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Aortoiliac and Renal Arteries: Prospective Intraindividual Comparison of Contrast-enhanced Three-dimensional MR Angiography and Multi–Detector Row CT Angiography¹

¹ From the Institute of Diagnostic Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (J.K.W., S.W., T.P., J.E.R., P.R.H., B.M., D.W.); and Department of Biostatistics, University of Zurich, Switzerland (B.S.). From the 2002 RSNA scientific assembly. Received February 1, 2002; revision requested April 1; revision received June 11; accepted October 4. Address correspondence to D.W. (e-mail: dominik.weishaupt@dmr.usz.ch).

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
PURPOSE: To compare contrast material–enhanced three-dimensional (3D) magnetic resonance (MR) angiography and multi–detector row computed tomographic (CT) angiography in the same patients for assessment of the aortoiliac and renal arteries, with digital subtraction angiography (DSA) as the standard of reference.

MATERIALS AND METHODS: DSA, 3D MR angiography, and multi–detector row CT angiography were performed in 46 consecutive patients. A total of 769 arterial segments were analyzed for arterial stenosis by using a four-point grading system. Aneurysmal changes were noted. The time required for performing 3D reconstructions and image analysis of both MR and CT data sets was measured. Patient acceptance for each modality was assessed with a visual analogue scale. Statistical analysis of data was performed.

RESULTS: Sensitivity of MR angiography for detection of hemodynamically significant arterial stenosis was 92% for reader 1 and 93% for reader 2, and specificity was 100% and 99%, respectively. Sensitivity of CT angiography was 91% for reader 1 and 92% for reader 2, and specificity was 99% and 99%, respectively. Differences between the two modalities were not significant. Interobserver and intermodality agreement was excellent ( = 0.88–0.90). The time for performance of 3D reconstruction and image analysis of CT data sets was significantly longer than that for MR data sets (P < .001). Patient acceptance was best for CT angiography (P = .016).

CONCLUSION: There is no statistically significant difference between 3D MR angiography and multi–detector row CT angiography in the detection of hemodynamically significant arterial stenosis of the aortoiliac and renal arteries.

© RSNA, 2003

Index terms: Aorta, stenosis or obstruction, 981.721 • Arteries, iliac, 98.721 • Computed tomography (CT), angiography, 961.12916, 98.12916 • Computed tomography (CT), multi–detector row, 961.12915, 98.12915 • Magnetic resonance (MR), three-dimensional, 961.12949, 98.12949 • Magnetic resonance (MR), vascular studies, 961.12942, 98.12942 • Renal arteries, stenosis or obstruction, 961.721

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Both magnetic resonance (MR) angiography and computed tomographic (CT) angiography are increasingly used for noninvasive imaging of virtually the entire vascular territory, including the aortoiliac and renal arteries. Contrast material–enhanced three-dimensional (3D) MR angiography has become a widely accepted technique for depicting vascular disease that affects the aorta and its abdominal and pelvic branches (1–8). The main advantages of MR angiography include the lack of ionizing radiation and the absence of a contrast agent that is potentially toxic to the kidneys. Disadvantages include a tendency to overestimate stenosis because of signal intensity loss in tightly stenotic lesions and difficulty in depicting small vessels (8).

Results of several studies have demonstrated successful application of CT angiography by using single–detector row helical CT for evaluation of patients with vascular disease of the aortoiliac and renal arteries (9–14). The recent introduction of multi–detector row CT scanners has promoted the use of CT angiography for assessing the vascular system. Multi–detector row CT has substantially improved CT angiography by offering shorter acquisition time, increased volume coverage, lower dose of contrast medium, and improved spatial resolution for assessing smaller arterial branches (15,16). Aside from the radiation issue, which we agree is of limited importance in older patients with atherosclerotic disease, the main disadvantages of multi–detector row CT angiography include the use of iodinated contrast medium with its possible side effects, the time-consuming 3D reconstruction techniques, and the difficulty in assessing arterial luminal stenosis in the setting of hyperattenuating eccentrically located vessel wall calcifications (11,17).

Both MR angiography and multi–detector row CT angiography are potent tools. In patients without contraindications for either modality, use of each is based in most centers on equipment availability, individual preference of the radiologist or referring physician, and patient acceptance (18). To compare imaging modalities directly, it is necessary to perform the examinations that are being evaluated in the same patient cohort. Apart from a comparison of MR angiography and single–detector row helical CT angiography in the evaluation of renal arteries in living renal donors and abdominal aortic aneurysms before stent-graft placement (19–21), there has been no published article, to our knowledge, in which contrast-enhanced MR angiography has been compared with multi–detector row CT angiography for the evaluation of the aortoiliac and renal arteries in the same patient.

The purpose of our study, therefore, was to compare contrast-enhanced 3D MR angiography and multi–detector row CT angiography in the same patients for assessment of the aortoiliac and renal arteries, with digital subtraction angiography (DSA) as the standard of reference.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Patients
During a 12-month period, 46 consecutive patients (39 men, seven women; mean age, 68 years; age range, 50–82 years) who underwent elective DSA of the aortoiliac or renal arteries for clinical indications were prospectively included in this study. Clinical indications for DSA were symptomatic aortoiliac occlusive disease in 39 patients and preoperative assessment of aortoiliac aneurysm in four patients. All 39 patients with suspected arterial occlusive disease suffered from intermittent claudication. No patient suffered from rest pain. Three additional patients were referred for DSA with suspicion for renal arterial hypertension. If a transluminal therapeutic procedure was considered feasible on the basis of DSA findings, the patient was scheduled for a second session.

Exclusion criteria for participation in the study were a history of renal insufficiency, adverse reactions to iodinated or paramagnetic contrast agents, or contraindications for MR imaging (eg, pacemaker or claustrophobia). During the study period, none of the 46 patients were excluded from the study. The study was approved by the hospital institutional review board, and informed consent was obtained from all patients.

All patients underwent DSA, MR angiography, and CT angiography within 1 week. DSA was performed first, followed by MR angiography before CT angiography (23 patients) or CT angiography before MR angiography (23 patients). The mean delay between DSA and MR angiography was 4 days (range, 1–6 days) and between DSA and CT angiography, 3 days (range, 1–5 days). The mean delay between MR and CT angiography was 3 days (range, 2–5 days).

DSA Procedure
Intraarterial DSA was performed transfemorally in all 46 patients with a 4-F pigtail catheter (AngiOptic; Angiodynamics, Queensbury, NY) by using one of two units (Integris V3000 or Integris V5000; Philips Medical Systems, Best, the Netherlands). For evaluation of the abdominal aorta and renal arteries, the catheter tip was positioned between the 12th thoracic and first lumbar vertebrae, and 30 mL of a nonionic iodinated contrast material (300 mg of iodine per milliliter of iopromidum, Ultravist 300; Schering, Berlin, Germany) was injected. The catheter tip was subsequently positioned above the aortic bifurcation for DSA of the pelvic arteries with 20 mL of contrast material. In all patients, additional oblique projections were obtained for evaluation of the aortoiliac arteries. In particular, the arterial segments of both renal arteries were examined by using additional 15° left and right anterior oblique projections. Lateral projections were performed only if mandatory. No prior conscious sedation was performed in any patient. DSA was performed in all patients without any complications.

Since our angiography suite is not yet connected to the picture archiving and communication system, or PACS, images from DSA were printed as hard copies with customized window width and level settings to allow clear delineation of the enhanced lumen.

MR Angiography
Contrast-enhanced 3D MR angiography was performed in all 46 patients with a 1.5-T imager (Signa CV/i; GE Medical Systems, Milwaukee, Wis), which was equipped with a fast three-axis gradient system characterized by a peak gradient amplitude of 40 mT/m and a slew rate of 150 mT/m/msec. An anteroposterior phased-array surface coil (torso array coil) was used for signal reception. The coil was placed around the patient to cover the vasculature from the proximal abdominal aorta to the level of the inguinal ligaments, including the renal and pelvic arteries.

On the basis of a two-dimensional gradient-echo localizing sequence (repetition time msec/echo time msec, 150/1; flip angle, 60°), 3D MR angiography was performed in the coronal plane by using a 3D Fourier transform gradient-recalled-echo sequence with spoiling gradients (22). The sequence used the following parameters: 5/1; flip angle, 30°; sampling bandwidth, ±62.5 kHz. Section thickness was adapted individually to ensure coverage of the entire vascular territory (9–16 cm) and ranged between 2.4 and 3.0 mm. The combination of a 256 x 192 matrix with a 32–36 x 32–38-cm field of view resulted in voxel dimensions of 1.3–1.4 x 1.7–2.0 x 2.4–3.0 mm. Zero interpolation was performed with adding of extra zeros to the k space data in all three planes before Fourier transform to improve image quality. The number of sections after zero interpolation ranged from 80 to 110.

Before collecting the 3D data set, the transit time of a 2-mL test bolus of gadopentetate dimeglumine (Magnevist; Schering) between the injection site (antecubital fossa) and the abdominal aorta was determined by using a multiphase sagittal single-section gradient-recalled-echo sequence (5/1; flip angle, 60°). The test bolus was administered at a constant flow rate of 2 mL/sec by using an automated injector (MR Spectris; Medrad, Pittsburgh, Pa) and was followed by a 15-mL saline flush administered at the same flow rate. The mean delay time of the contrast material was 22 seconds (range, 19–28 seconds).

Patients were instructed to hyperventilate before MR angiography and to hold their breath during imaging for a mean duration of 28 seconds (range, 24–33 seconds). Gadopentetate dimeglumine was administered at a dose of 0.3 mmol per kilogram of body weight (23) at a flow rate of 2 mL/sec, followed by a 15-mL saline flush at the same flow rate. MR angiography was performed in all 46 patients without any complications, and none of the studies had to be repeated because of technical problems.

The intravenous catheter was placed while the patient was in the MR suite. The examination time, defined as the time from patient entry into the MR suite until the source data were available for 3D reconstruction, was recorded for each patient by one radiologist (J.K.W.).

Multi–Detector Row CT Angiography
All 46 patients were examined with a SOMATOM Volume Zoom multi–detector row CT scanner (Siemens, Forchheim, Germany). After obtaining an initial scout image (120 kV, 100 mAs), the scanning range was planned to encompass the aortoiliac vascular system from the proximal abdominal aorta to the level of the inguinal ligaments (mean coverage, 35 cm; range, 32–38 cm).

For optimal intraluminal contrast enhancement, the delay time between start of contrast material administration and start of scanning was obtained for each patient individually by using a bolus-tracking technique (CARE-Bolus, Volume Zoom Navigator; Siemens). For this purpose, a single nonenhanced low-dose scan (20 mAs) at the level of the proximal abdominal aorta was obtained first. On the basis of this transverse image, a region of interest with an area of 10–15 mm² was set in the lumen of the proximal abdominal aorta by one radiologist (J.K.W.). This region of interest served as a reference for the following dynamic measurements of contrast enhancement. Subsequently, a nonionic iodinated contrast medium (300 mg of iodine per milliliter of iopromidum) was administered via a 20–22-gauge needle that was placed into a superficial vein located in the antecubital fossa. The volume of contrast medium (mean, 130 mL; range, 120–140 mL) was subsequently adjusted for the scanning length of each patient to establish a bolus duration that was equivalent to the scanning duration (15).

The contrast medium was administered with an automated injector (Ulrich Medical, Ulm-Jungingen, Germany) at a flow rate of 3 mL/sec (16). The contrast material bolus was followed by 30 mL of saline administered at the same flow rate. At 10 seconds after the start of contrast material administration, repetitive low-dose monitoring scans (120 kV, 20 mAs, 0.5-second scanning time, 1-second interscan delay) were obtained. After reaching the preset contrast enhancement level of 100 HU (mean number of repetitive scans, 10), the multi–detector row CT scan was initiated automatically 3 seconds later. During these 3 seconds, a breath-hold signal for the patient was given. Data acquisition was performed craniocaudally with a nominal section thickness of 1 mm, a table feed of 6 mm per rotation, and a 0.5-second gantry rotation period. These parameters resulted in a pitch of 6, which is equivalent to a pitch of 1.5 with conventional CT systems. The x-ray tube voltage setting was 120 kV, and the current varied between 200 and 280 mA, depending on patient size and the heat limitations of the tube. All scanning was performed with breath holding in inspiration (mean, 29 seconds; range, 27–32 seconds).

Transverse sections were reconstructed on a workstation (Volume Zoom Navigator; Siemens) with a section width of 1.25 mm at an interval of 0.6 mm (0.65-mm overlap), resulting in a mean of 583 transverse images (range, 531–632 images). The reconstruction field of view varied between 32 and 34 cm, depending on patient size. This field of view, combined with a matrix size of 512 x 512 and a section width of 1.25 mm, resulted in voxel dimensions of 0.6–0.7 x 0.6–0.7 x 1.25 mm. Multi–detector row CT angiography was performed in all 46 patients without any complications, and none of the studies had to be repeated because of technical problems.

The intravenous catheter was placed while the patient was in the CT suite. The examination time, defined as the time from patient entry into the CT suite until the source data were available for 3D reconstruction, was recorded for each patient by one radiologist (J.K.W.).

Assessment of Patient Acceptance
After the three examinations, each patient was asked to give a subjective score of discomfort with each of the three imaging modalities. A visual analogue scale was used, which was presented as a line of defined length (100 mm) with anchors on either end. The patients were instructed by one radiologist (J.K.W.) to grade their subjective impression of discomfort in all three examinations by placing a mark between the two anchors without being told about the precise distance between them. The left anchor (0 mm) represented "no discomfort, excellently tolerated," and the right anchor (100 mm) represented "very uncomfortable, hardly tolerable." The distance between the left anchor and the patient’s mark was measured, and patient acceptance for each modality was expressed in millimeters (24). After completing the discomfort rating with the visual analogue scale, the patients were asked to describe the factor that provided the most discomfort during all three procedures with the following possibilities in a prepared questionnaire: confinement, keeping still, noise, puncture of a vessel, application of a pressure bandage, nothing, or other.

3D Reconstruction
All data from MR and CT angiography were transferred to a dedicated workstation (Advantage Windows 4.0; GE Medical Systems) with commercially available software that allows generation of different reconstructions, including maximum intensity projections (MIPs) and volume-rendered images.

One radiologist (S.W.) experienced in 3D reconstruction techniques performed all standardized reconstructions, including MIPs and volume-rendered images of all MR and CT data sets in all patients. This radiologist was not involved in the following image analysis and was blinded to patient data and DSA results. The radiologist was only aware of the fact that the patients were examined for evaluation of occlusive arterial disease, renal arterial hypertension, or preoperative assessment of an aortoiliac aneurysm. To minimize any recall bias, reconstructions of MR data were created immediately, and after a delay of 4 weeks, reconstructions of CT data sets were created. All reconstructions of either MR or CT data sets were performed in random order.

For generation of both MIPs and volume-rendered images of MR angiographic data, volumes of interest were selected manually from the stack of coronal source images to include only the aortoiliac and renal arteries. Prior to creating MIPs and volume-rendered images from CT data sets, segmentation of obscuring bone structures was performed as follows: In a first step, a bone model was created on the basis of the CT data set. A mean attenuation threshold level of 160 HU was applied to remove most of the nonosseous structures and small branches of the great vessels with Hounsfield unit values less than this threshold (13). Since values of the great vessels were higher than 160 HU in all patients, supplemental manual cutting (region-of-interest drawing and "scalpel cuts") and region growing were performed to remove all vessels from the bone model (25). In a second step, the resultant bone model was subtracted from the intact CT data set to obtain a CT data set without bone structures. After segmentation, both the contrast-enhanced vascular lumen and the vascular wall calcifications were displayed on multi–detector row CT images.

Both MIPs and volume-rendered images of MR and CT data sets were generated by using the commercially available software installed on the workstation (Advantage Windows 4.0; GE Medical Systems). This software automatically creates MIPs by casting imaginary rays along a predetermined projection through the volumetric data set and encoding the maximum value encountered by each ray (26). For volume-rendered images, the color and opacity of a pixel in the image are computed as a weighted sum of the color and opacity of the voxels along a line through the volume (27). This is made possible by using a percentage classification transfer function, which was established individually for the data set of each patient to maximize contrast material–filled vascular structures while eliminating partially enhancing surrounding tissue. The lower threshold of the low-to-high opacity curve was subjectively adjusted to represent the signal intensity and attenuation of the vasculature.

For each patient, 36 MIPs and 36 volume-rendered images from both MR and CT angiography were created perpendicular to the superoinferior axis, covering 360° of rotation in 10° increments. Time (in minutes) per patient for generation of these standardized MIPs and volume-rendered images was noted for both MR and CT angiographic data sets. All volume-rendered images and MIPs were stored on the hard-disk memory of the workstation for subsequent image analysis.

Image Analysis
DSA was interpreted on hard copies by two vascular radiologists (T.P., B.M.). Interpretation disagreements were resolved by means of consensus review. Both radiologists were blinded to the MR, CT, and clinical data and were not involved in the further course of the study. DSA served as the standard of reference.

MR and CT angiograms were interpreted independently by two radiologists (reader 1 [P.R.H.] and reader 2 [D.W.]). For MR angiography, reader 1 had 5 years of experience, and reader 2 had 4 years of experience. For multi–detector row CT angiography, both readers had 2 years of experience. Both readers were blinded to the results of DSA. Separate image reading sessions were organized for both readers by the study coordinator, who attended all reading sessions. Reader 1 reviewed all MR images in random order, and 4 weeks later, assessed the CT images in random order. Reader 2 assessed the CT images in random order, and 4 weeks later, reviewed all MR images in random order.

Data interpretation for both MR and CT angiography was performed on an interactive workstation (Advantage Windows 4.0; GE Medical Systems). The reconstructed coronal MR and transverse CT images (source data), along with the standardized MIPs and volume-rendered images (as created by the radiologist experienced in 3D reconstruction), were available for both readers on the workstation. For image analysis of the standardized MIPs, volume-rendered images, and source data, use of a cine mode allowed rapid interactive interpretation on the workstation. Interactive reformatting of both MR and CT source data was also made available on the workstation. Interactive reformatting included interactive viewing of the source images and interactive generation of reconstructions in other planes (including transverse, coronal, sagittal, and curved reconstructions) by the readers themselves. For image interpretation, the readers were instructed to use only the prepared standardized MIPs and volume-rendered images of MR and CT data in a first step and, if necessary, to use the source data for interactive reformatting in a second step. Both readers were allowed to individually adjust window centers and level settings of the MR and CT images for image analysis. If arterial wall calcifications were present at CT, the readers were asked to use a standard bone window setting (window width, 2,000 HU; center level, 500 HU) for image analysis to minimize "blooming" of arterial wall calcifications.

For analysis purposes, the arterial vascular system was divided into 16 segments: the suprarenal and infrarenal aorta; the renal arteries, divided into proximal, middle, and distal thirds as seen from the aortic origin to the renal hilum; the common iliac arteries; the external iliac arteries, divided into a proximal and distal portion; and the internal iliac arteries. When accessory renal arteries were present, these arteries were also divided into proximal, middle, and distal thirds. Each segment was analyzed with regard to image quality (diagnostic vs nondiagnostic) and the presence of arterial stenosis and aneurysm. Image quality of an arterial segment was rated to be diagnostic if all clinically relevant diagnostic information could be obtained with good differentiation of arterial vasculature from background tissue. Image quality was considered nondiagnostic if diagnostic information could not be derived because of blurring of the arterial segment or inadequate vessel enhancement.

The presence of arterial stenosis was ranked as follows: grade 1, normal vessel or vessel irregularities (<10% luminal narrowing); grade 2, mild arterial stenosis (<50% luminal narrowing); grade 3, severe arterial stenosis (50%–99% luminal narrowing); or grade 4, occlusion. Grading of arterial stenosis was performed by using an electronic caliper. Stenosis grades 1 and 2 (<50% luminal narrowing) were considered hemodynamically insignificant arterial stenosis, whereas grades 3 and 4 (50%–100% luminal narrowing) were considered hemodynamically significant arterial stenosis. When two or more stenotic luminal changes were detected in the same vessel segment, the most severe change was used for grading and analysis.

Presence and location of aneurysmal changes were noted separately. Abdominal aortic aneurysms were defined as present when the diameter of the aorta exceeded 3.5 cm at short-axis measurement (1). Aortic aneurysms were classified as suprarenal when the distance of the proximal extent, or "neck," of the aneurysm extended over the origins of the renal artery by more than 1 cm. A juxtarenal aneurysm was defined as one with an infrarenal neck less than 1 cm long, whereas an aneurysm was considered infrarenal if the infrarenal neck was 1 cm or longer (1). An iliac aneurysm was diagnosed in the presence of a focal increase in arterial diameter that exceeded the diameter of the adjacent vessel by more than 50% (1). Changes consistent with fibromuscular dysplasia were noted separately and were graded as grade 3 stenosis on the basis of the assumption that they were hemodynamically significant (5).

The time (in seconds) for analysis of MR and CT images on the basis of the prepared standardized MIPs, volume-rendered images, and source data (including reformatting of source data if necessary) was recorded for each patient for both readers by the study coordinator. Because of the high memory capacity of the workstation, time for loading the standardized MIPs and volume-rendered images or source data was negligible. Hence, the time noted by the study coordinator only corresponded to the time required for data analysis. The study coordinator also noted the number and locations of vascular segments where each of the readers performed additional interactive reformatting. In addition, the study coordinator noted the reason for additional interactive reformatting (ie, tortuous course of the vessel or calcification of the vessel wall).

Statistical Analysis
Times for the MR and CT examinations, performance of 3D reconstruction, and image analysis were given as means and ranges and were analyzed for statistical significance by using the Wilcoxon signed rank test. Differences between visual analogue scale scores were also analyzed in a pairwise manner by performing the Wilcoxon signed rank test with Bonferroni correction for multiple testing (P values of .05/3 = .017 required for statistical significance). Sensitivity, specificity, positive and negative predictive values, and accuracy for determination of hemodynamically significant arterial stenosis were calculated for all 16 segments combined and for each of the following four vascular regions separately: main renal arteries, including accessory renal arteries; both common iliac arteries; both external iliac arteries; and both internal iliac arteries. The 95% CIs were calculated on the basis of binominal probabilities. The statistical significance of the differences in sensitivities and specificities between MR and CT angiography for both readers was assessed by using the McNemar test for paired data. A Bonferroni correction was used to adjust for multiple comparisons (two modalities with two readers yields four comparisons) requiring P values of .05/4 = .0125 for statistical significance. Interobserver agreements of grading vascular lesions between both readers within each imaging modality were determined by calculating values and 95% CIs (poor agreement, = 0; slight agreement, = 0.01–0.20; fair agreement, = 0.21–0.40; moderate agreement, = 0.41–0.60; good agreement, = 0.61–0.80; and excellent agreement, = 0.81–1.00) (28). values were also computed for intermodality agreement between MR and CT angiography for both readers.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Assessment of Patient Acceptance
The patients considered multi–detector row CT angiography to be the least uncomfortable imaging procedure and DSA to be the most uncomfortable. The mean (± SD) visual analogue scale scores for discomfort during imaging were 41.0 mm ± 33.0 for DSA, 27.9 mm ± 25.7 for MR angiography, and 15.5 mm ± 19.8 for CT angiography. A pairwise comparison between the three imaging modalities showed that the differences were statistically significant between DSA and CT angiography (P < .001), as well as between MR and CT angiography (P = .016). There was no significant difference between DSA and MR angiography (P = .037). The most disturbing factors were noise and having to keep still during MR angiography. For DSA, puncture of a femoral artery and application of the pressure bandage after the procedure were reported to cause most of the discomfort.

DSA Findings
For the DSA images obtained in all 46 patients, findings in all possible 736 vascular segments were considered to be diagnostic. DSA showed 11 accessory renal arteries in nine patients, bringing the total number of vascular segments that could be assessed to 769. Four patients had one accessory renal artery on the right side, four had one accessory renal artery on the left side, and one demonstrated simultaneous presence of one right-sided accessory renal artery and two left-sided accessory renal arteries.

Overall, DSA was used to identify 693 hemodynamically insignificant (<50% of luminal narrowing) and 76 hemodynamically significant arterial stenoses (50%–100% of luminal narrowing). Ten of these 76 arterial segments were occluded. These findings and a breakdown of the degrees and sites of arterial stenoses and the corresponding MR and CT angiographic results for the two readers are summarized in Table 1. Changes consistent with fibromuscular dysplasia were present unilaterally in one patient on the middle and distal segments of one renal artery.

View larger version (115K): [in this window] [in a new window] [Download PPT slide]   Figure 1a. Images in an 81-year-old man with aneurysms in both common iliac arteries. (a) Frontal intraarterial DSA image demonstrates a large aneurysm (large arrows) in the right common iliac artery and a smaller aneurysm (small arrows) in the left common iliac artery. Note additional infrarenal aortic elongation and buckling, as well as ectasia of both external iliac arteries. (b) Anteroposterior volume-rendered image of coronal contrast-enhanced 3D MR angiogram (5/1; flip angle, 30°) obtained in the same patient as in a shows the same findings (arrows) as those on the DSA image. (c) The same aneurysms (arrows) are also depicted on the anteroposterior volume-rendered multi-detector row CT angiogram (nominal section thickness, 1 mm; pitch, 6). Both aneurysms were detected by both readers on the basis of analysis of the standardized volume-rendered images and MIPs. No additional interactive reformatting was needed with either modality.

View larger version (78K): [in this window] [in a new window] [Download PPT slide]   Figure 1b. Images in an 81-year-old man with aneurysms in both common iliac arteries. (a) Frontal intraarterial DSA image demonstrates a large aneurysm (large arrows) in the right common iliac artery and a smaller aneurysm (small arrows) in the left common iliac artery. Note additional infrarenal aortic elongation and buckling, as well as ectasia of both external iliac arteries. (b) Anteroposterior volume-rendered image of coronal contrast-enhanced 3D MR angiogram (5/1; flip angle, 30°) obtained in the same patient as in a shows the same findings (arrows) as those on the DSA image. (c) The same aneurysms (arrows) are also depicted on the anteroposterior volume-rendered multi-detector row CT angiogram (nominal section thickness, 1 mm; pitch, 6). Both aneurysms were detected by both readers on the basis of analysis of the standardized volume-rendered images and MIPs. No additional interactive reformatting was needed with either modality.

View larger version (89K): [in this window] [in a new window] [Download PPT slide]   Figure 1c. Images in an 81-year-old man with aneurysms in both common iliac arteries. (a) Frontal intraarterial DSA image demonstrates a large aneurysm (large arrows) in the right common iliac artery and a smaller aneurysm (small arrows) in the left common iliac artery. Note additional infrarenal aortic elongation and buckling, as well as ectasia of both external iliac arteries. (b) Anteroposterior volume-rendered image of coronal contrast-enhanced 3D MR angiogram (5/1; flip angle, 30°) obtained in the same patient as in a shows the same findings (arrows) as those on the DSA image. (c) The same aneurysms (arrows) are also depicted on the anteroposterior volume-rendered multi-detector row CT angiogram (nominal section thickness, 1 mm; pitch, 6). Both aneurysms were detected by both readers on the basis of analysis of the standardized volume-rendered images and MIPs. No additional interactive reformatting was needed with either modality.

MR Angiography
On all MR angiograms, the aortoiliac and renal arteries were evaluated as being diagnostic by both readers.

Reader 1.—Reader 1 identified 696 hemodynamically insignificant arterial stenoses (<50% luminal narrowing). Seventy-three hemodynamically significant arterial stenoses (50%–100% luminal narrowing) were identified. Eight of these 73 arterial segments were occluded. Table 1 shows the breakdown of findings of reader 1 for all 769 arterial segments in all 46 patients. The mean time for evaluation of all arterial segments in each patient was 4.2 minutes (range, 2.2–5.5 minutes). Image analysis was based on the standardized MIPs and volume-rendered images alone in 727 segments (95%). Interactive reformatting by reader 1 was necessary in 42 of 769 segments (5%) (Table 2).

Reader 1 versus reader 2.—There was good interobserver agreement ( = 0.68; 95% CI: 0.65, 0.71) for all degrees of arterial stenosis (grades 1–4). There was excellent agreement between the two readers for diagnosing hemodynamically insignificant versus significant arterial stenosis ( = 0.89; 95% CI: 0.86, 0.92) and good agreement for determination of nonocclusion versus occlusion ( = 0.70; 95% CI: 0.69, 0.71).

Multi–Detector Row CT Angiography
On all multi–detector row CT angiograms, the aortoiliac and renal arteries were evaluated as being diagnostic by both readers.

Reader 1.—Reader 1 depicted 694 hemodynamically insignificant arterial stenoses (<50% luminal narrowing) and 75 significant arterial stenoses (50%–100% luminal narrowing). Ten of these 75 arterial segments were occluded. Table 1 demonstrates the breakdown of findings of reader 1 for all 769 arterial segments in all 46 patients. The mean time for evaluation of all arterial segments in each patient was 5.4 minutes (range, 3.1–6.3 minutes). Image analysis was based on the standardized MIPs and volume-rendered images alone in 672 segments (87%). Interactive reformatting by reader 1 was necessary in 97 of 769 arterial segments (13%) (Table 2).

Reader 2.—Reader 2 reported 693 hemodynamically insignificant arterial stenoses (<50% luminal narrowing) and 76 significant arterial stenoses (50%–100% luminal narrowing). Ten of these 76 arterial segments were occluded. Table 1 demonstrates the breakdown of findings by reader 2 for all 769 arterial segments in all 46 patients. The mean time for evaluation of all arterial segments in each patient was 4.6 minutes (range, 2.8–6.0 minutes). Image analysis was based on the standardized MIPs and volume-rendered images alone in 668 segments (87%). Interactive reformatting by reader 2 was necessary in 101 of 769 arterial segments (13%) (Table 2).

Reader 1 versus reader 2.—There was good interobserver agreement ( = 0.71; 95% CI: 0.68, 0.74) for all degrees of arterial stenosis (grades 1–4). There was excellent agreement between the two readers for diagnosing hemodynamically insignificant versus significant arterial stenosis ( = 0.88; 95% CI: 0.84, 0.90) and excellent agreement for determination of nonocclusion versus occlusion ( = 0.90; 95% CI: 0.83, 0.97).

MR versus CT Angiography
The mean examination time, defined as the time from patient entry into the MR or CT suite until the source data were available for 3D reconstruction, was 35 minutes for MR angiography (range, 31–39 minutes, depending on the physical conditions of the patient and the time to achieve intravenous access) and 24 minutes for CT angiography (range, 21–32 minutes, depending on the physical conditions of the patient and the time to achieve intravenous access). This difference was statistically significant (P < .001). The mean times it took the radiologist experienced in 3D reconstruction to generate the standardized MIP and volume-rendered images were 6 minutes (range, 4–7 minutes) and 7 minutes (range, 5–9 minutes) for MR angiography, respectively, and 25 minutes (range, 18–36 minutes) and 29 minutes (range, 20–45 minutes) for CT angiography, respectively. The differences in times between MR and CT angiography for the generation of MIPs and volume-rendered images were statistically significant (P < .001).

Both readers needed significantly more time per patient for analysis of CT images than that for MR images (5.4 minutes vs 4.2 minutes, respectively, for reader 1 and 4.6 minutes vs 3.8 minutes, respectively, for reader 2; P < .001 for both readers). Overall, there were significantly more arterial segments on CT images than on MR images, for which both readers performed additional interactive reformatting (MR images: 42 segments for reader 1 and 39 segments for reader 2; CT images: 97 segments for reader 1 and 101 segments for reader 2; P = .002 for reader 1 and P = .001 for reader 2) (Table 2). On both MR and CT images, interactive reformatting was most commonly performed for analysis of renal or internal iliac arteries. Less frequently, interactive reformatting was performed for the assessment of the common iliac and external iliac arteries, and no interactive reformatting was needed for evaluation of the supra- and infrarenal abdominal aorta (Table 2). On MR images, the tortuous course of arterial segments was reported by both readers to be the main reason for additional reformatting. In addition, arterial wall calcifications hampered analysis of standardized MIPs and volume-rendered images on CT images (Figs 2–4).

View larger version (127K): [in this window] [in a new window] [Download PPT slide]   Figure 2a. Images in a 68-year-old man with right leg claudication. (a) Frontal DSA image demonstrates hemodynamically significant arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the right common iliac artery. (b, c) Both readers graded the arterial stenosis of the right common iliac artery as hemodynamically significant stenosis (grade 3; arrows) on the basis of standardized volume-rendered images obtained from coronal contrast-enhanced 3D MR angiographic data (b; anteroposterior view) and multi-detector row CT angiographic data (c; anteroposterior view). Interactive reformatting was not performed by both readers. In addition, hemodynamically significant stenosis (grade 3) of the proximal segment of the left external iliac artery was also noted by both readers on volume-rendered images from MR and multi-detector row CT angiography and DSA.

View larger version (46K): [in this window] [in a new window] [Download PPT slide]   Figure 2b. Images in a 68-year-old man with right leg claudication. (a) Frontal DSA image demonstrates hemodynamically significant arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the right common iliac artery. (b, c) Both readers graded the arterial stenosis of the right common iliac artery as hemodynamically significant stenosis (grade 3; arrows) on the basis of standardized volume-rendered images obtained from coronal contrast-enhanced 3D MR angiographic data (b; anteroposterior view) and multi-detector row CT angiographic data (c; anteroposterior view). Interactive reformatting was not performed by both readers. In addition, hemodynamically significant stenosis (grade 3) of the proximal segment of the left external iliac artery was also noted by both readers on volume-rendered images from MR and multi-detector row CT angiography and DSA.

View larger version (89K): [in this window] [in a new window] [Download PPT slide]   Figure 2c. Images in a 68-year-old man with right leg claudication. (a) Frontal DSA image demonstrates hemodynamically significant arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the right common iliac artery. (b, c) Both readers graded the arterial stenosis of the right common iliac artery as hemodynamically significant stenosis (grade 3; arrows) on the basis of standardized volume-rendered images obtained from coronal contrast-enhanced 3D MR angiographic data (b; anteroposterior view) and multi-detector row CT angiographic data (c; anteroposterior view). Interactive reformatting was not performed by both readers. In addition, hemodynamically significant stenosis (grade 3) of the proximal segment of the left external iliac artery was also noted by both readers on volume-rendered images from MR and multi-detector row CT angiography and DSA.

View larger version (142K): [in this window] [in a new window] [Download PPT slide]   Figure 3a. Images in a 67-year-old man with left leg claudication. (a) Frontal DSA image demonstrates high-grade arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the left common iliac artery, which was also diagnosed by both readers on (b) the corresponding standardized volume-rendered image (anteroposterior view; arrow) reconstructed from coronal contrast-enhanced 3D MR angiographic data. Additional interactive reformatting was not needed by both readers. (c) Because of overlying calcifications, grading of arterial stenosis was not considered possible on standardized volume-rendered images (anteroposterior view) obtained with multi-detector row CT angiography. (d) After evaluating transverse source images, however, arterial stenosis of the left common iliac artery (arrow) was diagnosed correctly as grade 3 by both readers. In addition, a hemodynamically significant arterial stenosis of the right common iliac artery is noted on the DSA image, as well as on the MR angiogram. Because of overlaying calcification, the stenosis is not seen on c. However, the stenosis was correctly classified on the basis of source data (not shown). Extensive calcifications (white areas) of both renal arteries, the infrarenal aorta, the splenic artery, and both internal iliac arteries are noted on the volume-rendered image obtained with multi-detector row CT angiography.

View larger version (90K): [in this window] [in a new window] [Download PPT slide]   Figure 3b. Images in a 67-year-old man with left leg claudication. (a) Frontal DSA image demonstrates high-grade arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the left common iliac artery, which was also diagnosed by both readers on (b) the corresponding standardized volume-rendered image (anteroposterior view; arrow) reconstructed from coronal contrast-enhanced 3D MR angiographic data. Additional interactive reformatting was not needed by both readers. (c) Because of overlying calcifications, grading of arterial stenosis was not considered possible on standardized volume-rendered images (anteroposterior view) obtained with multi-detector row CT angiography. (d) After evaluating transverse source images, however, arterial stenosis of the left common iliac artery (arrow) was diagnosed correctly as grade 3 by both readers. In addition, a hemodynamically significant arterial stenosis of the right common iliac artery is noted on the DSA image, as well as on the MR angiogram. Because of overlaying calcification, the stenosis is not seen on c. However, the stenosis was correctly classified on the basis of source data (not shown). Extensive calcifications (white areas) of both renal arteries, the infrarenal aorta, the splenic artery, and both internal iliac arteries are noted on the volume-rendered image obtained with multi-detector row CT angiography.

View larger version (95K): [in this window] [in a new window] [Download PPT slide]   Figure 3c. Images in a 67-year-old man with left leg claudication. (a) Frontal DSA image demonstrates high-grade arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the left common iliac artery, which was also diagnosed by both readers on (b) the corresponding standardized volume-rendered image (anteroposterior view; arrow) reconstructed from coronal contrast-enhanced 3D MR angiographic data. Additional interactive reformatting was not needed by both readers. (c) Because of overlying calcifications, grading of arterial stenosis was not considered possible on standardized volume-rendered images (anteroposterior view) obtained with multi-detector row CT angiography. (d) After evaluating transverse source images, however, arterial stenosis of the left common iliac artery (arrow) was diagnosed correctly as grade 3 by both readers. In addition, a hemodynamically significant arterial stenosis of the right common iliac artery is noted on the DSA image, as well as on the MR angiogram. Because of overlaying calcification, the stenosis is not seen on c. However, the stenosis was correctly classified on the basis of source data (not shown). Extensive calcifications (white areas) of both renal arteries, the infrarenal aorta, the splenic artery, and both internal iliac arteries are noted on the volume-rendered image obtained with multi-detector row CT angiography.

View larger version (108K): [in this window] [in a new window] [Download PPT slide]   Figure 3d. Images in a 67-year-old man with left leg claudication. (a) Frontal DSA image demonstrates high-grade arterial stenosis (grade 3, 50%-99% luminal narrowing; arrow) of the left common iliac artery, which was also diagnosed by both readers on (b) the corresponding standardized volume-rendered image (anteroposterior view; arrow) reconstructed from coronal contrast-enhanced 3D MR angiographic data. Additional interactive reformatting was not needed by both readers. (c) Because of overlying calcifications, grading of arterial stenosis was not considered possible on standardized volume-rendered images (anteroposterior view) obtained with multi-detector row CT angiography. (d) After evaluating transverse source images, however, arterial stenosis of the left common iliac artery (arrow) was diagnosed correctly as grade 3 by both readers. In addition, a hemodynamically significant arterial stenosis of the right common iliac artery is noted on the DSA image, as well as on the MR angiogram. Because of overlaying calcification, the stenosis is not seen on c. However, the stenosis was correctly classified on the basis of source data (not shown). Extensive calcifications (white areas) of both renal arteries, the infrarenal aorta, the splenic artery, and both internal iliac arteries are noted on the volume-rendered image obtained with multi-detector row CT angiography.

View larger version (148K): [in this window] [in a new window] [Download PPT slide]   Figure 4a. Images in a 73-year-old man with generalized atherosclerosis and left leg claudication. (a) Frontal DSA image shows hemodynamically insignificant stenosis (grade 2, 10%-50% luminal narrowing; arrow) of the proximal segment of the left renal artery. (b, c) Arterial stenosis was graded as hemodynamically insignificant (grade 2; arrow) by both readers on the basis of anteroposterior standardized volume-rendered images reconstructed from coronal contrast-enhanced 3D MR angiographic data, without the need for additional interactive reformatting. Neither reader was able to assess the proximal segment of the left renal artery due to overlying arterial wall calcification (arrow) on standardized volume-rendered images obtained with multi-detector row CT angiography. Therefore, analysis of the source data was required by both readers. (d) On the transverse source image of multi-detector row CT angiographic data, reader 2 correctly graded arterial stenosis as grade 2 (arrow). Reader 1 overestimated arterial stenosis as grade 3 (50%-99% luminal narrowing). Note calcification of the right proximal renal artery.

View larger version (100K): [in this window] [in a new window] [Download PPT slide]   Figure 4b. Images in a 73-year-old man with generalized atherosclerosis and left leg claudication. (a) Frontal DSA image shows hemodynamically insignificant stenosis (grade 2, 10%-50% luminal narrowing; arrow) of the proximal segment of the left renal artery. (b, c) Arterial stenosis was graded as hemodynamically insignificant (grade 2; arrow) by both readers on the basis of anteroposterior standardized volume-rendered images reconstructed from coronal contrast-enhanced 3D MR angiographic data, without the need for additional interactive reformatting. Neither reader was able to assess the proximal segment of the left renal artery due to overlying arterial wall calcification (arrow) on standardized volume-rendered images obtained with multi-detector row CT angiography. Therefore, analysis of the source data was required by both readers. (d) On the transverse source image of multi-detector row CT angiographic data, reader 2 correctly graded arterial stenosis as grade 2 (arrow). Reader 1 overestimated arterial stenosis as grade 3 (50%-99% luminal narrowing). Note calcification of the right proximal renal artery.

View larger version (127K): [in this window] [in a new window] [Download PPT slide]   Figure 4c. Images in a 73-year-old man with generalized atherosclerosis and left leg claudication. (a) Frontal DSA image shows hemodynamically insignificant stenosis (grade 2, 10%-50% luminal narrowing; arrow) of the proximal segment of the left renal artery. (b, c) Arterial stenosis was graded as hemodynamically insignificant (grade 2; arrow) by both readers on the basis of anteroposterior standardized volume-rendered images reconstructed from coronal contrast-enhanced 3D MR angiographic data, without the need for additional interactive reformatting. Neither reader was able to assess the proximal segment of the left renal artery due to overlying arterial wall calcification (arrow) on standardized volume-rendered images obtained with multi-detector row CT angiography. Therefore, analysis of the source data was required by both readers. (d) On the transverse source image of multi-detector row CT angiographic data, reader 2 correctly graded arterial stenosis as grade 2 (arrow). Reader 1 overestimated arterial stenosis as grade 3 (50%-99% luminal narrowing). Note calcification of the right proximal renal artery.

View larger version (92K): [in this window] [in a new window] [Download PPT slide]   Figure 4d. Images in a 73-year-old man with generalized atherosclerosis and left leg claudication. (a) Frontal DSA image shows hemodynamically insignificant stenosis (grade 2, 10%-50% luminal narrowing; arrow) of the proximal segment of the left renal artery. (b, c) Arterial stenosis was graded as hemodynamically insignificant (grade 2; arrow) by both readers on the basis of anteroposterior standardized volume-rendered images reconstructed from coronal contrast-enhanced 3D MR angiographic data, without the need for additional interactive reformatting. Neither reader was able to assess the proximal segment of the left renal artery due to overlying arterial wall calcification (arrow) on standardized volume-rendered images obtained with multi-detector row CT angiography. Therefore, analysis of the source data was required by both readers. (d) On the transverse source image of multi-detector row CT angiographic data, reader 2 correctly graded arterial stenosis as grade 2 (arrow). Reader 1 overestimated arterial stenosis as grade 3 (50%-99% luminal narrowing). Note calcification of the right proximal renal artery.

Reader 2.—Reader 2 agreed on 698 of 769 segments (91%) when assessing arterial stenosis on MR and CT images. The intermodality agreement for reader 2 in evaluating all degrees of arterial stenosis was good ( = 0.67; 95% CI: 0.64, 0.70). There was excellent intermodality agreement for reader 2 for diagnosis of hemodynamically insignificant versus significant arterial stenosis ( = 0.90; 95% CI: 0.87, 0.93) and excellent agreement for determination of nonocclusion versus occlusion ( = 0.84; 95% CI: 0.75, 0.93).

MR and CT Angiography versus DSA
Tables 3 and 4 summarize true-positive, true-negative, false-positive, and false-negative findings, as well as sensitivities, specificities, positive and negative predictive values, and accuracies for detection and grading of hemodynamically significant arterial stenosis (50%–100% luminal narrowing) for all 16 segments combined and for each of the four vascular regions separately. Overall, there was no statistically significant difference in sensitivity (P = .22 for reader 1 and P = .13 for reader 2) and specificity (P = .73 for reader 1 and P = .76 for reader 2) between MR and CT angiography for both readers in the detection and grading of hemodynamically significant arterial stenosis.

	DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

Contrast-enhanced 3D MR angiography has been proven useful for assessing the aortoiliac and renal arteries (1,3–8). The technique is based on the availability of high-performance gradient systems and is capable of reducing data collection times sufficiently to acquire the entire 3D MR image data set during the intraarterial phase of intravenously administered extracellular contrast agents (22). A current imaging technique involving a single bolus injection protocol has proven a highly robust technique with few technical problems (4,7). In our study, all possible 769 arterial segments were considered diagnostic by both readers. Good image quality is reflected in the comparative analysis with DSA. The results reported herein, with total sensitivities of 92% and 93% for readers 1 and 2, respectively, and specificities of 100% and 99%, respectively, for detection of luminal narrowing of at least 50% in aortoiliac and renal arteries, were in accordance with the results of previous studies. Sensitivities between 85% and 99% and specificities between 86% and 100% for the detection of hemodynamically significant arterial stenosis of aortoiliac and renal arteries have been reported in the literature (4–8).

Single–detector row helical CT has also been used for evaluation of the aortoiliac and renal arteries (9–14). The trade-off between scan volume and spatial resolution along the z axis of single–detector row helical CT was a substantial limitation when imaging the aortoiliac arteries with a single iodine-based contrast material injection was desired (34). Nevertheless, by using a relatively small craniocaudal scanning range (6–12 cm) that enabled imaging with high collimation (2–3 mm), single–detector row helical CT has been shown to depict both hemodynamically significant renal artery stenosis and accessory renal arteries with high diagnostic accuracy (13,14,35). By using sequential single–detector row helical CT, Raptopoulos and coworkers (13) were able to achieve sufficient vessel enhancement for assessing an extended vascular territory that ranged from the celiac axis down to the femoral arteries. They used two sessions of helical scanning with a collimation of 3 and 5 mm, respectively, with two separate bolus injections of iodinated contrast agent. By substantially increasing the dose of contrast agent, they demonstrated a sensitivity of 94% and a specificity of 97% for the detection of severely stenotic (85% luminal narrowing) aortoiliac arterial segments.

With the introduction of multi–detector row CT scanners, CT angiography is gaining increasing importance (15). With multi–detector row CT scanners, CT angiography can be performed more efficiently because of faster scanning speed and higher longitudinal spatial resolution than was possible with single–detector row helical CT scanners. In a comparative study of CT angiography of the aorta and iliac arteries by using a four-channel CT scanner and a one-channel CT scanner, Rubin et al (15) showed that CT angiography with a multi–detector row CT scanner was faster and that scanning was possible with thinner collimation and a reduced contrast material dose.

In our study, by using a half-second multi–detector row CT scanner and a 1-mm nominal section thickness, the mean craniocaudal distance of 35 cm could be scanned during one breath hold. When combined with optimized arterial contrast enhancement by using a computer-assisted bolus-tracking technique, high-quality CT angiograms of the aortoiliac and renal arteries could be obtained, which allowed high-quality multiplanar reformations in any desired imaging plane. The excellent quality of CT angiograms obtained with a multi–detector row CT scanner in this study is reflected in the total sensitivities for reader 1 and reader 2 of 91% and 92%, respectively, and in the total specificity of 99% and 99%, respectively, for the detection of hemodynamically significant arterial stenosis of aortoiliac and renal arteries.

For the grading of individual arteries, sensitivity and specificity in detecting hemodynamically significant stenosis were lowest for renal arteries and for internal iliac arteries for both readers. Underestimation or overestimation of arterial stenosis due to vessel wall calcifications on CT angiograms has been reported in several studies (11,12,27,35,36). For MIPs, in particular, which display only the voxels with the highest signal intensity along parallel rays, difficulties in the quantification of arterial lumen narrowing on CT angiograms have been outlined (11,36). In our experience, extensive arterial wall calcifications of both renal and internal iliac arteries can be seen frequently in patients with suspected occlusive disease. Although we did not evaluate this issue systematically in our study, the small vessel diameter combined with vessel wall calcifications may have contributed to the higher rate of false-negative and false-positive findings in both renal and internal iliac arteries.

It is important to note that the apparent obscuration of the arterial lumen by calcium strongly depends on the window settings. Therefore, for minimizing the effect of apparent "blooming" of calcium, we routinely use a bone window setting (window width, 2,000 HU; center level, 500 HU) for the evaluation of arterial segments when calcium is present. Inappropriate window setting by reader 1 during image analysis of multi–detector row CT angiograms may have caused more overestimation of arterial stenosis of the proximal renal arteries compared with that of reader 2.

The results of our study demonstrate that there is no statistically significant difference in the diagnostic performance of MR angiography compared with that of multi–detector row CT angiography for the detection of hemodynamically significant arterial stenosis of the aortoiliac and renal arteries. Several issues should be addressed, however, which may influence the use of either modality in clinical practice.

There is general agreement that, apart from the radiation issue, a major advantage of MR angiography is that patients with preexisting renal insufficiency may undergo imaging without risk. In light of the fact that these patients—especially those with diabetes—often have concurrent arterial occlusive diseases or aneurysms (37), this issue is even more important. Conversely, the major advantage of multi–detector row CT in particular is the increased volume coverage, which permits acquisition of the entire aorta (15) or the aortoiliac arteries and the peripheral vessels of the lower extremity within one acquisition, combined with a high spatial resolution (38). Although the development of moving table techniques for contrast-enhanced 3D MR angiography allows coverage from the midabdominal aorta to the foot during a single contrast material injection (6,7,39,40), covering a large volume over several vessel territories with sufficient intraarterial contrast enhancement and minimal venous overlay remains a challenge with MR angiography. In addition, the limited spatial resolution of MR angiography is another disadvantage, especially when evaluating vessels with small diameters (7). In our study, voxel volumes were 9–19 times larger with MR angiography than those with multi–detector row CT angiography. Although this smaller voxel volume did not influence the results of our study, it may be relevant when assessing smaller vessel diameters or finer luminal abnormalities. Despite the impairment of vessel analysis due to vessel wall calcifications, the possibility of localizing arterial wall calcifications that may have therapeutic relevance may be an advantage of multi-detector CT angiography (41). Another potential advantage of multi–detector row CT angiography over MR angiography relates to the limited anteroposterior coverage of MR angiography, with which additional vascular abnormalities, such as coexisting collateral pathways or extraarterial findings, may be missed.

In general, the use of MR angiography or multi–detector row CT angiography in patients without contraindication to either modality may be influenced by several factors, including examination time, time for generation of 3D reconstructions, time for image analysis, patient acceptance, and cost.

The results of our study have shown that the examination time, defined as the time from patient entry into the MR or CT suite until the source data were available for 3D reconstruction, was significantly shorter for multi–detector row CT than that for MR angiography (24 minutes vs 35 minutes, respectively; P < .001).

Conversely, time for generation of standardized 3D reconstructions (including MIPs and volume-rendered images) was significantly more time-consuming for CT data sets than for MR data sets. There is general agreement that analysis of contrast-enhanced MR angiograms should be based on a combination of MIPs and multiplanar reconstructions (42). Therefore, we generated MIPs as a standard 3D reconstruction technique for subsequent image analysis. The use of shaded-surface displays appears to be of little value in interpretation of MR angiograms (42). A rational use of 3D reconstruction techniques, which are mandatory for efficient interpretation of multi–detector row CT angiograms, is not defined, to the best of our knowledge, although efficient handling of complex CT data sets is of paramount importance, considering the large amounts of transverse images associated with multi–detector row CT.

In current publications that deal with multi–detector row CT angiography, most authors use a combination of MIPs, volume-rendered images, shaded-surface displays, and multiplanar reconstructions for image analysis of multi–detector row CT angiograms (15,16,43). For the sake of comparison, we generated standardized MIPs and volume-rendered images for both MR and CT angiograms in this study. If necessary, both readers were allowed to perform additional interactive reformatting, including viewing of source data and generation of multiplanar reconstructions. We believe that the stepwise analysis involving standardized reformations in a first step, followed by individual reformatting of the source data in a second step, reflects clinical practice and was performed similarly in other studies that deal with either MR or CT angiography (15,16,43).

The most time-consuming procedure of 3D reconstruction of multi–detector row CT angiograms in our study was the segmentation of surrounding nonvascular structures. The time for segmentation strongly depends on both hardware and software of the workstation. Future software upgrades that allow automated segmentation will be available for routine clinical use in the future (44,45) and may reduce the time required for generation of 3D reconstructions of CT angiographic data.

The results of our study have also shown that for both readers, not only 3D reconstruction of CT data but also image analysis of multi–detector row CT angiography was significantly more time-consuming than was image analysis for MR angiograms. Both readers performed additional reformatting on significantly more arterial segments in CT data sets than in MR data sets, which may account for the lengthier analysis time of CT angiography. Besides a tortuous course of a vessel, both readers reported calcifications of the vessel wall as the main reason for additional interactive reformatting for CT angiography.

In our study, multi–detector row CT angiography was considered more comfortable than MR angiography and DSA and was the most preferred examination. Patient preference for CT angiography is probably best explained by the short acquisition time, resulting in a short examination time for the patient. Surprisingly, there was no statistically significant difference in patient acceptance between MR angiography and DSA, although on average, patients rated MR angiography as more comfortable than DSA. Noise, having to keep still during MR angiography, and the lengthy imaging time may be considered causative, although we did not investigate these aspects systematically in our study.

Cost issues of DSA, MR angiography, and multi–detector row CT angiography were not addressed in our study. However, both MR and CT angiography offer savings in areas such as hospital admission costs, catheters, and other materials used for DSA (32,46). Further prospective investigations are warranted to compare MR and CT angiography for evaluation of the aortoiliac and renal arteries in terms of cost-effectiveness, as this analysis may also guide physicians in choosing MR or CT angiography.

We acknowledge several limitations of our study. A possible limitation relates to the limited prevalence of hemodynamically significant arterial stenoses that affected 76 of 769 vascular segments (10%). This may limit the calculated descriptive statistics for each of the four different vascular regions.

Another limitation relates to the design of the study, since we compared only the diagnostic performance of MR angiography and multi–detector row CT angiography of the aortoiliac and renal arteries and did not fully exploit the potential of either modality to image larger vascular territories. Moreover, evaluation of the visceral arteries for presence of arterial stenosis was precluded in this study. Furthermore, image analysis did not include additional criteria, including arterial stenosis length, diffuseness of the disease, and localization and extent of arterial wall calcification. All of these parameters may be important for patient care.

For lack of a more accurate technique, we used DSA as the standard of reference for evaluation of aneurysmal changes. Limitations of this technique in the detection of mural thrombus may result in undersizing the aneurysms, as well as underestimating the number of aneurysms. However, since evaluation of MR images did not include additional sequences, such as gradient-recalled-echo or spin-echo sequences, which are considered mandatory for assessment of the arterial wall and mural thrombus, this may not have influenced the results. Furthermore, multi–detector row CT angiography did not show more aneurysmal changes than did DSA.

Although we applied an electronic caliper for quantification of arterial stenosis on MR and CT angiograms, we used only a four-point scale to grade arterial stenosis. Therefore, subtle discrepancies between MR and CT angiography in the quantification of arterial stenosis cannot be obtained from this study. In addition, the percentage of discrepancies between DSA, MR angiography, and CT angiography in the evaluation of arterial stenosis, which approaches 50%, can not be obtained from our results.

The fact that DSA was not performed with the patients in conscious sedation as is performed routinely in other institutions may have been a disadvantage for DSA when assessing patient preferences for one of the three imaging modalities.

In this study, we did not evaluate the added diagnostic value of MIPs, volume-rendered images, and interactive reformatting for analysis of the MR and CT angiograms separately. Further studies are needed to address the diagnostic effect of different 3D reconstruction techniques in evaluating multi–detector row CT angiograms in particular. Finally, the results of our study may have been influenced by the hardware and software of the workstation used for performing 3D reconstructions.

In conclusion, the results of our study have demonstrated for the first time, to our knowledge, in a prospective, blinded, intraindividual comparison that there is no statistical difference in the diagnostic performance of contrast-enhanced 3D MR angiography and multi–detector row CT angiography in the accurate identification of hemodynamically significant arterial stenosis of the aortoiliac and renal arteries. When compared with multi–detector row CT angiography, times for performing 3D reconstructions and analysis of MR angiograms were shorter, but multi–detector row CT angiography was better accepted by patients.

	FOOTNOTES

 
Abbreviations: DSA = digital subtraction angiography, MIP = maximum intensity projection, 3D = three dimensional

Author contributions: Guarantors of integrity of entire study, J.K.W., D.W.; study concepts, J.K.W., D.W., P.R.H.; study design, J.K.W., D.W.; literature research, J.K.W.; clinical studies, J.K.W., T.P., J.E.R.; data acquisition, J.K.W., D.W., T.P., P.R.H.; data analysis/interpretation, J.K.W., D.W., T.P., J.E.R., P.R.H.; statistical analysis, B.S., J.K.W.; manuscript preparation and definition of intellectual content, J.K.W., D.W.; manuscript editing, revision/review, and final version approval, all authors.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

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