doi: 10.1161/CIRCIMAGING.108.784702
Original Articles |
Intrinsic Gating for Small-Animal Computed Tomography
A Robust ECG-Less Paradigm for Deriving Cardiac Phase Information and Functional Imaging
From the Departments of Radiology (J.D., H.-U.K.), Medical Physics in Radiology (S.H.B., J.K., W.S., F.K.), Statistics (A.K.-S.), German Cancer Research Center (DKFZ), Heidelberg, Germany; Siemens Medical Solutions, Forchheim, Germany (M.G.); Department of Molecular Cardiology, University of Frankfurt, Germany (M.I., S.D.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (R.G.); Department of Radiology, University Hospital Heidelberg, Germany (H.-U.K.); Department of Experimental Molecular Imaging, RWTH-Aachen University, Germany (F.K.).
Correspondence to Julien Dinkel, Department of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. E-mail j.dinkel{at}dkfz-heidelberg.de
Received April 8, 2008; accepted September 24, 2008.
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Abstract |
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Background— A projection-based method of intrinsic cardiac gating in small-animal computed tomography imaging is presented.
Methods and Results— In this method, which operates without external ECG monitoring, the gating reference signal is derived from the raw data of the computed tomography projections. After filtering, the derived gating reference signal is used to rearrange the projection images retrospectively into data sets representing different time points in the cardiac cycle during expiration. These time-stamped projection images are then used for tomographic reconstruction of different phases of the cardiac cycle. Intrinsic gating was evaluated in mice and rats and compared with extrinsic retrospective gating. An excellent agreement was achieved between ECG-derived gating signal and self-gating signal (coverage probability for a difference between the 2 measurements to be less than 5 ms was 89.2% in mice and 85.9% in rats). Functional parameters (ventricular volumes and ejection fraction) obtained from the intrinsic and the extrinsic data sets were not significantly different. The ease of use and reliability of intrinsic gating were demonstrated via a chemical stress test on 2 mice, in which the system performed flawlessly despite an increased heart rate. Because of intrinsic gating, the image quality was improved to the extent that even the coronary arteries of mice could be visualized in vivo despite a heart rate approaching 430 bpm. Feasibility of intrinsic gating for functional imaging and assessment of cardiac wall motion abnormalities was successfully tested in a mouse model of myocardial infarction.
Conclusions— Our results demonstrate that self-gating using advanced software postprocessing of projection data promises to be a valuable tool for rodent computed tomography imaging and renders ECG gating with external electrodes superfluous.
Key Words: flat-panel detector • imaging • intrinsic gating • small-animal imaging • tomography
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Introduction |
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Rodent models, particularly transgenic mouse models of cardiac disease, play a major role in cardiovascular research and have proven their value and clinical relevance to human medicine.1 In this context, the assessment of cardiac morphology and function is important. Currently, the myocardial function and structure of rodents are predominantly studied by using MRI2 or echocardiography. However, MRI has limitations. Dedicated small-animal MRI systems are expensive, and access to these systems is limited. Furthermore, studies are complex and time consuming, and the quality of the MR scans often is reduced by blood flow and motion generated artifacts. Echocardiographic techniques are rarely 3D,3 and global functional parameters must be approximated from 2D cross-sectional data.4
Small-animal computed tomography (CT) imaging, despite its manifold applications as a sensitive and cost-effective diagnostic tool, does not yet play a significant role in the assessment of cardiac morphology and function. Recently developed small-animal CT scanners based of the flat-panel detector provide a higher scanning speed when compared with that of most commercial microfocus CT systems, which makes cardiac imaging feasible in principle. Here, gating permits physiological heart and lung motion to be taken into consideration during scanning. The gating signal can be used to suppress motion artifacts and acquire functional information. Both prospective5–7 and retrospective8–10 methods for respiratory and cardiac gating have been described, and their benefit for image analysis has been demonstrated.7–10
Regardless of whether they are retrospective or prospective, all gating methods currently in use in small-animal CT imaging depend on ECG to derive a gating reference signal. In addition, heart movement attributable to respiration must either be suppressed via intubation or detected by a pneumatic cushion and taken into consideration. Self-gating (synonymous with image-based, intrinsic, or raw data–based gating) in small-animal CT, in which the gating information is taken directly from the acquired projection data, has so far only been demonstrated for respiratory motion imaging.10
Small-animal MRI can also be used to acquire self-gated 4D imaging of the heart. A 1D projection-based self-gating method has been already demonstrated for cardiac MRI with radial k-space acquisition.11 Other MR self-gating methods are using a synchronization signal extracted from the echo peak MR magnitude of a nontriggered radial acquisition.12
However, cardiac self-gating in small-animal CT imaging that takes into account the characteristics of flat panel–based cone-beam CT scanners (eg, wide z-coverage, relatively slow data acquisition rate, and continuous volumetric sampling) is presented here for the first time.
To demonstrate that the proposed method was equivalent to established ECG-based gating method, 2 different approaches were used. In a prospective approach, before the reconstruction, we analyzed the ECG-derived gating signal and the intrinsic gating signal and demonstrated an excellent agreement between the 2. In a retrospective outcome-based approach, we compared cardiac function parameters derived from the 2 gating methods. To illustrate the robustness of the proposed self-gating method and its potential future usefulness, we performed dobutamine stress CT scans in 2 mice and scans of a murine model of infarction.
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Methods |
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Flat Panel–Based Volume CT Scanner and Scans
A prototype volume CT (VCT) scanner was used for image acquisition and gating experiments. Its main features were a flat-panel detector and a modified x-ray tube, both mounted on a multislice CT gantry.9,10,13 The flat-panel detector (PaxScan 4030CB, Varian Medical Systems) used by this prototype scanner consisted of 2048x1536 detector pixels over an active area of 40x30 cm2, resulting in a pixel size of 1942 µm2. For this experiment, the active detector area was limited to 192 lines in the z direction and 1024 rows in the x–y direction to increase the frame rate. Moreover, the detector was read out in a 2x2 binning mode, ie, 4 neighboring pixels were averaged. This resulted in a decreased scan field of view of 25x25x4.5 cm3, which was still big enough to cover the entire thorax and diaphragm of a rat. The resulting frame rate was 100 frames per second (fps), corresponding to an exposure time of 10 ms per projection.
The spatial resolution of the scanner, as computed by scanning a tungsten wire phantom, was 24 lp/cm at 10% modulation transfer function. This isotropic spatial resolution translated into a minimal detectable feature size of 
200 µm.
For retrospectively gated imaging, projection images were acquired over 16 complete rotations with a rotation time of 5 s, for a total scan time of 80 s. A tube voltage of 80 kV and a tube current of 50 mA with continuous radiation were selected. Both extrinsic and intrinsic motion-gated reconstructions were performed for each animal. The reconstruction field of view for mice and rats was 4.5 cm transaxially, with a reconstruction matrix of 512x512 pixels and an axial slice spacing of 0.2 mm, resulting in a voxel size of 0.08x0.08x0.20 mm3. A sharp reconstruction kernel (H80s) was used for image reconstruction.
Extrinsic Gating
Extrinsic respiratory gating was performed as described previously.9 A commercial small-animal monitoring unit (1025L and Signal Breakout Module, SA Instruments) was used to track the respiration movements by using a pneumatic cushion. ECG signals were received from electrodes affixed to the paws of the animal. Its waveform was processed to detect R waves. Commercially available software was used for synchronization of the physiological waveforms and the acquired projection images.
Intrinsic Cardiac Gating
A region of interest (ROI) covering the heart on all projections was defined. If the heart was not in the geometric isocenter of the CT scanner, it was automatically tracked by a custom-developed sinusoidal ROI tracking method in the projection images throughout the 360° rotation. Within this ROI, the center of mass (COM) in the craniocaudal direction (P) was calculated from the raw projection data. To calculate the COM, each line sum of projection values (mz) was multiplied with a weighting factor equal to the z position of that particular line. Weighted projection values from all lines were summed and divided by the total sum of projection values from the ROI (M) as shown below. 
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The variations attributable to the angular position of the gantry had a fixed periodicity of 500 projections, reflecting the number of projections in 1 rotation around the animal. The influence of angular position should be minimized to derive a gating reference signal. Therefore, the COM of each projection throughout 1 rotation was normalized to the median of the COM values at this particular angular position for all acquired rotations. This minimized the influence of angular position on the gating signal and revealed the cardiac pulsation in the craniocaudal direction. Despite this processing, however, the oscillations in COM were only an approximate marker of cardiac pulsation attributable to image noise; the acquired data had to be further processed by using MATLAB (The MathWorks) for motion-gated reconstruction as described later.
Figure 1 illustrates the intrinsic gating approach and its main processing steps. The projections acquired during a rotation of the cone-beam CT x-ray scan (Figure 1A) were combined with a manually selected and automatically tracked ROI (Figure 1B). From this ROI, the vertical coordinate of the COM was calculated and normalized to take the influence of angular position into consideration (Figure 1C).
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After smoothing and filtering (Figure 1D) with a bandpass filter (180 to 550 bpm window for the mouse and 80 to 450 bpm window for the rat), the maxima were automatically determined by the zero crossings of the first derivative of the waveform (Figure 1E).
Intrinsic Respiratory Gating
Respiratory gating was performed by using a similar method, whereby the manually selected ROI covered the diaphragm instead of the heart. Neither a sinusoidal tracing function nor a frequency filter was necessary to extract a gating reference signal, because the diaphragm movement induced changes in the COM amplitude that were much stronger than those induced by heart movements. Here too, local maxima of the resulting curve were used as gating reference points.
Motion-Gated Reconstruction
Cardiac and respiratory gating reference points were derived for every cardiac and respiratory cycle for both extrinsic and intrinsic gating. During extrinsic gating, ECG electrodes and a compression cushion for respiratory movement were used. As a prerequisite for cardiac gating, respiratory gating is necessary to avoid the influence of diaphragmatic motion during breathing excursion resulting in displacement of the heart. All other steps such as retrospective binning of projections from several rotations according to their cardiac phase and volumetric reconstruction using these projection sets were identical in both gating methods. The steps involved in retrospective binning and reconstruction are described in detail9 and are briefly summarized in the following paragraphs.
The starting point of each respiratory cycle (0% point) was defined to correspond to the gating reference signal of every motion cycle. To reconstruct a given phase of the respiratory cycle, the projections acquired within that respiratory phase were selected for image reconstruction. Respiratory phases were defined by start and end points, given as the percentage of the cycle length.
The selected projections from the rebinning step, representing projections pertaining to a given phase of the respiratory cycle, were then interpolated to yield a new 360° projection data set consisting of 600 evenly distributed projections. If 
2 selected projections were found to be at identical positions (remember that the angular position of each projection was recorded during different rotations), they were averaged to improve the signal-to-noise ratio of the interpolated projection. If no projections were found for a selected angular position, interpolation from the closest neighboring projections was performed. Interpolation was weighted with respect to angular distance.
Only projections in respiratory motion-compensated expiration phase were selected for cardiac gated reconstruction. Optimal gating intervals depended on the animal being imaged and were empirically derived through experimentation. In rats and mice, the interval from 20% to 80% of the respiration phase was found to be optimal for reconstruction because the most intense motion occurred either before 20% or after 80% of the respiratory phase. For cardiac-gated reconstruction, respiratory motion gating was used first. Additionally, 10 phases of equal length were evenly defined over the cardiac cycle. Cardiac motion was visible between all of these phases. The end-diastolic phase was defined by the cardiac phase that showed the largest ventricular volume.
Animals and Contrast Media
All experiments using rats and mice were approved by the Governmental Review Committee on Animal Care.
To compare the 2 gating methods, 4 C3H/HeN wild-type mice (20 g) and 4 healthy Copenhagen rats (250 g) were scanned. To demonstrate potential future applications of self-gating, a scan of a murine model of infarction was executed, and a pharmacological cardiac stress test was performed on 2 mice.
Myocardial infarction was induced by permanent ligation of the left coronary artery in a 12-week-old BALB/c mouse. Left coronary artery ligation was performed as described previously.14 The infarction was confirmed through catheterization before CT scanning and via histology after the imaging was completed.
In the stress test model, 2 C3H/HeN wild-type mice were scanned before and during intravenous injection of dobutamine at a dose of 30 ng/g body weight min–1.15
For scanning and surgery, mice and rats were anesthetized by continuous inhalation of 3% sevoflurane (Sevorane; Abbot) in oxygen during preparation, injection of contrast media, and scanning.
The pneumatic cushion was attached to the animals to record the respiratory movements. ECG electrodes were affixed to the paws to monitor the ECG waveform. The animals were not intubated and were allowed to breathe freely throughout the experiment.
All rodents were scanned after the administration of the intravascular contrast agent Fenestra-VC (Advanced Research Technologies). A dose of 2.5 mL Fenestra-VC (50 mg iodine/mL) was injected into the tail vein of the rats 5 minutes before scanning. Mice received 0.5 mL of the same contrast agent.5,16
Postprocessing
The reconstructed image data sets were supplemented by a DICOM3-header to permit their import into standard postprocessing software. The CT image evaluation used multiplanar reformations from 4D data sets together with a commercial workstation (InSpace Siemens Medical Solutions). The Medical Imaging Interaction Toolkit (German Cancer Research Center)17 was used to semiautomatically segment heart volumes.
Data and Statistical Analysis
Physiological data such as cardiac ejection fraction were calculated from the self-gated 4D time series. The differences in volumes from the 2 ventricles during the end-diastolic and end-systolic phases were computed.
End-diastolic and end-systolic ventricular volumes as well as cardiac ejection fractions from intrinsic gating were compared with corresponding values from extrinsic methods and a 95% CI was calculated for mean differences.
The evaluation of the agreement between ECG and intrinsic gating signal was used as an objective quantitative measure for validation. We compared the median heart period on ECG signal and the median detected heart period based on the intrinsic cardiac motion over 4 s for the mice and rats, resulting in 20 measurements of the heart period during a total scan time of 80 s. The agreement between the 2 methods was evaluated by using coverage probability18 and 95% CIs. The 95% CI for the mean difference between the 2 measurements were derived from a linear mixed model with random effect for the rat and for the mouse.
Calculations were made with Excel 97 (Microsoft) and BiAS for Windows (Version 8.2 to 07/2006, Epsilon) Confidence intervals and coverage probability were calculated with R (R version 2.7.1, The R Foundation for Statistical Computing). To demonstrate the agreement between the gating signals of the 2 methods, we conducted a Bland Altman plot for the mice and rats heart rates.
The authors had full access to the data and take responsibility for its integrity. All authors have read and agree to the manuscript as written.
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Results |
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Evaluation of the Method
Mice and rats exhibited a gasping type of respiration with minimal changes in respiratory motion and ventilation frequency once a steady state of narcosis was reached. The respiration rate varied from 20 to 35 minute–1 in mice and 20 to 39 minute–1 in rats.
The heart rates varied within a range of 343 to 428 minute–1 in mice and 237 to 300 minute–1 in rats.
The measured intraindividual variation in the mean heart rate was marginal for both methods. The mean SD of measured heart rate was higher for the extrinsic method than for the intrinsic method (70 minute–1 versus 35 minute–1 in mice, respectively; 37 minute–1 versus 23 minute–1 in rats, respectively). The high SD indicates that the ECG is noisy. The intrinsic signal cannot be noisy because the signal is filtered. Actually, the mean SD of the intrinsic signal is related to the heart rate variability and to the uncertainties of the extracted heart frequency attributable to the low sampling resolution. An excellent agreement between intrinsic and extrinsic gating signals was observed. The mean difference between the 2 measurements was –0.20 ms in mice (95% CI –2.1 to 1.70) and 0.065 ms in rats (95% CI –1.00 to 1.10). Because the temporal resolution of the VCT for 1 projection is 10 ms, a difference between the 2 measurements of <5 ms would not have any consequences. A difference of 5 to 15 ms would lead to a nearly negligible angular error of the selected projection 0.72°. The coverage probability for a difference between the 2 measurements to be <5 ms was 89.2% in mice and 85.9% in rats. This excellent agreement is further demonstrated by Bland-Altman analysis shown in Figure 2. A clustered dispersion of the heart rate data are seen because the 4 rats (Figure 2A) and the 4 mice (Figure 2B) have different base heart rates. These results indicate that the intrinsic signals coincide well with the extrinsic gating signal. The mean difference between the 2 signals, given as mean ± SD, is 0.004±2.4 bpm in rats and 0.9±6.8 bpm in mice.
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Given such high agreement between the intrinsic and extrinsic gating signal, no significant difference in image quality between the reconstructions using these 2 different types of gating schemes was expected. This is borne out by the images analysis given below.
Quantitative Analyses of Functional Cardiac Imaging
Image reconstruction rendered 4D data sets of high quality. The VCT offered high contrast between the iodinated blood and the myocardium and after intrinsic gating allowed for clear delineation of epicardial and endocardial borders. Cardiac, mediastinal, and lung anatomy were clearly depicted, and even coronary arteries of mice were visible (Figure 3).
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Table 1 shows the mean end-diastolic and end-systolic ventricular volumes as well as cardiac ejection fractions revealed by semiautomated segmentation. The results of left ventricular (LV) and right ventricular (RV) volume and global functional measurements are also summarized. No outlier was found. The ventricular volumes and the functional parameters obtained from the intrinsic and extrinsic data sets were within 1 SD of each other and found to be not significantly different. Only for end-diastolic LV volumes in mice there was a trend to 4±3 µL higher values using the intrinsic gating method. All 95% CIs of the mean difference contained 0 and did not cover values indicating a relevant difference (Table 1).
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A literature search for the approximate values of ventricular volumes and the cardiac ejection fractions was conducted. Values determined by self-gated and extrinsically gated CT matched closely with those quoted in the literature.5,8 Minor differences in the values may derive from different animal sizes, ages, anesthesia states, the physiological conditions under which the animals were tested, and measurement error.19–21
Example of Potential Applications (Dobutamine Stress Cardiac VCT in Mice and Changes in Cardiac Geometry and Function in an Infarcted Mouse)
After dobutamine injection we observed a decrease in both LV end-diastolic volume and end-systolic volume. Ejection fraction and LV wall thickness increased during the dobutamine test (Table 2 and Figure 4). Online movies can be viewed in the Data Supplement (available online at http://circimaging.ahajournals.org.
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Cardiac VCT of a mouse with infarcted myocardium after left anterior descending artery ligation revealed gross dilatation of the left ventricle with marked thinning of the LV anterior wall and complete absence of systolic thickening. Dynamic analyses revealed clear akinesia of the infarcted myocardium during systole (Figure 5).
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Discussion |
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In this article, we have described the first use of a volumetric animal CT for 4D cardiac imaging in freely breathing rodents without the necessity of ECG or breath triggering.
The determination of both intrinsic gating signals for the cardiac and respiratory phases solely from the projection image data resulted in the ability to display the heart, visualize heart movement, and measure cardiac function under physiological conditions. An excellent agreement was achieved between ECG-derived gating signal and self-gating signal. In addition, functional parameters (ventricular volumes and ejection fraction) obtained from the intrinsic and the extrinsic data sets were not significantly different. Thus, using self-gating, the same level of fidelity than derived from extrinsic triggers was achieved. Excellent image quality, to the extent that the coronary arteries were visible in mice, was demonstrated.
Our results indicate that the self-gating may be superior to ECG-based gating for the following reasons.
Electrodeless Operation
Triggering based on ECG measurements is often difficult in rodents because of low signal amplitudes, low signal-to-noise ratio, and signal artifacts. Our results indicate that the extrinsic gating signal is noisy (demonstrating a high SD), a limitation of the extrinsic approach that often cannot be overcome by repositioning electrodes. Many techniques that are more or less successful in solving engineering problems have been proposed for managing some of the difficulties associated with ECG acquisition and subsequent R-wave detection.22 These methods, however, still require the use of ECG recording and lead systems, as well as additional setup time with each examination.
Moreover, because self-gating is based on the projection of heart movement instead of electric heart activity, unlike the ECG-based methods, no electromechanical concordance is assumed by intrinsic gating. Therefore, the gating results should be superior when there is dissociation between electric and mechanical events, such as in arrhythmia. In these cases, gating on intrinsic motion may solve the problem of detecting a noisy or aberrant signal and could allow for robust image reconstruction. It would, therefore, be interesting to use intrinsic cardiac and respiratory gating to perform 4D CT in rodent models with arrhythmia.
Improved Animal Handling
Intrinsic gating allows heart function to be measured very close to the natural state of the animal without the burden of additional preparatory time. Even real-time monitoring of the heart function as demonstrated in the stress test study is possible without additional preparatory efforts.
Theoretically, intrinsic gating has the potential to enable fetal cardiac imaging in small animals, in which an external ECG signal cannot be derived. For example, it might be possible to visualize the fetal heart and perform functional cardiac imaging in prenatal studies on congenital cardiac malformation in transgenic mice.23,24 Furthermore, gating can still be performed even when the animal is kept in a sterile container for infection control as long as the container is x-ray lucent.
Scanner Independent Operation
A key contribution of the research presented here is the simplicity of the algorithm that explicitly uses the 2D nature of the projection images in small-animal imaging. The intrinsic gating method is fully independent of the scanner hardware, and gating can be performed solely as a postprocessing step. There is no need to change any existing scanner accessories or for any synchronization between scanner and gating hardware.
For human subjects, intrinsic gating methods in multidetector CT have been successfully implemented and adapted for spiral acquisition.25,26 These algorithms, however, tend to be complex and difficult to translate into clinical routine. Furthermore, they differ significantly from those for small animals. More recent human CT scanners, with larger cone angle, permit cardiac scanning in a step-and-shoot mode to reduce the applied x-ray dose.27
Further tests are needed to determine whether the intrinsic gating scheme presented here could be adapted for use in the next generation of large cone-angle human CT scanners. Future preclinical validation studies must evaluate the ability of intrinsic gating to be adapted in terms of dose application and image quality on the recently introduced human large cone-angle CT.
The nearly perfect agreement between intrinsic and extrinsic gating signal indicates that the quality of intrinsic gating is already very close to the optimum level. Therefore, any algorithmic improvements would most likely result in minor, second-order improvements in the final image quality. Currently, the selection of the ROI is the only manual step in this algorithm. An automated method of ROI selection, which would make the process fully independent of the user, would facilitate the workflow.
The x-ray dose applied to the animal is often seen as a major limitation of microfocus CT imaging. However, taking into account previous dose measurements on mouse phantoms,28,29 the scan time, and our scan parameters, only a dose of 90 mGy was delivered to the animal. This dose stays within the limits set in previous studies5–10 with prospective or retrospective gating and cannot be expected to significantly affect the health of rodents. In general, dose usage is better in prospective methods, because all projections contribute to image reconstruction. However, this advantage holds true only for motion-compensated still imaging. For 4D series, the required number of projections may be equal for retrospective and prospective gated volume reconstruction and therefore the utilization of applied dosage.
Conclusions
This article reports on a method for intrinsic cardiac and respiratory gating that uses a flat-panel cone-beam CT scanner. This scheme enables the reconstruction of 4D image data without using any ECG capture for cardiac gating and any external monitoring for respiratory gating. The proposed algorithm is easy to implement and compatible with any existing scanner hardware, making the external gating hardware superfluous. Our experience shows that this method is robust and promises to become an important tool in the preclinical study of cardiac disease on VCT. Furthermore, we expect that intrinsic retrospective cardiac gating will be considered for experiments in the next generation of large cone-angle human CT.
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Acknowledgments |
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We thank Karin Leotta for her excellent technical assistance during data acquisition and postprocessing. Special thanks also go to Hakim Boumaza for help with mathematical analysis.
Sources of Funding
This work was supported by the transregional grant "Vascular Differentiation and Remodeling" from the German Research Foundation (TR23, DFG).
Disclosures
Dr Grasruck is an employee of Siemens Medical Systems. The other authors have no disclosures.
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Footnotes |
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Drs Dinkel and Bartling contributed equally to this work.
The online Data Supplement is available at http://circimaging.ahajournals.org/cgi/content/full/1/3/235/DC1.
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References |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Yutzey KE, Robbins J. Principles of genetic murine models for cardiac disease. Circulation. 2007; 115: 792–799.
2. Schneider JE, Wiesmann F, Lygate CA, Neubauer S. How to perform an accurate assessment of cardiac function in mice using high-resolution magnetic resonance imaging. J Cardiovasc Magn Reson. 2006; 8: 693–701.[CrossRef][Medline]
3. Dawson D, Lygate CA, Saunders J, Schneider JE, Ye X, Hulbert K, Noble JA, Neubauer S. Quantitative 3-dimensional echocardiography for accurate and rapid cardiac phenotype characterization in mice. Circulation. 2004; 110: 1632–1637.
4. Ghanem A, Röll W, Hashemi T, Dewald O, Djoufack PC, Fink KB, Schrickel J, Lewalter T, Lüderitz B, Tiemann K. Echocardiographic assessment of left ventricular mass in neonatal and adult mice: accuracy of different echocardiographic methods. Echocardiography. 2006; 23: 900–907.[CrossRef][Medline]
5. Badea CT, Fubara B, Hedlund LW, Johnson GA. 4-D micro-CT of the mouse heart. Mol Imaging. 2005; 4: 110–116.[Medline]
6. Ford NL, Nikolov HN, Norley CJ, Thornton MM, Foster PJ, Drangova M, Holdsworth DW. Prospective respiratory-gated micro-CT of free breathing rodents. Med Phys. 2005; 32: 2888–2898.[CrossRef][Medline]
7. Buliev IG, Badea CT, Kolitsi Z, Pallikarakis N. Estimation of the heart respiratory motion with applications for cone beam computed tomography imaging: a simulation study. IEEE Trans Inf Technol Biomed. 2003; 7: 404–411.[CrossRef][Medline]
8. Drangova M, Ford NL, Detombe SA, Wheatley AR, Holdsworth DW. Fast retrospectively gated quantitative four-Dimensional (4D) cardiac micro computed tomography imaging of free-breathing mice. Invest Radiol. 2007; 42: 85–94.[CrossRef][Medline]
9. Bartling SH, Stiller W, Grasruck M, Schmidt B, Peschke P, Semmler W, Kiessling F. Retrospective motion-gating in small animal CT of mice and rats. Invest Radiol. 2007; 42: 704–714.[CrossRef][Medline]
10. Bartling SH, Dinkel J, Stiller W, Grasruck M, Madisch I, Kauczor HU, Semmler W, Gupta R, Kiessling F. Intrinsic respiratory gating in small animal CT. Eur Radiol. 2008; 18: 1375–1384.[CrossRef][Medline]
11. Larson AC, White RD, Laub G, McVeigh ER, Li D, Simonetti OP. Self-gated cardiac cine MRI. Magn Reson Med. 2004; 51: 93–102.[CrossRef][Medline]
12. Hiba B, Richard N, Janier M, Croisille P. Cardiac and respiratory double self-gated cine MRI in the mouse at 7 T. Magn Reson Med. 2006; 55: 506–513.[CrossRef][Medline]
13. Gupta R, Grasruck M, Suess C, Bartling SH, Schmidt B, Stierstorfer K, Popescu S, Brady T, Flohr T. Ultra-high resolution flat-panel volume CT: Fundamental principles, design architecture, and system characterization. Eur Radiol. 2006; 16: 1191–1205.[CrossRef][Medline]
14. Patten RD, Aronovitz MJ, Deras-Mejia L, Pandian NG, Hanak GG, Smith JJ, Mendelsohn ME, Konstam MA. Ventricular remodeling in a mouse model of myocardial infarction. Am J Physiol. 1998; 274: H1812–H1820.[Medline]
15. Sebag IA, Handschumacher MD, Ichinose F, Morgan JG, Hataishi R, Rodrigues ACT, Guerrero JL, Steudel W, Raher MJ, Halpern EF, Derumeaux G, Bloch KD, Picard MH, Scherrer-Crosbie M. Quantitative assessment of regional myocardial function in mice by tissue doppler imaging: comparison with hemodynamics and sonomicrometry. Circulation. 2005; 111: 2611–2616.
16. Bartling S, Stiller W, Semmler W, Kiessling F. Small animal computed tomography imaging. Curr Med Imaging Rev. 2007; 1: 45–59.
17. Wolf I, Vetter M, Wegner I, Böttger T, Nolden M, Schöbinger M, Hastenteufel M, Kunert T, Meinzer HP. The medical imaging interaction toolkit. Med Image Anal. 2005; 9: 594–604.[CrossRef][Medline]
18. Lin L, Hedayat AS, Wu W. A unified approach for assessing agreement for continuous and categorical data. J Biopharm Stat. 2007; 17: 629–652.[CrossRef][Medline]
19. Roth DM, Swaney JS, Dalton ND, Gilpin EA, Ross J Jr. Impact of anesthesia on cardiac function during echocardiography in mice. Am J Physiol Heart Circ Physiol. 2002; 282: H2134–H2140.
20. Rottman JN, Ni G, Khoo M, Wang Z, Zhang W, Anderson ME, Madu EC. Temporal changes in ventricular function assessed echocardiographically in conscious and anesthetized mice. J Am Soc Echocardiogr. 2003; 16: 1150–1157.[CrossRef][Medline]
21. Schaefer A, Meyer GP, Brand B, Hilfiker-Kleiner D, Drexler H, Klein G. Effects of anesthesia on diastolic function in mice assessed by echocardiography. Echocardiography. 2005; 22: 665–670.[CrossRef][Medline]
22. Mitchell GF, Jeron A, Koren G. Measurement of heart rate and Q-T interval in the conscious mouse. Am J Physiol. 1998; 274: H747–H751.[Medline]
23. Leatherbury L, Yu Q, Lo CW. Noninvasive phenotypic analysis of cardiovascular structure and function in fetal mice using ultrasound. Birth Defects Res C Embryo Today. 2003; 69: 83–91.[CrossRef][Medline]
24. Weninger WJ, Mohun T. Phenotyping transgenic embryos: a rapid 3-D screening method based on episcopic fluorescence image capturing. Nat Genet. 2002; 30: 59–65.[CrossRef][Medline]
25. Kachelrieß M, Sennst DA, Maxlmoser W, Kalender WA. Kymogram detection and kymogram-correlated image reconstruction from subsecond spiral computed tomography scans of the heart. Med Phys. 2002; 29: 1489–1503.[CrossRef][Medline]
26. Ertel D, Pflederer T, Achenbach S, Kachelrieß M, Steffen P, Kalender WA. Validation of a raw data-based synchronization signal (kymogram) for phase-correlated cardiac image reconstruction. Eur Radiol. 2008; 18: 253–262.[CrossRef][Medline]
27. Kido T, Kurata A, Higashino H, Sugawara Y, Okayama H, Higaki J, Anno H, Katada K, Mori S, Tanada S, Endo M, Mochizuki T. Cardiac imaging using 256-detector row four-dimensional CT: preliminary clinical report. Radiat Med. 2007; 25: 38–44.[CrossRef][Medline]
28. Greschus S, Kiessling F, Lichy MP, Moll J, Mueller MM, Savai R, Rose F, Ruppert C, Günther A, Luecke M, Fusenig NE, Semmler W, Traupe H. Potential applications of flat-panel volumetric CT in morphologic and functional small animal imaging. Neoplasia. 2005; 7: 730–740.[CrossRef][Medline]
29. Boone JM, Velazquez O, Cherry SR. Small-animal X-ray dose from micro-CT. Mol Imaging. 2004; 3: 149–158.[CrossRef][Medline]
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