SEARCH

SEARCH BY CITATION

Keywords:

  • arterial input function;
  • dynamic contrast enhanced MRI: contrast agent;
  • phase imaging;
  • flow compensation;
  • colorimetry

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

Purpose

To measure the arterial input function (AIF) in a mouse tail at high temporal resolution with signal phase of MR projections.

Methods

The technique involves the acquisition of one 2D image before injection, followed by a series of projections before, during, and after contrast injection. Differences in the signal phase, relative to the mean preinjection phase, were calculated and converted into a concentration of Gd.

Results

An AIF with a temporal resolution of 100 ms was measured and verified with colorimetry (in a flow phantom) and mass spectrometry analysis (in vivo). The projection-based AIF is expected to better represent the rapid contrast kinetics in the blood following injection, thus improving the accuracy of quantitative dynamic contrast-enhanced-MRI analysis. Colorimetry experiments confirmed that signal phase is preferred over magnitude for a precise determination of an AIF. In-vivo experiments demonstrate the feasibility of our approach in mice.

Conclusion

AIFs can be measured quickly and precisely using phase from projections. Phase data are sensitive to the flow velocity; but this sensitivity is significantly reduced when flow compensation was used. Magn Reson Med 71:238–245, 2014. © 2013 Wiley Periodicals, Inc.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

With the growing popularity of dynamic contrast-enhanced (DCE) MRI in cancer research [1-4], requirements for data of high spatial and temporal resolution have become apparent [5]. DCE-MRI data are analyzed quantitatively through pharmacokinetic modeling [6]. However, most models require that the concentration–time curves are accurately characterized in the tissue of interest, and in a vessel feeding the tissue of interest [7], commonly referred to as an arterial input function (AIF) [8]. Typical model parameters describe physical properties of the investigated tissue [9] and may be used to identify the presence of abnormal vasculature [2], such as that observed in tumors [10]. Improving sensitivity and specificity of DCE-MRI analysis requires that these parameters are accurately determined [11]; this may be achieved with a high-quality measurement of the AIF [5].

Ideally, an artery supplying the region of interest will be analyzed [8, 9]. But, this can be challenging in cases where the artery is located far from the imaging site [4] or when partial-volume effects corrupt the signal from small supplying arteries [12]. Measuring the AIF in small animals, such as mice, is further complicated owing to the animals' small body size [13, 14] and rapid heart rate [8, 15]. Although AIFs from tails in rats have been measured successfully [16], few vessels in the mouse are sufficiently large to measure the AIF with adequate temporal and spatial resolutions.

The accuracy of the AIF will have a significant impact on the pharmacokinetic model parameters [13, 17-19]. Therefore, it is highly preferred that the AIF be acquired for each experiment [13], including studies performed on the same patient multiple times [9]. Most groups have opted to use a population-averaged AIF [18, 20, 21] for their analysis. Although the population-averaged AIF is expected to approximate the true curve, it does not account for interindividual [8] or intraindividual [2, 22] differences. Additionally, a population-averaged AIF may only be accurate for a specific injection protocol, contrast agent dose, and strain of animal.

To adequately capture the important, rapid enhancement after injection, temporal resolutions higher than typically employed may improve the accuracy of the sampled AIF [9, 13, 23]. Although fast imaging techniques have been proposed, the temporal resolution is limited by the time needed to acquire a full image [20, 21]. A recent study by Ragan et al. [24] showed that it was possible to estimate the AIF with a compressed sensing approach known as cardiac anatomy-constrained temporally unrestricted sampling. This technique updates the dynamic images with two radial acquisitions per measurement, providing an effective temporal resolution of 84 ms. Their AIF was measured in the left ventricle of a mouse heart. Another mouse-based AIF was performed by Fruytier et al. [25]. Their AIF was measured with a temporal resolution of 1.19 s in the iliac artery with a fast gradient echo pulse sequence.

Traditionally, the AIF was determined from changes in the longitudinal (r1) or transverse (r2) relaxivity [21], and converted to a concentration assuming a linear relationship [17]. Recent studies have shown that the AIF may also be determined from the signal phase [26]. Phase data have the advantages that it evolves linearly with concentration over a wide range [26, 27], it is expected to have a signal-to-noise ratio (SNR) up to a full order of magnitude greater than the magnitude data [26, 28], it is less sensitive to partial-volume effects [25], and it is relatively insensitive to T1 and T2 relaxation [29].

We introduce a novel method for measuring the AIF in a mouse tail using MR projections and the phase of the MR signal. This method involves the acquisition of a single 2D image and a series of projections collected before, during, and after the contrast injection. The mouse tail was chosen for our analysis because of its simple geometry; it contains four small, isolated point-like vessels in a tissue background void of complicated organs. As the vessels are located near the surface, the projection may be oriented such that the vessels are well separated in the acquired profile. Projection data have a temporal resolution equal to the repetition time, thus offering significant gains in the temporal resolution of the AIF. As a projection-based AIF is measured rapidly on an individual basis, it would be applicable to DCE-MRI studies performed in small animals.

METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

The study was performed in three parts: (1) a calibration experiment designed to determine the conversion factor between signal phase and concentration of Gd, (2) a flow-phantom experiment designed to simulate blood flow in vivo, and (3) a projection-based AIF measurement, performed in vivo.

A calibration phantom was constructed by inserting a capillary tube of inner diameter (i.d.) 0.4 mm inside a larger glass spotting tube (i.d. = 3.7 mm). The region between the tubes was filled with tap water to represent the tissue in the tail. The tap water provides additional signal for magnet shimming and provides a nonenhancing region to correct for hardware-related phase fluctuations [29]. A number of Gd-based solutions, diluted in saline to concentrations between 2 and 10 mM, were injected through the capillary tube at three physiologically relevant flow velocities [30]: (1) 0 cm/s, (2) ∼15 cm/s (1.00 mL/min flow rate) and (3) ∼30 cm/s (2.00 mL/min flow rate). A KD Scientific power injector (model 780220) was used for the injection to reduce variation in injection profile. Data were collected, for all concentrations and flow velocities, for images (matrix size 256 × 256) and projections (matrix size 256 × 1, number of repetitions = 256).

The flow phantom was inspired by the system presented by Akbudak et al. [29]. It consists of a peristaltic pump (Minipuls 2, Gilson) and three types of tubing: latex (i.d. = 3.2 mm), tygon (i.d. = 3.2 mm), and viton (i.d. = 1 mm). To span the length to and from the center of the scanner bore to the pump in the adjacent room, 8 m of viton tubing was used. Initially, the system, having a total volume of 24 ± 1 mL, was flushed with tap water. The recirculation beaker of approx. 2 mL served as a mixing site for the dye and water.

As a colorimeter was used for measurement of dye concentrations, a 0.8-mL bolus of 0.101 mM Allura Red 40 dye (Kool-Aid, Kraft Foods), mixed with 10 mM Gd-DTPA, was injected at a rate of 11 mL/min with the power injector. The bolus was allowed to circulate for ∼8 min.

As the fluid flowed through a semi-micro cuvette, the concentration of dye in the tubing was measured with a custom-built colorimeter, consisting of a light emitting diode (LED)(OVLGC0C6B9, OPTEK Technology Inc., Carrollton, TX) and a photodiode (MTD5052N, Marktech Optoelectronics, Latham, NY). Two operational amplifiers (TL082, Texas Instruments, Dallas, TX) were used to provide a supplying voltage to the LED and to convert the photocurrent produced by the photodiode into an output voltage. The voltage was recorded with an oscilloscope (TDS 3054B, Tektronix, Long Branch, NJ) and converted to a concentration of dye [31]. The system was calibrated using a set of known solutions of Allura Red 40 dye.

MRI acquisition took place using a small bore Biospec 70/30 Bruker 7.0 T MRI scanner (Bruker BioSpin, Ltd., Etlingen, Germany). A birdcage coil with 7.0-cm inner diameter and an actively decoupled tail-specific surface coil (width 7 mm, length 18 mm) were used for signal excitation and reception, respectively. Projections were obtained by setting all phase-encode gradients to 0 mT/cm. A standard FLASH pulse sequence (parameters pulse repetition time/echo time (TE) = 100 ms/4.6 ms, flip angle 90°, field of view = 15 × 15 mm2, slice thickness 1 mm, and matrix size 256 × 256 for2-D images or 256 × 1 for projections) was used for data collection. The same sequence with a longer TE = 8.0 ms was used to confirm the calibration constant, but the shorter echo time is preferred for higher SNR. A reference phantom in the field of view showed that phase drift is not a concern for our experiments.

All animal-based scans were approved by the Animal Care Committee at UBC. Healthy NOD/SCID immune compromised mice were anesthetized with isoflurane, mixed with oxygen, to a dose of 2%. A butterfly needle was inserted into the tail vein of the mouse and secured in place with fast drying glue. The animal was placed supine on an animal bed and centered in the scanner. A standard multislice FLASH experiment (pulse repetetion time/TE = 100/3.096 ms, flip angle 30°, five slices, field of view = 15 × 15 mm2, and slice thickness 1 mm) was performed to align the tail vessels with the main magnetic field [26]. Proper alignment is required to maximize the SNR and to avoid fringe fields [32]. Retrospective analysis shows that we were able to achieve tail alignment to 8.9° or less resulting in a negligible error in the concentration assessment.

In a separate experiment, an image-based AIF was measured to provide an estimate of the long-term concentration following bolus injection. (FLASH, TE = 6.874 ms, eight time points, and temporal resolution 37 s)

The injection was initiated with the power injector set for a flow rate of 1.00 mL/min, which corresponds to an approximate flow velocity of 15 cm/s in the tubing (PE 20, i.d. = 0.38 mm), at the start of the fourth image. 1.0 M Gd-DTPA was diluted with saline to a final concentration of 30 mM and injected to a volume of 5 μL/g (or dose of 0.15 μmol/g body weight). The injection was preceded with a 25 μL saline prebolus and followed with a 40 μL saline flush [17].

A projection-based AIF was measured with the acquisition of one preinjection image (256 × 256 matrix size), followed by a series of projections (256 × 1 matrix size, and 2560 projections total) before, during, and after contrast injection (TE = 3.92 ms). The average intravascular phase, in each of the clearly enhancing tail vessels, was calculated and converted into a concentration. The injection was initiated after ∼256 projections.

When investigating the effect of flow compensation, we applied first-order flow compensation in the slice, read, and phase-encode directions. First-order phase correction will cancel the effects of spins moving with constant velocity during the time of encoding to readout. It will not cancel pulsatile flow effects, which we expect to be minimal in veins and arteries further away from the heart (such as the tail).

The proposed projection-based method is outlined in Figure 1. It involves the acquisition of one 2D image before injection, followed by a series of projections. The projections were acquired under identical scanning conditions, but with phase-encode gradients switched off. The MR signal from the vessel was isolated by subtracting the profile corresponding to the tissue background; this was obtained by projecting the 2D baseline image along the phase-encode direction, after the vessel data had been removed in the image (application of the central-slice theorem [33]). The AIF was determined by comparing the mean phase for each projection with the preinjection value. This phase difference was then converted to a concentration of Gd using the calibration factor determined previously.

image

Figure 1. Schematic of the projection-based AIF measurement. One 2D image is acquired preinjection, followed by a series of projections before, during, and after contrast injection. This technique may be used to increase the temporal resolution of the AIF as only one projection is required per data point.

Download figure to PowerPoint

To verify that the concentration at 20-min postinjection is correct, blood samples from four NOD/SCID mice were analyzed for Gd concentration using inductively coupled plasma mass spectrometry (service provided by Matthew Norman at Exova, Surrey, Canada). Mice used for this analysis were not scanned but had similar weights (range 22.0–30.5 g). The mice were injected with a 30 mM bolus of Gd, diluted in saline, to a dose of 5 μL/g weight. The injection was performed manually over a period of ∼20 s. Animals were euthanized ∼20 min after injection and a cardiac puncture was performed to extract 200–500 μL blood. Samples were brought to a final volume of 10 mL, with 1% nitric acid (concentration 0.22 M) to prevent biodegradation [34].

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

The calibration experiment was performed to determine the conversion factor from phase difference to a concentration of Gd, and to evaluate the need for flow compensation. The results from this analysis verified that the phase varies linearly over the range of concentrations chosen, regardless of the flow velocity or echo time. Phase–concentration curves for the projection data are summarized in Figure 2. The slopes of these curves were consistent for all cases studied (three flow velocities, flow compensation absent/present, two echo times, and images/projections) and had a value of (0.213 ± 0.001) rad/mM/ms. This value is consistent with the predicted value of 0.212 rad/mM/ms for a long cylinder oriented parallel to B0:

  • display math

Here γ is the proton gyrometric ratio (4.258 × 107 Hz/T), B0 is the strength of the main magnetic field (7.0 T), and χm is the molar susceptibility of the contrast agent (3.4 × 10−7 mM for Gd) [35]. The phase–concentration relationship holds in the presence and absence of flow compensation. But there appears to be a flow-dependent phase shift that is significantly reduced when flow compensation is used. As constant blood flow cannot be assumed in vivo, flow compensation was applied for all future scans.

image

Figure 2. Calibration factor converting a phase difference into a concentration of Gd for projections. Gd-based solutions, diluted in saline, were injected through a capillary tube at three biologically relevant flow velocities. The experiment was performed with a standard FLASH pulse sequence, with and without flow compensation. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Download figure to PowerPoint

The flow-phantom experiment was designed to evaluate and cross-validate the projection-based AIF in an environment of recirculating fluid. The results from a concurrent optical and MR measurement are summarized in Figure 3. A schematic diagram of our flow system is displayed in the inset of Figure 3a. Figure 3a shows the concentration–time curve for the measurement of the dye concentration at different distances downstream from the injection site. Greater dispersion of the bolus (lower peak height and broader width) can be seen in the curve corresponding to the measurement made further downstream. Figure 3b compares the MR measurement of magnitude and phase during bolus passage. The magnitude data do not accurately reproduce the first pass of the bolus, likely a result of T2* relaxation. Although the magnitude data do show signs of recirculation, they are not to the same extent observed with the phase-based or colorimetric measurement. Figure 3c compares the optical- and phase-based concentration–times curves measured simultaneously. The first bolus passage is narrower and higher on MR compared with colorimetry. Subsequent recirculation peaks agree very well between the two modalities.

image

Figure 3. Signal–time curves for the colorimetry phantom: (a) Colorimetric concentration-time curves for two different locations of the cuvette, inset shows a schematic of the colorimetric phantom, (b) magnitude and phase from MR, and (c) comparison of phase-based and colorimetric concentration in simultaneous acquisition. The colorimetric curve has been shifted in time to account for different locations of MR coil and cuvette. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Download figure to PowerPoint

An image-based AIF (temporal resolution 37 s) is shown in Figure 4. At this resolution, the shape of the curve is not well characterized, particularly at the peak. Further, it is unclear if the concentration at the peak has experienced a phase wrap (phase exceeds 2π radians and was reset to a value within this range). This AIF suggests a peak concentration of either 1.46 or 5.78 mM and a long term concentration of 0.34 mM. The lack of quantitative information from this curve motivated the proposal of using MR projection data to measure the AIF.

image

Figure 4. Image-based AIF in the mouse tail. The AIF was measured in the vessel indicated by the arrow. At a temporal resolution of 37 s, it is unclear if the measurement at the peak has exceeded the dynamic range of 2π radians and was phase wrapped to a lower angle. By increasing the temporal resolution, phase wraps will be more obvious. In addition, the details of the curve are not well characterized, and the temporal location of the injection is unknown. Increasing the temporal resolution will reduce ambiguities in both. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Download figure to PowerPoint

A projection-based AIF, having a temporal resolution of 100 ms, is shown in Figure 5. At this temporal resolution, the details of the curve are well characterized for all times, and it is clear when the Gd bolus entered the blood stream. A double exponential [8, 21], modulated by a sigmoid function [20] was fitted to the curve, having the functional form C(t) = (0.81*e−0.081*t+0.34)/(1+4.0*e0.99*t). The double exponential proposed by Lyng et al. [21] is also plotted. This curve was derived from the data acquired from the left ventricle of three separate mice, sampled with a temporal resolution of 13 s.

image

Figure 5. Projection-based AIF in a mouse tail having a temporal resolution of 100 ms with a five-parameter fit overlaid. The double exponential proposed by Lyng [21] based on a temporal resolution of 13 s is shown for comparison (dashed line). Their curve overestimates the concentration following injection and appears to be shifted temporally relative to our measurement.

Download figure to PowerPoint

Figure 6 shows four AIFs measured in four different mice. The AIF was obtained by averaging the phase–time curves from all pixels associated with a vessel (typically 2–6 pixels along the projection). The four curves not only show similarities in shape and peak height but also differ from one another in terms of the rates of enhancement, wash out, and final concentration 10-min postinjection. Superimposed on the figure, is a population-averaged AIF (thick black curve).

image

Figure 6. AIF measured in four individual mice. The AIFs all have a similar shape, but show markable differences following the injection. The population-averaged result (solid black line) differs from each of the individual curves.

Download figure to PowerPoint

The results from mass spectrometry showed a blood concentration of 0.170–0.195 mM for the mice of weight 22–24 g, 0.293 mM for the 30.5 g mouse, and 34.8 mM for the stock solution.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

We acquired an AIF in a mouse tail with a temporal resolution of 100 ms using a projection-based approach. Our method allows us to isolate the enhancement in the tail vein from the projection through a subtraction of the background profile. The AIF was calculated by comparing the average phase between each projection and the preinjection value, and then converting the phase change into a concentration with our calibration factor.

The results from mass spectrometry suggest that the steady-state Gd concentration (20-min postinjection) should be ∼0.2–0.3 mM. This is in agreement with our projection-based AIF. If all contrast agent were to remain intra-vascular, we would expect a steady-state concentration of 2.0 ± 0.4 mM Gd. This assumes a total blood volume of 6–8% body weight and a 30 ± 5 mM Gd-DTPA bolus (error reflects mass spectrometry measurement) of volume 5 μL/g body weight. However, the contrast agent will readily perfuse into the extracellular–extravascular space after injection, resulting in the lower, observed steady-state concentration in the vasculature. Our results suggest that the Gd fills an apparent distribution space of roughly 10 times the blood volume. A possible explanation is the extraction of Gd by the kidney and other tissues immediately following injection [10].

Concentration–time curves obtained with the signal phase show remarkable agreement with the optical concentration measurements (Fig. 3c). However, the first peak between the MR measurement and colorimetry differ. The discrepancy in the peak height and width of the first pass arises from the different sizes of sensitive volume. The gadolinium concentration is measured in a 1-mm slice of the viton tubing, a volume much smaller than the injected volume. In contrast, the colorimetry measurement takes place in a semi-micro cuvette with a volume of 3 mL. This exceeds the injected bolus volume of 0.8 mL, and thus the maximum concentration of Allura Red 40 dye is lower by a factor 3.75. As the mixing is not instantaneous, the peak width of the colorimetric curve increases, its height decreases, and the maximum of the peak is shifted to a later time. All subsequent peaks better resemble one another due to bolus mixing in both the cuvette and the recirculation beaker.

The AIF proposed by Lyng et al. has become the standard population-averaged curve for experiments performed in mice. Their curve has a temporal resolution of 13 s and was determined from changes in T1 [21]. A double exponential, C(t) = Xext+Yeyt, was fitted to the postinjection data where X = 5.8 mM, x = 4.4 min−1, Y = 0.7 mM, and y = 0.05 min. At their temporal resolution, it is unclear when the bolus injection began, how long it lasted, or if a recirculation peak is present. It is, therefore, difficult to temporally align the Lyng population-averaged AIF to independently acquired DCE data. Furthermore, when fitting the Lyng curve to DCE data of higher temporal resolution (<13 s), concentrations following injection will be overestimated, thus leading to errors in pharmacokinetic model parameters.

Other attempts to measure murine AIFs have typically been derived from the observed change in the signal intensity [18, 19] or T1 [17, 26], and then converted into a concentration assuming a linear relationship [36]. However, magnitude-based AIFs suffer from a few limitations. First, there is evidence that the signal intensity only varies linearly with concentration over a narrow range of concentrations. This is a result of competing T1 and T2* relaxation effects at high concentrations [17, 37]. The validity of magnitude-based AIFs becomes questionable, when the peak concentrations are expected to approach this limit. In addition, the signal intensity is dramatically reduced at the peak due to T2* relaxation [26], which will make an accurate measure of the concentration difficult. Losses in SNR, due to T2*-dephasing, may be partially recovered by minimizing the TE or reducing the concentration of the injected bolus. In comparison, the T1-based approach requires that a preinjection T1 map be determined, potentially increasing the total time of the experiment. As displayed in Figure 3b, the magnitude data at the first peak is not representative of the true concentration.

Reference region and reference tissue methods have been proposed to avoid the issue of measuring the AIF altogether [38, 39].

Our methods offers an alternative to overcome many of the above-mentioned limitations by evaluating changes in the signal phase. Although phase-based measurements are relatively new [29], the number of studies using phase have dramatically increased over the last few years [13, 27, 35]. Phase is relatively immune to T1 and T2 relaxation times [29], is independent of the blood hematocrit [37], has an increased SNR compared to magnitude data [26] and has an established linear relationship with concentration over a large range [13].

Contrary to magnitude-based imaging techniques, flow in blood vessels cannot be sufficiently suppressed with saturation pulses. Our phantom experiment revealed a velocity-dependent phase shift, when flow compensation was not used. This shift appeared to be consistent for all concentrations as the slopes of the phase–concentration curves were similar for all cases studied. When flow compensation was applied prior to data acquisition, the phase shift was reduced significantly, such that curves for the 15 and 30 cm/s flow velocities were nearly identical. More specifically, the signal phase was similar at each concentration, independent of the flow velocity (Fig. 2b). This suggests that first-order phase compensation may be sufficient, even in the presence of variable flow velocities, such as possible during an injection, and the associated increase in heart and respiration rates.

Measuring the AIF in small animals is difficult due to the limited number of larger vessels. Some groups have chosen to measure the AIF in the left ventricle of the heart [8, 24, 40] or in the iliac artery [13, 25]. The left ventricle is attractive for its large size and relatively stationary blood for a short period of time. But, proper gating is essential for an accurate measurement. Measuring the AIF in the iliac artery may be advantageous, as it is generally closer to the imaging plane, but the presence of a number of organs will make a projection-based approach difficult. The tail was chosen for this application, as it contains four large, widely spaced vessels (arteries and veins), and few anatomic structures in the background. With a carefully aligned and straight vessel, SNR can be increased by choosing a thicker slice.

The bolus injection does not occur instantaneously, so the early stages of the AIF will be dependent on the injection protocol. For a simple model of the AIF, we assume a rectangular injection profile. The early upslope of the AIF is expected to have the functional form of a square convolved with a double exponential as shown in Fig. 7a). A closer look at the up-slope of the projection-based AIF reveals that the enhancement follows expectations for the first 3 s. Beyond this time, the curve levels off rapidly, despite more contrast agent being injected. Possible reasons for the disagreement between the simple model and our observation includes a nonrectangular bolus profile, early contrast perfusion into the extracellular–extravascular space, and recirculation of blood during the injection period. To assist with our interpretation of the up-slope, the bolus injection duration (red line) and the expected time interval at which the recirculation peak may occur (green line) were plotted. The recirculation time was estimated from an assumed blood volume of 6–8% body weight [41] and a cardiac output of 0.73 ± 0.19 mL/min/g [42]. From Fig. 7b, it is expected that the recirculation peak is masked by our injection and will not be observed. This is consistent with another animal-based study [18]. Based on the figure, the injection protocol will have a significant impact on the early enhancement characteristics of the curve. As such, the AIF should be measured for each injection protocol used. The projection-based AIF technique will help reduce errors when injections differ between experiments.

image

Figure 7. Impacts of the injection protocol on the expected shape of the AIF. The results for a square injection protocol, and a double exponential clearance from the vasculature, is shown in (a), whereas the observed upslope from the projection-based AIF is shown in (b). These results suggest that the shape of the AIF differs from expectations when measured in vivo. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Download figure to PowerPoint

Our study has a few limitations. An earlier experiment suggested that the location of the butterfly needle can have a dramatic effect on the SNR, potentially from magnetic susceptibility of the metal. The results from that study (not shown) suggested that the SNR was minimally affected when the butterfly needle was placed outside the sensitive region of the surface coil. Although residual effects on B0 inhomogeneity, associated changes to the slice profile, and alteration of gradients might still be present, we did not detect them. To avoid such potential problems, one can use nonmetallic cannulations, like plastic catheters.

Single MR projections tend to be noisy. The SNR can be maximized by constructing a special surface coil for the tail, using a 90° flip angle and a minimum echo time. As our time resolution is quite high, further improvements can be achieved in practice by time averaging projection profiles.

For less stable magnets, our method could be subject to phase drift. To compensate, a nonenhancing, external reference phantom was placed next to the mouse tail. For our analysis, phase drift was generally negligible, but it could be corrected for, if required.

Phase measurements have a limited dynamic range of 2π. For a given TE, phase wraps could occur at high concentrations and thus lead to ambiguities in the measured AIF. Although the TE may be limited to a minimum value, this rarely has practical implications. Our results show that the concentration at the peak for a 30 mM bolus injection is ∼2 mM, which is lower than we expected. At this peak concentration, we could increase the echo time to 14.75 ± 0.07 ms before phase wrapping becomes an issue at a field strength of 7 T. In general, a longer TE time will allow for greater phase sensitivity to a change in concentration, but will be at the cost of reduced SNR. Increasing the TE too much could be detrimental to our measurement, as the subtraction of a noisy background profile could introduce additional sources of noise. It should be noted that even if phase wraps were to occur, the high temporal resolution will allow the detection of these wraps, even during the “difficult”, rapid enhancement period.

Perfusion of the contrast agent into the surrounding tail tissue will lead to local tissue enhancement. As a result, the projection profile will be further altered and thus limits our ability to measure the AIF accurately. It is expected that tissue enhancement will occur at a slow rate relative to changes in the blood. Therefore, it may be possible to measure the degree of tissue enhancement temporally and correct the projections for it. We are currently investigating how tissue enhancement may be determined accurately with a minimal loss to our temporal resolution. A further complication could arise if surrounding tissue enhances such that a strong concentration inhomogeneity occurred in the direct vicinity of the vessel. Although previous work has not reported errors of this nature, future work needs to identify the degree to which such heterogeneities cause inaccuracies.

CONCLUSIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

High-temporal resolution AIFs (δ t = 100 ms) were successfully measured using a projection-based approach and validated with colorimetry measurements using a custom-built flow phantom that simulated an in vivo environment. As each projection requires only 100-ms acquisition time, it could be acquired in conjunction with a DCE-MRI experiment for interleaved acquisition of an AIF without a significant loss in the temporal resolution. This study shows that a projection-based approach may be used to significantly increase the temporal resolution of the AIF on an individual basis.

Acknowledgments

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES

Thank you to Jennifer Baker, for catheterizing the mouse tails and assistance with scanning, and to Maria Jose Gandolfo, for her help with collecting blood samples for mass spectrometry.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. Acknowledgments
  9. REFERENCES