Faculty Bibliography

PURPOSE: To evaluate pathologic outcomes and associations with MRI features in small renal masses measuring up to 20mm METHODS: 86 patients (61+/-13 years; 45M/41F) with 92 renal masses measuring up to 20mm that underwent MRI prior to tissue diagnosis were included. Two radiologists independently evaluated all masses for microscopic lipid, hemorrhage, T2-hyperintensity, T2-homogeneity, cystic/necrotic areas, hypervascularity, enhancement homogeneity, circumscribed margins, and predominantly exophytic location. These MRI features, as well as patient age, gender, and history of RCC, were compared with pathologic findings using Fisher's exact test, unpaired t-test, and multivariate logistic regression. RESULTS: 26.1% (24/92) of masses under 2cm were benign, only 32.6% (30/92) were clear-cell RCC, and only 7.6% (7/92) were high-grade. Among 16 masses measuring up to 1cm, only 12.5% (2/16) were clear-cell RCC, and none was high-grade. Within the entire cohort, no MRI or clinical feature showed a significant difference between benign and malignant lesions (p>/=0.053). However, for both readers, clear-cell RCC exhibited a significantly higher frequency of T2-hyperintensity, cystic/necrotic areas, and hypervascularity, and a significantly lower frequency of hemorrhage, T2-homogeneity, and enhancement homogeneity (p<0.001-0.036). Hypervascularity was a significant independent predictor of clear-cell RCC for both readers (p=0.002-0.007), as was T2-hyperintensity for reader 2 (p=0.007). CONCLUSION: A substantial fraction of small renal masses were benign, and when malignant, largely exhibited indolent pathologic characteristics, particularly when measuring under 1cm Although small benign and malignant masses could not be differentiated on MRI, hypervascularity showed a significant independent association with clear-cell RCC in comparison with other lesions.

PURPOSE: To present results of a pilot study to develop software that identifies regions suspicious for prostate transition zone (TZ) tumor, free of user input. MATERIALS AND METHODS: Eight patients with TZ tumors were used to develop the model by training a Naive Bayes classifier to detect tumors based on selection of most accurate predictors among various signal and textural features on T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) maps. Features tested as inputs were: average signal, signal standard deviation, energy, contrast, correlation, homogeneity and entropy (all defined on T2WI); and average ADC. A forward selection scheme was used on the remaining 20% of training set supervoxels to identify important inputs. The trained model was tested on a different set of ten patients, half with TZ tumors. RESULTS: In training cases, the software tiled the TZ with 4 x 4-voxel "supervoxels," 80% of which were used to train the classifier. Each of 100 iterations selected T2WI energy and average ADC, which therefore were deemed the optimal model input. The two-feature model was applied blindly to the separate set of test patients, again without operator input of suspicious foci. The software correctly predicted presence or absence of TZ tumor in all test patients. Furthermore, locations of predicted tumors corresponded spatially with locations of biopsies that had confirmed their presence. CONCLUSION: Preliminary findings suggest that this tool has potential to accurately predict TZ tumor presence and location, without operator input.J. Magn. Reson. Imaging 2013; (c) 2013 Wiley Periodicals, Inc.

INTRODUCTION: Tumor grade plays a critical role in the management of papillary non-invasive urothelial carcinoma (UC). Since grading of UC relies on morphologic criteria, variability in interpretation exists among pathologists. The objective of this study was to examine inter-observer variability in the grading of papillary non-invasive UC at a single academic medical center. MATERIALS AND METHODS: One general pathologist and two genitourinary pathologists were blinded to patient identity and graded 98 consecutive UC specimens using the 1973 and 2004 classification systems. Kappa statistics (kappa) were used to measure inter-observer reproducibility to account for agreement expected purely by chance. By convention, varkappa values from 0.21-0.4 represent "fair", from 0.41-0.6 represent "moderate", and > 0.6 represent "substantial" agreement. RESULTS: Raw percentage agreement among all three pathologists was only 26% using the 1973 system and 47% using the 2004 system. When measured by kappa, overall agreement was only "fair" for both systems and while higher for the 2004 system than the 1973, this was not significant (: 0.38 versus 0.26, respectively). There were no significant differences in agreement when comparing the specialists agreement between themselves with agreement between each specialist and the generalist (varkappa: 0.31-0.37 versus varkappa: 0.18-0.46). CONCLUSIONS: The current grading system continues to demonstrate challenges in reproducibility among general and specialized pathologists. The degree of variability has significant implications on management decisions for non-invasive UC. Our findings underscore the need to identify molecular markers that can provide a more objective and reliable risk stratification system to guide patient management.

BACKGROUND: Increasing evidence supports the use of magnetic resonance (MR)-targeted prostate biopsy. The optimal method for such biopsy remains undefined, however. OBJECTIVE: To prospectively compare targeted biopsy outcomes between MR imaging (MRI)-ultrasound fusion and visual targeting. DESIGN, SETTING, AND PARTICIPANTS: From June 2012 to March 2013, prospective targeted biopsy was performed in 125 consecutive men with suspicious regions identified on prebiopsy 3-T MRI consisting of T2-weighted, diffusion-weighted, and dynamic-contrast enhanced sequences. INTERVENTION: Two MRI-ultrasound fusion targeted cores per target were performed by one operator using the ei-Nav|Artemis system. Targets were then blinded, and a second operator took two visually targeted cores and a 12-core biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biopsy information yield was compared between targeting techniques and to 12-core biopsy. Results were analyzed using the McNemar test. Multivariate analysis was performed using binomial logistic regression. RESULTS AND LIMITATIONS: Among 172 targets, fusion biopsy detected 55 (32.0%) cancers and 35 (20.3%) Gleason sum >/=7 cancers compared with 46 (26.7%) and 26 (15.1%), respectively, using visual targeting (p=0.1374, p=0.0523). Fusion biopsy provided informative nonbenign histology in 77 targets compared with 60 by visual (p=0.0104). Targeted biopsy detected 75.0% of all clinically significant cancers and 86.4% of Gleason sum >/=7 cancers detected on standard biopsy. On multivariate analysis, fusion performed best among smaller targets. The study is limited by lack of comparison with whole-gland specimens and sample size. Furthermore, cancer detection on visual targeting is likely higher than in community settings, where experience with this technique may be limited. CONCLUSIONS: Fusion biopsy was more often histologically informative than visual targeting but did not increase cancer detection. A trend toward increased detection with fusion biopsy was observed across all study subsets, suggesting a need for a larger study size. Fusion targeting improved accuracy for smaller lesions. Its use may reduce the learning curve necessary for visual targeting and improve community adoption of MR-targeted biopsy.