Development of a Multiparametric Renal CT Algorithm for Diagnosis of Clear Cell Renal Cell Carcinoma Among Small (≤ 4 cm) Solid Renal Masses.

BACKGROUND. The MRI clear cell likelihood score predicts the likelihood that a renal mass is clear cell renal cell carcinoma (ccRCC). A CT-based algorithm has not yet been established. OBJECTIVE. The purpose of our study was to develop and evaluate a CT-based algorithm for diagnosing ccRCC among small (≤ 4 cm) solid renal masses. METHODS. This retrospective study included 148 patients (73 men, 75 women; mean age, 58 ± 12 [SD] years) with 148 small (≤ 4 cm) solid (> 25% enhancing tissue) renal masses that underwent renal mass CT (unenhanced, corticomedullary, and nephrographic phases) before resection between January 2016 and December 2019. Two radiologists independently evaluated CT examinations and recorded calcification, mass attenuation in all phases, mass-to-cortex corticomedullary attenuation ratio, and heterogeneity score (score on a 5-point Likert scale, assessed in corticomedullary phase). Features associated with ccRCC were identified by multivariable logistic regression analysis and then used to create a five-tiered CT score for diagnosing ccRCC. RESULTS. The masses comprised 53% (78/148) ccRCC and 47% (70/148) other histologic diagnoses. The mass-to-cortex corticomedullary attenuation ratio was higher for ccRCC than for other diagnoses (reader 1: 0.84 ± 0.68 vs 0.68 ± 0.65, p = .02; reader 2: 0.75 ± 0.29 vs 0.59 ± 0.25, p = .02). The heterogeneity score was higher for ccRCC than other diagnoses (reader 1: 4.0 ± 1.1 vs 1.5 ± 1.6, p < .001; reader 2: 4.4 ± 0.9 vs 3.3 ± 1.5, p < .001). Other features showed no difference. A five-tiered diagnostic algorithm including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score had interobserver agreement of 0.71 (weighted κ) and achieved an AUC for diagnosing ccRCC of 0.75 (95% CI, 0.68-0.82) for reader 1 and 0.72 (95% CI, 0.66-0.82) for reader 2. A CT score of 4 or greater achieved sensitivity, specificity, and PPV of 71% (95% CI, 59-80%), 79% (95% CI, 67-87%), and 79% (95% CI, 67-87%) for reader 1 and 42% (95% CI, 31-54%), 81% (95% CI, 70-90%), and 72% (95% CI, 56-84%) for reader 2. A CT score of 2 or less had NPV of 85% (95% CI, 69-95%) for reader 1 and 88% (95% CI, 69-97%) for reader 2. CONCLUSION. A five-tiered renal CT algorithm, including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score, had substantial interobserver agreement, moderate AUC and PPV, and high NPV for diagnosing ccRCC. CLINICAL IMPACT. The CT algorithm, if validated, may represent a useful clinical tool for diagnosing ccRCC.

The Effect of Mask Wearing on the Accuracy of Radiology Reports in an Academic Hospital Setting.

PURPOSE: In response to the pandemic, some public health agencies recommend the wearing of surgical masks in indoor spaces including radiology common reporting rooms. We aim to demonstrate whether mask wearing may lead to increased errors incidence in radiology reports. MATERIALS AND METHODS: Our prospective studywas conveyed in 2 parts. Firstly, the participants were surveyed if they believed that mask affected dictation. Then participants performed a dictation: they read artificial radiology reports using a commercial voice recognition (VR) system. They performed this task 5 times, each time donning a different mask in random order: a surgical mask, surgical visor, N-95, combination of 2 surgical masks and no mask. Error rates were compared with the Friedman test followed by pairwise Wilcoxon with bootstrapping. Multivariate Poisson regression was performed to test for interaction effects between potential predictors. RESULTS: 52 members of an academic radiology department participatedin the study (January - March 2021) . 65.4% of survey participants did not think or were not sure whether mask wearing could affect dictation process. Treating the no-mask condition as baseline, our study found that mean error rates significantly increased up to 2 times the baseline rate when a surgical mask, surgical visor, N-95 or a combination of 2 masks was donned (p < 0.0001). No significant differences in error rates were found between the different mask types (p > 0.05). Error rates were higher for participants with shorter VR training time (p < 0.0001) or who were non-native English speakers (p < 0.0001). There were no interaction effects between mask type, VR training time or English nativity, suggesting these variables to be independent predictors for error rate. Academic rank did not significantly affect the error rate. CONCLUSION: radiologists underestimate the influence of masks on dictation accuracy. mask wearing may lead to significant increase in dictational errors.

Proposed Modifications to the Multiparametric CT Score for Diagnosis of ccRCC Using Hyperattenuation, Segmental Enhancement Inversion, and ADER: A Secondary Analysis.

In a secondary analysis of 148 small (≤ 4 cm) solid renal masses, none of three CT features (hyperattenuation on unenhanced images, segmental enhancement inversion, or arterial-to-delayed enhancement ratio) significantly improved the performance of a multiparametric CT score for the diagnosis of clear cell renal cell carcinoma.

Classification and communication of critical findings in emergency radiology: a scoping review.

PURPOSE: To identify the published standards for the classification and communication of critical actionable findings in emergency radiology, and the associated facilitators and barriers to communication and message management/dissemination of such findings. MATERIALS AND METHODS: Search terms for resources pertaining to critical findings (CFs) in emergency radiology were applied to 2 databases (PubMed, Embase). Screening of hits using the following pre-established inclusion and exclusion criteria were performed by 3 analysts with subsequent consensus discussion for discrepancies: 1) The resources include any standards for the classification and/or communication of imaging findings as critical OR 2) The resource discusses any facilitators to the communication of CFs OR 3) The resource discusses any barriers to the communication of CFs. Resources with explicit focus on a pediatric population or predominant focus on artificial intelligence/natural language processing were omitted. Accompanying gray literature search was used to expand included resources. Data extraction included: year, country, resource type, scope/purpose, participants, context, standards to identifying/communicating CFs, facilitators/barriers, method type, recommendations, applicability, and disclosures. RESULTS: Seventy-six resources were included in the final analysis, including 16 societal/commission guidelines. Among the guidelines, no standardized list of CFs was identified, with typical recommendations suggesting application of a local policy. Communication standards included direct closed-loop communication for high acuity findings, with more flexible communication channels for less acute findings. Applied interventions for CFs management, most frequently fell into 4 categories: electronic (n=10), hybrid i.e., electronic/administrative (n = 3), feedback/education (n=5), and administrative (n=4). CONCLUSION: There are published standards, policies and interventions for the management of CFs in emergency radiology. 3-tier stratification (e.g. critical/urgent/incidental) based on time-sensitivity and severity is most common with most critical findings necessitating closed-loop communication. Awareness of systemic facilitators and barriers should inform local policy development. Electronic and administrative communication pathways are useful adjuncts. Further research should offer comparative analyses of different CF interventions with regards to cost-effectiveness, notification time, and user feedback.