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(Radiology. 1999;212:890-895.)
© RSNA, 1999

Technical Developments

Pulmonary Perfusion: Respiratory-triggered Three-dimensional MR Imaging with Arterial Spin Tagging-Preliminary Results in Healthy Volunteers1

David A. Roberts, MD, PhD, Warren B. Gefter, MD, Joshua A. Hirsch, MD, Rahim R. Rizi, PhD, Lawrence Dougherty, PhD, Robert E. Lenkinski, PhD, John S. Leigh, Jr, PhD and Mitchell D. Schnall, MD, PhD

1 From the Department of Radiology, University of Pennsylvania Medical Center, 1 Silverstein, 3400 Spruce St, Philadelphia, PA 19104-4283. Received March 5, 1998; revision requested June 5; final revision received October 27; accepted March 16, 1999. Supported in part by a seed grant from the Society for Thoracic Radiology. Address reprint requests to D.A.R. (e-mail: roberts@oasis.rad.upenn.edu).


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
The authors used a spin-tagging method of magnetic resonance perfusion imaging to measure pulmonary perfusion in eight healthy volunteers with use of a respiratory-triggered three-dimensional pulse sequence. The average signal intensity (SI) decrease upon arterial labeling was 24%. The perfusion SI increased by 21% after exercise (P = .02). Focal blood flow abnormalities were observed in a patient with chronic obstructive pulmonary disease.

Index terms: Lung, MR, 60.121412, 60.121417 • Lung, perfusion, 60.91 • Lung, ventilation, 60.91


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
The imaging of pulmonary perfusion has many important applications in medicine and has proved useful in the diagnosis of pulmonary vascular disease and in the evaluation of disease in patients with emphysema. Pulmonary embolism is a major cause of morbidity and mortality in the United States (1). Data indicate that there is an increase in the mortality of patients who are not appropriately treated for pulmonary embolism, indicating the critical need for accurate diagnosis of this disease (2). The diagnosis of pulmonary embolism is based on the demonstration of decreased or absent blood flow in a focal region of the lung without a corresponding ventilation abnormality. Currently, the most commonly used noninvasive imaging method is radionuclide ventilation-perfusion scanning. Although normal or grossly abnormal ventilation-perfusion scans provide extremely useful clinical information, there is an unacceptably high frequency of equivocal results that necessitates further evaluation (3). Although pulmonary angiography is a highly accurate and safe method, there is evidence that it is underused, perhaps due to its relative expense and invasiveness (4,5). The development of an accurate, noninvasive method of pulmonary perfusion imaging would constitute an advance in patient care.

Magnetic resonance (MR) imaging of the lung parenchyma is intrinsically difficult due to the large degree of microscopic magnetic field inhomogeneity, which causes the observed transverse relaxation time (T2*) to be extremely short (6,7). However, the recent development of gradient-echo pulse sequences with extremely short echo time and projection reconstruction techniques has allowed investigators to image the pulmonary parenchyma (8–10). Recently, several MR methods of pulmonary perfusion imaging have been described (11–16). To date, the MR methods described have been breath-hold techniques that are based on dynamic observation of the pulmonary magnetization after either injection of a bolus of paramagnetic contrast agent (13,15,16) or spatially selective inversion of the mediastinum (12,14). An alternative noninvasive technique exploits differences in signal intensity (SI) between different cardiac phases (11). Although promising, these methods necessitate breath-holding maneuvers, which are often impossible for patients with pulmonary disease. In addition, injection of a contrast agent for the perfusion study introduces additional risk and expense. The quality of subsequent MR angiograms is also reduced by contrast material injection owing to reduced background suppression, which causes a reduction in the contrast-to-noise ratio.

The arterial spin-tagging method of perfusion imaging is based on the steady-state magnetic labeling of the arterial water supplying an organ (17,18). This results in a measurable change in the steady-state magnetization from which values for tissue-specific perfusion can be calculated. This method has been applied successfully in both animal and human studies (17–23). To our knowledge, the application of this method to the study of pulmonary perfusion has not been reported. In this study, we evaluated use of a three-dimensional, respiratory-triggered implementation of this technique to depict regional pulmonary perfusion in healthy subjects without the need for breath holding.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Human Subjects
This study was conducted according to a protocol approved by our institutional review board. Informed consent was obtained from all volunteers after the nature of the study was fully explained. Eight healthy adult subjects (three men, five women; age range, 21–33 years; average age, 27 years ± 5 [SD]) participated in this study. None of the subjects had a history of pulmonary disease, and all were nonsmokers.

Image Acquisition
MR imaging data were acquired with a 1.5-T imaging system equipped with high-power gradients (Echospeed Signa, revision 5.6 software; GE Medical Systems, Milwaukee, Wis). The gradients had a peak amplitude of 2.2 G/cm. For monitoring purposes, cardiac electrodes were placed on the chest wall, and a respiratory excursion transducer was looped around the chest. A quadrature birdcage coil encompassing the entire body was used for signal transmission. To maximize the signal-to-noise ratio (SNR), a phased-array coil was placed around the thorax for signal reception that consisted of anterior and posterior two-element arrays. An automated gradient shim was performed, and the radio-frequency (RF) synthesizer frequency was centered on the proton water resonance frequency.

The pulse sequence used to acquire data appears in Figure 1. It is a three-dimensional, compact, gradient-echo pulse sequence that incorporates an asymmetric, truncated sinc RF slab excitation pulse of 1.28-msec duration. The following imaging parameters were used: repetition time msec/echo time msec of 50/716–760 with 30° flip angle, 7–10-mm section thickness, 40–48-cm field of view, and 256 x 64 x 16 matrix. The nominal in-plane resolution was approximately 2 x 8 mm. To minimize the echo time, a fractional echo was acquired with a 64-kHz receiver bandwidth. A sagittal volume was excited that included the right lung, as indicated in Figure 2. Trapezoidal gradient and RF pulses were placed in the interpulse interval to label blood flow according to the principle of flow-induced adiabatic fast passage (24,25). The offset frequency of the labeling pulse was adjusted in each case so that the location of the plane of arterial labeling intersected the right pulmonary artery (Fig 2). In all subjects, the right pulmonary artery was readily identified on the scout localizer image by both the radiologist (D.A.R.) and technologist. The amplitude of the labeling RF pulse, Bi, was 24 mG, and its duration was 40 msec, corresponding to a duty cycle of 80%. The amplitude of the inversion gradient, Gi, was 0.1 G/cm. Under these conditions, the labeling RF pulse created a band of saturation approximately 0.6 mm thick, as indicated by the lines in Figure 2. On the basis of measurements obtained on our localizer images, the average diameter of the right pulmonary artery was 1.6 cm. Assuming that the right pulmonary artery receives half the normal cardiac output of 5 L/min, then the estimated average velocity of flow is 8.3 cm/sec. This yields an adiabaticity factor (21) for the inversion of 2.8, yielding an estimated degree of inversion of 95%. As the duty cycle is 80%, this yields an estimated net inversion efficiency of 76%. This likely represents an overestimation of the degree of inversion as higher velocities occur during the cardiac cycle that yield lower inversion efficiencies. Although one would ideally like to achieve 100% inversion efficiency to maximize the observed SI change, this was the highest achievable value to remain within limitations of the specific absorption rate.



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  		Figure 1. Schematic depicts the three-dimensional, compact, gradient-echo pulse sequence used to acquire MR perfusion image data. It shows the RF and gradient (Gx, Gy, and Gz) waveforms. An arterial labeling RF pulse is applied in the presence of a gradient during the interpulse interval to provide continuous magnetic labeling of pulmonary arterial blood flow. The amplitude, Bi, of the RF pulse is 24 mG, and the duration of the pulse, Ti, is 40 msec. The flip angle, {theta}, is 30°. The time axis is not to scale. C = crusher gradient, Gi = inversion gradient.

 


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  		Figure 2. T1-weighted localizer MR image illustrates the experimental design of the perfusion measurement and the locations of the planes of arterial labeling for the inversion image (line on the right) and for the magnetization transfer control image (line on the left) relative to the image volume (rectangle). Under the conditions used in this experiment, the labeling RF pulse created a band of saturation approximately 0.6 mm thick, as indicated by the lines. Arterial blood in the right pulmonary artery (arrow) was labeled during acquisition of the inversion image.

 
The pulse sequence was triggered to the respiratory cycle, as shown in Figure 3. The excitation and arterial labeling RF pulses and gradients were applied continuously to maintain a steady-state condition. However, data acquisition was performed during only the end-expiratory phase of the respiratory cycle, as indicated by the black bars in the diagram. Sixteen slab encodings were acquired at end expiration, requiring a temporal window of 800 msec. This approach maximized the signal from the lung, which was observed to be higher at end expiration.



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  		Figure 3. Schematic depicts respiratory triggering performed by monitoring the patient's chest excursion. The trigger was set so data acquisition was enabled during only the end-expiratory phase of the respiratory cycle ({block}).

 
Magnitude image data were acquired in the presence of arterial labeling (inversion) and under control conditions in which the amplitude of the label RF was set to zero (control). To correct for magnetization transfer effects of the labeling RF pulse (26), an additional acquisition (magnetization transfer control) was performed in which the plane of arterial labeling was located in a symmetric location on the opposite side of the image volume, as shown in Figure 2. This geometry reproduced the off-resonance effects of the pulse in the absence of arterial labeling and allowed estimated correction for these effects. The entire data acquisition typically required less than 15 minutes.

This method, as described, does not provide an absolute quantitation of perfusion. Instead, images are produced of the relative regional SI change induced by means of arterial labeling. For this reason, accurate knowledge of the degree of arterial inversion at the level of the pulmonary artery is not important for the detection of spatial defects in a given individual. However, this does become important when attempting to compare results obtained in the same individual at different points in time.

Exercise Studies
Subjects (n = 8) were instructed to exercise by performing a leg-raising maneuver until the point of exhaustion. The basal heart rate and the heart rate immediately after exercise were recorded. Perfusion data were acquired before and after exercise. Comparison of the heart rate and the pre- and postexercise data was performed by means of the paired Student t test. In one patient, images obtained after exercise were corrupted by motion artifact and were excluded. Therefore, postexercise data were available in only seven patients.

Data Analysis
All data analysis was performed off-line on a workstation (Silicon Graphics, Mountain View, Calif) by using the Interactive Data Language (Research Systems, Boulder, Colo). Calculation of the perfusion images typically required 10 minutes per patient, including both data transfer to the workstation and subsequent analysis. The total time necessary to produce perfusion images of the right lung was 30 minutes.

Prior to formation of magnitude image subtraction data, the inversion image data were corrected for off-resonance effects of the labeling RF. A region of interest was drawn interactively around the lung in each image in the control and magnetization transfer control data sets. Pixels composing pulmonary parenchyma were then identified by means of segmentation of the magnitude image data within these regions of interest by using an upper threshold of 150. This value was chosen empirically, as segmentation at this level eliminated contributions from the pulmonary arteries in all patients. Note that this form of segmentation does not eliminate contributions from the bronchi, which are expected to have zero SI as they contain air. This represents a small error in the analysis. The degree of magnetization transfer saturation, S, caused by the labeling pulse in pulmonary parenchyma was computed as the ratio of the average SI with the pulse divided by the average SI without the pulse. This was computed for each section in the magnetization transfer control acquisition as a function of distance, z', from the plane of the lateral labeling pulse. It is important to note that the physical location of the plane used to determine the degree of saturation was different from the corresponding plane in the inversion data set. Therefore, a point-by-point correction could not be performed. The computation yielded a correction factor, S'(z'), for magnetization transfer effect as a function of z'. Assuming that the lung is spatially homogeneous in its off-resonance properties, the appropriate correction factor for arterial spin-tagging images is S(z) = S'(z'), where z is the distance of an arterial spin-tagging image from the plane of arterial labeling. In some cases, the extreme medial or lateral images in the volume contained so little lung parenchyma that an accurate calculation could not be performed. In these cases, no correction was performed (S[z] = 1.0).

Images of the regional percentage SI change after correction for off-resonance effects ({Delta}CORR) induced upon arterial labeling in a section located a distance, z, from the plane of arterial labeling were calculated as

where Mc and Mi are the magnitude SI in images acquired under control conditions (no labeling RF) and under conditions of arterial labeling, respectively. This calculation was not performed in pixels on the control image in which the SI was zero. In these pixels, the value of {Delta}CORR was set to zero.

The SI in the control image was determined by computing the average value in a small region of interest placed around the peripheral aspect of the lung in the central section. The noise was computed as the SD in a small region of interest outside the body, in the upper left corner of the same section. This location was chosen to minimize the effect of potential respiratory motion artifacts on the noise calculation. The SNR was then computed as their ratio.

Values for the mean SI change in pulmonary parenchyma were computed as follows: (a) a region of interest was interactively placed around the lung in each of the control images, and (b) segmentation within this region was then performed with use of an upper threshold of 150 to identify pixels composing lung parenchyma. Inspection of the segmented images showed that this eliminated contributions from the central pulmonary arteries.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Statistical analysis of the perfusion data acquired in eight subjects appears in the Table. The average SNR obtained in the lung parenchyma in eight subjects was 48 ± 15 (mean ± SD). The average percentage SI change at rest before and after correction for off-resonance effects was 32% ± 3 and 24% ± 2, respectively (n = 8). These data demonstrate that approximately one-third of the observed SI change is due to off-resonance effects, most of which arise from sections closest to the plane of arterial labeling. Typical results obtained from a healthy volunteer at rest appear in Figure 4. In all subjects, readily observable changes in the pulmonary magnetization were observed to the level of the pleura. Only minimal respiratory motion artifacts were observed.


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  		Perfusion Data in Eight Healthy Subjects
 


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  		Figure 4. Images depict results of the arterial spin-tagging perfusion measurement technique in a resting healthy volunteer. A, Sagittal MR images of the corrected percentage SI change after correction for off-resonance effects induced by arterial labeling appear next to B, the corresponding control images. The SI changes are scaled from 0 (black) to 80% (white). Small SI changes in the chest wall have been excluded from display by means of segmentation. The section location progresses from most medial (top left) to most lateral (bottom right). Black defects (arrows in the second column) shown in some of the blood flow images (B) represent central pulmonary arteries that have been excluded from the analysis as have pulmonary veins and bronchi.

 
Results of exercise testing also appear in the Table. The average heart rate was 60 beats per minute ± 6 and 93 beats per minute ± 12 before and after exercise, respectively (n = 7, P = .001). The average percentage SI change after correction for off-resonance effects before and after exercise was 24% ± 2 and 29% ± 5, respectively (P = .02). Thus, there was a 21% increase in the observed SI change after exercise.

We also obtained preliminary data in a patient with chronic obstructive pulmonary disease (Fig 5). The reformatted sagittal computed tomographic (CT) images reveal bullous disease, which asymmetrically affects the right upper and middle lobes, with relative sparing of the right lower lobe (Fig 5, top row). Despite the presence of bullous disease, an SNR of approximately 11:1 was obtained in the affected parts of the lung on the control images (Fig 5, middle row). The arterial spin-tagging perfusion images demonstrated marked hypoperfusion in a distribution that closely paralleled the distribution of chronic obstructive pulmonary disease (Fig 5, bottom row). Hypoperfusion was observed to the extreme lateral aspect of the lung, where off-resonance effects were quite small.



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  		Figure 5. Top row: Reformatted, sagittal, nonenhanced CT images obtained in a patient with underlying chronic obstructive pulmonary disease reveal asymmetric bullous disease (arrows) preferentially affecting the right upper and middle lobes. Middle row: Despite the presence of bullous disease, the SNR in the affected areas was 11:1 on the control images. Bottom row: The corresponding arterial spin-tagging perfusion images demonstrate focal defects (arrows) in perfusion that correlate well with the distribution of involvement depicted at CT.

 

   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Despite its relatively low SNR, the human lung otherwise represents an ideal organ for application of the arterial spin-tagging method of perfusion imaging. In addition to having a well-defined arterial blood supply, the lung also possesses an extremely large tissue-specific perfusion and blood volume. Each lung receives approximately one-half the cardiac output, yielding a typical volumetric flow rate of 2,500 mL/min in a 70-kg person. The right lung weighs approximately 625 g (27), yielding a tissue-specific perfusion of 4.0 mL · g-1 · min-1. This value is more than four times larger than the values reported for human gray matter (28). In addition, the lung also has a relatively large blood volume compartment (29–31). In contrast to prior implementations of this technique, we made no attempt to suppress the intravascular compartment as this is extremely difficult due to the short transverse relaxation time. As a consequence, the observed SI changes at arterial labeling are a function of not only perfusion but also the blood volume and the artery-to-capillary transit time (26). Specifically, assuming an apparent T1 of 1.0 seconds, a partition coefficient of 1.0, and an effective degree of labeling of 65%, the predicted SI change based on perfusion alone should be approximately 8%, accounting for approximately one-third of the SI changes observed in this study. The majority of the observed SI changes are probably due to blood volume effects. These factors make the absolute quantitation of pulmonary perfusion difficult with this approach.

However, the presence of thromboembolic disease leads to decreases in pulmonary perfusion and blood volume while at the same time prolonging the transit time. All of these changes are expected to lead to a marked reduction in the observed SI change upon arterial labeling. Therefore, the arterial spin-tagging method should be especially sensitive to the presence of pulmonary thromboembolic disease. This may have important clinical implications as recent data suggest that as many as 30% of patients with pulmonary emboli have involvement at the subsegmental level or below (32). This area has been difficult to evaluate with cross-sectional imaging techniques (33,34).

The assumption of a spatially uniform off-resonance characteristic in the lung represents a potential source of error. It is indeed probable that in the presence of disease there are marked regional variations in the magnetization transfer properties of the lung that would invalidate this assumption. The use of amplitude-modulated control irradiation would eliminate this as a potential source of error; however, such pulses could not be implemented at present owing to limitations of the RF amplifier.

The spin-tagging pulse labels all blood flow occurring at the level of the pulmonary hilum. Therefore, the perfusion images reflect contributions from both the pulmonary and bronchial arteries. This is an important difference from radionuclide ventilation-perfusion scanning in which, in the absence of shunt formation, uptake reflects only pulmonary arterial flow. Results obtained with the arterial spin-tagging technique may differ from those obtained on ventilation-perfusion scans, especially in patients with chronic lung disease in whom prominent bronchial collateral vessels may exist. In addition, this may decrease the sensitivity of this method for the detection of pulmonary embolism as bronchial supply to the affected segment may persist.

The arterial spin-tagging method may be used to obtain noninvasive images of pulmonary blood flow without the need for patient breath holding. The arterial spin-tagging technique is entirely noninvasive and eliminates the risks and expense associated with contrast material administration. In comparison with previously described MR techniques for pulmonary perfusion imaging (11,12,14), this technique does not require breath holding, a task that is often impossible for patients with pulmonary disease. In fact, this method is ideally suited to the evaluation of disease in patients receiving artificial ventilation as nearly perfect respiratory triggering may be achieved in this setting. As a steady-state technique, it theoretically allows a greater effect of arterial labeling to build up during the acquisition. Alternative MR pulmonary perfusion imaging techniques that require the intravenous injection of paramagnetic contrast agents have also been described (13,16). These methods suffer from the need for breath holding, a task that is often impossible for patients with clinically important pulmonary disease. Although pulmonary MR angiography has been shown to be a highly accurate and safe method for the diagnosis of pulmonary embolism, the need to inject gadolinium for the perfusion study inevitably reduces the quality of subsequent MR angiograms owing to decreased background suppression. In addition, the accuracy of pulmonary MR angiography at the subsegmental level and below is not known (34). There is evidence that a major fraction of pulmonary emboli occur at the subsegmental level or below (32). As the spin-tagging method does not involve contrast material injection, this technique may become useful as a means of focusing the MR angiographic examination in a specific region of the lung, thereby potentially increasing the spatial resolution and diagnostic yield of pulmonary MR angiograms and allowing the diagnosis of subsegmental pulmonary embolism. In addition, in conjunction with recently developed noninvasive methods of MR ventilation imaging (35,36), it has the potential to constitute a component of an entirely noninvasive, high-spatial-resolution form of MR ventilation-perfusion imaging.

The clinical utility of the arterial spin-tagging method, although promising, may be limited by several technical factors. Specifically, its success rate and accuracy in a patient population are unknown. Techniques must be developed to allow perfusion imaging of the left lung, where effects due to cardiac motion and intracardiac labeling of blood flow must be addressed. Such techniques may lead to increases in acquisition time. The arterial spin-tagging method in isolation is likely to suffer from indeterminate results in the clinical setting of pulmonary embolism for the same reasons that radionuclide scanning does. Despite these limitations, it is reasonable to conjecture that this method, coupled with high-spatial-resolution MR angiography and ventilation imaging, may form an important part of an integrated functional and anatomic MR examination of the lung.


   Acknowledgments
 
The authors are grateful to David Alsop, PhD, and Leon Axel, PhD, MD, from the Department of Radiology, University of Pennsylvania Medical Center for helpful discussion and advice. We are also grateful to Zahi Fayad, PhD, from the Department of Radiology, Mount Sinai Medical Center, New York, NY, for stimulating discussion. Valuable technical assistance was provided by Norman Butler, MRT.


   Footnotes
 
Abbreviations: RF = radio frequency SI = signal intensity SNR = signal-to-noise ratio

Author contributions: Guarantor of integrity of entire study, D.A.R.; study concepts, D.A.R., J.S.L.; study design, D.A.R., M.D.S., R.E.L.; definition of intellectual content, M.D.S., D.A.R., J.S.L.; literature research, D.A.R.; clinical studies, D.A.R., R.E.L., L.D., M.D.S.; data acquisition, J.A.H., D.A.R., R.R.R.; data analysis, D.A.R., R.R.R.; statistical analysis, D.A.R.; manuscript preparation and editing, D.A.R.; manuscript review, R.R.R., W.B.G., R.E.L., M.D.S.


   References
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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U. J. Schoepf, R. Bruening, H. Konschitzky, C. R. Becker, A. Knez, J. Weber, O. Muehling, P. Herzog, A. Huber, R. Haberl, et al.
Pulmonary Embolism: Comprehensive Diagnosis by Using Electron-Beam CT for Detection of Emboli and Assessment of Pulmonary Blood Flow
Radiology, December 1, 2000; 217(3): 693 - 700.
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D. D. Maki, W. B. Gefter, and A. Alavi
Recent Advances in Pulmonary Imaging
Chest, November 1, 1999; 116(5): 1388 - 1402.
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