Matthias Haas1, Bernd Hamm2, Stefan M Niehues2. 1. Department of Radiology, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, D-12203 Berlin, Germany. Electronic address: Matthias.Haas@charite.de. 2. Department of Radiology, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, D-12203 Berlin, Germany.
Abstract
RATIONALE AND OBJECTIVES: Today, lung volumes can be easily calculated from chest computed tomography (CT) scans. Modern postprocessing workstations allow automated volume measurement of data sets acquired. However, there are challenges in the use of lung volume as an indicator of pulmonary disease when it is obtained from routine CT. Intra-individual variation and methodologic aspects have to be considered. Our goal was to assess the reliability of volumetric measurements in routine CT lung scans. MATERIALS AND METHODS: Forty adult cancer patients whose lungs were unaffected by the disease underwent routine chest CT scans in 3-month intervals, resulting in a total number of 302 chest CT scans. Lung volume was calculated by automatic volumetry software. On average of 7.2 CT scans were successfully evaluable per patient (range 2-15). Intra-individual changes were assessed. RESULTS: In the set of patients investigated, lung volume was approximately normally distributed, with a mean of 5283 cm(3) (standard deviation = 947 cm(3), skewness = -0.34, and curtosis = 0.16). Between different scans in one and the same patient the median intra-individual standard deviation in lung volume was 853 cm(3) (16% of the mean lung volume). CONCLUSIONS: Automatic lung segmentation of routine chest CT scans allows a technically stable estimation of lung volume. However, substantial intra-individual variations have to be considered. A median intra-individual deviation of 16% in lung volume between different routine scans was found.
RATIONALE AND OBJECTIVES: Today, lung volumes can be easily calculated from chest computed tomography (CT) scans. Modern postprocessing workstations allow automated volume measurement of data sets acquired. However, there are challenges in the use of lung volume as an indicator of pulmonary disease when it is obtained from routine CT. Intra-individual variation and methodologic aspects have to be considered. Our goal was to assess the reliability of volumetric measurements in routine CT lung scans. MATERIALS AND METHODS: Forty adult cancerpatients whose lungs were unaffected by the disease underwent routine chest CT scans in 3-month intervals, resulting in a total number of 302 chest CT scans. Lung volume was calculated by automatic volumetry software. On average of 7.2 CT scans were successfully evaluable per patient (range 2-15). Intra-individual changes were assessed. RESULTS: In the set of patients investigated, lung volume was approximately normally distributed, with a mean of 5283 cm(3) (standard deviation = 947 cm(3), skewness = -0.34, and curtosis = 0.16). Between different scans in one and the same patient the median intra-individual standard deviation in lung volume was 853 cm(3) (16% of the mean lung volume). CONCLUSIONS: Automatic lung segmentation of routine chest CT scans allows a technically stable estimation of lung volume. However, substantial intra-individual variations have to be considered. A median intra-individual deviation of 16% in lung volume between different routine scans was found.
Authors: Jan Mueller; Stefan Karrasch; Roberto Lorbeer; Tatyana Ivanovska; Andreas Pomschar; Wolfgang G Kunz; Ricarda von Krüchten; Annette Peters; Fabian Bamberg; Holger Schulz; Christopher L Schlett Journal: Eur Radiol Date: 2018-08-27 Impact factor: 5.315
Authors: Stefan F Nemec; Francesco Molinari; Valerie Dufresne; Natacha Gosset; Mario Silva; Alexander A Bankier Journal: Eur Radiol Date: 2015-01-11 Impact factor: 5.315
Authors: Keno K Bressem; Lisa C Adams; Jakob Albrecht; Antonie Petersen; Hans-Martin Thieß; Alexandra Niehues; Stefan M Niehues; Janis L Vahldiek Journal: Pol J Radiol Date: 2020-10-30
Authors: Krystle M Leung; Douglas Curran-Everett; Elizabeth A Regan; David A Lynch; Francine L Jacobson Journal: J Med Imaging (Bellingham) Date: 2019-12-10