Multislice CT urography: state of the art

CT of the urinary tract revisited

Computed tomography (CT) of the abdomen is usually appropriate for the initial imaging of many urinary tract diseases, due to its wide availability, fast scanning and acquisition of thin slices and isotropic data, that allow the creation of multiplanar reformatted and three-dimensional reconstructed images of excellent anatomic details. Non-enhanced CT remains the standard imaging modality for assessing renal colic. The technique allows the detection of nearly all types of urinary calculi and the estimation of stone burden. CT is the primary diagnostic tool for the characterization of an indeterminate renal mass, including both cystic and solid tumors. It is also the modality of choice for staging a primary renal tumor. Urolithiasis and urinary tract malignancies represent the main urogenic causes of hematuria. CT urography (CTU) improves the visualization of both the upper and lower urinary tract and is recommended for the investigation of gross hematuria and microscopic hematuria, in patients with predisposing factors for urologic malignancies. CTU is highly accurate in the detection and staging of upper tract urothelial malignancies. CT represents the most commonly used technique for the detection and staging of bladder carcinoma and the diagnostic efficacy of CT staging improves with more advanced disease. Nevertheless, it has limited accuracy in differentiating non-muscle invasive bladder carcinoma from muscle-invasive bladder carcinoma. In this review, clinical indications and the optimal imaging technique for CT of the urinary tract is reviewed. The CT features of common urologic diseases, including ureterolithiasis, renal tumors and urothelial carcinomas are discussed.

U-Net based deep learning bladder segmentation in CT urography

OBJECTIVES

To develop a U-Net-based deep learning approach (U-DL) for bladder segmentation in computed tomography urography (CTU) as a part of a computer-assisted bladder cancer detection and treatment response assessment pipeline.

MATERIALS AND METHODS

A dataset of 173 cases including 81 cases in the training/validation set (42 masses, 21 with wall thickening, 18 normal bladders), and 92 cases in the test set (43 masses, 36 with wall thickening, 13 normal bladders) were used with Institutional Review Board approval. An experienced radiologist provided three-dimensional (3D) hand outlines for all cases as the reference standard. We previously developed a bladder segmentation method that used a deep learning convolution neural network and level sets (DCNN-LS) within a user-input bounding box. However, some cases with poor image quality or with advanced bladder cancer spreading into the neighboring organs caused inaccurate segmentation. We have newly developed an automated U-DL method to estimate a likelihood map of the bladder in CTU. The U-DL did not require a user-input box and the level sets for postprocessing. To identify the best model for this task, we compared the following models: (a) two-dimensional (2D) U-DL and 3D U-DL using 2D CT slices and 3D CT volumes, respectively, as input, (b) U-DLs using CT images of different resolutions as input, and (c) U-DLs with and without automated cropping of the bladder as an image preprocessing step. The segmentation accuracy relative to the reference standard was quantified by six measures: average volume intersection ratio (AVI), average percent volume error (AVE), average absolute volume error (AAVE), average minimum distance (AMD), average Hausdorff distance (AHD), and the average Jaccard index (AJI). As a baseline, the results from our previous DCNN-LS method were used.

RESULTS

In the test set, the best 2D U-DL model achieved AVI, AVE, AAVE, AMD, AHD, and AJI values of 93.4 ± 9.5%, -4.2 ± 14.2%, 9.2 ± 11.5%, 2.7 ± 2.5 mm, 9.7 ± 7.6 mm, 85.0 ± 11.3%, respectively, while the corresponding measures by the best 3D U-DL were 90.6 ± 11.9%, -2.3 ± 21.7%, 11.5 ± 18.5%, 3.1 ± 3.2 mm, 11.4 ± 10.0 mm, and 82.6 ± 14.2%, respectively. For comparison, the corresponding values obtained with the baseline method were 81.9 ± 12.1%, 10.2 ± 16.2%, 14.0 ± 13.0%, 3.6 ± 2.0 mm, 12.8 ± 6.1 mm, and 76.2 ± 11.8%, respectively, for the same test set. The improvement for all measures between the best U-DL and the DCNN-LS were statistically significant (P < 0.001).

CONCLUSION

Compared to a previous DCNN-LS method, which depended on a user-input bounding box, the U-DL provided more accurate bladder segmentation and was more automated than the previous approach.

Deep-learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography

PURPOSE

We are developing a computerized segmentation tool for the inner and outer bladder wall as a part of an image analysis pipeline for CT urography (CTU).

MATERIALS AND METHODS

A data set of 172 CTU cases was collected retrospectively with Institutional Review Board (IRB) approval. The data set was randomly split into two independent sets of training (81 cases) and testing (92 cases) which were manually outlined for both the inner and outer wall. We trained a deep-learning convolutional neural network (DL-CNN) to distinguish the bladder wall from the inside and outside of the bladder using neighborhood information. Approximately, 240 000 regions of interest (ROIs) of 16 × 16 pixels in size were extracted from regions in the training cases identified by the manually outlined inner and outer bladder walls to form a training set for the DL-CNN; half of the ROIs were selected to include the bladder wall and the other half were selected to exclude the bladder wall with some of these ROIs being inside the bladder and the rest outside the bladder entirely. The DL-CNN trained on these ROIs was applied to the cases in the test set slice-by-slice to generate a bladder wall likelihood map where the gray level of a given pixel represents the likelihood that a given pixel would belong to the bladder wall. We then used the DL-CNN likelihood map as an energy term in the energy equation of a cascaded level sets method to segment the inner and outer bladder wall. The DL-CNN segmentation with level sets was compared to the three-dimensional (3D) hand-segmented contours as a reference standard.

RESULTS

For the inner wall contour, the training set achieved the average volume intersection, average volume error, average absolute volume error, and average distance of 90.0 ± 8.7%, -4.2 ± 18.4%, 12.9 ± 13.9%, and 3.0 ± 1.6 mm, respectively. The corresponding values for the test set were 86.9 ± 9.6%, -8.3 ± 37.7%, 18.4 ± 33.8%, and 3.4 ± 1.8 mm, respectively. For the outer wall contour, the training set achieved the values of 93.7 ± 3.9%, -7.8 ± 11.4%, 10.3 ± 9.3%, and 3.0 ± 1.2 mm, respectively. The corresponding values for the test set were 87.5 ± 9.9%, -1.2 ± 20.8%, 11.9 ± 17.0%, and 3.5 ± 2.3 mm, respectively.

CONCLUSIONS

Our study demonstrates that DL-CNN-assisted level sets can effectively segment bladder walls from the inner bladder and outer structures despite a lack of consistent distinctions along the inner wall. However, even with the addition of level sets, the inner and outer walls may still be over-segmented and the DL-CNN-assisted level sets may incorrectly segment parts of the prostate that overlap with the outer bladder wall. The outer wall segmentation was improved compared to our previous method and the DL-CNN-assisted level sets were also able to segment the inner bladder wall with similar performance. This study shows the DL-CNN-assisted level set segmentation tool can effectively segment the inner and outer wall of the bladder.

Qualitative and quantitative radiological analysis of non-contrast CT is a strong indicator in patients with acute pyelonephritis

OBJECTIVE

To evaluate the performance of non-contrast computed tomography (CT) by reporting the difference in attenuation between normal and inflamed renal parenchyma in patients clinically diagnosed with acute pyelonephritis (APN).

MATERIAL AND METHODS

This is a retrospective study concerned with non-contrast CT evaluation of 74 patients, admitted with a clinical diagnosis of APN and failed to respond to 48h antibiotics treatment. Mean attenuation values in Hounsfield units (HU) were measured in the upper, middle and lower segments of the inflamed and the normal kidney of the same patient. Independent t-test was performed for statistical analysis. Image evaluation included receiver operating characteristic (ROC), visual grading characteristic (VGC) and kappa analyses.

RESULTS

The mean attenuation in the upper, middle and lower segments of the inflamed renal cortex was 32%, 25%, and 29% lower than the mean attenuation of the corresponding cortical segments of the contralateral normal kidney, respectively (p<0.01). The mean attenuation in the upper, middle, and lower segments of the inflamed renal medulla was 48%, 21%, and 30%, lower than the mean attenuation of the corresponding medullary segments of the contralateral normal kidney (p<0.02). The mean attenuation between the inflamed and non-inflamed renal cortex and medulla was 29% and 30% lower respectively (p<0.001). The AUCROC (p<0.001) analysis demonstrated significantly higher scores for pathology detection, irrespective of image quality, compared to clinical and laboratory results with an increased inter-reader agreement from poor to substantial.

CONCLUSION

Non-contrast CT showed a significant decrease in the parenchymal density of the kidney affected with APN in comparison to the contralateral normal kidney of the same patient. This can be incorporated in the diagnostic criteria of APN in NCCT in the emergency setting.

Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

PURPOSE

The authors are developing a computerized system for bladder segmentation in CT urography (CTU) as a critical component for computer-aided detection of bladder cancer.

METHODS

A deep-learning convolutional neural network (DL-CNN) was trained to distinguish between the inside and the outside of the bladder using 160 000 regions of interest (ROI) from CTU images. The trained DL-CNN was used to estimate the likelihood of an ROI being inside the bladder for ROIs centered at each voxel in a CTU case, resulting in a likelihood map. Thresholding and hole-filling were applied to the map to generate the initial contour for the bladder, which was then refined by 3D and 2D level sets. The segmentation performance was evaluated using 173 cases: 81 cases in the training set (42 lesions, 21 wall thickenings, and 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, and 13 normal bladders). The computerized segmentation accuracy using the DL likelihood map was compared to that using a likelihood map generated by Haar features and a random forest classifier, and that using our previous conjoint level set analysis and segmentation system (CLASS) without using a likelihood map. All methods were evaluated relative to the 3D hand-segmented reference contours.

RESULTS

With DL-CNN-based likelihood map and level sets, the average volume intersection ratio, average percent volume error, average absolute volume error, average minimum distance, and the Jaccard index for the test set were 81.9% ± 12.1%, 10.2% ± 16.2%, 14.0% ± 13.0%, 3.6 ± 2.0 mm, and 76.2% ± 11.8%, respectively. With the Haar-feature-based likelihood map and level sets, the corresponding values were 74.3% ± 12.7%, 13.0% ± 22.3%, 20.5% ± 15.7%, 5.7 ± 2.6 mm, and 66.7% ± 12.6%, respectively. With our previous CLASS with local contour refinement (LCR) method, the corresponding values were 78.0% ± 14.7%, 16.5% ± 16.8%, 18.2% ± 15.0%, 3.8 ± 2.3 mm, and 73.9% ± 13.5%, respectively.

CONCLUSIONS

The authors demonstrated that the DL-CNN can overcome the strong boundary between two regions that have large difference in gray levels and provides a seamless mask to guide level set segmentation, which has been a problem for many gradient-based segmentation methods. Compared to our previous CLASS with LCR method, which required two user inputs to initialize the segmentation, DL-CNN with level sets achieved better segmentation performance while using a single user input. Compared to the Haar-feature-based likelihood map, the DL-CNN-based likelihood map could guide the level sets to achieve better segmentation. The results demonstrate the feasibility of our new approach of using DL-CNN in combination with level sets for segmentation of the bladder.

Detection of urinary bladder mass in CT urography with SPAN

PURPOSE

The authors are developing a computer-aided detection system for bladder cancer on CT urography (CTU). In this study, the authors focused on developing a system for detecting masses fully or partially within the contrast-enhanced (C) region of the bladder.

METHODS

With IRB approval, a data set of 70 patients with biopsy-proven bladder lesions fully or partially immersed within the contrast-enhanced region (C region) of the bladder was collected for this study: 35 patients for the training set (39 malignant, 7 benign lesions) and 35 patients for the test set (49 malignant, 4 benign lesions). The bladder in the CTU images was automatically segmented using the authors' conjoint level set analysis and segmentation system, which they developed specifically to segment the bladder. A closed contour of the C region of the bladder was generated by maximum intensity projection using the property that the dependently layering contrast material in the bladder will be filled consistently to the same level along all CTU slices due to gravity. Potential lesion candidates within the C region contour were found using the authors' Straightened Periphery ANalysis (SPAN) method. SPAN transforms a bladder wall to a straightened thickness profile, marks suspicious pixels on the profile, and clusters them into regions of interest to identify potential lesion candidates. The candidate regions were automatically segmented using the authors' autoinitialized cascaded level set segmentation method. Twenty-three morphological features were automatically extracted from the segmented lesions. The training set was used to determine the best subset of these features using simplex optimization with the leave-one-out case method. A linear discriminant classifier was designed for the classification of bladder lesions and false positives. The detection performance was evaluated on the independent test set by free-response receiver operating characteristic analysis.

RESULTS

At the prescreening step, the authors' system achieved 84.4% sensitivity with an average of 4.3 false positives per case (FPs/case) for the training set, and 84.9% sensitivity with 5.4 FPs/case for the test set. After linear discriminant analysis (LDA) classification with the selected features, the FP rate improved to 2.5 FPs/case for the training set, and 4.3 FPs/case for the test set without missing additional true lesions. By varying the threshold for the LDA scores, at 2.5 FPs/case, the sensitivities were 84.4% and 81.1% for the training and test sets, respectively. At 1.7 FPs/case, the sensitivities decreased to 77.8% and 75.5%, respectively.

CONCLUSIONS

The results demonstrate the feasibility of the authors' method for detection of bladder lesions fully or partially immersed in the contrast-enhanced region of CTU.

A Survey of Radiation Doses in CT Urography Before and After Implementation of Iterative Reconstruction

OBJECTIVE

The purpose of this study was to survey the radiation dose used in CT urography (CTU) in routine clinical practice, both before and after implementation of a scanning protocol that uses iterative reconstruction (Adaptive Iterative Dose Reduction 3D [AIDR 3D]).

MATERIALS AND METHODS

We retrospectively surveyed dose reports from consecutive CTU examinations performed in 2011 with the use of 64- and 320-MDCT scanners that were reconstructed with filtered back projection (FBP) and from CTU examinations performed from May 2012 through November 2013 that were reconstructed with the use of AIDR 3D. Findings from these dose reports were then correlated with such patient characteristics as weight and body mass index (BMI; weight in kilograms divided by the square of height in meters). Only dose reports from single-bolus three-phase CTU examinations were included in the study. The volume CT dose index, dose-length product (DLP), and effective dose were surveyed both per examination and per phase by use of published effective dose DLP conversion factors. Image quality was evaluated subjectively for a subset of patients.

RESULTS

The two study cohorts included 82 patients (median patient weight, 75.0 kg; median BMI, 25.3) who underwent CTU with FBP and 85 patients (median patient weight, 78.0 kg; median BMI, 24.5) who underwent CTU with AIDR 3D. The median total DLP and median effective dose were 924 mGy · cm and 13.0 mSv, respectively, in the CTU with the FBP cohort and 433 mGy · cm and 6.1 mSv, respectively, in the CTU with the AIDR 3D cohort. The median DLP in the unenhanced, nephrogenic, and excretory phases was 218, 300, and 441 mGy · cm, respectively, in patients undergoing CTU with FBP and 114, 121, and 190 mGy · cm, respectively, in patients undergoing CTU with AIDR 3D. Image quality was diagnostic in both groups, with relatively fewer artifacts noted on scans obtained using CTU with AIDR 3D.

CONCLUSION

Our study presents detailed dose data from three-phase CTU examinations performed both before and after implementation of iterative reconstruction. Implementation of a CTU protocol using iterative reconstruction resulted in a mean effective dose of 6.1 mSv with preservation of clinical diagnostic image quality.

Ureter tracking and segmentation in CT urography (CTU) using COMPASS

PURPOSE

The authors are developing a computerized system for automated segmentation of ureters in CTU, referred to as combined model-guided path-finding analysis and segmentation system (COMPASS). Ureter segmentation is a critical component for computer-aided diagnosis of ureter cancer.

METHODS

COMPASS consists of three stages: (1) rule-based adaptive thresholding and region growing, (2) path-finding and propagation, and (3) edge profile extraction and feature analysis. With institutional review board approval, 79 CTU scans performed with intravenous (IV) contrast material enhancement were collected retrospectively from 79 patient files. One hundred twenty-four ureters were selected from the 79 CTU volumes. On average, the ureters spanned 283 computed tomography slices (range: 116-399, median: 301). More than half of the ureters contained malignant or benign lesions and some had ureter wall thickening due to malignancy. A starting point for each of the 124 ureters was identified manually to initialize the tracking by COMPASS. In addition, the centerline of each ureter was manually marked and used as reference standard for evaluation of tracking performance. The performance of COMPASS was quantitatively assessed by estimating the percentage of the length that was successfully tracked and segmented for each ureter and by estimating the average distance and the average maximum distance between the computer and the manually tracked centerlines.

RESULTS

Of the 124 ureters, 120 (97%) were segmented completely (100%), 121 (98%) were segmented through at least 70%, and 123 (99%) were segmented through at least 50% of its length. In comparison, using our previous method, 85 (69%) ureters were segmented completely (100%), 100 (81%) were segmented through at least 70%, and 107 (86%) were segmented at least 50% of its length. With COMPASS, the average distance between the computer and the manually generated centerlines is 0.54 mm, and the average maximum distance is 2.02 mm. With our previous method, the average distance between the centerlines was 0.80 mm, and the average maximum distance was 3.38 mm. The improvements in the ureteral tracking length and both distance measures were statistically significant (p < 0.0001).

CONCLUSIONS

COMPASS improved significantly the ureter tracking, including regions across ureter lesions, wall thickening, and the narrowing of the lumen.

Ureteral Dilatation with No Apparent Cause on Intravenous Urography: Normal or Abnormal? A Pilot Study

A pilot study was done in 18 adults to assess the significance of ureteral dilatation having no apparent cause seen on Intravenous Urography (IVU). A clinicoradiological evaluation was undertaken to evaluate the cause of ureteral dilatation, including laboratory investigations and sonography of the genitourinary tract. This was followed, if required, by CT Urography (using a modified technique). In 9 out of 18 cases, the cause of ureteral dilatation on laboratory investigations was urinary tract infection (6) and tuberculosis (3). In the remaining 9 cases, CTU identified the cause as extrinsic compression by a vessel (3), extrinsic vascular compression of the ureter along with ureteritis (2), extrinsic vascular impression on the right ureter and ureteritis in the left ureter (1), ureteral stricture (2), and ureteral calculus (1). Extrinsic vascular compression and strictures did not appear to be clinically significant in our study. Hence, ureteral dilatation without any apparent cause on intravenous urogram was found to be clinically significant in 12 out of 18 (66.6%) cases. We conclude that ureteral dilatation with no apparent cause on IVU may indicate urinary tract tuberculosis, urinary tract infection (E. coli), or a missed calculus. Thus, cases with a dilated ureter on IVU, having no obvious cause, should undergo a detailed clinicoradiological evaluation and CTU should be used judiciously.

Added Value of Using a CT Coronal Reformation to Diagnose Adnexal Torsion

Objective

To evaluate the increased value of using coronal reformation of a transverse computed tomography (CT) scan for detecting adnexal torsion.

Materials and Methods

This study included 106 woman suspected of having adnexal torsion who underwent CT with coronal reformations and subsequent surgical exploration. Two readers independently recorded the CT findings, such as the thickening of a fallopian tube, twisting of the adnexal pedicle, eccentric smooth wall thickening of the torsed adnexal mass, eccentric septal thickening of the torsed adnexal mass, eccentric poor enhancement of the torsed adnexal mass, uterine deviation to the twisted side, ascites or infiltration of pelvic fat, and the overall impression of adnexal torsion with a transverse scan alone or combined with coronal reformation and a transverse scan. The areas under the receiver operating characteristic curves (AUCs), sensitivity, specificity, and positive predictive value were used to compare diagnostic performance.

Results

Fifty-two patients were confirmed to have adnexal torsion. The addition of coronal reformations to the transverse scan improved AUCs for readers 1 and 2 from 0.74 and 0.75 to 0.92 and 0.87, respectively, for detecting adnexal torsion (p < 0.001 and p = 0.004, respectively). Sensitivity of CT for detecting twisting of the adnexal pedicle increased significantly for readers 1 and 2 from 0.27 and 0.29 with a transverse scan alone to 0.79 and 0.77 with a combined coronal reformation and a transverse scan, respectively (p < 0.001 and p < 0.001, respectively).

Conclusion

Use of a coronal reformation with transverse CT images improves detection of adnexal torsion.

Urinary bladder segmentation in CT urography (CTU) using CLASS

PURPOSE

The authors are developing a computerized system for bladder segmentation on CTU, as a critical component for computer aided diagnosis of bladder cancer.

METHODS

A challenge for bladder segmentation is the presence of regions without contrast (NC) and filled with intravenous contrast (C). The authors have designed a Conjoint Level set Analysis and Segmentation System (CLASS) specifically for this application. CLASS performs a series of image processing tasks: preprocessing, initial segmentation, 3D and 2D level set segmentation, and postprocessing, designed according to the characteristics of the bladder in CTU. The NC and the C regions of the bladder were segmented separately in CLASS. The final contour is obtained in the postprocessing stage by the union of the NC and C contours. With Institutional Review Board (IRB) approval, the authors retrospectively collected 81 CTU scans, in which 40 bladders contained lesions, 26 contained diffuse wall thickening, and 15 were considered to be normal. The bladders were segmented by CLASS and the performance was assessed by rating the quality of the contours on a 10-point scale (1 = "very poor," 5 = "fair," 10 = "perfect"). For 30 bladders, 3D hand-segmented contours were obtained and the segmentation accuracy of CLASS was evaluated and compared to that of a single level set method in terms of the average minimum distance, average volume intersection ratio, average volume error and Jaccard index.

RESULTS

Of the 81 bladders, the average quality rating for CLASS was 6.5 ± 1.3. Thirty nine bladders were given quality ratings of 7 or above. Only five bladders had ratings under 5. The average minimum distance, average volume intersection ratio, average volume error, and average Jaccard index for CLASS were 3.5 ± 1.3 mm, (79.0 ± 8.2)%, (16.1 ± 16.3)%, and (75.7 ± 8.4)%, respectively, and for the single level set method were 5.2 ± 2.6 mm, (78.8 ± 16.3)%, (8.3 ± 33.1)%, (71.0 ± 15.4)%, respectively.

CONCLUSIONS

The results demonstrate the potential of CLASS for segmentation of the bladder.

CT urography: segmentation of urinary bladder using CLASS with local contour refinement

We are developing a computerized system for bladder segmentation on CT urography (CTU), as a critical component for computer-aided detection of bladder cancer. The presence of regions filled with intravenous contrast and without contrast presents a challenge for bladder segmentation. Previously, we proposed a conjoint level set analysis and segmentation system (CLASS). In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast-filled (C) region separately and automatically conjoins the NC and C region contours; however, inaccuracies in the NC and C region contours may cause the conjoint contour to exclude portions of the bladder. To alleviate this problem, we implemented a local contour refinement (LCR) method that exploits model-guided refinement (MGR) and energy-driven wavefront propagation (EDWP). MGR propagates the C region contours if the level set propagation in the C region stops prematurely due to substantial non-uniformity of the contrast. EDWP with regularized energies further propagates the conjoint contours to the correct bladder boundary. EDWP uses changes in energies, smoothness criteria of the contour, and previous slice contour to determine when to stop the propagation, following decision rules derived from training. A data set of 173 cases was collected for this study: 81 cases in the training set (42 lesions, 21 wall thickenings, 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, 13 normal bladders). For all cases, 3D hand segmented contours were obtained as reference standard and used for the evaluation of the computerized segmentation accuracy. For CLASS with LCR, the average volume intersection ratio, average volume error, absolute average volume error, average minimum distance and Jaccard index were 84.2 ± 11.4%, 8.2 ± 17.4%, 13.0 ± 14.1%, 3.5 ± 1.9 mm, 78.8 ± 11.6%, respectively, for the training set and 78.0 ± 14.7%, 16.4 ± 16.9%, 18.2 ± 15.0%, 3.8 ± 2.3 mm, 73.8 ± 13.4% respectively, for the test set. With CLASS only, the corresponding values were 75.1 ± 13.2%, 18.7 ± 19.5%, 22.5 ± 14.9%, 4.3 ± 2.2 mm, 71.0 ± 12.6%, respectively, for the training set and 67.3 ± 14.3%, 29.3 ± 15.9%, 29.4 ± 15.6%, 4.9 ± 2.6 mm, 65.0 ± 13.3%, respectively, for the test set. The differences between the two methods for all five measures were statistically significant (p < 0.001) for both the training and test sets. The results demonstrate the potential of CLASS with LCR for segmentation of the bladder.

MDCT of Small Bowel Obstruction: How Reliable Are Oblique Reformatted Images in Localizing Point of Transition?

The goal of this study is to prospectively assess the additional value of oblique reformatted images for localizing POT, having surgery as a reference standard. Materials and Methods. 102 consecutive patients with suspected small bowel obstruction (SBO) underwent 64-slice multidetector row CT (MDCT) using surgical findings as reference standard. Two independent GI radiologists reviewed the CT scans to localize the exact POT by evaluating axial images (data set A) followed by axial, coronal, and oblique MPR images. CT findings were compared to surgical findings in terms of diagnostic performance. McNemar's test was used to detect any statistical difference in POT evaluation between datasets A and B. Kappa statistics were applied for measuring agreement between two readers. Results. There was a diagnostic improvement of 9.9% in the case of the less experienced radiologist in localizing POT by using oblique reformatted images. The more experienced radiologist showed diagnostic improvement by 12.9%.

Performance of computed tomographic urography for the detection of bladder tumors in patients with microscopic hematuria

OBJECTIVE

Our objective was to evaluate the sensitivity, specificity, predictive value, and accuracy of computed tomographic urography for the detection of bladder tumors in patients with microscopic hematuria.

MATERIAL AND METHODS

Patients with microscopic hematuria initially evaluated with computed tomography and cystoscopy from January 2006 to December 2009 were evaluated. Computed tomography detecting a bladder lesion suspicious of malignancy was considered positive. Cystoscopy was classified as positive when a lesion requiring biopsy or resection was found. Performance characteristics of computed tomography were determined by comparing with cystoscopic and pathological findings.

RESULTS

A total of 112 patients were eligible for analysis. Seven tumors were found on cystoscopy; of these, 2 were correctly diagnosed by computed tomography and 5 were missed. An additional case was considered erroneously positive. The results are a sensitivity of 29%, specificity of 99%, positive predictive value of 67%, negative predictive value of 95%, and accuracy of 95%.

CONCLUSIONS

Although computed tomography has a high specificity its sensitivity is limited. For this reason conventional cystoscopy should be considered the standard for bladder evaluation of patients with microscopic hematuria.

Segmentation of urinary bladder in CT urography

We are developing a Conjoint Level set Analysis and Segmentation System (CLASS) for bladder segmentation on CTU, which is a critical component for computer aided diagnosis of bladder cancer. A challenge for bladder segmentation is the presence of regions without contrast (NC) and filled with IV contrast (C). According to the characteristics of the bladder in CTU, CLASS is designed to perform number tasks such as preprocessing, initial segmentation, 3D and 2D level set segmentation and post-processing. CLASS segments separately the NC and the C regions of the bladder. In the post-processing stage the final contour is obtained based on the union of the NC and C contours. 70 bladders were segmented. Of the 70 bladders 31 contained lesions, 24 contained wall thickening, and 15 were normal. The performance of CLASS was assessed by rating the quality of the contours on a 5-point scale (1="very poor", 3="fair", 5="excellent"). The average quality ratings for the 12 completely no contrast (NC) and 5 completely contrast-filled (C) bladder contours were 3.3±1.0 and 3.4±0.5, respectively. The average quality ratings for the 53 NC and 53 C regions of the 53 partially contrast-filled bladders were 4.0±0.7 and 4.0±1.0, respectively. Quality ratings of 4 or above were given for 87% (46/53) NC and 77% (41/53) C regions. Only 4% (2/53) NC and 9% (5/53) C regions had ratings under 3. After combining the NC and C contours for each of the 70 bladders, 66% (46/70) had quality ratings of 4 or above. Only 6% (4/70) had ratings under 3. The average quality rating was 3.8±0.7. The results demonstrate the potential of CLASS for automated segmentation of the bladder.

Auto-initialized cascaded level set (AI-CALS) segmentation of bladder lesions on multidetector row CT urography

RATIONALE AND OBJECTIVES

To develop a computerized system for segmentation of bladder lesions on computed tomography urography (CTU) scans for detection and characterization of bladder cancer.

MATERIALS AND METHODS

We have developed an auto-initialized cascaded level set method to perform bladder lesion segmentation. The segmentation performance was evaluated on a preliminary dataset including 28 CTU scans from 28 patients collected retrospectively with institutional review board approval. The bladders were partially filled with intravenous contrast material. The lesions were located fully or partially within the contrast-enhanced area or in the non-contrast-enhanced area of the bladder. An experienced abdominal radiologist marked 28 lesions (14 malignant and 14 benign) with bounding boxes that served as input to the automated segmentation system and assigned a difficulty rating on a scale of 1 to 5 (5 = most subtle) to each lesion. The contours from automated segmentation were compared to three-dimensional contours manually drawn by the radiologist. Three performance metric measures were used for comparison. In addition, the automated segmentation quality was assessed by an expert panel of two experienced radiologists, who provided quality ratings of the contours on a scale from 1 to 10 (10 = excellent).

RESULTS

The average volume intersection ratio, the average absolute volume error, and the average distance measure were 67.2 ± 16.9%, 27.3 ± 26.9%, and 2.89 ± 1.69 mm, respectively. Of the 28 segmentations, 18 were given quality ratings of 8 or above. The average rating was 7.9 ± 1.5. The average quality ratings for lesions with difficulty ratings of 1, 2, 3, and 4 were 8.8 ± 0.9, 7.9 ± 1.8, 7.4 ± 0.9, and 6.6 ± 1.5, respectively.

CONCLUSION

Our preliminary study demonstrates the feasibility of using the three-dimensional level set method for segmenting bladder lesions in CTU scans.

Usefulness of computed tomography performed immediately after excretory urography in patients with delayed opacification or dilated upper urinary tract of unknown cause

PURPOSE

To evaluate the diagnostic value of computed tomography (CT) performed immediately after excretory urography (EU) in patients with delayed renal opacification or dilated upper urinary system with nonconclusive diagnosis after EU.

MATERIALS AND METHODS

CT was performed immediately after EU in 39 patients with delayed opacification or dilated upper urinary system of unknown cause, without additional intravenous contrast administration for the CT study. We classified EU + CT findings as benign or malignant causes and we compared our results with the final diagnosis.

RESULTS

The combination of EU + CT correctly diagnosed 38 out of the 39 cases with a sensitivity of 97%. Correct diagnosis was established in all malignant cases (n = 17) but one benign case consistent with blood clots in the upper urinary tract was incorrectly diagnosed as a multicentric urothelial carcinoma. Sensitivity, specificity, and accuracy for the diagnosis of the underlying cause with EU + CT was 100%, 95%, and 97%, respectively. The final diagnoses were: urothelial carcinoma (n = 10), stone disease (n = 10), bladder tumor (n = 4), benign post-treatment ureteral stenosis (n = 4), ureteral invasion (n = 3), benign bladder disease (n = 2), urinary tract infections (n = 2), crossing vessels (n = 1), ureteropelvic junction obstruction (n = 1), retrocaval ureter (n = 1), and blood clots in the upper urinary tract due to bleeding renal metastasis from lung cancer (n = 1).

CONCLUSION

Combined EU and CT study allowed correct diagnosis of the underlying cause of delayed excretion or upper urinary tract dilatation in 97% of cases. The combination of EU and CT provides diagnosis reducing time and radiation.

Contrast-material-enhanced MR urography in evaluation of postoperative lower urinary tract fistulae and leakages

Urinary fistulas and leakages of lower urinary tract are serious complications of various surgical procedures. Radiologists need to have enough information about these situations to perform precise diagnosis and treatment. Various techniques [such as intravenous pyelography, ultrasound, computed tomography (CT), CT urography, cystoscopy, cystography and magnetic resonance (MR) imaging] are used for the diagnosis of these conditions. Application of all these techniques reduces the comfort and cooperation of the patients and increases the cost. Here we present four postoperative patients with lower urinary tract fistula or leakage. To the best of our knowledge, there is no report regarding the use of contrast-material-enhanced MR urography (CE-MRU) in the demonstration of postoperative lower urinary tract fistulae and leakages. In conclusion, CE-MRU could show the existence and location of the urinary fistulae and leakages clearly without the need for another investigation technique, as described in our patients. Also, CE-MRU is a safe and relatively inexpensive technique that avoids exposure to radiation as well as nephrotoxic and more allergic contrast-material administration.

High prevalence of upper urinary tract involvement detected by 111indium-oxine leukocyte scintigraphy in patients with candiduria

The purpose of this investigation was to assess the prevalence of upper urinary tract involvement in patients with candiduria by means of (111)indium-oxine-labeled leukocyte scintigraphy. An observational cohort study of patients with confirmed candiduria was conducted in an acute-care teaching hospital in Spain from March 2006 through February 2009. An (111)In-labeled leukocyte scan was performed in order to assess the upper urinary tract involvement. A series of non-matched patients without candiduria nor bacteriuria undergoing scintigraphy to exclude infections in other sites than the urinary tract was also studied. Demographics, baseline illness, and clinical data were recorded. Candiduria was detected in 428 patients, and scintigraphy was performed in 35 of these patients. Twenty-nine patients without candiduria nor bacteriuria were also studied. Positive renal scintigraphy was documented in 24 (68%) patients with confirmed candiduria and in 3 (10%) patients without candiduria (p < 0.005). Renal uptake was not associated with a higher mortality nor with re-admissions. Subclinical pyelonephritis could be more frequent in patients with candiduria than it has been previously considered.

Influence of multiplanar reformations on low-contrast performance in thin-collimated multidetector computed tomography

OBJECTIVES

: To analyze the influence of multiplanar reformations of thin-collimated multidetector computed tomography datasets on low-contrast performance.

MATERIALS AND METHODS

: A low-contrast phantom simulating focal hypodense lesions (-20 HU object contrast) was scanned on a 64-slice spiral CT scanner at 4 different dose levels (25 mAs, 50 mAs, 100 mAs, 200 mAs, and no dose modulation). Other scanner parameters were as follows: tube voltage = 120 kVp, rotation time = 0.8 s, reconstructed slice thickness = 0.625 mm, reconstruction interval = 0.5 mm, reconstruction kernel = standard. Coronal reformations were created using the open-source software OsiriX. A sliding-thin-slab (STS) averaging algorithm was applied to each axial and each reformatted dataset with an increasing slab thickness from 1 to 20 slices. The low-contrast performance of all datasets was calculated semiautomatically using a reader-independent, statistical approach and is expressed as the visibility index. The results were analyzed for differences between the coronal reformations and the original axial datasets. In addition, the statistical approach used herein was validated against a reader study.

RESULTS

: The visibility index of the coronal reformatted datasets over all lesion sizes was inferior when compared with the original axial datasets and reached 75.4% (±11.7%), 79.9% (±16.3%), 79.4% (±5.5%), and 93.7% (±14.6%) for dose levels of 25, 50, 100, and 200 mAs, respectively. The overall mean low-contrast performance was 82.1% of the axial dataset (P < 0.05, except for 200 mAs). The deterioration of low-contrast performance was inversely correlated with lesion size (R = 0.91). The use of the STS averaging algorithm significantly improved image quality for all datasets (112.6%-180.2%) with the beneficial effect being stronger for the coronal reformations. There was no statistically significant difference in the evaluation of low-contrast performance between the statistical approach and the ready study.

CONCLUSION

: Coronal reformations of thin-collimated multidetector computed tomography datasets show a significant reduction of low-contrast performance when compared with the original axial dataset, especially in high noise data. The use of an STS averaging algorithm had a significant benefit for both, coronal and axial orientations. The effect was more pronounced with coronal reformations and should be routinely applied to improve image quality.

Acute Pyelonephritis and Renal Abscesses in Adults—Correlating Clinical Parameters with Radiological (Computer Tomography) Severity

Introduction: The aim of this study is to evaluate the correlations between clinical and biochemical parameters with radiological severity of CT diagnosed acute pyelonephritis (APN) and renal abscesses, thereafter defining clinical predictors to identify patients with severe APN or renal abscesses. Materials and Methods: The inpatient medical records of all patients diagnosed with APN or renal abscesses admitted over one year were reviewed. Patients with CT imaging performed were classified into 3 groups—mild APN, severe APN and renal abscesses. Clinical and biochemical parameters were correlated with radiological severity. Results: One hundred and thirty patients were included in the study. Male gender, older age, presence of diabetes mellitus and unobstructing renal stones were significantly associated with severe APN or renal abscesses. Clinical and biochemical parameters that were associated with more severe disease include a higher leucocyte count and C-reactive proteins, left neutrophil shift, thrombocytosis or thrombocytopenia, low serum albumin, acute renal impairment and bacteremia. The percentage of patients had positive urine and blood cultures were 40.8% and 30.7% respectively. Of these patients, 97.9% had severe APN or renal abscesses on CT imaging had diabetes mellitus (DM), hypotension, acute renal failure or leucocyte count of >20K. Conclusion: Our study showed a good correlation between clinical and radiological severity in adult patients with APN and renal abscesses. Patients with severe APN or renal abscesses were likely to be diabetics presenting with hypotension, acute renal impairment and a leucocyte count of greater than 20K. Key words: Computer topography (CT), Pyelonephritis, Renal abscess, Severity

Accuracy and factors affecting the outcome of multi-detector computerized tomography urography for bladder tumors in the clinical setting

Purpose

The objective of this study was to investigate the diagnostic accuracy of multi-detector computerized tomography urography (MDCTU) for the detection of bladder tumors.

Materials and Methods

We retrospectively reviewed the medical records of 143 patients who were scanned by use of 64-channel MDCTU and who underwent cystoscopy due to painless hematuria or a clinical suspicion of bladder tumor. We examined the accuracy of MDCTU for the detection of bladder tumors by comparing the results obtained by MDCTU with those obtained by cystoscopy. The associations between tumor characteristics, frequency of transurethral resection (TUR), and bladder volume and detectability of bladder tumors on MDCTU were also analyzed.

Results

Of 143 patients, 50 patients had a history of urothelial carcinomas. In these patients, the sensitivity and specificity of MDCTU were 60.0% and 80.0%, respectively. In 93 patients without previous urothelial carcinomas, the sensitivity and specificity of MDCTU were 86.7% and 96.8%, respectively. Falsely diagnosed cases had a smaller distended bladder volume (p=0.014) and a smaller tumor size (p=0.022) than did true diagnosed cases. The false-negative rate increased when the bladder tumor was located at the bladder neck. In the univariate analysis, the tumor location, size, frequency of TUR, bladder volume, and initial hematuria were associated with detectability by MDCTU (p<0.05).

Conclusions

To improve the accuracy of MDCTU for diagnosing bladder tumors, bladder filling is recommended. Thus, cystoscopy should be considered as a standard diagnostic tool for bladder tumors even in patients with normal MDCTU results, especially in the evaluation of recurrent, bladder neck-located, small, or sessile bladder tumors.

[The ureters: findings at multidetector computed tomography]

Multidetector computed tomography (MDCT) and advances in CT urography techniques have enabled vast improvements in the depiction of the ureter. Studies of the ureter can find a wide variety of conditions including congenital defects and anatomic variants (anomalies in the origin, distribution, and distal insertion of the ureter) as well as all benign and malignant causes of focal and diffuse wall thickening (inflammatory and infectious processes, and neoplasms, as well as iatrogenic thickening and postsurgical changes). Other benign processes like ureteral kinking and stenosis due to extrinsic compression of the iliac vessels are also well characterized by MDCT. The aim of this article is to show the spectrum of ureteral variants and disease apart from common entities related to stones.

The role of emergency ultrasound for evaluating acute pyelonephritis in the ED

BACKGROUND

Controversy remains over the imaging method of choice for evaluating acute pyelonephritis (APN) in the emergency department (ED).

OBJECTIVE

The aim of the study was to determine the efficacy of ultrasound in the diagnosis and management of patients presented to the ED with APN.

METHODS

This was a retrospective study of prospectively collected data. A cohort of ED patients diagnosed as APN were prospectively registered, and their medical records were then retrospectively reviewed for the presence of complications (admitted >14 days, admission to intensive care unit, or received invasive procedures), significant abnormalities (hydronephrosis, polycystic kidney diseases, renal abscess, emphysematous pyelonephritis), and mild abnormalities (cysts, stones, swelling).

RESULTS

The study included 243 patients. Most of the patients received one or more renal imaging studies (n = 206) and 39.5% of which were considered abnormal. The rates of significant abnormalities on different imaging methods were Kidney-ureter-bladder (KUB), 16.3%; emergency ultrasound (EUS), 39.6%; combination of KUB and EUS, 56.6%; and computed tomography, 58.8%. Factors contributed to complicated APN were elderly, male, a history of preexisting renal diseases, current use of catheters, previous renal calculi, and diabetes mellitus. Significant abnormalities can be identified by EUS in 61% of patients with complicated APN. In fact, the presence of significant sonographic abnormalities effectively diverted 34.3% of patients to receive surgical interventions (percutaneous nephrostomy, abscess aspiration, ureteroscopic stone manipulation, lithotripsy, or nephrectomy).

CONCLUSION

Structural abnormalities are not uncommon in ED patients with APN. Early assessment of these patients with EUS is likely to have a great impact on their diagnosis and management.

Imaging in percutaneous nephrolithotomy

Image guidance is a critical factor for the performance of urologic interventions. Percutaneous minimally invasive procedures have been developed and are being used with constantly increasing frequency. Procedures such as percutaneous nephrolithotomy (PCNL) are not performed without any image guidance. Recent developments in medical imaging, such as three-dimensional radiographic fluoroscopy, CT, and magnetic resonance (MR) fluoroscopy, four-dimensional ultrasonography, and image fusion techniques, propose a new generation of image-guidance tools that promise to improve patient care. These developments have been used or have the potential to be used in PCNL and other urologic interventional procedures. Moreover, advanced needles and needle guidance systems provide a new perspective for the nephrolithotomy suite of the future. The current review presents existing imaging technology in PCNL and interventional urology as well as advanced imaging techniques that are being or are expected to be evaluated in PCNL practice.

MDCT Urography: Exploring a new paradigm for imaging of bladder cancer

OBJECTIVE

The purpose of this article is to review the epidemiology, staging, and treatment of bladder cancer; to discuss the role of MDCT urography for the evaluation of patients with known or suspected bladder cancer; and to address the role of MDCT urography in patients who require follow-up imaging after a diagnosis of bladder cancer has been made.

CONCLUSION

MDCT urography now has a large role in the evaluation of patients with known and suspected bladder cancer. However, its precise role has not been established. Because many bladder neoplasms will not be detected by MDCT urography and more research is needed to determine the optimal technique for diagnosing bladder cancer, we think that MDCT urography cannot replace cystoscopy at present.

Imaging of hematuria

Hematuria may have a number of causes, of which the more common are urinary tract calculi, urinary tract infection, urinary tract neoplasms (including renal cell carcinoma and urothelial tumors), trauma to the urinary tract, and renal parenchymal disease. This article discusses the current status of imaging of patients suspected of having urologic causes of hematuria. The role of all modalities, including plain radiography, intravenous urography or excretory urography, retrograde pyelography, ultrasonography, and multidetector computed tomography (MDCT) in evaluation of these patients is discussed. The article highlights the current status of MDCT urography in imaging of patients with hematuria, and discusses various-often controversial-issues, such as optimal protocol design, accuracy of the technique in imaging of the urothelium, and the significant issue of radiation dose associated with MDCT urography.

Influence of bladder distension on opacification of urinary collecting system during CT urography

The purpose of the study was to evaluate and compare opacification of the renal collecting system and ureters detected by computed tomographic urography (CTU) performed 20 min and 1 h after the ingestion of 1,000 ml of water. CTU was performed on 89 patients (55 men, 34 women; age 28-77 years) and 168 collecting systems and ureters were evaluated. A 16-detector-row scanner (Sensation 16, Siemens) was used; a two-phase protocol with a split bolus of contrast agent (total 120 ml) was applied. A combined nephrographic-excretory phase was obtained 100 s after the second injection. Three-dimensional reconstructions of the excretory phase were created and used to evaluate the degree of opacification of the collecting system and ureters. In 44 patients, water was administered 20 min before examination, and in 45 patients, 1 h before examination. CTU performed 1 h after water ingestion demonstrated complete opacification of calices in 87.5%, of renal pelvis in 97.5%, of upper ureter in 91.8% and of lower ureter in 87.5% of patients. CTU performed 20 min after water ingestion demonstrated complete opacification of calices in 79.5%, of renal pelvis in 85%, of upper ureter in 62.5% and of lower ureter in 54.5% of patients. Complete opacification of the proximal and distal ureter in the group with a 1-h delay was statistically higher (P<0.01). CTU performed on the distended bladder, 1 h after the oral ingestion of water, enables excellent opacification of collecting system, including distal ureters.

Multidetector computerized tomography urography as the primary imaging modality for detecting urinary tract neoplasms in patients with asymptomatic hematuria

PURPOSE

We determined whether multidetector computerized tomography urography is sensitive and specific for detecting urinary tract neoplasms when used as the primary imaging modality for evaluating patients with hematuria.

MATERIALS AND METHODS

A retrospective review was performed of the radiological, urological and pathological records of 468 patients without a history of urinary neoplasms who presented with hematuria. All patients underwent multidetector computerized tomography urography and complete urological evaluation, including cystoscopy. Laboratory urinalysis and cytology were done in 350 and 318 of the 468 patients, respectively. Multivariate logistic regression analysis was performed using the variables multidetector computerized tomography urography diagnosis, worst urine cytology, number of red blood cells per high power field, gross hematuria, age and gender to predict urinary tract neoplasm.

RESULTS

A total of 50 urinary neoplasms were diagnosed in 468 patients. Multidetector computerized tomography urography detected 32 of 50 neoplasms for a sensitivity of 64%, specificity of 98%, positive predictive value of 76% and negative predictive value of 96%. There were 10 false-positive and 18 false-negative multidetector computerized tomography urography studies. Multivariate logistic regression showed that abnormal multidetector computerized tomography urography findings, ie neoplasm (p <0.0001), and suspicious or positive urine cytology (p = 0.0009) were significant. Patients with an abnormal multidetector computerized tomography urography diagnosis and suspicious or positive urine cytology had 44 and 47 times greater odds, respectively, of having urinary neoplasms compared to the odds in those with normal examinations.

CONCLUSIONS

Multidetector computerized tomography urography is relatively sensitive and highly specific for detecting urinary neoplasms. It may serve as the primary imaging modality to evaluate patients with hematuria. Multidetector computerized tomography urography does not eliminate the role of cystoscopy in the evaluation of hematuria.

Contrast medium induced nephropathy in urological practice

PURPOSE

Contrast medium induced nephropathy is the third cause of in-hospital acute renal failure. The first studies in this area were done with reference to urological practice only. Although various guidelines on the management of contrast medium induced nephropathy were provided by the European Society of Urogenital Radiology, more recently many investigators have focused their attention on contrast medium use in interventional vascular radiology and cardiology. We critically reviewed the literature to clarify the impact of contrast medium induced nephropathy in urology and the possible prophylactic measures against it.

MATERIALS AND METHODS

A MEDLINE/PubMed, EMBASE and Cochrane Library search for 1971 to 2006 was performed. All articles related to the use of contrast medium in urological practice and contrast medium induced nephropathy were reviewed.

RESULTS

Many pathological conditions frequently seen by urologists are diagnosed by imaging requiring contrast medium. A basic understanding of the risk factors for contrast medium induced nephropathy and the strategies for its prevention are useful to prepare urological patients for these procedures. Prophylaxis includes the discontinuation of potentially nephrotoxic drugs and the use of protocols for periprocedural hydration.

CONCLUSIONS

The general approach to the recognition and prevention of contrast medium induced nephropathy in patients at risk should be extended to urological clinical practice since no definitive evidence based data are available regarding contrast medium induced nephropathy management in urological patients. Moreover, these patients can frequently present with the most significant risk factor for contrast medium mediated kidney damage, that is preexisting acute or chronic renal failure. Controlled trials are needed to establish the incidence of contrast medium induced nephropathy in diagnostic or interventional procedures in uroradiology.

Value of automated coronal reformations from 64-section multidetector row computerized tomography in the diagnosis of urinary stone disease

PURPOSE

We determined the value of automated coronal reformation using 64-detector computerized tomography for the detection of urinary stones.

MATERIALS AND METHODS

A total of 72 patients underwent unenhanced 64-detector computerized tomography to diagnose urinary stones. Two radiologists independently reviewed coronal reformations and axial images at separate reading sessions. The stone detection rate, reader confidence and interpretation time per radiologist were recorded. Two radiologists reviewed coronal and axial images in consensus and served as the reference standard.

RESULTS

A total of 175 stones were diagnosed by consensus. Using coronal reformations 162 stones (92.6%) were detected by reader 1 and 157 (89.7%) were detected by reader 2. Using axial images 157 stones (90.3%) were detected by reader 1 and 155 (88.6%) were detected by reader 2. The reading time of coronal reformations was significantly shorter than that of axial images for each reader (p <0.01). Using coronal imaging to complement axial imaging 12 additional stones were detected and 23 were diagnosed with increased confidence by reader 1, while an additional 15 were detected and 8 were diagnosed with increased confidence by reader 2. The mean size of stones detected with coronal reformations alone was significantly smaller than that of the total stones. Excellent interobserver agreement was noted for coronal reformations and axial images (kappa coefficient: 0.91 and 0.904, respectively).

CONCLUSIONS

Review of automated coronal reformations allows equally accurate and more rapid detection of urinary stones compared with axial images alone. In addition, coronal reformation of 64-detector computerized tomography adds value when used in conjunction with axial data sets.

Accuracy of intermediate dose of furosemide injection to improve multidetector row CT urography

OBJECTIVE

Evaluate the usefulness of intermediate dose furosemide to improve visualization of the intrarenal collecting system and ureter using MDCTU.

MATERIALS AND METHODS

Two groups of 100 patients without urinary tract disease or major abdominal pathology underwent MDCTU. Group I (various abdominal indications) was performed without any additional preparation and Group II (suspicion of urinary tract disease) 10 min after injection of furosemide (20mg). MIP images of the excretory phase were post-processed. Maximal short-axis diameter of the pelvis and ureter were measured on axial images for all phases. Visualization of the collecting system wall and the identification of the whole ureter were assessed.

RESULTS

Mean pelvic diameter before contrast was (7.4mm, S.D.+/-2.7; 13.4mm, S.D.+/-4.1), on cortico-medullary phase (8.4mm, S.D.+/-4.2; 14.3mm, S.D.+/-4), on nephrographic phase (8.1mm, S.D.+/-2.5; 14.8mm, S.D.+/-4) and on excretory phase (9.7 mm, S.D.+/-3.4; 14.9 mm, S.D.+/-4.5), respectively, for Groups I and II. Intrarenal collecting system wall was clearly identified on both corticomedullary and nephrographic phases in 91% of Group II against 20% of Group I. Opacification of the entire ureter was excellent on excretory phase in 96% of Group II against 13% of Group I. The difference between the mean values for the two groups was statistically significant for all phases (p<10(-9)).

CONCLUSION

Intermediate-dose furosemide (20mg) before MDCTU is a very simple add-on for accurate depiction of pelvicalyceal details and collecting system wall without artefacts. The procedure is associated with a constant and complete visualisation of the entire urete.

Multidetector computed tomography urography for diagnosing upper urinary tract urothelial tumour

OBJECTIVE

To evaluate multidetector computed tomography urography (MDCTU) for diagnosing upper urinary tract (UUT) urothelial tumour by comparison with retrograde ureteropyelography (RUP).

PATIENTS AND METHODS

MDCTU and RUP were used in a selected series of adult patients presenting with haematuria. Entry criteria were based on findings on intravenous urography and were chosen to ensure a high prevalence of UUT urothelial tumour to allow a valid retrospective comparison of the diagnostic techniques. MDCTU and RUP studies were scored for the presence and absence of UUT urothelial tumour by two radiologists, retrospectively and independently, and while unaware of the demographic and clinical information. The reference standards were the histopathology and clinical follow-up.

RESULTS

MDCTU and RUP were used in 106 patients over a 24-month period. RUP was attempted in 151 of 212 UUTs; the corresponding MDCTU for each UUT was reviewed. MDCTU was a true-positive (TP) for urothelial tumour in 31, true-negative (TN) in 111, false-positive (FP) in eight and false-negative (FN) in one UUT, giving a sensitivity of 0.97, a specificity of 0.93, a positive predictive value (PPV) of 0.79 and a negative PV (NPV) of 0.99. RUP was technically successful and diagnostic in 96% of the UUTs (143/151). For diagnosing urothelial tumour, RUP was TP in 26, TN in 112, FP in four and FN in one UUT, giving a sensitivity of 0.97, specificity of 0.93, a PPV of 0.79 and NPV of 0.99.

CONCLUSION

This study validates quantitatively the use of MDCTU for diagnosing UUT urothelial tumour.