Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors

Accurate survival prediction for bladder cancer patients who have undergone radical cystectomy can improve their treatment management. However, the existing predictive models do not take advantage of both clinical and radiological imaging data. This study aimed to fill this gap by developing an approach that leverages the strengths of clinical (C), radiomics (R), and deep-learning (D) descriptors to improve survival prediction. The dataset comprised 163 patients, including clinical, histopathological information, and CT urography scans. The data were divided by patient into training, validation, and test sets. We analyzed the clinical data by a nomogram and the image data by radiomics and deep-learning models. The descriptors were input into a BPNN model for survival prediction. The AUCs on the test set were (C): 0.82 ± 0.06, (R): 0.73 ± 0.07, (D): 0.71 ± 0.07, (CR): 0.86 ± 0.05, (CD): 0.86 ± 0.05, and (CRD): 0.87 ± 0.05. The predictions based on D and CRD descriptors showed a significant difference (p = 0.007). For Kaplan-Meier survival analysis, the deceased and alive groups were stratified successfully by C (p < 0.001) and CRD (p < 0.001), with CRD predicting the alive group more accurately. The results highlight the potential of combining C, R, and D descriptors to accurately predict the survival of bladder cancer patients after cystectomy.

A Survey of Practicing Radiologists on the Use of Premedication Before Intravenous Iodinated Contrast Medium Administration

OBJECTIVE

To determine whether updated guidance by the ACR in 2017 advocating use of intravenous (IV) premedication in emergency department (ED) patients and inpatients with reported iodinated contrast allergy was associated with a change in clinical practice.

METHODS

An anonymous survey was distributed via e-mail in October 2020 to practicing radiologist members of the ACR interrogating use of corticosteroid premedication for two clinical vignettes: an indicated routine (perform within 24 hours) inpatient contrast-enhanced CT (CE-CT) and an indicated urgent (perform within 6 hours) ED CE-CT. In both scenarios, the patient had a prior moderate hypersensitivity reaction to iodinated contrast media. Clinical management was evaluated. Data were compared to historical controls from 2009.

RESULTS

The response rate was 11% (724 of 6,616). For the inpatient scenario, 72% (518 of 724) would use corticosteroid premedication with CE-CT, and 28% (200 of 724) would perform noncontrast CT. For the ED scenario, 67% (487 of 724) would use corticosteroid premedication with CE-CT, and 30% (217 of 724) would perform noncontrast CT. Oral premedication (85%, 439 of 518) was preferred for routine inpatients, and rapid IV premedication (89%, 433 of 487) was preferred for urgent ED patients. Of those who provided rapid IV dosing data in the ED, two doses of corticosteroids were used by 53% (216 of 410) and one dose was used by 45% (185 of 410), with academic radiologists more likely than private or hybrid practice radiologists to administer two doses (74% [74 of 100] versus 48% [151 of 312], P < .001, odds ratio, 3.03; 95% confidence interval, 1.84-5.00). Rapid IV premedication was more commonly used in 2020 than in 2009 (60% [433 of 724] versus 29% [20 of 69], P < .001, odds ratio, 3.65; 95% confidence interval, 2.12-6.26). Antihistamine use was common in both inpatient (93%, 480 of 518) and ED settings (92%, 447 of 487). Only 32% (229 of 721) of radiologists practiced in accordance with ACR guidelines, suggesting no need for routine premedication before CE-CT in patients with prior severe hypersensitivity reaction to gadolinium-based contrast media. Nonetheless, most (93%, 670 of 724) said the ACR Manual on Contrast Media was a major determinant of their practice.

CONCLUSIONS

Use of rapid IV premedication in urgent settings has increased since 2009, following updated ACR guidelines, but there is disagreement over whether one or two corticosteroid doses is required. Despite reported high reliance on ACR guidelines, deviations from those guidelines remain common. In general, when ACR guidelines were not followed, it was in a risk-averse direction.

Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study

This observer study investigates the effect of computerized artificial intelligence (AI)-based decision support system (CDSS-T) on physicians’ diagnostic accuracy in assessing bladder cancer treatment response. The performance of 17 observers was evaluated when assessing bladder cancer treatment response without and with CDSS-T using pre- and post-chemotherapy CTU scans in 123 patients having 157 pre- and post-treatment cancer pairs. The impact of cancer case difficulty, observers’ clinical experience, institution affiliation, specialty, and the assessment times on the observers’ diagnostic performance with and without using CDSS-T were analyzed. It was found that the average performance of the 17 observers was significantly improved (p = 0.002) when aided by the CDSS-T. The cancer case difficulty, institution affiliation, specialty, and the assessment times influenced the observers’ performance without CDSS-T. The AI-based decision support system has the potential to improve the diagnostic accuracy in assessing bladder cancer treatment response and result in more consistent performance among all physicians.

Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support

We evaluated the intraobserver variability of physicians aided by a computerized decision-support system for treatment response assessment (CDSS-T) to identify patients who show complete response to neoadjuvant chemotherapy for bladder cancer, and the effects of the intraobserver variability on physicians' assessment accuracy. A CDSS-T tool was developed that uses a combination of deep learning neural network and radiomic features from computed tomography (CT) scans to detect bladder cancers that have fully responded to neoadjuvant treatment. Pre- and postchemotherapy CT scans of 157 bladder cancers from 123 patients were collected. In a multireader, multicase observer study, physician-observers estimated the likelihood of pathologic T0 disease by viewing paired pre/posttreatment CT scans placed side by side on an in-house-developed graphical user interface. Five abdominal radiologists, 4 diagnostic radiology residents, 2 oncologists, and 1 urologist participated as observers. They first provided an estimate without CDSS-T and then with CDSS-T. A subset of cases was evaluated twice to study the intraobserver variability and its effects on observer consistency. The mean areas under the curves for assessment of pathologic T0 disease were 0.85 for CDSS-T alone, 0.76 for physicians without CDSS-T and improved to 0.80 for physicians with CDSS-T (P = .001) in the original evaluation, and 0.78 for physicians without CDSS-T and improved to 0.81 for physicians with CDSS-T (P = .010) in the repeated evaluation. The intraobserver variability was significantly reduced with CDSS-T (P < .0001). The CDSS-T can significantly reduce physicians' variability and improve their accuracy for identifying complete response of muscle-invasive bladder cancer to neoadjuvant chemotherapy.

Cocaine nephropathy: A rare cause of abnormal nephrograms

Cocaine use is associated with a variety of renal injuries. Although rhabdomyolysis is the most common cause of cocaine-induced nephropathy, cocaine can also cause renal vasculitis, acute interstitial nephritis, acute tubular necrosis, thrombotic microangiopathy, and renal infarction. We present a rare case of cocaine-induced nephropathy in a 30-year-old male who presented with acute kidney injury and abnormal nephrograms at contrast-enhanced computed tomography. Mechanisms of cocaine-induced renal injury and differential causes of abnormal nephrograms encountered at imaging are discussed. Cocaine-induced nephropathy is a rare but important cause of abnormal nephrograms and should be considered in the differential diagnosis when clinically appropriate.

Diagnostic Accuracy of CT for Prediction of Bladder Cancer Treatment Response with and without Computerized Decision Support

RATIONALE AND OBJECTIVES

To evaluate whether a computed tomography (CT)-based computerized decision-support system for muscle-invasive bladder cancer treatment response assessment (CDSS-T) can improve identification of patients who have responded completely to neoadjuvant chemotherapy.

MATERIALS AND METHODS

Following Institutional Review Board approval, pre-chemotherapy and post-chemotherapy CT scans of 123 subjects with 157 muscle-invasive bladder cancer foci were collected retrospectively. CT data were analyzed with a CDSS-T that uses a combination of deep-learning convolutional neural network and radiomic features to distinguish muscle-invasive bladder cancers that have fully responded to neoadjuvant treatment from those that have not. Leave-one-case-out cross-validation was used to minimize overfitting. Five attending abdominal radiologists, four diagnostic radiology residents, two attending oncologists, and one attending urologist estimated the likelihood of pathologic T0 disease (complete response) by viewing paired pre/post-treatment CT scans placed side-by-side on an internally-developed graphical user interface. The observers provided an estimate without use of CDSS-T and then were permitted to revise their estimate after a CDSS-T-derived likelihood score was displayed. Observer estimates were analyzed with multi-reader, multi-case receiver operating characteristic methodology. The area under the curve (AUC) and the statistical significance of the difference were estimated.

RESULTS

The mean AUCs for assessment of pathologic T0 disease were 0.80 for CDSS-T alone, 0.74 for physicians not using CDSS-T, and 0.77 for physicians using CDSS-T. The increase in the physicians' performance was statistically significant (P < .05).

CONCLUSION

CDSS-T improves physician performance for identifying complete response of muscle-invasive bladder cancer to neoadjuvant chemotherapy.

Radiographic stool quantification: an equivalence study of 484 symptomatic and asymptomatic subjects

PURPOSE

To determine if symptomatic patients referred for radiographic stool quantification have equivalent stool burden to asymptomatic patients.

METHOD

This was an IRB-approved HIPAA-compliant retrospective equivalence cohort study. An a priori equivalence power calculation was performed. Consecutive abdominal radiographs performed in adult outpatients with bloating, constipation, diarrhea, or abdominal pain to assess "fecal loading" [n = 242 (fecal cohort)] were compared to those performed in asymptomatic adult outpatients to assess "renal stones" [n = 242 (renal cohort)]. Radiographs were randomized and reviewed by two blinded independent abdominal radiologists. Exclusion criteria, designed to avoid unblinding, included urinary tract calculi ≥ 0.5 cm, multiple urinary tract calculi, and ureteral stent(s). Readers scored all radiographs (n = 484) for stool burden using validated Leech criteria [scale: 0 (none) to 15 (extreme diffuse)]. Mean Leech scores and 95% confidence intervals were calculated. Multivariable generalized linear modeling was performed to adjust for baseline medication use, age, and gender. The adjusted parameter estimate was used to test for equivalence in the mean difference between cohorts using Schuirmann's method of two one-sided t-tests. Inter-reader agreement was assessed with intraclass correlation coefficients.

RESULTS

Overall mean Leech scores for fecal [6.9 (95% CI 6.7, 7.2)] and renal [7.3 (95% CI 7.1, 7.5)] cohorts were equivalent within a margin of 0.75 (adjusted mean difference: - 0.4 [90% CI - 0.7, - 0.04]; p value = 0.02). Inter-reader agreement was good [ICC: 0.62 (95% CI 0.56, 0.68)].

CONCLUSION

Radiographic stool quantification produces equivalent results in symptomatic and asymptomatic adults and is of uncertain value.

Deep Learning Approach for Assessment of Bladder Cancer Treatment Response

We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre- and posttreatment computed tomography scans of 123 patients (cancers, 129; pre- and posttreatment cancer pairs, 158) undergoing chemotherapy were collected. After chemotherapy 33% of patients had T0 stage cancer (complete response). Regions of interest in pre- and posttreatment scans were extracted from the segmented lesions and combined into hybrid pre -post image pairs (h-ROIs). Training (pairs, 94; h-ROIs, 6209), validation (10 pairs) and test sets (54 pairs) were obtained. The DL-CNN consisted of 2 convolution (C1-C2), 2 locally connected (L3-L4), and 1 fully connected layers. The DL-CNN was trained with h-ROIs to classify cancers as fully responding (stage T0) or not fully responding to chemotherapy. Two radiologists provided lesion likelihood of being stage T0 posttreatment. The test area under the ROC curve (AUC) was 0.73 for T0 prediction by the base DL-CNN structure with randomly initialized weights. The base DL-CNN structure with pretrained weights and transfer learning (no frozen layers) achieved test AUC of 0.79. The test AUCs for 3 modified DL-CNN structures (different C1-C2 max pooling filter sizes, strides, and padding, with transfer learning) were 0.72, 0.86, and 0.69. For the base DL-CNN with (C1) frozen, (C1-C2) frozen, and (C1-C2-L3) frozen, the test AUCs were 0.81, 0.78, and 0.71, respectively. The radiologists' AUCs were 0.76 and 0.77. DL-CNN performed better with pretrained than randomly initialized weights.

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.

A pictorial review of bladder cancer nodal metastases

Lymph node involvement in bladder cancer is common and has prognostic implications. Early and accurate identification of metastatic lymph nodes is, therefore, important in ensuring appropriate patient triage and management. The purpose of this review is to provide a pictorial and educational overview of the staging and imaging appearance of metastatic lymph nodes in bladder cancer. Additionally, a secondary aim of this manuscript is to provide a review of the diagnostic accuracy of common imaging modalities available for detecting metastatic lymph nodes in affected patients.

(Lack of) Measurable Clinical or Knowledge Gains From Resident Participation in Noon Conference

RATIONALE AND OBJECTIVES

The objective of this study was to determine whether noon conference attendance by diagnostic radiology residents is predictive of measurable performance.

METHODS

This single-center retrospective Health Insurance and Portability and Accountability Act (HIPAA)-compliant cross-sectional study was considered "not regulated" by the institutional review board. All diagnostic radiology residents who began residency training from 2008 to 2012 were included (N = 54). Metrics of clinical performance and knowledge were collected, including junior and senior precall test results, American Board of Radiology scores (z-score transformed), American College of Radiology in-training scores (years 1-3), on-call "great call" and minor and major discrepancy rates, on-call and daytime case volumes, and training rotation scores. Multivariate regression models were constructed to determine if conference attendance, match rank order, or starting year could predict these outcomes. Pearson bivariate correlations were calculated.

RESULTS

Senior precall test results were moderately correlated with American Board of Radiology (r = 0.41) and American College of Radiology (r = 0.38-0.48) test results and mean rotation scores (r = 0.41), indicating moderate internal validity. However, conference attendance, match rank order, and year of training did not correlate with (r = -0.16-0.16) or predict (P > .05) measurable resident knowledge. On multivariate analysis, neither match rank order (P = .14-.96) nor conference attendance (P = .10-.88) predicted measurable clinical efficiency or accuracy. Year started training predicted greater cross-sectional case volume (P < .0001, β = 0.361-0.516) and less faculty-to-resident feedback (P < 0.0001, β = [-0.628]-[-0.733]).

CONCLUSIONS

Residents with lower conference attendance are indistinguishable from those who attend more frequently in a wide range of clinical and knowledge-based performance assessments, suggesting that required attendance may not be necessary to gain certain measurable core competencies.

Imaging appearance of fibrosing diseases of the retroperitoneum: can a definitive diagnosis be made?

PURPOSE

To assess the frequency with which previously reported characteristic findings of retroperitoneal fibrosis (RPF) (a circumferential or almost circumferential peri-aortic mass centered at L4, which does not displace the abdominal aorta or proximal common iliac arteries) are present in patients with RPF, in patients with other fibrosing diseases, and in cancer patients referred to a subspecialty clinic with a suspected diagnosis of RPF, in order to determine whether diagnostic percutaneous biopsy can be avoided in some patients.

METHODS

This HIPAA-compliant Institutional Review Board-approved retrospective study assessed clinical and CT and MR imaging abnormalities on imaging studies in 92 patients referred to a subspecialty clinic with suspected RPF over a 14-year period. Two reviewers, in consensus, determined the frequency of different CT and MRI findings in three groups of patients (Group 1: those with an eventual diagnosis of RPF, Group 2: those with a fibrosing disease associated with vascular or urologic abnormalities, and Group 3: those with cancer). Assessed imaging features included the presence of retroperitoneal masses, whether masses were single or multiple, whether such masses were circumferential or nearly circumferential, whether they displaced the aorta away from the spine (with the degree of such displacement measured), and whether there were abnormalities outside of the peri-aortic region of the retroperitoneum. The frequency with which findings previously reported as characteristic of RPF were present was determined for each of the three groups. Imaging results were correlated with the final diagnoses.

RESULTS

Of 68 subjects eventually diagnosed with retroperitoneal fibrosis (RPF) (Group 1), 47 had peri-aortic retroperitoneal masses, 18 of which displaced the aorta anteriorly away from the spine. Of 12 subjects with fibrosing abnormalities related to vascular or urologic disease (Group 2), six had retroperitoneal masses, none of which displaced the aorta away from the spine. Of 12 subjects with malignancies (Group 3), six had peri-aortic retroperitoneal masses only two of whom had aortic displacement. Only 34 of 68 Group 1 subjects had peri-aortic masses characteristic of RPF, compared with six Group 2 subjects and one Group 3 subject. Subjects with characteristic retroperitoneal masses were significantly more likely to have benign disease than cancer (p = 0.009).

CONCLUSION

Many patients with RPF do not have characteristic imaging findings. Contrary to prior publications, absence of aortic displacement is not seen in all patients with RPF and is seen in some cancer patients. Nonetheless, when infiltrative peri-aortic retroperitoneal soft tissue that does not displace the aorta is encountered on CT or MRI, RPF can be diagnosed with a high degree of confidence, obviating the need for biopsy.

Expanding the Definition of a Benign Renal Cyst on Contrast-enhanced CT: Can Incidental Homogeneous Renal Masses Measuring 21-39 HU be Safely Ignored?

RATIONALE AND OBJECTIVE

We aimed to determine the frequency and clinical significance of homogeneous renal masses measuring 21-39 Hounsfield units on contrast-enhanced computed tomography (CT).

METHODS

Subjects 40-69 years old undergoing portal-venous-phase contrast-enhanced abdominal CT from January 1, 2006 to December 31, 2010 with slice thickness ≤5 mm and no prior CT or magnetic resonance imaging were identified (n = 1387) for this institutional review board-approved retrospective cohort study. Images were manually reviewed by three radiologists in consensus to identify all circumscribed homogeneous renal masses (maximum of three per subject) ≥10 mm with a measured attenuation of 21-39 Hounsfield units. Exclusion criteria were known renal cancer or imaging performed for a renal indication. The primary outcome was retrospective characterization as a clinically significant mass, defined as a solid mass, a Bosniak IIF/III/IV mass, or extirpative therapy or metastatic renal cancer within 5 years' follow-up.

RESULTS

Eligible masses (n = 74) were found in 5% (63/1387) of subjects. Of those with a reference standard (n = 42), none (0% [95% CI: 0.0%-8.4%]) were determined to be clinically significant.

CONCLUSION

Incidental renal masses on contrast-enhanced CT that are homogeneous and display an attenuation of 21-39 Hounsfield units are uncommon in patients 40-69 years of age, unlikely to be clinically significant, and may not need further imaging evaluation. If these results can be replicated in an independent and larger population, the practical definition of a benign cyst on imaging may be able to be expanded.

Urinary bladder cancer staging in CT urography using machine learning

PURPOSE

To evaluate the feasibility of using an objective computer-aided system to assess bladder cancer stage in CT Urography (CTU).

MATERIALS AND METHODS

A dataset consisting of 84 bladder cancer lesions from 76 CTU cases was used to develop the computerized system for bladder cancer staging based on machine learning approaches. The cases were grouped into two classes based on pathological stage ≥ T2 or below T2, which is the decision threshold for neoadjuvant chemotherapy treatment clinically. There were 43 cancers below stage T2 and 41 cancers at stage T2 or above. All 84 lesions were automatically segmented using our previously developed auto-initialized cascaded level sets (AI-CALS) method. Morphological and texture features were extracted. The features were divided into subspaces of morphological features only, texture features only, and a combined set of both morphological and texture features. The dataset was split into Set 1 and Set 2 for two-fold cross-validation. Stepwise feature selection was used to select the most effective features. A linear discriminant analysis (LDA), a neural network (NN), a support vector machine (SVM), and a random forest (RAF) classifier were used to combine the features into a single score. The classification accuracy of the four classifiers was compared using the area under the receiver operating characteristic (ROC) curve (A_z ).

RESULTS

Based on the texture features only, the LDA classifier achieved a test A_z of 0.91 on Set 1 and a test A_z of 0.88 on Set 2. The test A_z of the NN classifier for Set 1 and Set 2 were 0.89 and 0.92, respectively. The SVM classifier achieved test A_z of 0.91 on Set 1 and test A_z of 0.89 on Set 2. The test A_z of the RAF classifier for Set 1 and Set 2 was 0.89 and 0.97, respectively. The morphological features alone, the texture features alone, and the combined feature set achieved comparable classification performance.

CONCLUSION

The predictive model developed in this study shows promise as a classification tool for stratifying bladder cancer into two staging categories: greater than or equal to stage T2 and below stage T2.

Urinary bladder cancer staging in CT urography using machine learning

PURPOSE

To evaluate the feasibility of using an objective computer-aided system to assess bladder cancer stage in CT Urography (CTU).

MATERIALS AND METHODS

A dataset consisting of 84 bladder cancer lesions from 76 CTU cases was used to develop the computerized system for bladder cancer staging based on machine learning approaches. The cases were grouped into two classes based on pathological stage ≥ T2 or below T2, which is the decision threshold for neoadjuvant chemotherapy treatment clinically. There were 43 cancers below stage T2 and 41 cancers at stage T2 or above. All 84 lesions were automatically segmented using our previously developed auto-initialized cascaded level sets (AI-CALS) method. Morphological and texture features were extracted. The features were divided into subspaces of morphological features only, texture features only, and a combined set of both morphological and texture features. The dataset was split into Set 1 and Set 2 for two-fold cross-validation. Stepwise feature selection was used to select the most effective features. A linear discriminant analysis (LDA), a neural network (NN), a support vector machine (SVM), and a random forest (RAF) classifier were used to combine the features into a single score. The classification accuracy of the four classifiers was compared using the area under the receiver operating characteristic (ROC) curve (A_z ).

RESULTS

Based on the texture features only, the LDA classifier achieved a test A_z of 0.91 on Set 1 and a test A_z of 0.88 on Set 2. The test A_z of the NN classifier for Set 1 and Set 2 were 0.89 and 0.92, respectively. The SVM classifier achieved test A_z of 0.91 on Set 1 and test A_z of 0.89 on Set 2. The test A_z of the RAF classifier for Set 1 and Set 2 was 0.89 and 0.97, respectively. The morphological features alone, the texture features alone, and the combined feature set achieved comparable classification performance.

CONCLUSION

The predictive model developed in this study shows promise as a classification tool for stratifying bladder cancer into two staging categories: greater than or equal to stage T2 and below stage T2.

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.

Bladder Cancer Segmentation in CT for Treatment Response Assessment: Application of Deep-Learning Convolution Neural Network-A Pilot Study

Assessing the response of bladder cancer to neoadjuvant chemotherapy is crucial for reducing morbidity and increasing quality of life of patients. Changes in tumor volume during treatment is generally used to predict treatment outcome. We are developing a method for bladder cancer segmentation in CT using a pilot data set of 62 cases. 65 000 regions of interests were extracted from pre-treatment CT images to train a deep-learning convolution neural network (DL-CNN) for tumor boundary detection using leave-one-case-out cross-validation. The results were compared to our previous AI-CALS method. For all lesions in the data set, the longest diameter and its perpendicular were measured by two radiologists, and 3D manual segmentation was obtained from one radiologist. The World Health Organization (WHO) criteria and the Response Evaluation Criteria In Solid Tumors (RECIST) were calculated, and the prediction accuracy of complete response to chemotherapy was estimated by the area under the receiver operating characteristic curve (AUC). The AUCs were 0.73 ± 0.06, 0.70 ± 0.07, and 0.70 ± 0.06, respectively, for the volume change calculated using DL-CNN segmentation, the AI-CALS and the manual contours. The differences did not achieve statistical significance. The AUCs using the WHO criteria were 0.63 ± 0.07 and 0.61 ± 0.06, while the AUCs using RECIST were 0.65 ± 007 and 0.63 ± 0.06 for the two radiologists, respectively. Our results indicate that DL-CNN can produce accurate bladder cancer segmentation for calculation of tumor size change in response to treatment. The volume change performed better than the estimations from the WHO criteria and RECIST for the prediction of complete response.

Effect of available intravenous access on accuracy and timeliness of epinephrine administration

PURPOSE

To evaluate the effect of available intravenous (IV) access on the accuracy and timeliness of epinephrine administration during a surprise mock severe contrast reaction.

METHODS

Informed consent was waived for this prospective randomized IRB-approved study. Radiology trainees with previous annual hands-on contrast reaction training (n = 46) were randomized to one of two surprise mock contrast reactions over a 23-month period: Group 1-severe laryngeal edema with IV access present (n = 27) or Group 2-severe laryngeal edema without IV access present (n = 19). Both intramuscular (IM, Epi-Pen(®)) and IV epinephrine were available in both scenarios. Time-to-treat and epinephrine administration error rates were compared by study group and by route of administration using two-tailed Student's t test or χ (2) test. Epinephrine administration errors were correlated with training experience using Pearson's correlation.

RESULTS

Mean time to epinephrine administration was significantly faster for scenarios without IV access (Group 2: 35 ± 16 s vs. Group 1: 62 ± 49 s, p = 0.03), and for intramuscular administrations overall (IM: 42 ± 34 s vs. IV: 98 ± 46 s, p < 0.001). Epinephrine administration errors were common: (63% [17/27, Group 1] vs. 61% [11/18, Group 2], p = 1.00), had no relationship with time to most recent hands-on training (r = 0.24, p = 0.11), and were not predicted by year of post-graduate training (r = 0.04, p = 0.79).

CONCLUSIONS

Lack of IV access is associated with a faster epinephrine administration time but no improvement in epinephrine administration error rate among radiology trainees responding to a surprise mock severe contrast reaction. Annual hands-on training appears to have little effect on epinephrine administration accuracy.

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.

Optimizing the post-graduate institutional program evaluation process

BACKGROUND

Reviewing program educational efforts is an important component of postgraduate medical education program accreditation. The post-graduate review process has evolved over time to include centralized oversight based on accreditation standards. The institutional review process and the impact on participating faculty are topics not well described in the literature.

METHODS

We conducted multiple Plan-Do-Study-Act (PDSA) cycles to identify and implement areas for change to improve productivity in our institutional program review committee. We also conducted one focus group and six in-person interviews with 18 committee members to explore their perspectives on the committee's evolution. One author (MLL) reviewed the transcripts and performed the initial thematic coding with a PhD level research associate and identified and categorized themes. These themes were confirmed by all participating committee members upon review of a detailed summary. Emergent themes were triangulated with the University of Michigan Medical School's Admissions Executive Committee (AEC).

RESULTS

We present an overview of adopted new practices to the educational program evaluation process at the University of Michigan Health System that includes standardization of meetings, inclusion of resident members, development of area content experts, solicitation of committed committee members, transition from paper to electronic committee materials, and focus on continuous improvement. Faculty and resident committee members identified multiple improvement areas including the ability to provide high quality reviews of training programs, personal and professional development, and improved feedback from program trainees.

CONCLUSIONS

A standing committee that utilizes the expertise of a group of committed faculty members and which includes formal resident membership has significant advantages over ad hoc or other organizational structures for program evaluation committees.

Mass-like peripheral zone enhancement on CT is predictive of higher-grade (Gleason 4 + 3 and higher) prostate cancer

PURPOSE

To determine whether focal peripheral zone enhancement on routine venous-phase CT is predictive of higher-grade (Gleason 4 + 3 and higher) prostate cancer.

MATERIALS AND METHODS

IRB approval was obtained and informed consent waived for this HIPAA-compliant retrospective study. Forty-three patients with higher-grade prostate cancer (≥Gleason 4 + 3) and 96 with histology-confirmed lower-grade (≤Gleason 3 + 4 [n = 47]) or absent (n = 49) prostate cancer imaged with venous-phase CT comprised the study population. CT images were reviewed by ten blinded radiologists (5 attendings, 5 residents) who scored peripheral zone enhancement on a scale of 1 (benign) to 5 (malignant). Mass-like peripheral zone enhancement was considered malignant. Likelihood ratios (LR) and specificities were calculated. Multivariate conditional logistic regression analyses were conducted.

RESULTS

Scores of "5" were strongly predictive of higher-grade prostate cancer (pooled LR+ 9.6 [95% CI 5.8-15.8]) with rare false positives (pooled specificity: 0.98 [942/960, 95% CI 0.98-0.99]; all 10 readers had specificity ≥95%). Attending scores of "5" were more predictive than resident scores of "5" (LR+: 14.7 [95% CI 5.8-37.2] vs. 7.6 [95% CI 4.2-13.7]) with similar specificity (0.99 [475/480, 95% CI 0.98-1.00] vs. 0.97 [467/480, 95% CI 0.96-0.99]). Significant predictors of an assigned score of "5" included presence of a peripheral zone mass (p < 0.0001), larger size (p < 0.0001), and less reader experience (p = 0.0008). Significant predictors of higher-grade prostate cancer included presence of a peripheral zone mass (p = 0.0002) and larger size (p < 0.0001).

CONCLUSION

Focal mass-like peripheral zone enhancement on routine venous-phase CT is specific and predictive of higher-grade (Gleason 4 + 3 and higher) prostate cancer.

Renal Masses: Imaging Evaluation

This article illustrates the imaging characteristics of cystic and solid renal masses, along with a summary of identified imaging criteria that may be of use to differentiate masses that are more likely to be benign from those that are more likely to be malignant. In addition, important features of known or suspected renal cancers that should be identified before treatment are summarized, including staging of renal cancer and RENAL nephrometry. Finally, the imaging appearance of patients following treatment of renal cancer, including after partial or total nephrectomy, thermal ablation, or chemotherapy for metastatic disease, is reviewed.

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.

Indirect Cost and Harm Attributable to Oral 13-Hour Inpatient Corticosteroid Prophylaxis before Contrast-enhanced CT

PURPOSE

To estimate the effect of an oral 13-hour inpatient corticosteroid premedication regimen on length of stay, hospital cost, and hospital-acquired infections (HAIs) by using a combination of real and hypothetical study populations.

MATERIALS AND METHODS

Institutional review board approval was obtained and informed consent waived for this HIPAA-compliant retrospective study. Inpatients who received an oral 13-hour corticosteroid premedication regimen before contrast material-enhanced CT (n = 1424) from 2008 to 2013 were matched by age, sex, and year when CT was performed to a control cohort (n = 1425) of patients who underwent contrast-enhanced CT without premedication and who had similar rates of 13 comorbid diseases. Length of stay in the hospital and time from admission to CT were compared by using the Mann-Whitney U test. Rates of prospectively reported HAIs were compared by using χ(2) tests. The indirect cost and risk of HAI with premedication were estimated by using published data.

RESULTS

Premedicated inpatients had a significantly longer median length of stay (+25 hours; 158 vs 133 hours, P < .001), a significantly longer median time to CT (+25 hours, 42 vs 17 hours, respectively; P < .001), and a significantly greater risk of HAI (5.1% [72 of 1424] vs 3.1% [44 of 1424], respectively; P = .008) compared with nonpremedicated control subjects. On the basis of these data and existing references, the prolonged length of stay was estimated to result in 0.04 HAI-related deaths and a cost of $159 131 (in U.S. dollars) for each prevented reaction of any severity and 32 HAI-related deaths and a cost of $131 211 400 for each prevented reaction-related death.

CONCLUSION

Oral 13-hour inpatient corticosteroid prophylaxis is associated with substantial cost relative to its modest benefit, and may cause more indirect harm than the direct harm that it prevents.

Treatment Response Assessment for Bladder Cancer on CT Based on Computerized Volume Analysis, World Health Organization Criteria, and RECIST

OBJECTIVE

The purpose of this study was to evaluate the accuracy of our autoinitialized cascaded level set 3D segmentation system as compared with the World Health Organization (WHO) criteria and the Response Evaluation Criteria In Solid Tumors (RECIST) for estimation of treatment response of bladder cancer in CT urography.

MATERIALS AND METHODS

CT urograms before and after neoadjuvant chemo-therapy treatment were collected from 18 patients with muscle-invasive localized or locally advanced bladder cancers. The disease stage as determined on pathologic samples at cystectomy after chemotherapy was considered as reference standard of treatment response. Two radiologists measured the longest diameter and its perpendicular on the pre- and posttreatment scans. Full 3D contours for all tumors were manually outlined by one radiologist. The autoinitialized cascaded level set method was used to automatically extract 3D tumor boundary. The prediction accuracy of pT0 disease (complete response) at cystectomy was estimated by the manual, autoinitialized cascaded level set, WHO, and RECIST methods on the basis of the AUC.

RESULTS

The AUC for prediction of pT0 disease at cystectomy was 0.78 ± 0.11 for autoinitialized cascaded level set compared with 0.82 ± 0.10 for manual segmentation. The difference did not reach statistical significance (p = 0.67). The AUCs using RECIST criteria were 0.62 ± 0.16 and 0.71 ± 0.12 for the two radiologists, both lower than those of the two 3D methods. The AUCs using WHO criteria were 0.56 ± 0.15 and 0.60 ± 0.13 and thus were lower than all other methods.

CONCLUSION

The pre- and posttreatment 3D volume change estimates obtained by the radiologist's manual outlines and the autoinitialized cascaded level set segmentation were more accurate for irregularly shaped tumors than were those based on RECIST and WHO criteria.

Abdominopelvic hemorrhage: correlation of CT positivity with the subsequent decision to perform blood transfusion

The purpose of this study is to determine the role of computed tomography (CT) on the decision to administer blood transfusions in patients with abdominopelvic hemorrhage (trauma, surgery, invasive procedure, and spontaneous) and to determine the clinical parameters most likely to influence the decision to administer blood transfusions in patients with spontaneous abdominopelvic hemorrhage. In this IRB approved and HIPPA compliant study, retrospective analysis was performed on 298 patients undergoing abdominal and pelvic CT for suspected abdominopelvic hemorrhage and the CT reports and electronic medical records were reviewed. Odds ratios and 95% CI were calculated to compare the odds of abdominopelvic hemorrhage and transfusion for categorical and continuous predictors. The presence of abdominopelvic hemorrhage by CT was significantly associated with blood transfusions for trauma patients (p-value <0.0001) only. 106 patients with suspected spontaneous abdominopelvic hemorrhage had the lowest CT positivity rate (n = 23, 21.7%) but the highest blood transfusion rate (n = 62, 58.5%) compared to the patients with abdominopelvic hemorrhage from known preceding causes. In patients with spontaneous abdominopelvic hemorrhage, low hemoglobin and hematocrit levels immediately prior to obtaining the CT study were more predictive for receiving a blood transfusion (p-value <0.0001) than the presence of hemorrhage by CT. CT positivity is strongly correlated with the decision to administer blood transfusions for patients with abdominopelvic hemorrhage from trauma, indicating that CT studies play a significant role in determining the clinical management of trauma patients. For patients with spontaneous abdominopelvic hemorrhage, the decision to transfuse depends not on the CT study but on the patient's hemoglobin and hematocrit levels. CT studies should therefore not be performed for the sole purpose of determining the need for blood transfusion in patients with spontaneous abdominopelvic hemorrhage.

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.

Residents' ability to interpret radiology images: development and improvement of an assessment tool

RATIONALE AND OBJECTIVES

Despite increasing radiology coverage, nonradiology residents continue to preliminarily interpret basic radiologic studies independently, yet their ability to do so accurately is not routinely assessed.

MATERIALS AND METHODS

An online test of basic radiologic image interpretation was developed through an iterative process. Educational objectives were established, then questions and images were gathered to create an assessment. The test was administered online to first-year interns (postgraduate year [PGY] 1) from 14 different specialties, as well as a sample of third- and fourth-year radiology residents (PGY3/R2 and PGY4/R3).

RESULTS

Over a 2-year period, 368 residents were assessed, including PGY1 (n = 349), PGY3/R2 (n = 14), and PGY4/R3 (n = 5) residents. Overall, the test discriminated effectively between interns (average score = 66%) and advanced residents (R2 = 86%, R3 = 89%; P < .05). Item analysis indicated discrimination indices ranging from -0.72 to 48.3 (mean = 3.12, median 0.58) for individual questions, including four questions with negative discrimination indices. After removal of the negatively indexed questions, the overall predictive value of the instrument persisted and discrimination indices increased for all but one of the remaining questions (range 0.027-70.8, mean 5.76, median 0.94).

CONCLUSIONS

Validation of an initial iteration of an assessment of basic image-interpretation skills led to revisions that improved the test. The results offer a specific test of radiologic reading skills with validation evidence for residents. More generally, results demonstrate a principled approach to test development.

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.

Focal nodular prostatic peripheral zone enhancement on CT to predict clinically significant (Gleason 4+3 and higher) prostate cancer

173

Background: CTs are insensitive for prostate cancer and inaccurate for local prostate cancer staging. However, enhancing peripheral zone nodules can be seen on a CT, and their significance is uncertain. The purpose of this study was to determine whether focal nodular enhancement within the prostatic peripheral zone on a CT is predictive of clinically significant prostate cancer. Methods: Institutional review board approval was obtained and informed consent waived for this Health Insurance Portability and Accountability Act-compliant retrospective study. Forty-three patients with high-grade prostate cancer (Gleason 4+3 [n=14], 3+5 [n=1], 4+4 [n=1], 4+5 [n=19], 5+4 [n=8]) and 96 with cystoprostatectomy-confirmed low-grade (Gleason 3+4 [n=24], 3+3 [n=23]) or absent (n=49) prostate cancer imaged with contrast-enhanced CT within nine months of histology (median: 18 days) comprised the study population. CT images were reviewed by 10 blinded radiologists (five attendings, five residents) who scored peripheral zone enhancement on a scale of 1 (benign) to 5 (malignant). Focal nodular enhancement was considered malignant. Likelihood ratios (LR) and specificities were calculated. Results: Scores of ‘5’ were strongly predictive of clinically significant prostate cancer (pooled LR+: 9.6 [95% CI: 5.8-15.8]) with rare false positives (pooled specificity: 0.98 [942/960, 95% CI: 0.98-0.99]). Attendings outperformed residents (LR+: 14.7 [95% CI: 5.8-37.2] vs. 7.6 [95% CI: 4.2-13.7]) with similar specificity (0.99 [475/480, 95% CI: 0.98-1.00] vs. 0.97 [467/480, 95% CI: 0.96-0.99]). Conclusions: Focal nodular peripheral zone enhancement on a CT is specific and predictive of clinically significant prostate cancer.

Contrast medium-induced nephrotoxicity risk assessment in adult inpatients: a comparison of serum creatinine level- and estimated glomerular filtration rate-based screening methods

PURPOSE

To compare serum creatinine (SCr) level- and estimated glomerular filtration rate (eGFR)-based screening methods for identifying adult inpatients at risk for contrast medium-induced nephrotoxicity (CIN).

MATERIALS AND METHODS

Institutional review board approval was obtained; informed consent was waived for this HIPAA-compliant retrospective study. Computed tomographic examinations performed during 10 years in adult inpatients with stable renal function were identified (n = 28 390). The proportion of inpatients meeting various eGFR (≥60, <60, <45, <30, 30-44, 45-59 mL/min/1.73 m(2)) and SCr (<1.5, ≥1.5, ≥1.6, ≥1.7, ≥1.8, ≥1.9, ≥2.0 mg/dL) thresholds were contrasted with each other and with published guidelines (≥2.0 mg/dL [SCr] and <45 mL/min/1.73 m(2) [eGFR]) using McNemar and binomial tests.

RESULTS

Most inpatients were considered low risk for CIN with commonly used thresholds: 92.6% (26 285 of 28 390) had SCr <1.5 mg/dL; 91.3% (25 922 of 28 390) had eGFR of ≥45 mL/min/1.73 m(2). Using SCr threshold of ≥1.5 mg/dL, identified inpatients had the following eGFRs: 19.6% (413 of 2105), 45-59 mL/min/1.73 m(2); 51.1% (1075 of 2105), 30-44 mL/min/1.73 m(2); 28.6% (603 of 2105), <30 mL/min/1.73 m(2); and 0.7% (14 of 2105), ≥60 mL/min/1.73 m(2) . Using SCr threshold of ≥2.0 mg/dL, identified inpatients had the following eGFRs: 100% (658 of 658), <45 mL/min/1.73 m(2); 74.6% (491 of 658), <30 mL/min/1.73 m(2). Threshold of SCr ≥2.0 mg/dL could not be used to identify eGFR <30 mL/min/1.73 m(2) in 0.4% (112 of 28 390) and <45 mL/min/1.73 m(2) in 6.4% (1810 of 28 390) of all inpatients. Using eGFR <45 mL/min/1.73 m(2) instead of SCr of ≥1.5 mg/dL would result in a significant but small increase in identified inpatients (8.7% [2468 of 28 390; 95% confidence interval: 8.4%, 9.0%] vs 7.4% [2105 of 28 390; 95% confidence interval: 7.1%, 7.7%]; P < .0001).

CONCLUSION

Screening using eGFR <45 mL/min/1.73 m(2) instead of common SCr thresholds would significantly increase the number of inpatients identified to be at risk for CIN but would reduce misidentification of a large number of inpatients at low risk according to eGFR criteria.

Contrast material-induced nephrotoxicity and intravenous low-osmolality iodinated contrast material: risk stratification by using estimated glomerular filtration rate

PURPOSE

To determine the effect of intravenous (IV) low-osmolality iodinated contrast material (LOCM) on the development of post-computed tomography (CT) acute kidney injury (AKI), stratified by pre-CT estimated glomerular filtration rate (eGFR), in patients with stable renal function.

MATERIALS AND METHODS

Institutional review board approval was obtained and patient consent waived for this HIPAA-compliant, retrospective study. CT examinations performed over a 10-year period on unique adult inpatients with sufficient serum creatinine (SCr) data and stable renal function (difference between baseline and pre-CT SCr within 0.3 mg/dL and 50% of baseline) were identified. A 1:1 propensity score matched cohort analysis with multivariate analysis of effects was performed with post-CT AKI as the primary outcome measure (8826 nonenhanced and 8826 IV contrast agent-enhanced CT studies in 17 652 patients). Propensity matching was performed with respect to likelihood of receiving IV contrast material (19 tested covariates). Post-CT AKI with Acute Kidney Injury Network SCr criteria was the primary endpoint. A stepwise multivariate conditional logistic regression model was performed to identify the effect of IV LOCM on post-CT AKI.

RESULTS

After 1:1 propensity matching, IV LOCM had a significant effect on the development of post-CT AKI (P = .04). This risk increased with decreases in pre-CT eGFR (≥ 60 mL/min/1.73 m(2): odds ratio, 1.00; 95% confidence interval: 0.86, 1.16; 45-59 mL/min/1.73 m(2): odds ratio, 1.06; 95% confidence interval: 0.82, 1.38; 30-44 mL/min/1.73 m(2): odds ratio, 1.40; 95% confidence interval: 1.00, 1.97; <30 mL/min/1.73 m(2): odds ratio, 2.96; 95% confidence interval: 1.22, 7.17).

CONCLUSION

IV LOCM is a nephrotoxic risk factor in patients with a stable eGFR less than 30 mL/min/1.73 m(2), with a trend toward significance at 30-44 mL/min/1.73 m(2). IV LOCM does not appear to be a nephrotoxic risk factor in patients with a pre-CT eGFR of 45 mL/min/1.73 m(2) or greater.

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.

Contrast material-induced nephrotoxicity and intravenous low-osmolality iodinated contrast material

PURPOSE

To determine whether intravenous low-osmolality iodinated contrast material is associated with post-computed tomography (CT) acute kidney injury (AKI).

MATERIALS AND METHODS

Institutional review board approval was obtained and patient consent waived for this HIPAA-compliant retrospective study. CT examinations performed over a 10-year period in adult inpatients with sufficient serum creatinine (SCr) data were identified. A one-to-one propensity-matched matched cohort analysis with multivariate analysis of effects was performed with post-CT AKI as the primary outcome measure (10,121 unenhanced and 10,121 intravenous contrast-enhanced CT examinations in 20,242 patients). Propensity matching was performed with respect to likelihood of patient receiving intravenous contrast material (36 tested covariates). The primary endpoint was post-CT AKI by using Acute Kidney Injury Network SCr criteria; the secondary endpoint was post-CT AKI by using traditional SCr criteria for contrast material-induced nephrotoxicity (CIN; SCr increase ≥0.5 mg/dL [44.20 μmol/L] or ≥25%). Multivariate subgroup threshold analysis was performed (SCr <1.5 [<132.60 μmol/L]; ≥1.5 to ≥2.0 mg/dL [≥132.60 to ≥176.80 μmol/L]) and adjusted for assigned propensity scores.

RESULTS

Intravenous low-osmolality iodinated contrast material had a significant effect on the development of post-CT AKI for patients with pre-CT SCr levels of 1.6 mg/dL (141.44 μmol/L) or greater (odds ratio, 1.45; 95% confidence interval [CI]: 1.11, 1.89;P = .007). This effect strengthened as pre-CT SCr increased. Patients with stable SCr less than 1.5 mg/dL (132.60 μmol/L) were not at risk for developing CIN (P = .25, power > 95%). Both endpoints demonstrated similar results (eg, SCr ≥1.6 mg/dL [141.44 μmol/L] by using traditional CIN criteria: odds ratio, 1.64; 95% CI: 1.18, 2.28; P = .003). Post-CT AKI was prevalent in both the unenhanced and contrast-enhanced CT subgroups, and it increased with increases in pre-CT SCr. Many risk factors contributed to development of post-CT AKI, regardless of iodinated contrast material.

CONCLUSION

Intravenous low-osmolality iodinated contrast material is a nephrotoxic risk factor, but not in patients with a stable SCr level less than 1.5 mg/dL. Many factors other than contrast material can affect post-CT AKI rates.

Effect of abrupt substitution of gadobenate dimeglumine for gadopentetate dimeglumine on rate of allergic-like reactions

PURPOSE

To evaluate the effect of abruptly substituting gadobenate dimeglumine for gadopentetate dimeglumine on allergic-like reactions.

MATERIALS AND METHODS

The institutional review board approved and waived patient consent for this HIPAA-compliant retrospective study. Allergic-like reactions related to gadolinium-based contrast media were assessed 2 years before and 3.5 years after gadobenate dimeglumine was substituted for gadopentetate dimeglumine. Reaction rates and severity were compared by using χ(2) tests, Fisher exact tests, odds ratios (ORs), and confidence intervals (CIs).

RESULTS

Allergic-like reactions (137 mild, 19 moderate, and six severe) occurred in 162 (0.15%) of 105 607 injections of gadolinium-based contrast media (gadopentetate dimeglumine, 31 540; gadobenate dimeglumine, 66 152; other, 7915). Gadobenate dimeglumine was associated with significantly more overall (0.19% [123 of 66 152] vs 0.08% [24 of 31 540]; OR, 2.4; 95% CI: 1.6, 3.8; P < .0001) and mild (0.16% [107 of 66 152] vs 0.06% [18 of 31 540]; OR, 2.8; 95% CI: 1.7, 4.7; P < .0001) allergic-like reactions than was gadopentetate dimeglumine. The reaction rate for gadobenate dimeglumine peaked (maximum per quarter, 0.38% [16 of 4262]; minimum per quarter, 0.07% [three of 4237]) in the 2nd year after it replaced gadopentetate dimeglumine (maximum per quarter, 0.10% [four of 4122]; minimum per quarter, 0.05% [two of 4222]) and then declined in the 3rd year. The final gadobenate dimeglumine reaction rate (last 3 quarters, 0.12% [17 of 14 387]) did not significantly differ from the original baseline reaction rate with gadopentetate dimeglumine.

CONCLUSION

After gadobenate dimeglumine was substituted for gadopentetate dimeglumine, a significant transient increase occurred in the frequency of reported allergic-like reactions that demonstrated a temporal pattern suggestive of the Weber effect (a transient increase in adverse event reporting that tends to peak in the 2nd year after a new agent or indication is introduced). © RSNA, 2012.

Teaching management of contrast reactions: does it work and how often do we need to refresh?

RATIONALE AND OBJECTIVES

Knowledge of the management of acute contrast reactions is lacking among radiologists. Training in the management of acute contrast reactions occurs at the investigators' institution and others, but the durability of that training and the need for refresher training have not been assessed.

MATERIALS AND METHODS

A prospective assessment of changes in trainees' knowledge and confidence following a required educational course concerning reactions to contrast material was conducted. Assessments were performed prior to and immediately following the course and at 1, 3, 6, and 9 months after the course.

RESULTS

Trainees' knowledge significantly improved following the course and remained improved for 6 months (P < .0001). By 9 months, knowledge was no longer improved over baseline (P = .0644). Trainees' confidence also improved following the course and remained improved throughout follow-up (P = .0356 at 9 months). At 6 months, however, confidence had significantly declined relative to levels immediately after the course (P = .0241). Trainees' knowledge was not dependent on postgraduate year (PGY), but PGY-2 residents were significantly less confident in their ability to manage a contrast reaction than PGY-5 and PGY-6 trainees. Trainees who managed contrast reactions during the follow-up period were more confident in their abilities than trainees who did not (P = .0097).

CONCLUSIONS

These data suggest the need for biannual refresher training in the management of acute contrast reactions to maintain trainees' knowledge and confidence.

Patterns of intravenous contrast material use and corticosteroid premedication in children--a survey of Society of Chairs of Radiology in Children's Hospitals (SCORCH) member institutions

BACKGROUND

There are few data available concerning the use of intravenous contrast materials in children.

OBJECTIVE

To assess patterns of intravenous iodinated/gadolinium-based contrast material (ICM/GBCM) use in children.

MATERIALS AND METHODS

Society of Chairs of Radiology in Children's Hospitals (SCORCH) members were invited to complete a Web-based survey regarding intravenous contrast material use at their institutions.

RESULTS

Sixty-six percent (42/64) of SCORCH member institutions responded, 76% of which are academic hospitals. Ioversol and gadopentetate dimeglumine are the most commonly used ICMs and GBCMs (52% and 81%, respectively). Premedication policies to mitigate risk of allergic-like contrast reactions are more common for ICMs than GBCMs (71% vs. 32%). For both ICMs and GBCMs, most institutions premedicate or avoid contrast material in the setting of a prior allergic-like contrast reaction of any severity. Policies regarding ICM and GBCM use in children with renal insufficiency are in place at 74% and 88% of institutions, respectively, but are variable.

CONCLUSION

Policies concerning premedication for prevention of allergic-like contrast agent reactions and administration of contrast materials in children with renal insufficiency are variable and not consistently present at all pediatric institutions. This highlights the need for standardization of practice patterns and pediatric-specific research on these topics.

Apprenticeships ease the transition to independent call: an evaluation of anxiety and confidence among junior radiology residents

RATIONALE AND OBJECTIVES

The aims of this study were to quantify resident anxiety when beginning independent call and to assess whether an apprenticeship experience (buddy call) can lessen anxiety and improve confidence.

MATERIALS AND METHODS

A prospective cohort comparison of two groups of radiology residents beginning independent call, one of which was provided with a buddy call experience, was performed. Anxiety and confidence were assessed using the Endler Multidimensional Anxiety Scales-State (EMAS-S), with total score, autonomic emotional, and cognitive worry components, and a five-point, Likert-type scale, respectively. Both groups were asked about the perceived value of a buddy call experience.

RESULTS

EMAS-S scores improved significantly over 5 days of call in both groups (control, n = 10, P = .0005; buddy call, n = 9, P = .0001), and image interpretation confidence correspondingly increased (control, P = .0004; buddy call, P = .003). Compared to the control group, autonomic emotional scores were significantly lower in the buddy call group on the first day of independent call (P = .040), and cognitive worry and total EMAS-S scores were significantly lower on day 5 (both P values = .03). Buddy call was independently associated with improved autonomic emotional and film interpretation confidence scores (both P values = .02). All members of the buddy call group indicated that the experience was very helpful in preparing for call.

CONCLUSIONS

Beginning independent call is associated with high anxiety, and buddy call reduces that anxiety, beyond the effect of time alone. Residents who participated in buddy call found it helpful in preparing for independent call. These findings support the use of buddy call and tiered call structures as means to introduce junior residents to independent call.

Safety of gadolinium-based contrast material in sickle cell disease

PURPOSE

To assess the safety of intravenously administered gadolinium-based contrast material in sickle cell disease (SCD) patients.

MATERIALS AND METHODS

All pediatric and adult SCD patients evaluated by magnetic resonance imaging (MRI) at our institution between January 1995 and July 2009 were identified. The medical records of SCD patients who underwent contrast-enhanced MRI as well as an equal-sized cohort of SCD patients who underwent unenhanced MRI were reviewed for adverse (vaso-occlusive and hemolytic) events within 1 week following imaging.

RESULTS

Eight (five mild and three moderate) adverse events were documented within 1 week following contrast-enhanced MRI (38 patients and 61 contrast injections), while six (five mild and one moderate) similar events occurred within 1 week following unenhanced MRI (61 patients and 61 unenhanced MRI examinations). This difference in the number of adverse events was not statistically significant (odds ratio = 1.4; 95% confidence interval [CI] 0.4, 5.2). No severe adverse event occurred in either patient cohort.

CONCLUSION

Gadolinium-based contrast materials do not appear to be associated with increased risk of vaso-occlusive or hemolytic adverse events when administered to SCD patients. Larger, prospective studies using multiple gadolinium-based contrast materials would be useful to confirm the results of our investigation.