Comparative evaluation of super high-resolution CT scan and virtual bronchoscopy for the detection of XXXX .

@entity5 @entity1 @entity75 @entity3137
OBJECTIVES: Novel imaging modalities are currently available for the noninvasive evaluation of the tracheobronchial tree. This study was undertaken to compare the diagnostic potentials of conventional CT scanning, super high-resolution CT (SHR-CT) scanning, and virtual bronchoscopy (VB) directly with fiberoptic bronchoscopy (FB) for the detection of @entity5 . DESIGN: Prospective observer study, in which 44 consecutive @entity1 with @entity5 were evaluated using several diagnostic imaging modalities. Images of the thorax were interpreted by individuals blind to the results of FB for the detection of @entity3137 . MEASUREMENTS AND RESULTS: Image acquisition and simulation of the tracheobronchial anatomy were created successfully in all @entity1 . Thirty-two @entity1 who underwent both SHR-CT scanning and VB had correlative FBs within 1 month. In all nine @entity1 who had a normal anatomy, SHR-CT scanning and VB accurately correlated with the FB findings. However, CT scanning demonstrated two @entity75 in one @entity1 . Twenty-three @entity1 had a total of 35 abnormal FB findings. The sensitivities of SHR-CT scanning and VB for the detection of endoluminal, obstructive, and @entity3137 were 90%, 100%, and 16%, respectively. The overall sensitivities and specificities of SHR-CT scanning and VB were 83% and 100%, respectively. In contrast, CT scanning had sensitivities of 50%, 72%, and 0% for the detection of endoluminal, obstructive, and @entity3137 with an overall sensitivity and specificity of 59%, and 85%, respectively. There was no case in which conventional CT scanning was better at detecting lesions than either SHR-CT scanning or VB. CONCLUSIONS: SHR-CT scanning and VB are accurate, noninvasive methods for identifying obstructions and endoluminal lesions within the respiratory tract. Thus, these novel imaging techniques are valuable as complementary modalities to FB, providing information that is useful for the detection and management of airway @entity5 .
