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1
Department of Oncology, Transplants and Advanced Technologies in Medicine,
Division of Diagnostic and Interventional Radiology, University of Pisa, Via
Roma 67, 56100, Pisa, Italy.
2
Second Department of Radiology, Pisa University Hospital, 56100, Pisa,
Italy.
Received March 17, 2000;
accepted after revision May 31, 2000.
Address correspondence to E. Neri.
Abstract
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SUBJECTS AND METHODS. Twenty-six patients, having neoplastic lesions (n = 9), calculi (n = 8), pelviureteric junction stenoses (n = 4), postoperative fibrotic strictures (n = 3), and extrinsic compressions of the ureter (n = 2), underwent unenhanced MR urography. Virtual endoscopy of the upper urinary tract was obtained using a thresholding technique and surface-rendering MR urography data sets.
RESULTS. Virtual endoscopy of the renal pelvis and calices was feasible in all cases on the side of the urinary obstruction. Virtual endoscopy of the ureter was obtained for a diameter of at least larger than 5 mm. The nondilated side could be partially explored in 11 cases (43%). The mean virtual endoscopy threshold required for the visualization of the urinary tract was 157.36-159.94. The mean time for virtual endoscopy was 13.8 min. Endoluminal masses were found in three (12%) of 26 cases on the renal pelvis (corresponding to neoplastic lesions), and occlusions, in 23 (88%) of 26 on the pelviureteric junction and ureter (neoplastic lesions and other abnormalities).
CONCLUSION. Virtual endoscopy of MR urography data sets is feasible in patients with urinary tract dilatation. Virtual endoscopy displays the renal pelvis, calices, and ureter and, moreover, can show endoluminal changes caused by abnormalities.
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MR urography provides a projectional road map of the entire urinary tract. Two methods have been proposed for MR urography, on the basis of unenhanced and gadolinium-enhanced studies. The unenhanced study is based on the acquisition of so-called water images using heavily T2-weighted turbo spin-echo or half-Fourier acquisition single-shot turbo spin-echo sequences and other variations of these techniques. These approaches do not require contrast medium administration and are feasible in patients with urinary tract obstruction [7,8,9,10,11,12,13,14,15,16,17,18,19,20]. The gadolinium-enhanced study, performed using T1-weighted gradient-echo sequences, provides morphologic and functional information about the urinary tract [21, 22]. The feasibility of a so-called virtual ureterorenoscopy with gadolinium-enhanced MR urography also has been proposed. This technique permits simulation of endoscopic images from the calices to the ureteral orifices in the bladder and identification of all filling defects that are diagnosed on MR urography [23].
Virtual endoscopy of MR imaging data sets has been successfully applied to the study of vessels, the biliary tract, the colon, and cerebral ventricles [24,25,26,27,28,29,30,31]. To our knowledge, no researchers of virtual endos-copy of unenhanced MR urography have described their experience in the study of the upper urinary tract.
Therefore, we aimed to investigate, in a clinical setting, the feasibility of applying surface-rendered virtual endoscopy to the visualization of the upper urinary tract by processing unenhanced MR urography data sets.
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Our series included neoplastic lesions (n = 9) located in the renal pelvis, calices, and ureter; calculi (n = 8) located in the ureter; pelviureteric junction stenoses (n = 4); postoperative fibrotic strictures (n = 3); and extrinsic compressions (n = 2) located in the lumbar tract of the ureter.
Image Acquisition
MR imaging was performed with a 1.5-T magnet (Signa; General Electric
Medical Systems, Milwaukee, WI) using a body coil for both excitation and
signal reception (the surface torso array coil is not available at our
institution). To avoid peristaltic artifacts in all patients, 20 mg of
scopolamine methylbromide was injected IV before image acquisition.
MR urography was performed with a non—breath-hold fat-suppressed respiratory-triggered two-dimensional heavily T2-weighted fast spin-echo sequence in the coronal plane. Imaging parameters were as follows: TR range/TE, 7000-18,000/253; echo train length, 32; section thickness, 3 mm with no interslice gap; field of view, 35-45 cm; matrix size, 256 x 128 pixels; number of excitations, two to four; receive bandwidth, 16 kHz. Anteroposterior spatial presaturation was used for all images. Acquisition time ranged from 5 to 7 min.
Virtual Endoscopic Technique
To perform virtual endoscopy of the urinary tract, we transferred the
source images from the MR imaging unit to a dedicated workstation (Advantage
Windows 3.1; General Electric Medical Systems). Virtual endoscopic images were
generated with Navigator 2.0 software (General Electric Medical Systems).
Navigator reconstructed the MR images in three dimensions and created surface-rendered endoscopic images of the urinary tract. However, for generating virtual endoscopic images, Navigator required the manual segmentation of the urinary tract using a thresholding technique [32].
Virtual endoscopy was performed independently by two observers experienced in image processing and MR urography, who were asked to identify independently the optimal virtual endoscopy threshold; on the source MR images they traced a circular region of interest (maximum size, 1000 mm2) including the urinary tract and the surrounding tissue, and the relative histogram was obtained. Among the image pixels belonging to the urinary tract, the virtual endoscopy threshold was defined as the cluster of pixels having the minimum signal intensity on the histogram (Fig. 1).
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Virtual endoscopic images were always displayed in a combined fashion with MR source images; a dedicated function allowed the observers to select a point on the 3D perspective and to obtain simultaneously the corresponding coronal image crossing through this point [24, 25, 27, 28]. By the help of this function, virtual endoscopic findings could be correlated with the coronal images.
Analysis of Data
Virtual endoscopy thresholds selected by the observers were recorded for
each case. The observers were informed about the presence and location of the
abnormalities causing dilatation of the urinary tract and were asked to
evaluate the corresponding endoluminal image. The morphologic changes of the
urinary tract lumen were ranked by means of a four-point scale as normal lumen
(rank 0), stenosis (rank 1), endoluminal mass (rank 2), and occlusion (rank
3).
The time required for image processing, or virtual endoscopy time, was divided into a non—operator-dependent phase, including the transfer of the source images from the MR imaging unit to the workstation and the 3D reconstruction of the MR imaging data set (performed by the software itself), and an operator-dependent phase, including the virtual endoscopy threshold selection and the interpretation of virtual endoscopy perspectives. The non—operator-dependent phase was assumed to be equal for both observers because it included hardware-dependent procedures. The non—operator-dependent and operator-dependent phases were recorded.
Signal-to-Noise and Contrast-to-Noise Ratios
For the quantitative evaluation of mean signal-to-noise and
contrast-to-noise ratios, a circular region of interest consisting of a
minimum size of 5 mm2 was sampled at the levels of the renal
pelvis, the lumbar muscles, and noise outside of the abdomen. Measurements
were taken by the observers for the dilated and nondilated sides.
The signal-to-noise ratio was defined as the ratio of mean signal intensity in the renal pelvis to the standard deviation of noise, and contrast-to-noise ratio, as the difference in mean signal intensity between the renal pelvis and the lumbar muscles divided by the standard deviation of noise [33].
Statistical Analysis
Data of all patients were processed with Excel 97 software (Microsoft,
Redmond, WA). The correlation between the observers for the virtual endoscopy
threshold and the operator-dependent phase was determined with the Spearman's
rank correlation coefficient test. A correlation coefficient (r >
0.67) was considered indicative of good and statistically significant
correlation (p < 0.001)
[34].
The agreement between the observers for the assessment of endoluminal perspectives was evaluated using the Cohen kappa statistic. The kappa statistic describes the quality of agreement; kappa values between 0.40 and 0.75 represent fair to good agreement and kappa values greater than 0.75, excellent agreement.
The difference in mean signal-to-noise and contrast-to-noise ratios between the dilated and nondilated sides was evaluated with the Student's t test. A p value of less than 0.05 was considered to indicate a statistically significant difference [33].
Maximum and minimum values, the geometric mean, and the standard deviation were calculated for the virtual endoscopy threshold, non—operator-dependent phase, operator-dependent phase, and signal-to-noise and contrast-to-noise ratios.
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The mean virtual endoscopy threshold required for the visualization of the urinary tract was 157.36 signal intensity (minimum, 60; maximum, 260; SD, ±57.43) for one observer and 159.94 (minimum, 69; maximum, 250; SD, ±52.48) for the other. The correlation between the observers for virtual endoscopy threshold was excellent (r = 0.68; p < 0.001).
The mean non—operator-dependent phase time was 4.8 min (minimum, 3 min; maximum, 7 min; SD, ±1.23 min). The mean operator-dependent phase time was 9 min (minimum, 4 min; maximum, 16 min; SD, ±4.34 min) for one observer and 8 min (minimum, 4 min; maximum, 15 min; SD, ±3.24 min) for the other. The correlation between the observers for operator-dependent phase was excellent (r = 0.67; p < 0.001).
Virtual Endoscopy: Findings
Endoluminal masses were found in three (12%) of 26 patients in the renal
pelvis and corresponded to neoplastic lesions (Fig.
3A,3B,3C,3D,3E,3F,3G,3H,3I,3J).
Occlusions were found in 23 (88%) of 26 patients in the pelviureteric junction
and ureter and corresponded to neoplastic lesions (n = 6), calculi
(n = 8), postoperative strictures (n = 3), ureteroplelvic
junction stenosis (n = 4), and extrinsic ureteric compression
(n = 2). No stenosis was found. The agreement between the observers
for the evaluation of endoluminal patterns was excellent (
= 0.89; 95%
confidence interval). For endoluminal masses virtual endoscopy allowed the
study of renal calices, the pelvis, and the proximal portion of the
ureter.
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In three (12%) of 26 patients, the observers reported the occurrence of pierced surface artifacts at the level of the ureter [33]. These appeared as scattered holes of the internal surface of the ureter and were related to the inherent difficulties of the software in separating hyperintense voxels at the periphery of the ureter lumen from the surrounding tissue. An appropriate selection of virtual endoscopy threshold allowed the elimination of these artifacts.
Signal-to-Noise and Contrast-to-Noise Ratios
The mean signal-to-noise ratio was 52.22 ± 12.4 and 41.66 ±
12.99 for the dilated and nondilated sides, respectively. The mean
contrast-to-noise ratio was 50.11 ± 12.44 and 39.54 ± 12.55 for
the dilated and nondilated sides, respectively. The difference in mean
signal-to-noise ratio and contrast-to-noise ratio between dilated and
nondilated sides was statistically significant (p < 0.05).
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By contrast, in our study the dilatation of the urinary tract was a prerequisite for generating endoscopic images. In fact, the dilatation of the ureter or renal pelvis increased the availability of bright image pixels and, consequently, the voxels that virtual endoscopy could use to reconstruct the lumen in three dimensions and to create the virtual space for endoscopic navigation. We identified a lumen caliber of at least 5 mm for optimal display of the lumen because at lower diameters it appeared narrowed or occluded. In all patients, virtual endoscopy of the upper urinary tract was also performed on the nondilated side, but it failed to display the lumen with acceptable image quality in 15 (57%) of 26 patients. We considered virtual endoscopic images to be of acceptable quality when they showed a clear distinction between the virtual space for endoscopic navigation and the surface. This limitation was likely inherent to the thresholding method we were using; in fact, this method required a marked MR signal intensity difference between the urinary tract and the surrounding tissue to obtain the precise reconstruction of the lumen surface, and such condition was present only in patients with urinary obstruction. The statistically significant difference between the dilated and nondilated sides, for signal-to-noise and contrast-to-noise ratios, supports this consideration.
In this study, we also tried to analyze whether the virtual endoscopy threshold could affect the interobserver variability for the evaluation of endoluminal images. The excellent correlation between the observers suggests that virtual endoscopy threshold selection did not likely influence the assessment of virtual endoscopy patterns. However, this excellent correlation also can be explained by the observers' experience in image processing and virtual endoscopy and the use of common criteria (histogram evaluation) for threshold selection.
The criteria for the assessment of endoluminal patterns, previously described in the study of the biliary tract [27], were helpful even in the present study because of the similarities between MR cholangiography and MR urography data sets. The excellent correlation between the observers for the attribution of such patterns supports this evaluation method.
Most abnormal patterns were described by the observers as occlusion of the lumen, and all abnormalities were causing an obstruction at the level of the ureter or pelviureteric junction. No case of stenosis was identified in our study, and presumably this is related to the ureter caliber. In fact, because virtual endoscopy was feasible only when the ureter was dilated, we believe that the presence of stenosis cannot be easily appreciated in the narrowed tract because the space for navigation is dramatically reduced. Furthermore, dilatation of the ureter is not necessarily associated with stenosis of the lumen but has an obvious association with its obstruction.
In cases of neoplastic lesions presenting as endoluminal masses at the level of the renal pelvis, the distal portion of the ureter could not be explored. Virtual endoscopy depicted the endoluminal appearance of the lesions and the morphology, position with respect to calices, and extension of each lesion. However, we believe that the unique advantage of virtual endoscopy with respect to MR urographic source images was the morphologic assessment; position and extension of the lesions could be evaluated with coronal images as well.
An important issue related to virtual endoscopy is the time required for image processing. In our experience, the study of the urinary tract was not time-consuming. The total processing time (non—operator-dependent phase plus the operator-dependent phase) was approximately 12-13 min. If we consider a time range of 30-45 min for the entire examination, including patient preparation and acquisition of various imaging sequences, then unlike other applications (i.e., virtual colonoscopy), virtual endoscopy of the urinary tract did not significantly bias the total examination time.
Pierced surface artifacts in virtual endoscopy have been described in CT data sets [34]. In our experience, these artifacts did not influence the study of the urinary tract, but we recommend to future investigators the proper use of the virtual endoscopy threshold to avoid this occurrence.
Virtual endoscopy is therefore limited by the degree of dilatation of the ureter and by the occurrence of artifacts; these considerations do not reduce the value of virtual endoscopy in exploring the urinary tract. We believe this technique should be used as a complement to native images in difficult cases in which the degree of a stenosis or the extension of a lesion should be precisely determined in three dimensions. Moreover, we believe this tool will be an important piece of the future imaging-guided surgical tools that are under evaluation and development in different research projects.
In summary, virtual endoscopy of MR urography data sets is feasible in patients with urinary dilatation. It allows observers to visualize the renal pelvis, calices, and ureter and to see the effects of abnormalities on the urinary tract lumen (endoluminal masses and occlusions). Virtual endoscopy of the urinary tract can also be easily performed and does not bias the global examination time.
However, the aim of the present study was only to show the feasibility and issues related to this technique; we did not investigate whether virtual endoscopy can increase the diagnostic accuracy of MR urography. In our opinion, this issue will require further prospective study.
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