Sagittal reformations of volumetric inspiratory and expiratory high-resolution CT of the lung.

RATIONALE AND

OBJECTIVES

The purpose of this study is to determine whether sagittal reformations of volumetric high-resolution computed tomography (CT) provide additional information in evaluating lung abnormalities compared to axial high-resolution CT images.

MATERIALS AND

METHODS

Twenty-two consecutive patients who underwent combined inspiratory and expiratory volumetric high-resolution CT from May to July 2003 were studied. Using end-inspiratory and end-expiratory sagittal reformatted images, respiratory motion artifacts were evaluated at upper, middle, and lower lung areas bilaterally. Diaphragmatic motion artifacts were evaluated bilaterally. The detection of major and minor fissures was assessed. Additional findings on sagittal reformations were graded using a three-point scale: grade 1 = no additional findings; grade 2 = additional findings of no diagnostic significance; grade 3 = additional findings of diagnostic significance.

RESULTS

Respiratory motion artifacts were either imperceptible or present but not diagnostically limiting except for one case, in which diagnostically limiting image degradation was noted in the bilateral lower lung areas. Diaphragmatic motion artifacts were frequently present: 95% (21/22) at end-inspiration, and 86% (19/22) at end-expiration; however, diagnostically limiting artifacts were observed in only two cases. The grading of additional findings on sagittal reformatted images was statistically significant (grade 1, n = 13; grade 2, n = 7; grade 3, n = 2; median, 1; P = .004) compared to axial images. Additional findings included relationship between mass/nodules and fissure/pleura/pericardium (grade 2, n = 4; grade 3, n = 2), distribution of interstitial abnormalities of the lung (grade 2, n = 2), and diaphragmatic eventration (grade 2, n = 1).

CONCLUSION

Sagittal reformatted images of volumetric high-resolution CT provided additional information compared to volumetric axial images alone with statistical significance.