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首页医源资料库在线期刊放射学杂志2003年1月第226卷第1期

Retrospective and Prospective Electrocardiography-assisted Multi–Detector Row CT1

来源:放射学杂志
摘要:ImagingParametersforNon-ECG-assistedMulti-DetectorRowCTandProspectiveandRetrospectiveECG-assistedMulti-DetectorRowCTForECG-assistedacquisitions,thepatient’sECGwasdigitizedandcontinuouslyrecordedduringCTscanning。ProspectiveECG-assistedimagingwasperformedinaseq......

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Thoracic Aorta: Motion Artifact Reduction wit1 From the Institute of Diagnostic Radiology (J.E.R., J.K.W., D.W., B.M., P.R.H.) and Clinic of Cardiovascular Surgery (M.L.), University Hospital Zurich, Rämistrasse 100, CH-8091 Zurich, Switzerland. From the 2000 RSNA scientific assembly. Received February 19, 2001; revision requested March 26; revision received May 24; accepted June 22. 


     ABSTRACT

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ABSTRACT
INTRODUCTION
Materials and Methods
Results
Discussion
REFERENCES
 
The authors compared prospective (n = 20) and retrospective (n = 20) electrocardiography (ECG)-assisted multi–detector row computed tomography (CT) with non-ECG-assisted multi–detector row CT (n = 20) of the thoracic aorta with regard to reduction of motion-related artifacts. Image quality was rated for transverse source and sagittal oblique images of the thoracic aorta, including the aortic valve. ECG-assisted multi–detector row CT compared with non-ECG-assisted multi–detector row CT showed a significant reduction in motion artifacts for the entire thoracic aorta.

 

Index terms: Aorta, CT, 943.12915 • Computed tomography (CT), artifact • Computed tomography (CT), multi–detector row


     INTRODUCTION

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ABSTRACT
INTRODUCTION
Materials and Methods
Results
Discussion
REFERENCES
 
Computed tomographic (CT) angiography is an important imaging modality in the evaluation of the vascular system throughout the body. Single-channel spiral CT permits diagnostic imaging of various vascular diseases (1,2). Because of the three-dimensional visualization possibilities, CT angiography seems to be superior even to conventional angiography in certain vascular territories (3,4). Moreover, CT angiography compared with conventional angiography has the advantage of being a noninvasive technique, consuming fewer resources, and being more cost-efficient (5). With the recent introduction of multi–detector row spiral CT with subsecond rotation time, the temporal and spatial resolution of CT angiography has improved (2,68).

Despite these improvements, certain vascular areas are still vulnerable to motion artifacts. The thoracic aorta is known to cause many diagnostic difficulties and pitfalls in CT imaging, especially in patients suspected of having aortic dissection (912). Batra et al (13) categorized several possible pitfalls that occur during single-channel spiral CT of the thoracic aorta. Technical factors, streak artifacts, periaortic structures, aortic wall motion, aortic variations, and atherosclerotic plaques may simulate aortic dissection.

The recent introduction of prospective and retrospective electrocardiographically (ECG)-assisted imaging in combination with multi–detector row CT has created interest in cardiac and, especially, coronary artery imaging (14). Yet, to our knowledge, no study has been performed to determine the influence of ECG-assisted imaging of the thoracic aorta and its adjacent regions with regard to motion artifact reduction. The purpose of this study was to evaluate prospective and retrospective ECG-assisted multi–detector row CT of the thoracic aorta, in comparison with non-ECG-assisted multi–detector row spiral CT, with regard to reduction of motion-related artifacts.


     Materials and Methods

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ABSTRACT
INTRODUCTION
Materials and Methods
Results
Discussion
REFERENCES
 
Patient Selection
Between June and November 2000, 52 consecutive patients (22 women, 30 men; age range, 19–82 years; mean age, 60 years) with sinus rhythm were included in the study. All patients were referred to our diagnostic radiology department to rule out mediastinal disease: thoracic aortic aneurysm (n = 19), aortic dissection (n = 12), vascular involvement of mediastinal tumors (n = 6), pericardial disease (n = 3), postoperative evaluation of aortic stent-graft (n = 10), dysphagia (n = 2). The institutional review board approved the study. After informed consent was obtained from the patients, they were placed randomly into three groups. Among the three patient groups, no difference in sex and age was observed. A total of 60 multi–detector row CT acquisitions were obtained by using either a non-ECG-assisted CT protocol (n = 20) or a prospective (n = 20) or retrospective (n = 20) ECG-assisted CT protocol. Imaging was performed twice in eight patients on two different days; four of these patients underwent CT with different protocols and four patients underwent CT with the same protocol twice.

Imaging Technique
All CT imaging was performed with a multi–detector row scanner (Somatom Volume Zoom; Siemens Medical Systems, Erlangen, Germany). All examinations were performed during the patient’s inspiratory breath hold. First, a scout view of the thorax was used to plan CT data acquisition.

Second, a 20-mL bolus of iodixanol (Visipaque 320; Nycomed Amersham, Oslo, Norway) was administered intravenously at 3 mL/sec via an 18-gauge catheter placed in the cubital vein. After a delay of 10 seconds, a sequence of 10 transverse images at the level of the aortic arch was obtained, with an interval of 2 seconds between subsequent images. This sequence served to test the intravenous catheter, to practice breath hold with the patient, and to measure the time-attenuation curve at the level of the aortic arch, which permitted an individual delay time for optimal aortic enhancement. Delay times were determined by means of visually evaluating the contrast material inflow at the level of the aortic arch. The mean delay between start of injection of contrast material and start of scanning was 22 seconds ± 5 (SD).

Third, 130 mL of contrast material was injected into the cubital vein at 3 mL/sec, and the CT data set was acquired with a delay according to the previously determined transit time of the contrast material. The imaging volume extended from the proximal supraaortic vessels to 2 cm below the aortic valve.

Imaging parameters for non-ECG-assisted multi–detector row CT, prospective ECG-assisted multi–detector row CT, and retrospective ECG-assisted multi–detector row CT acquisitions are summarized in Table 1.


fig.ommitted TABLE 1. Imaging Parameters for Non-ECG-assisted Multi-Detector Row CT and Prospective and Retrospective ECG-assisted Multi-Detector Row CT

 

 
For ECG-assisted acquisitions, the patient’s ECG was digitized and continuously recorded during CT scanning. To achieve phase-consistent imaging regarding the QRS complex of the ECG signal, data within only a predefined interval of the cardiac cycle (in diastole in our study) were selected either for image reconstruction (retrospective ECG-assisted imaging) or for image acquisition (prospective ECG-assisted imaging). This interval was determined individually for each patient, depending on the recorded ECG. For prospective ECG-assisted scanning, the time gate of interest was defined as a relative delay time after the R wave of the ECG signal as a given percentage of the R-R interval. For retrospective ECG-assisted scanning, a method of fixed interval prior to the onset of the next R interval, an absolute-reverse phase method, was used as described elsewhere (14).

The differences in the ECG-assisted methods are depicted in Figure 1. Prospective ECG-assisted imaging was performed in a sequential mode with a collimation of 4 x 2.5 mm. Retrospective ECG-assisted, as well as non-ECG-assisted, multi–detector row CT was performed by using continuous spiral data acquisition with 4 x 1-mm collimation (14). By using a computer program (WINDOSE, version 2.1a; Scanditronix-Wellhöfer Dosimetrie, Schwarzenbruck, Germany), the effective irradiation dose of the contrast material–enhanced multi–detector row CT was computed for a craniocaudal range of 15 cm as follows (male population): prospective ECG-assisted multi–detector row CT, 3.65 mSv; retrospective ECG-assisted multi–detector row CT, 8.85 mSv; non-ECG-assisted multi–detector row CT, 4.50 mSv.


fig.ommitted Figure 1a. (a) Schematic shows prospective ECG-assisted imaging protocol. Four sequential images are acquired every second heartbeat at the same time in relationship with a fixed delay after the QRS complex of the ECG signal. After the table feed interval, another four sections (slice 1, 2, 3, and 4) are acquired exactly the same way from the next area just adjacent. (b) Schematic shows retrospective ECG-assisted imaging protocol. After acquisition of a spiral data set, data for image reconstruction are selected with a certain phase relation to the R-R interval of the ECG signal. Stacks of four transverse sections (slice 1, 2, 3, and 4) are selected in relationship with a fixed time prior to the onset of the next R wave of the ECG signal. By using a 180° interpolation algorithm with a given rotation time of 500 msec, a temporal resolution of 250 msec is achieved.

 

 

fig.ommitted Figure 1b. (a) Schematic shows prospective ECG-assisted imaging protocol. Four sequential images are acquired every second heartbeat at the same time in relationship with a fixed delay after the QRS complex of the ECG signal. After the table feed interval, another four sections (slice 1, 2, 3, and 4) are acquired exactly the same way from the next area just adjacent. (b) Schematic shows retrospective ECG-assisted imaging protocol. After acquisition of a spiral data set, data for image reconstruction are selected with a certain phase relation to the R-R interval of the ECG signal. Stacks of four transverse sections (slice 1, 2, 3, and 4) are selected in relationship with a fixed time prior to the onset of the next R wave of the ECG signal. By using a 180° interpolation algorithm with a given rotation time of 500 msec, a temporal resolution of 250 msec is achieved.

 

 
All patients were able to hold their breath during the CT data acquisition, with a scanning time of 35–40 seconds. The heartbeat rates ranged from 60 to 102 beats per minute during image acquisition.

Image Analysis
Images were analyzed by means of consensus reading by two experienced radiologists (P.R.H., D.W.) at separate workstations (Magic View; Siemens Medical Systems). Readout was based on the transverse source images and sagittal oblique reformation images. Both readers were blinded to the acquisition parameters.

Motion artifacts of the thoracic aorta were rated on transverse source images at the level of the origin of the left coronary artery and the right pulmonary artery, as well as on sagittal oblique reformation images at the level of the ascending aorta, aortic arch, supraaortic vessels, and descending aorta. In addition, the aortic valve was evaluated on both transverse source images and sagittal oblique reformation images (Fig 2).


fig.ommitted Figure 2a. Demonstration of different levels of the thoracic aorta and the aortic valve, which were rated for motion artifacts on (a) transverse source images and (b) sagittal oblique reformation images from the prospective ECG-assisted data set. Arrows indicate the following: 1, left coronary artery; 2, right pulmonary artery; 3, ascending aorta; 4, supraaortic vessels; 5, aortic arch; 6, descending aorta; 7, aortic valve.

 

 

fig.ommitted Figure 2b. Demonstration of different levels of the thoracic aorta and the aortic valve, which were rated for motion artifacts on (a) transverse source images and (b) sagittal oblique reformation images from the prospective ECG-assisted data set. Arrows indicate the following: 1, left coronary artery; 2, right pulmonary artery; 3, ascending aorta; 4, supraaortic vessels; 5, aortic arch; 6, descending aorta; 7, aortic valve.

 

 
Each radiologist evaluated the image quality in terms of motion artifacts of the thoracic aorta on a four-point scale: 1, no motion artifacts; 2, minimal motion artifacts; 3, moderate motion artifacts, still diagnostic; 4, severe motion artifacts, not diagnostic. No motion artifacts was assigned when the image was virtually free from image degradation. Moderate motion artifacts meant a virtually thickened aortic wall on transverse source images, as well as the presence of apparent step artifacts on the sagittal oblique reformation images. This present image degradation still did not markedly preclude interpretation. Severe motion artifacts did not allow a sufficient diagnostic interpretation. Minimal motion artifacts was assigned according to the radiologist’s subjective judgment between no and moderate motion artifacts. In addition, the aortic valve was rated on a four-point scale as follows: 1, no motion artifacts—visibility of all parts of the aortic valve, including the aortic orifice, the leaflets, and the aortic valve anulus; 2, minimal motion artifacts—visibility of a least two anatomic details of the aortic valve; 3, moderate motion artifacts—visibility of at least one anatomic detail; and 4, severe motion artifacts—no anatomic detail visible.

Descriptive statistics were calculated concerning motion artifacts for all locations on transverse source images and sagittal oblique reformation images and were also summarized for each imaging method. All data were analyzed by using the Kruskal-Wallis test. For all variables, the P value with this test was less than .001, so the three imaging protocols were subsequently compared by means of post hoc analysis with the Mann-Whitney U test. P values calculated according to the Monte Carlo method were used (SPSS for Windows, Version 10; SPSS, Chicago, Ill). After Bonferroni correction, P values less than .017 were considered to represent a significant difference.


     Results

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ABSTRACT
INTRODUCTION
Materials and Methods
Results
Discussion
REFERENCES
 
Prospective and retrospective ECG assistance was successful in all cases. Table 2 shows all nominal values of motion artifact rating for all acquisition protocols at all levels evaluated. A summary of motion artifacts for all evaluated locations revealed significantly more motion artifacts (P < .001) on the images acquired with non-ECG-assisted multi–detector row CT (median, 3.05) compared with images acquired with prospective (median, 1.2) or retrospective (median, 1.5) ECG-assisted multi–detector row CT (Fig 3). Compared with the non-ECG-assisted data acquisition, ECG-assisted imaging, independent of which method was used, depicted significantly fewer motion artifacts for each location. For seven of the eight levels evaluated, no significant difference was observed between the two ECG-assisted CT protocols (Fig 4). Only the ascending aorta on transverse source images at the level of the origin of the left coronary artery showed a significant difference between the ECG-assisted protocols (P = .006).


fig.ommitted TABLE 2. Nominal Values of Motion Artifact Rating for All Acquisition Protocols at All Levels Evaluated

 

 

fig.ommitted Figure 3. Box plots show the median (horizontal line in center of box) of mean values summarized over all locations. The box plot range is the 25th to the 75th percentile, and the minimum and maximum values are indicated by points (). In a summary of motion artifacts for all locations evaluated, prospective (gray box) and retrospective (black box) ECG-assisted multi-detector row CT images compared with the non-ECG-assisted (white box) multi-detector row CT images show significantly fewer motion artifacts (P < .001).

 

 

fig.ommitted Figure 4. Bar graph shows the mean values for motion artifacts among the three acquisitions for each location plotted in order of the distance to the heart. Compared with the non-ECG-assisted imaging method (white bars), both ECG-assisted imaging methods show significantly fewer motion artifacts for each location (P < .001). The greater the distance to the heart, the less important are the pulsation-related artifacts of the thoracic aorta on both transverse and sagittal oblique reformation images. The biggest difference is found at the level of the aortic valve; the smallest difference, still significant, is at the level of the descending aorta. Ao = aorta, asc = ascending, ax = transverse images, desc = descending, LCA = left coronary artery, obl = sagittal oblique reformation images, PA = pulmonary artery. Gray bars = prospective ECG-assisted multi-detector row CT, black bars = retrospective ECG-assisted multi-detector row CT.

 

 
The greatest difference in motion artifacts among the three acquisition protocols was seen at the level of the aortic valve. The aortic valveitself was clearly visible on only images acquired with retrospective or prospective ECG assistance (Fig 5).


fig.ommitted Figure 5a. (a-d) Sagittal oblique reformation images obtained in two male patients (aged 54 and 62 years) after placement of an endovascular stent-graft (arrow in b and d) into the thoracic aorta. (a, b) Non-ECG-assisted multi-detector row CT images show that step artifacts are clearly seen in the thoracic aorta. (c, d) Retrospective ECG-assisted multi-detector row CT images, in contrast, show that the motion artifacts are almost completely eliminated. The difference in motion artifact reduction is best demonstrated at the level of the ascending aorta (double-headed arrow in a and c). In addition, the aortic valve (arrowhead in a and c) is clearly visible on only the ECG-assisted image.

 

 

fig.ommitted Figure 5b. (a-d) Sagittal oblique reformation images obtained in two male patients (aged 54 and 62 years) after placement of an endovascular stent-graft (arrow in b and d) into the thoracic aorta. (a, b) Non-ECG-assisted multi-detector row CT images show that step artifacts are clearly seen in the thoracic aorta. (c, d) Retrospective ECG-assisted multi-detector row CT images, in contrast, show that the motion artifacts are almost completely eliminated. The difference in motion artifact reduction is best demonstrated at the level of the ascending aorta (double-headed arrow in a and c). In addition, the aortic valve (arrowhead in a and c) is clearly visible on only the ECG-assisted image.

 

 

fig.ommitted Figure 5c. (a-d) Sagittal oblique reformation images obtained in two male patients (aged 54 and 62 years) after placement of an endovascular stent-graft (arrow in b and d) into the thoracic aorta. (a, b) Non-ECG-assisted multi-detector row CT images show that step artifacts are clearly seen in the thoracic aorta. (c, d) Retrospective ECG-assisted multi-detector row CT images, in contrast, show that the motion artifacts are almost completely eliminated. The difference in motion artifact reduction is best demonstrated at the level of the ascending aorta (double-headed arrow in a and c). In addition, the aortic valve (arrowhead in a and c) is clearly visible on only the ECG-assisted image.

 

 

fig.ommitted Figure 5d. (a-d) Sagittal oblique reformation images obtained in two male patients (aged 54 and 62 years) after placement of an endovascular stent-graft (arrow in b and d) into the thoracic aorta. (a, b) Non-ECG-assisted multi-detector row CT images show that step artifacts are clearly seen in the thoracic aorta. (c, d) Retrospective ECG-assisted multi-detector row CT images, in contrast, show that the motion artifacts are almost completely eliminated. The difference in motion artifact reduction is best demonstrated at the level of the ascending aorta (double-headed arrow in a and c). In addition, the aortic valve (arrowhead in a and c) is clearly visible on only the ECG-assisted image.

 

 
A similar distinct reduction of motion-related artifacts was observed adjacent to the aortic valve, including the ascending aorta. On sagittal oblique images of the ascending aorta, step artifacts were almost completely eliminated with ECG-assisted multi–detector row CT in all cases (Fig 5).

The greater the distance to the heart, the lesser the influence of motion artifacts on imaging, and consequently the smaller the benefit of the ECG assistance. However, even at the level of the descending aorta, a significant advantage (P < .001) from ECG assistance was observed (Fig 4). The aortic arch seems to be less corrupted by motion artifacts than are the supraaortic vessels. Nevertheless, the reduction of motion artifact at the level of the aortic arch and supraaortic vessels with ECG-assisted multi–detector row CT was also significant (Fig 6).


fig.ommitted
 
Figure 6a. Transverse source images obtained in a 40-year-old male patient with type A dissection with an intraluminal flap at the level of the aortic arch. (a) Non-ECG-assisted multi-detector row CT image obtained at the initial examination shows motion artifacts that hamper visualization of the flap. The flap seems to be divided into two parts (arrows). (b) Prospective ECG-assisted image obtained after surgical replacement of the ascending aorta shows the intraluminal flap clearly visible as a single structure (arrows) without motion artifacts. This reduction of motion artifacts is caused possibly by a different hemodynamic situation after surgical intervention and definitely by ECG assistance during data acquisition.

 

 

fig.ommitted Figure 6b. Transverse source images obtained in a 40-year-old male patient with type A dissection with an intraluminal flap at the level of the aortic arch. (a) Non-ECG-assisted multi-detector row CT image obtained at the initial examination shows motion artifacts that hamper visualization of the flap. The flap seems to be divided into two parts (arrows). (b) Prospective ECG-assisted image obtained after surgical replacement of the ascending aorta shows the intraluminal flap clearly visible as a single structure (arrows) without motion artifacts. This reduction of motion artifacts is caused possibly by a different hemodynamic situation after surgical intervention and definitely by ECG assistance during data acquisition.

 

 

     Discussion

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ABSTRACT
INTRODUCTION
Materials and Methods
Results
Discussion
REFERENCES
 
Motion artifacts that cause diagnostic difficulties on CT images may occur in various parts of the body. Cardiac motion artifacts often hamper image quality of the thoracic aorta. Pseudodissection of the thoracic aorta is a well-known pitfall, which has been described in previous studies (912). This artifact occurs predominantly at the left anterior and right posterior aortic circumference. A summation effect of the pendular and the circular aortic motion produces a curvilinear separation of the aortic lumen, which simulates a dissection (9,10,12,13). However, characteristics of these artifacts are interindividually different. The recent introduction of multi–detector row spiral CT to clinical practice has brought advantages such as a high temporal and spatial resolution, a large volume coverage within a single breath hold, and the possibility of high-quality three-dimensional reformation images (68). For cardiac imaging, acquisitions with few motion artifacts have become possible in combination with ECG assistance (14).

In this study, significant motion artifact reduction for the thoracic aorta was achieved with retrospective and prospective ECG-assisted multi–detector row CT protocols. Anatomic structures adjacent to the heart—the aortic valve and ascending aorta—exhibited an especially obvious improvement in image quality. This improvement was less evident in more distal parts of the thoracic aorta, such as the aortic arch and descending aorta, which are already less affected by motion artifacts. The difference in this area was, however, still significant. The reason for the slightly increased difference between non-ECG-assisted and both ECG-assisted multi–detector row CT acquisitions at the supraaortic vessels compared with the aortic arch is possibly because the aortic arch is anatomically bigger than the supraaortic vessels and therefore less vulnerable to motion artifacts.

Considering that both ECG-assisted methods are fundamentally two different means of data acquisition (sequential vs spiral CT), no significant difference concerning reduction of motion artifacts of the thoracic aorta between the prospective or retrospective ECG-assisted multi–detector row CT protocol was observed, except at the level of the ascending aorta on transverse source images. With non-ECG-assisted multi–detector row spiral CT, motion artifacts appeared in a well-known manner at the level of the ascending aorta, such as step artifacts on sagittal oblique reformation images.

This study had some limitations. A technical limitation was that the sequential mode is vulnerable to so-called step artifacts. However, this was not a problem in our study. The prospective (sequential) ECG-assisted data sets were not rated differently than were the retrospective (spiral) ECG-assisted data sets. The prospective mode needs a rather rhythmic heartbeat; otherwise this method runs the risk of losing the ECG signal during acquisition. Concerning this limitation, authors of a recently published study (14) describe the retrospective ECG-assisted multi–detector row CT protocol as the best method in patients with moderate arrhythmic heart rates and extra systoles. In prospective ECG-assisted multi–detector row sequential CT, because only every second heartbeat triggers data acquisition, an intervening interval remains necessary for table feed. Therefore, the collimation of 2.50 mm per section was necessary to achieve a reasonable imaging volume that covered the region of interest in this study.

In seven of eight levels evaluated, no significant difference was observed between the ECG-assisted methods. Only the ascending aorta on transverse source images at the level of the origin of the left coronary artery showed a significant difference between the ECG-assisted protocols. This significant difference could mean that the thicker collimation with prospective ECG-assisted multi–detector row CT may mask some motion artifacts, which is an interesting subject for further investigation.

Although the patients were placed randomly into three groups and the images were read by means of consensus with both readers blinded to the acquisition parameters, the difference between the non-ECG-assisted and both ECG-assisted image sets was so pronounced that the readers were not really blinded. While eight patients were randomly placed in groups twice, which introduced a certain statistical dependency among the three groups, the statistical results did not change after data for these patients were eliminated and the statistical evaluation was recalculated. Furthermore, the patients in our study did not include cases of substantial arrhythmia or tachycardia. A correlation between the present ECG technique and the image quality was not performed.

Even with these limitations, our results showed a significant reduction of motion-related artifacts for the entire thoracic aorta with ECG-assisted multi–detector row CT. The maximum reduction was calculated at the level of the part of the heart that physiologically moves most—the aortic valve—followed by the ascending aorta. With non-ECG-assisted CT, motion artifacts at the level of the ascending aorta can simulate a type A dissection. Therefore, the possibility of motion-free visualization of the entire thoracic aorta with multi–detector row CT in combination with ECG assistance provides significant improvement to the diagnostic value of CT angiography and directly competes in our institution with transesophageal echocardiography for the evaluation of type A dissection (9,10). In conclusion, ECG-assisted multi–detector row CT compared with non-ECG-assisted multi–detector row CT shows a significant reduction of motion artifacts for the entire thoracic aorta.

 

     ACKNOWLEDGMENTS
 
The authors thank Burkhardt Seifert, PhD, Department of Biostatistics, University Hospital Zurich, for statistical assistance and Ninoslav Teodorovic, RT, Institute of Diagnostic Radiology, University Hospital Zurich, for his excellent image preparation and display.


     REFERENCES

Top
ABSTRACT
INTRODUCTION
Materials and Methods
Results
Discussion
REFERENCES
 

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作者: Justus E. Roos MD Jürgen K. Willmann MD Dominik 2007-5-12
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