Shape and texture-based radiomics signature on CT effectively discriminates benign from malignant renal masses.

OBJECTIVES: Using a radiomics framework to quantitatively analyze tumor shape and texture features in three dimensions, we tested its ability to objectively and robustly distinguish between benign and malignant renal masses. We assessed the relative contributions of shape and texture metrics separately and together in the prediction model. MATERIALS AND METHODS: Computed tomography (CT) images of 735 patients with 539 malignant and 196 benign masses were segmented in this retrospective study. Thirty-three shape and 760 texture metrics were calculated per tumor. Tumor classification models using shape, texture, and both metrics were built using random forest and AdaBoost with tenfold cross-validation. Sensitivity analyses on five sub-cohorts with respect to the acquisition phase were conducted. Additional sensitivity analyses after multiple imputation were also conducted. Model performance was assessed using AUC. RESULTS: Random forest classifier showed shape metrics featuring within the top 10% performing metrics regardless of phase, attaining the highest variable importance in the corticomedullary phase. Convex hull perimeter ratio is a consistently high-performing shape feature. Shape metrics alone achieved an AUC ranging 0.64-0.68 across multiple classifiers, compared with 0.67-0.75 and 0.68-0.75 achieved by texture-only and combined models, respectively. CONCLUSION: Shape metrics alone attain high prediction performance and high variable importance in the combined model, while being independent of the acquisition phase (unlike texture). Shape analysis therefore should not be overlooked in its potential to distinguish benign from malignant tumors, and future radiomics platforms powered by machine learning should harness both shape and texture metrics. KEY POINTS: • Current radiomics research is heavily weighted towards texture analysis, but quantitative shape metrics should not be ignored in their potential to distinguish benign from malignant renal tumors. • Shape metrics alone can attain high prediction performance and demonstrate high variable importance in the combined shape and texture radiomics model. • Any future radiomics platform powered by machine learning should harness both shape and texture metrics, especially since tumor shape (unlike texture) is independent of the acquisition phase and more robust from the imaging variations.

Peer learning is both preferable and less expensive than score-based peer review: Initial experience at a tertiary academic center.

PURPOSE: To examine radiologist experiences and perceptions during a transition from score-based peer review to a peer learning program, and to assess differences in time-cost efficiency between the two models of quality improvement. METHODS: Differences in Likert scale survey responses from radiologists (N = 27) in a multispecialty group at a single tertiary academic center before and following intervention were evaluated by Mann-Whitney U test. Multiple variable linear regression analysis assessed independent variables and program preference. RESULTS: All positive impacts rated significantly higher for the peer learning program. Workflow disruption for the peer learning program rated significantly lower. 70.4 % (19 of 27) preferred the new program, and 25.9 % (7 of 27) preferred the old program. Only the "worth investment" questionnaire score demonstrated a significant correlation to program preference and with an effect that was greatest among all variables (Beta = 1.11, p = 0.02). There was a significantly decreased amount of time per month used to complete peer learning exercises (0.76 ± 0.45 h, N = 27) versus peer review exercises (1.71 ± 1.84 h, N = 34, p = 0.011). The result was a difference of 0.95 ± 1.89 h/month (11.4 ± 22.7 h/year), translating to an estimated direct salary time-cost saving of $1653.68/year/radiologists and a direct productivity time-cost saving of $3469.39/year/radiologist when utilizing the peer learning program. CONCLUSIONS: There was a strongly positive perception of the new peer learning program. There was a substantial implied direct time-cost saving from the transition to the peer learning program. PRECIS: The peer learning model emphasizes learning from errors via feedback in a non-punitive environment. This model was positively perceived and demonstrated substantial implied direct time-cost saving.

Multi-attribute Raman spectroscopy (MARS) for monitoring product quality attributes in formulated monoclonal antibody therapeutics.

Rapid release of biopharmaceutical products enables a more efficient drug manufacturing process. Multi-attribute methods that target several product quality attributes (PQAs) at one time are an essential pillar of the rapid-release strategy. The novel, high-throughput, and nondestructive multi-attribute Raman spectroscopy (MARS) method combines Raman spectroscopy, design of experiments, and multivariate data analysis (MVDA). MARS allows the measurement of multiple PQAs for formulated protein therapeutics without sample preparation from a single spectroscopic scan. Variable importance in projection analysis is used to associate the chemical and spectral basis of targeted PQAs, which assists in model interpretation and selection. This study shows the feasibility of MARS for the measurement of both protein purity-related and formulation-related PQAs; measurements of protein concentration, osmolality, and some formulation additives were achieved by a generic multiproduct model for various protein products containing the same formulation components. MARS demonstrates the potential to be a powerful methodology to improve the efficiency of biopharmaceutical development and manufacturing, as it features fast turnaround time, good robustness, less human intervention, and potential for automation.

Multi-attribute method performance profile for quality control of monoclonal antibody therapeutics.

Multi-attribute method (MAM) using peptide map analysis with high resolution mass spectrometry is increasingly common in product characterization and the identification of critical quality attributes (CQAs) of biotherapeutic proteins. Capable of providing structural information specific to amino acid residues, quantifying relative abundance of product variants or degradants, and detecting profile changes between product lots, a robust MAM can replace multiple traditional methods that generate profile-based information for product release and stability testing. In an effort to provide informative and efficient analytical monitoring for monoclonal antibody (mAb) products, from early development to manufacturing quality control, we describe the desired MAM performance profile and address the major scientific challenges in MAM method validation. Furthermore, to support fast speed investigational product development, we describe a platform method validation strategy and results of an optimized MAM workflow. This strategy is applied to support the use of MAM for multiple mAb products with similar structures and physicochemical properties, requiring minimal product-specific method validation activities. Three mAb products were used to demonstrate MAM performance for common and representative product quality attributes. Method validation design and acceptance criteria were guided by the Analytical Target Profile concept, as well as relevant regulatory guidelines to ensure the method is fit-for-purpose. A comprehensive system suitability control strategy was developed, and reported here, to ensure adequate performance of the method including sample preparation, instrument operation, and data analysis. Our results demonstrated sufficient method performance for the characteristics required for quantitative measurement of product variants and degradants.

Epistaxis health disparities in the United States pediatric population.

OBJECTIVE: Despite epistaxis occurring in up to 60% of the population, few studies have investigated health status disparities in the pediatric epistaxis population. The aim of this study was to evaluate sociodemographic risk factors associated with epistaxis visits for pediatric patients. METHODS: Data were extracted from the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey Outpatient Department from 2001 to 2010. Outpatient visits of children less than 18 years who received a primary, secondary, or tertiary diagnosis of epistaxis (ICD-9CM code 784.7X) were included. Bivariate and stepwise multivariate regressions were conducted to develop a final model for epistaxis visits described by sociodemographics. RESULTS: Epistaxis visits accounted for 5 ±â€¯0.6 million visits in children less than 18 years. 51% and 33% of children presenting with epistaxis had private insurance and Medicaid, respectively (p = 0.001). 69% of epistaxis visits were evaluated at a pediatric clinic, 18% at an ENT/surgery clinic, and 13% at a general/family medicine clinic (p < 0.0001). After multivariate adjustment, epistaxis visits were associated with older age (p = 0.006). Black children were more likely to present with epistaxis (95% CI 1.3-4.1, p = 0.005) compared to white children. Allergic rhinitis, present in 11% of epistaxis visits, was a significant comorbidity associated with visits (95%CI 1.3-4.6, p = 0.008). Patients were also more likely to present to an ENT/surgery clinic (95% CI 4.5-16.5, p < 0.0001) compared to a general/family medicine clinic. CONCLUSIONS: Epistaxis visits by children are associated with age, race, and specialty. Targeted interventions to help reduce this common presentation should be developed.

Trends in Influenza and Pneumococcal Vaccination Among US Nursing Home Residents, 2006-2014.

BACKGROUND: Institutionalized adults are at increased risk of morbidity and mortality from influenza and pneumococcal infection. Influenza and pneumococcal vaccination have been shown to be effective in reducing hospitalization and deaths due to pneumonia and influenza in this population. OBJECTIVE: To assess trends in influenza vaccination coverage among US nursing home residents from the 2005-2006 through 2014-2015 influenza seasons and trends in pneumococcal vaccination coverage from 2006 to 2014 among US nursing home residents, by state and demographic characteristics. METHODS: Data were analyzed from the Centers for Medicare and Medicaid Services' (CMS's) Minimum Data Set (MDS). Influenza and pneumococcal vaccination status were assessed for all residents of CMS-certified nursing homes using data reported to the MDS by all certified facilities. RESULTS: Influenza vaccination coverage increased from 71.4% in the 2005-2006 influenza season to 75.7% in the 2014-2015 influenza season and pneumococcal vaccination coverage increased from 67.4% in 2006 to 78.4% in 2014. Vaccination coverage varied by state, with influenza vaccination coverage ranging from 50.0% to 89.7% in the 2014-2015 influenza season and pneumococcal vaccination coverage ranging from 55.0% to 89.7% in 2014. Non-Hispanic black and Hispanic residents had lower coverage compared with non-Hispanic white residents for both vaccines, and these differences persisted over time. CONCLUSION: Influenza and pneumococcal vaccination among US nursing home residents remains suboptimal. Nursing home staff can employ strategies such as provider reminders and standing orders to facilitate offering vaccination to all residents along with culturally appropriate vaccine promotion to increase vaccination coverage among this vulnerable population.

Intra-session test-retest reliability of magnitude and structure of center of pressure from the Nintendo Wii Balance Board™ for a visually impaired and normally sighted population.

Individuals with visual impairment (VI) have irreparable damage to one of the input streams contributing to postural stability. Here, we evaluated the intra-session test-retest reliability of the Wii Balance Board (WBB) for measuring Center of Pressure (COP) magnitude and structure, i.e. approximate entropy (ApEn) in fourteen legally blind participants and 21 participants with corrected-to-normal vision. Participants completed a validated balance protocol which included four sensory conditions: double-leg standing on a firm surface with eyes open (EO-firm); a firm surface with eyes closed (EC-firm); a foam surface with EO (EO-foam); and a foam surface with EC (EC-foam). Participants performed the full balance protocol twice during the session, separated by a period of 15min, to determine the intraclass correlation coefficient (ICC). Absolute reliability was determined by the standard error of measurement (SEM). The minimal difference (MD) was estimated to determine clinical significance for future studies. COP measures were derived from data sent by the WBB to a laptop via Bluetooth. COP scores increased with the difficulty of sensory condition indicating WBB sensitivity (all p<0.01). ICCs in the VI group ranged from 0.73 to 0.95, indicating high to very high correlations, and the normal group showed moderate to very high ICCs (0.62-0.94). The SEM was comparable between groups regardless of between-subject variability. The reliability of the WBB makes it practical to screen for balance impairment among VI persons.