PURPOSE: To test the hypothesis that, in magnetic resonance (MR) imaging of healthy individuals, equal relative changes in lung volume cause equal relative changes in MR signal intensity of the lung parenchyma. MATERIALS AND METHODS: In two experimental runs, 10 volunteers underwent spirometrically monitored MR imaging of the lungs, with MR images acquired at 10 incremental lung volumes ranging from total lung capacity to 10% above residual volume. Average signal intensity, signal variability, and signal intensity integrals were calculated for each volunteer and for each lung volume. The effect of lung volume on signal intensity was quantified using linear regression analysis complemented by the runs test. Slopes and intercepts of regression lines were compared with an analysis of covariance. Slopes of the lines of best fit for lung volumes and signal intensities from the two runs were compared to the slope of the line of identity. Comparisons between the two runs were visualized using Bland and Altman plots. RESULTS: The slopes of the 10 individual regression lines yielded no significant differences (F = 1.703, P = 0.101; F = 1.321, P = 0.239). The common slopes were -0.556 +/- 0.027 (P = 0.0001) for the first and -0.597 +/- 0.0031 (P = 0.0001) for the second experimental run. Both slopes displayed no significant nonlinearity (P = 0.419 and P = 0.067). There was a strong association between changes in lung volumes (rs = 0.991, P = 0.0001) and changes in signal intensity (rs = 0.889, P = 0.0001) in the two experimental runs. Lines of best fit for lung volume and signal intensities were not significantly different from the slope of the line of identity (P = 0.321 and P = 0.212, respectively). CONCLUSION: Equal changes in lung volume cause equal changes in MR signal intensity of the lung parenchyma. This linear and reproducible phenomenon could be helpful in comparing pulmonary MR signal intensity between individuals. 2004 Wiley-Liss, Inc.
PURPOSE: To test the hypothesis that, in magnetic resonance (MR) imaging of healthy individuals, equal relative changes in lung volume cause equal relative changes in MR signal intensity of the lung parenchyma. MATERIALS AND METHODS: In two experimental runs, 10 volunteers underwent spirometrically monitored MR imaging of the lungs, with MR images acquired at 10 incremental lung volumes ranging from total lung capacity to 10% above residual volume. Average signal intensity, signal variability, and signal intensity integrals were calculated for each volunteer and for each lung volume. The effect of lung volume on signal intensity was quantified using linear regression analysis complemented by the runs test. Slopes and intercepts of regression lines were compared with an analysis of covariance. Slopes of the lines of best fit for lung volumes and signal intensities from the two runs were compared to the slope of the line of identity. Comparisons between the two runs were visualized using Bland and Altman plots. RESULTS: The slopes of the 10 individual regression lines yielded no significant differences (F = 1.703, P = 0.101; F = 1.321, P = 0.239). The common slopes were -0.556 +/- 0.027 (P = 0.0001) for the first and -0.597 +/- 0.0031 (P = 0.0001) for the second experimental run. Both slopes displayed no significant nonlinearity (P = 0.419 and P = 0.067). There was a strong association between changes in lung volumes (rs = 0.991, P = 0.0001) and changes in signal intensity (rs = 0.889, P = 0.0001) in the two experimental runs. Lines of best fit for lung volume and signal intensities were not significantly different from the slope of the line of identity (P = 0.321 and P = 0.212, respectively). CONCLUSION: Equal changes in lung volume cause equal changes in MR signal intensity of the lung parenchyma. This linear and reproducible phenomenon could be helpful in comparing pulmonary MR signal intensity between individuals. 2004 Wiley-Liss, Inc.
Authors: Francesca Pennati; James D Quirk; Dmitriy A Yablonskiy; Mario Castro; Andrea Aliverti; Jason C Woods Journal: Radiology Date: 2014-06-15 Impact factor: 11.105
Authors: Jürgen Biederer; S Mirsadraee; M Beer; F Molinari; C Hintze; G Bauman; M Both; E J R Van Beek; J Wild; M Puderbach Journal: Insights Imaging Date: 2012-01-15
Authors: Lorenzo Ball; Anja Braune; Peter Spieth; Moritz Herzog; Karthikka Chandrapatham; Volker Hietschold; Marcus J Schultz; Nicolò Patroniti; Paolo Pelosi; Marcelo Gama de Abreu Journal: Front Physiol Date: 2018-08-13 Impact factor: 4.566
Authors: Julian Glandorf; Filip Klimeš; Andreas Voskrebenzev; Marcel Gutberlet; Lea Behrendt; Cristian Crisosto; Frank Wacker; Pierluigi Ciet; Jim M Wild; Jens Vogel-Claussen Journal: PLoS One Date: 2020-12-30 Impact factor: 3.240
Authors: Pierluigi Ciet; Harm A W M Tiddens; Piotr A Wielopolski; Jim M Wild; Edward Y Lee; Giovanni Morana; Maarten H Lequin Journal: Pediatr Radiol Date: 2015-09-05