Faculty Bibliography

The Medicare Access and CHIP Reauthorization Act (MACRA) of 2015 advances the goal of tying Medicare payments to quality and value. In April 2016, CMS published an initial proposed rule for MACRA, renaming it the Quality Payment Program (QPP). Under QPP, clinicians receive payments through either advanced alternative payment models or the Merit-Based Incentive Payment System (MIPS), a consolidation of existing federal performance programs that applies positive or negative adjustments to fee-for-service payments. Most physicians will participate in MIPS. This review highlights implications of the QPP and MIPS for radiologists. Although MIPS incorporates radiology-specific quality measures, radiologists will also be required to participate in other practice improvement activities, including patient engagement. Recognizing physicians' unique practice patterns, MIPS will provide special considerations in performance evaluation for physicians with limited face-to-face patient interaction. Although such considerations will affect radiologists' likelihood of success under QPP, many practitioners will be ineligible for the considerations under currently proposed criteria. Reporting using qualified clinical data registries will benefit radiologists' performance by allowing expanded arrays of MIPS and non-MIPS specialty-specific measures. A group practice reporting option will substantially reduce administrative burden but introduce new challenges by requiring uniform determination of patient-facing status and performance measurement for all of the group's physicians (diagnostic radiologists, interventional radiologists, and nonradiologists) under the same taxpayer identification number. Given that the initial MIPS performance period begins in 2017, radiologists must begin preparing for QPP and taking actions to ensure their future success under this new quality-based payment system.

PURPOSE: To evaluate whole-pancreas 3D-histogram ADC metrics in acute pancreatitis. METHODS: In 41 patients with acute pancreatitis undergoing MRI/MRCP with DWI, 3D-volumes-of-interest encompassing the entire pancreas were placed to derive whole-pancreas histogram ADC metrics. RESULTS: There were trends toward higher 0-10th percentile ADC, higher 10-25th percentile ADC, lower skewness, and higher kurtosis in patients with new complications (p=0.065-0.095). Conventional mean ADC showed no association with new complications (p=0.203). Kurtosis had highest area-under-the-curve (0.784) for predicting new complications (sensitivity=75.0%; specificity=91.9%). CONCLUSION: Findings suggest whole-pancreas histogram ADC metrics assist early management of acute pancreatitis, (e.g., patient selection for more intensive monitoring/intervention).

Improvements in prostate MR imaging techniques and the introduction of MR imaging-targeted biopsies have had central roles in prostate cancer (PCa) management. The role of MR imaging has progressed from largely staging patients with biopsy-proven PCa to detecting, characterizing, and guiding the biopsy of suspected PCa. These diagnostic advances, combined with improved therapeutic interventions, have led to a more sophisticated and individually tailored approach to patients' unique PCa profile. This review discusses the MR imaging, a standardized reporting scheme, and the role of fusion-targeted prostate biopsy.

Scientific rigor should be consistently applied to quality improvement (QI) research to ensure that healthcare interventions improve quality and patient safety before widespread implementation. This article provides an overview of the various study designs that can be used for QI research depending on the stage of investigation, scope of the QI intervention, constraints on the researchers and intervention being studied, and evidence needed to support widespread implementation. The most commonly used designs in QI studies are quasi-experimental designs. Randomized controlled trials and cluster randomized trials are typically reserved for large-scale research projects evaluating the effectiveness of QI interventions that may be implemented broadly, have more than a minimal impact on patients, or are costly. Systematic reviews of QI studies will play an important role in providing overviews of evidence supporting particular QI interventions or methods of achieving change. We also review the general requirements for developing quality measures for reimbursement, public reporting, and pay-for-performance initiatives. A critical part of the testing process for quality measures includes assessment of feasibility, reliability, validity, and unintended consequences. Finally, publication and critical appraisal of QI work is discussed as an essential component to generating evidence supporting QI initiatives in radiology.

Promoting quality and safety research is now essential for radiology as reimbursement is increasingly tied to measures of quality, patient safety, efficiency, and appropriateness of imaging. This article provides an overview of key features necessary to promote successful quality improvement efforts in radiology. Emphasis is given to current trends and future opportunities for directing research. Establishing and maintaining a culture of safety is paramount to organizations wishing to improve patient care. The correct culture must be in place to support quality initiatives and create accountability for patient care. Focused educational curricula are necessary to teach quality and safety-related skills and behaviors to trainees, staff members, and physicians. The increasingly complex healthcare landscape requires that organizations build effective data infrastructures to support quality and safety research. Incident reporting systems designed specifically for medical imaging will benefit quality improvement initiatives by identifying and learning from system errors, enhancing knowledge about safety, and creating safer systems through the implementation of standardized practices and standards. Finally, validated performance measures must be developed to accurately reflect the value of the care we provide for our patients and referring providers. Common metrics used in radiology are reviewed with focus on current and future opportunities for investigation.

PURPOSE: The aim of this study was to evaluate the feasibility of using Twitter polls to assess public opinion regarding session content at a national specialty society meeting. METHODS: Twitter polls allow users to embed multiple-choice questions within tweets and automatically aggregate responses. Two radiologists attending the 2016 annual meeting of the ACR posted a Twitter poll containing the hashtag #ACR2016 during 10 meeting sessions addressing socioeconomics/advocacy, patient experience, and social media/informatics (20 polls total). Each poll contained a question asking for an opinion regarding the session's content. Polls were open for responses for 24 hours. RESULTS: The average number of responses per poll was significantly higher for the user with the larger number of Twitter followers (24.3 +/- 14.4 versus 11.2 +/- 9.8, P = .015). A total of 57% of respondents agreed that radiologists' payments should shift to value-based payments, and 86% agreed that radiologists should routinely survey their patients to monitor quality; however, 83% disagreed with basing physician payments on patient satisfaction scores. A total of 85% disagreed that the artificial intelligence supercomputer Watson will entirely replace radiologists. A total of 76% agreed that social media can drive business at less cost than standard marketing. A total of 56% agreed with the direction of the ACR's advocacy and regulatory efforts, whereas 74% considered the ACR's advocacy efforts to be moderately or very useful for their practice. A total of 50% planned to change their practice on the basis of keynote remarks by Dr Ezekiel Emanuel. CONCLUSIONS: Twitter polls provide a free and easy infrastructure to potentially capture global public sentiment during the course of a medical society meeting. Their use may enrich and promote discussions of key session content.

OBJECTIVE: The purpose of this study was to apply a visual assessment of the intensity and pattern of T1 hyperintensity at MRI to differentiate hemorrhagic renal cysts from renal cell carcinoma (RCC). MATERIALS AND METHODS: A total of 144 T1-hyperintense renal lesions (62 cysts, all showing no enhancement on subtracted contrast-enhanced images and either 2-year stability or unenhanced CT density > 70 HU, and 82 histologically confirmed RCCs) in 144 patients were included. Two radiologists independently characterized qualitative features of the T1 hyperintensity in each lesion on unenhanced T1-weighted images. An additional radiologist placed ROIs to measure lesions' T1 signal intensity normalized to that of the psoas muscle. Chi-square and unpaired t tests were performed to compare the pattern of T1 hyperintensity between groups. RESULTS: The T1 hyperintensity was considered marked in 62.9% of cysts and 17.1% of RCCs for reader 1 and in 46.8% of cysts and 8.5% of RCCs for reader 2 (p < 0.001). The T1 hyperintensity exhibited a diffusely homogeneous distribution in 88.7% of cysts and 7.3% of RCCs for reader 1 and in 72.6% of cysts and 4.9% of RCCs for reader 2 (p < 0.001). The combination of both diffusely homogeneous distribution and marked degree of T1 hyperintensity achieved sensitivities of 40.3-56.5%, specificities of 97.6-98.8%, and accuracies of 73.6-79.9% for the diagnosis of T1-hyperintense cysts. The two cases of RCC exhibiting this imaging pattern for at least one reader were both papillary RCCs. Normalized signal intensity was 2.39 +/- 0.99 in T1-hyperintense cysts versus 2.12 +/- 0.84 in T1-hyperintense RCCs (p = 0.088). CONCLUSION: Diffuse T1 hyperintensity, particularly when marked, strongly indicates a hemorrhagic cyst rather than an RCC. Deferral of follow-up imaging may be considered when this imaging appearance is encountered at unenhanced MRI.

PURPOSE: The purpose of the study is to perform a meta-analysis of studies investigating the diagnostic performance of apparent diffusion coefficient (ADC) values in separating high-risk from low-risk prostate cancer (PCa). METHODS: MEDLINE and EMBASE databases were searched in December 2015 for studies reporting diagnostic performance of ADC values for discriminating high-risk from low-risk PCa and providing sufficient data to construct 2 x 2 contingency tables. Diagnostic performance was quantitatively pooled using a bivariate random-effects model including subgroup analysis and assessment of study heterogeneity and methodological quality. RESULTS: 13 studies were included, providing 1107 tumor foci in 705 patients. Heterogeneity among studies was moderate (tau2 = 0.222). Overall sensitivity was 76.9% (95% CI 68.6-83.6%); overall specificity was 77.0% (95% CI 69.9-82.8%); and summary AUC was 0.67. Inverse correlation between sensitivity and specificity (rho = -0.58) indicated interstudy heterogeneity was partly due to variation in threshold for test positivity. Primary biases were readers' knowledge of Gleason score during ADC measurement, lack of prespecified ADC thresholds, and lack of prostatectomy as reference in some studies. Higher sensitivity was seen in studies published within the past 2 years and studies not using b value of at least 2000; higher specificity was associated with involvement of one, rather than two, readers measuring ADC. Field strength, coil selection, and advanced diffusion metrics did not significantly impact diagnostic performance. CONCLUSION: ADC values show moderate accuracy in separating high-risk from low-risk PCa, although important biases may overestimate performance and unexplained sources of heterogeneity likely exist. Further studies using a standardized methodology and addressing identified weaknesses may help guide the use of ADC values for clinical decision-making.