PURPOSE: To evaluate assessment of diffuse lung disease with helical computed tomography (CT) and maximum intensity projection (MIP) and minimum intensity projection images. MATERIALS AND METHODS: Six patients with suspected lung disease (the control group) and 20 patients with documented disease underwent axial helical CT through the upper and lower lung fields. Findings on the MIP and minimum intensity projection images of each helical data set were compared with findings on the thin-section scan obtained at the midplane of the series. RESULTS: Owing to markedly improved visualization of peripheral pulmonary vessels (n = 26) and improved spatial orientation, MIP images were superior to helical scans to help identify pulmonary nodules and characterize them as peribronchovascular (n = 2) or centrilobular (n = 7). Minimum intensity projection images were more accurate than thin-section scans to help identify lumina of central airways (n = 23) and define abnormal low (n = 15) and high (ground-glass) (n = 8) lung attenuation. Conventional thin-section scans depicted fine linear structures more clearly than either MIP or minimum intensity projection images, including the walls of peripheral, dilated airways (n = 3) and interlobular septa (n = 3). MIP and minimum intensity projection images added additional diagnostic findings to those on thin-section scans in 13 (65%) of 20 cases. CONCLUSION: MIP and minimum intensity projection images of helical data sets may help diagnosis of a wide spectrum of diffuse lung diseases.
PURPOSE: To evaluate assessment of diffuse lung disease with helical computed tomography (CT) and maximum intensity projection (MIP) and minimum intensity projection images. MATERIALS AND METHODS: Six patients with suspected lung disease (the control group) and 20 patients with documented disease underwent axial helical CT through the upper and lower lung fields. Findings on the MIP and minimum intensity projection images of each helical data set were compared with findings on the thin-section scan obtained at the midplane of the series. RESULTS: Owing to markedly improved visualization of peripheral pulmonary vessels (n = 26) and improved spatial orientation, MIP images were superior to helical scans to help identify pulmonary nodules and characterize them as peribronchovascular (n = 2) or centrilobular (n = 7). Minimum intensity projection images were more accurate than thin-section scans to help identify lumina of central airways (n = 23) and define abnormal low (n = 15) and high (ground-glass) (n = 8) lung attenuation. Conventional thin-section scans depicted fine linear structures more clearly than either MIP or minimum intensity projection images, including the walls of peripheral, dilated airways (n = 3) and interlobular septa (n = 3). MIP and minimum intensity projection images added additional diagnostic findings to those on thin-section scans in 13 (65%) of 20 cases. CONCLUSION: MIP and minimum intensity projection images of helical data sets may help diagnosis of a wide spectrum of diffuse lung diseases.
Authors: Christian Booz; Thomas J Vogl; U Joseph Schoepf; Damiano Caruso; Maria Cristina Inserra; Ibrahim Yel; Simon S Martin; Andreas M Bucher; Lukas Lenga; Danilo Caudo; Teresa Schreckenbach; Niklas Schoell; Christian Huegel; Jan Stratmann; Mariuca Vasa-Nicotera; Daniel E Rachovitsky-Duarte; Andrea Laghi; Domenico De Santis; Silvio Mazziotti; Tommaso D'Angelo; Moritz H Albrecht Journal: Eur J Radiol Date: 2020-12-14 Impact factor: 4.531