Measuring Lung Water: Ex Vivo Validation of Multi-image Gradient Echo MRI

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1 JOURNAL OF MAGNETIC RESONANCE IMAGING 34: (2011) Technical Note Measuring Lung Water: Ex Vivo Validation of Multi-image Gradient Echo MRI Sebastiaan Holverda, PhD, 1 * Rebecca J. Theilmann, PhD, 2 Rui C. Sá, PhD, 1 Tatsuya J. Arai, MSc, 1 Evan T. Hall, MSc, 1 David J. Dubowitz, MD, PhD, 2 G. Kim Prisk, PhD, DSc, 1,2 and Susan R. Hopkins, MD, PhD 1,2 Purpose: To validate a fast gradient echo sequence for rapid (9 s) quantitative imaging of lung water. Materials and Methods: Eleven excised pig lungs were imaged with a fast GRE sequence in triplicate, in the sagittal plane at 2 levels of inflation pressure (5 and 15 cm H 2 O), an intervention that alters T 2 *, but not total lung water. Images were acquired alternating between two closelyspaced echoes and data were fit (voxel-by-voxel) to a single exponential to determine T 2 * and water content, and compared with gravimetric measurements of total water. Results: T 2 * averaged ms at 5 cm H 2 O and ms at 15 cm H 2 O(P < 0.05). The measure was reliable (R 2 ¼ 0.99), with an average mean error of 1.8%. There was a significant linear relationship between the two measures of water content: The regression equations for the relationship were y ¼ 0.92x þ 19 (R 2 ¼ 0.94), and y ¼ 1.04x þ 4(R 2 ¼ 0.96), for 5 and 15 cm H 2 O inflation pressure respectively. Y-intercepts were not statistically different from zero (P ¼ 0.86). Conclusion: The multi-echo GRE sequence is a reliable and valid technique to assess water content in the lung. This technique enables rapid assessment of lung water, which is advantageous for in vivo studies. Key Words: T 2 *; proton density; validation; quantitative J. Magn. Reson. Imaging 2011; 34: VC 2011 Wiley-Liss, Inc. AN ALTERATION IN regional lung water content occurs in many pathologic lung conditions, such as pulmonary interstitial edema, as well as resulting from physiological interventions. Changes in regional lung water have the potential to significantly affect gas exchange 1 Department of Medicine, Division of Physiology, University of California, San Diego, La Jolla, California, USA. 2 Department of Radiology, University of California, San Diego, La Jolla, California, USA. Grant support: NIH grants HL081171, HL and AHA N. Authors SH and RJT have contributed equally to this work. *Address reprint requests to: S.H., Division of Physiology, Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla CA, sholverda@ucsd.edu Received March 3, 2010; Accepted March 7, DOI /jmri View this article online at wileyonlinelibrary.com. by thickening the gas exchange barrier and by altering local blood flow (1). Quantitative assessment of lung water content is thus valuable in the evaluation and monitoring of lung disease, in assessing treatment response, and in the study of pulmonary physiology. The estimation of lung water content was one of the first applications of MRI, and the principles behind it are based on the fact that the signal of any MR image is related to the number of protons present (2,3). Several validation studies have shown excellent correlations between gravimetric and MRI water content in excised animal lungs (2,4,5). Due to long imaging times of these T 2 -decay studies (> 6 min per slice) (5), this approach is not suitable for physiological human studies that require imaging to be completed within a single breathhold. The development of rapid imaging techniques such as gradient echo (GRE) imaging makes it possible to measure proton density of the lung in a single breathhold (6). Our recent implementation of an imaging sequence for rapid, quantitative, lung water imaging is new, and produced highly reproducible values of lung water in vivo (7). This sequence adapted a fast GRE sequence to collect 12 images alternating between two closelyspaced echoes in a single 9-s breathhold. The resulting data were fit with a single exponential decay function to determine T 2 * and lung water by back-extrapolating signal to an echo time of zero. This technique enables the assessment of lung water content in a single breathhold and, thus, may offer significant advantages in the study of human lung disease and physiology. Although the values of lung water obtained by Theilmann et al (7) were found to be consistent with previous studies, it is unknown how accurately these values represent absolute water content. The goal of this work was to validate a multi-gradient echo sequence against absolute water content measured gravimetrically in excised pig lungs. METHODS Isolated Lung Preparation A tissue transfer agreement, approved by the Institutional Animal Care and Use Committee, was used to VC 2011 Wiley-Liss, Inc. 220

2 Measuring Lung Water 221 obtain lungs from healthy animals undergoing terminal studies. Seven white farm or Yucatan pigs (weight range: kg) were sacrificed by overdose of pentobarbital. The animals were pretreated with heparin 5000 U intravenously to prevent clotting and exsanguinated passively. The heart and lungs were harvested as a block. The right and left lung were dissected free of the heart and extraneous tissue and then cannulated by means of the mainstem bronchus. Each lung was kept under 0.9% saline soaked gauze and at 4 C until imaging. The lungs were weighed (Ohaus balance, Florham Park, NJ) immediately before and after scanning to ensure that the water content did not change during the scan session. After scanning, lungs were inflated and dried under positive pressure (25 cm H 2 O) with dry air for several days until the weight remained constant (i.e., within 1 g). The gravimetric water content was then calculated as the wet weight minus the dry weight. MRI Measurements Imaging was carried out on a 1.5 Tesla GE HDx EXCITE twinspeed scanner (Milwaukee, WI) using a multi-gradient echo sequence previously described by Theilmann et al (7). A brief overview of the methods is described below. A total of 11 lungs (5 left, 6 right) were studied. Although it has been shown that T 2 * values in the lung vary with different degrees of lung inflation (7), total lung water content will not be affected by the amount of gas in the lung. Therefore, to provide validation for varying T 2 *, each lung was inflated and scanned at 5 and 15 cm H 2 O positive inflation pressure in the sagittal plane. The order of the inflation pressure was balanced between lungs to control for any ordering effects. These two inflation pressures were selected to approximate those at functional residual capacity and a lung volume that is closer to total lung capacity (8). To avoid drying of the lung during scanning, each excised lung was placed on plastic crates above saline impregnated gauze in a closed plastic container. Multiple sagittal two-dimensional (2D) images were acquired encompassing the entire lung. The sagittal plane was selected for imaging because this plane is subject to the effects of gravity on alveolar size, density and perfusion, and is commonly used in human studies (9,10). Each scan included simultaneous imaging of a gadolinium-doped water phantom for absolute calibration (Berlex Imaging, Magnevist, 469 mg/ml gadopentetate dimeglumine, 1:5500 dilution; T 1 ¼ 1100 ms, T 2 ¼ 1000 ms, T 2 * T 2 ). Each measurement was repeated three times while keeping prescan, gain, power, and shim values constant, to assess reliability. Pulse Sequence and Acquisition With this fast gradient echo pulse sequence, 12 sets of image data per slice were acquired within 9 sec with images alternating between a long (TE2 ¼ 1.40 ms) and a short echo time (TE1 ¼ 1.03 ms). Sequence parameters were TR ¼ 10 ms, flip angle ¼ 10 deg, slice thickness ¼ 15 mm, receiver bandwidth ¼ 125 khz, and a full acquisition matrix of Sequence parameters were purposely selected to duplicate an in vivo study previously reported (7). However, for this project, TE2 was shifted to a shorter echo time (1.40 ms) to ensure a sufficient signal to noise ratio. Note that with this model, density of the lung is reduced due to the low pulmonary blood volume post mortem (i.e., less blood, fewer protons). Calculation of T 2 * and Lung Water Content Two regions of interest (ROIs) were drawn manually for each scan using Matlab in which one ROI encompassed the entire lung and the other ROI placed within the boundaries of the phantom within the imaging slice. Images for both the short (TE1) and the long echo time (TE2) were averaged on a voxel-per-voxel basis. T 2 * was determined from I j k ¼ I 0 exp t j T 2, where j is the average of 4 images at each echo time (t 1 ¼ TE1, t 2 ¼ TE2) and k is the voxel of interest. The signal at an echo time of zero (I 0 ) was extrapolated for each voxel using the signal at the short echo time and the computed T 2 *. Assuming that the signal within the doped-water phantom is a good representation of the signal within the lung without any partial volume effects (i.e., 100% water), an absolute measure of lung water content can be obtained. Because the decay constants of the reference phantom were much longer than in the lung, this will result in a coherent build-up of signal in the phantom toward steady state for the imaging sequence used. Given that the relaxation decay constants of the reference phantom were static, a correction factor (c p ¼ 1.78) was empirically determined and applied to ensure that the mean phantom signal provides an accurate reference for absolute calibration (7). Lung water content per voxel (M 0 ) within the imaging slice was then calculated as the ratio, (I 0 W H20 )/(c p I p ), where I p is the mean signal of the phantom at TE1 and W H2O is the gravitational weight of a voxel without any partial volume effects (i.e., 100% water). Total lung water content was then calculated by integrating the lung water content across all voxels within the lung ROI of the imaging slice. Summation of M 0 across all slices yielded entire lung total lung water content. The results of the three acquisitions were averaged. Statistical Analysis The relationship between gravimetric and MR water content was characterized using linear regression, and the slope and strength of the association (R 2 ) were obtained (GraphPad Prism 5.02). A paired t-test was used for comparison between 5 and 15 cm H 2 O inflation pressure. Differences between slopes and y-intercepts of the 2 inflation pressures, as well as comparisons of the two regression lines with the line of identity, were assessed by an F-test. A Bland- Altman analysis was performed on the pooled data. All data are expressed as means 6 SD. P < 0.05 was considered significant.

3 222 Holverda et al. Figure 1. The relation between MRI water content measurements obtained from 2 different repetitions shows a high reproducibility. The line corresponds to the regression fit with R 2 ¼ 0.996, slope ¼ , and intercept ¼ 1 6 2g. RESULTS Lung Volume and Density On average, the lungs weighed g before and g after scanning (P ¼ 0.14), and there was less than 1% weight loss during the MR scan, which is negligible. Overall, as lung volume increased from 5 to 15 cm H 2 O inflation pressure ( cm 3 versus cm 3, P < 0.001), as expected the density of the lung was significantly reduced from 0.15 to 0.12 g/cm 3 (P < 0.001). and a slope of and y-intercept of 4 6 9g for 15 cm H 2 O inflation pressure. There was no significant difference in slope (P ¼ 0.245) and y-intercept (P ¼ 0.859) between the two linear fits for 5 and 15 cm H 2 O inflation pressure. The pooled slope (6 standard error) equals , and the pooled y-intercept equals g(R 2 ¼ 0.95). In addition, when compared with the line of identity (slope ¼ 1 and a y-intercept ¼ 0), the slopes of the 2 linear fits were not significantly different from 1 (P ¼ 0.28 and P ¼ 0.60 for 5 and 15 cm H 2 O), and the corresponding y-intercepts not significantly different from zero (P ¼ 0.08 and P ¼ 0.70 for 5 and 15 cm H 2 O). Figure 3 shows a Bland-Altman plot for the pooled data. The slope of the linear regression is and is not different from zero (P ¼ 0.70). It demonstrates that lung water content determined by MRI yields a small but systematic overestimation (bias ¼ 86 9 g, 6%). T 2 * Values Figure 4 shows a T 2 * and M 0 image of a lung slice for both inflation pressures. In Table 1 the average values for T 2 * and summed M 0 values are presented for each entire lung. T 2 * values were reduced at 15 cm H 2 O inflation pressure (P < 0.05). DISCUSSION The results of this study show that the multi-gradient echo sequence is a reliable assessment of lung water Lung Water Content Figure 1 shows a significant linear relation (R 2 ¼ 0.996) between the first and second repetition of MRI measurements, showing excellent reproducibility. The three repetitions yielded an average mean error (as a percentage of mean water content) of 1.8%. Figure 2 shows the correlation between lung water content measured gravimetrically and lung water content measured by the multi-gradient echo sequence at both lung volumes. The mean water content averaged g with 5 cm H 2 O and g with 15 cm H 2 O inflation pressure and were not significantly different (P ¼ 0.97). Average M 0 values, T 2 * values and gravimetric weight for each entire lung are shown in Table 1. As can be seen from Figure 2, on average, the water content assessed by MRI was higher than the gravimetric water content by % and % for 5 and 15 cm H 2 O inflation pressure respectively. The regression analyses for both pressures show a significant linear relationship (R 2 ¼ 0.94 and 0.96 for 5 and 15 cm H 2 O inflation pressure) between MRI and gravimetric measures of lung water. The regression lines had a corresponding slope (6 standard error) of and y-intercept (6 standard error) of g for 5 cm H 2 O, Figure 2. The MRI water content measurements, averaged over 3 repetitions, plotted as a function of gravimetric measurements for two inflation pressures, 5 and 15 cm H 2 O. The error bars are depicted, but in most cases are too small to exceed the size of the symbol. The regression line for the pooled data is plotted and has a slope and y-intercept (6 standard error) of and g, respectively. The regression line for 5 cm H 2 O inflation pressure corresponds to a slope of and y-intercept of g. For 15 cm H 2 Oinflationpressuretheslopeequals and the y-intercept ¼ 4 6 9g.

4 Measuring Lung Water 223 Table 1 Gravimetric Lung Weight, Average T 2 * at Both 5 cm H 2 O and 15 cm H 2 O Inflation Pressure, and Summed M 0 Values for Each Entire Lung Over 3 Repetitions* T 2 * (ms) M 0 (g) Lung 5 cm H 2 O 15 cm H 2 O Mean of 5 and 15 cm H 2 O Gravimetric weight (g) Mean * Values are mean 6 SD. * Significantly different from 5 cm H 2 O inflation pressure. with an excellent test retest reliability (R 2 ¼ 0.996). Lung water content measured by our multi-gradient echo sequence demonstrates a significant linear correlation with gravimetric water content values in ex vivo inflated pig lungs, regardless of the level of lung inflation, showing that T 2 * effects were accounted for appropriately. On average, there was a small overestimation of total lung water content of 8 g, irrespective of lung weight. MR techniques have been shown to be a robust method for lung water quantification. Early studies in excised rat lungs demonstrated that the MR values were well correlated with the gravimetric data (2,3). More recently, Estilaei et al (5) validated lung water content measurements using a single slice multi-echo pulse sequence to produce a T 2 -decay curve of porcine lung tissue and a water phantom. Compared with our study, their results yielded a similar slope ( ), and a y-intercept of g. They found a mean difference between the gravimetric and MRI water contents of %. These results are comparable with the results found in our study, with the difference that they, on average, showed a slight underestimation of total water content, where our results show a systematic overestimation of total water content. Our results using a GRE sequence systematically overestimated water content. We believe this discrepancy to be due to 2 issues. First, to prevent the blood from clotting, the animals were pretreated with heparin and some of the voxels in the lung have a very low signal because harvested lungs contain markedly less blood than lungs in vivo. Thus, the overall density was very low ( at 5 cm H 2 O inflation pressure), representing a worst case scenario compared with in situ lungs, where lung density has been shown to approximate 0.3 g/cm 3 (9,11,12). Second, our data is presented and analyzed after calculating the magnitude of the complex data. In the presence of noise and low SNR conditions (exacerbated in these excised lungs) the image intensity will be biased and lead to an overestimation of the mean signal (Rician distribution), an effect which will be augmented by multiple slices contributing to the error observed. In Figure 3. Bland-Altman plot for the pooled data. The dashed lines show the 95% limits of agreement. There is a small but systematic overestimation (bias ¼ g) when water content is assessed by using the multi-gradient echo sequence. The linear regression line has a slope of that is not significantly different from zero (P ¼ 0.70). Figure 4. Example of M 0 and T 2 * images (64 64) of a single right lung slice at both inflation pressures (top two rows). It can be appreciated from the images that lung volume is increased at 15 cm H 2 O inflation pressure, and there is a gradient in both M 0 and T 2 *. For average values of M 0 and T 2 * see Table 1. The bottom row shows images of the signal intensity of the same right lung slice at TE1 (S TE1 ) before the incorporation of a ROI.

5 224 Holverda et al. keeping with this, the results show on average an overestimation of lung water content of less than 7.5%. However, this is a level of error consistent with many biological measurements. No difference was found between the linear regression curves for 5 and 15 cm H 2 O. This indicates that the imaging sequence is accurate and consistent regardless of lung volume or density. It is well described that not only is T 2 * in the lung very short it also varies considerably with lung volume (4,7). Therefore, we collected images at two different inflation pressures to account for the effect of differing T 2 *. Our data shows that changing lung volume did not affect our assessment of total lung water content, despite a small but significant reduction in T 2 * with increased inflation pressure. Our results show a linear relationship between gravimetric and MR measurements of lung water content regardless of the level of lung inflation. In conclusion, the data in the present study show that lung water content measured by a multi-gradient echo sequence correlates linearly with gravimetrically measured water content at two different levels of lung inflation. Our imaging approach appears to overestimate absolute water content, but the errors are systematic and are <10% (10 g) of the actual gravimetric values. At higher absolute water contents such as in the in vivo human lung (approximately 1 kg), this suggests that a constant overestimation of 10 g would results in an error of 1%. Thus, our multi-gradient echo imaging sequence is a valid technique to assess water content in the lung. This technique is capable of acquiring data within a breathhold, which is advantageous in human lung imaging under various conditions, including interventions in health and disease. ACKNOWLEDGMENT The authors gratefully acknowledge the excellent surgical support from Zhenxing Fu, PhD. REFERENCES 1. Hopkins SR, Kleinsasser A, Bernard S, et al. Hypoxia has a greater effect than exercise on the redistribution of pulmonary blood flow in swine. J Appl Physiol 2007;103: Cutillo A, Morris A, Blatter D, et al. Determination of lung water content and distribution by nuclear magnetic resonance. J Appl Physiol 1984;57: Hayes C, Case T, Ailion D, et al. Lung water quantitation by nuclear magnetic resonance imaging. Science 1982;216: Mayo J, MacKay A, Whittall K, Baile E, Pare P. Measurement of lung water content and pleural pressure gradient with magnetic resonance imaging. J Thorac Imaging 1995;10: Estilaei M, MacKay A, Whittall K, Mayo J. In vitro measurements of water content and T2 relaxation times in lung using a clinical MRI scanner. J Magn Reson Imaging 1999;9: Hatabu H, Alsop D, Listerud J, Bonnet M, Gefter W. T2* and proton density measurement of normal human lung parenchyma using submillisecond echo time gradient echo magnetic resonance imaging. Eur J Radiol 1999;29: Theilmann R, Arai T, Samiee A, et al. Quantitative MRI measurement of lung density must account for the change in T(2) (*) with lung inflation. J Magn Reson Imaging 2009;30: Rahn H, Otis A, Chadwick L, Fenn W. The pressure-volume diagram of the thorax and lung. Am J Physiol 1946;146: Hopkins S, Henderson A, Levin D, et al. Vertical gradients in regional lung density and perfusion in the supine human lung: the Slinky effect. J Appl Physiol 2007;103: Prisk G, Yamada K, Henderson A, et al. Pulmonary perfusion in the prone and supine postures in the normal human lung. J Appl Physiol 2007;103: Almquist H, Palmer J, Jonson B, Wollmer P. Pulmonary perfusion and density gradients in healthy volunteers. J Nucl Med 1997;38: Brudin L, Rhodes C, Valind S, Wollmer P, Hughes J. Regional lung density and blood volume in nonsmoking and smoking subjects measured by PET. J Appl Physiol 1987;63: