et al., Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the fleisehner society. Radiology, 2005, 237 (2) :395 -400.

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