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To detect potentially curable hepatocellular carcinoma (HCC), clinical practice guidelines recommend semiannual surveillance US of the liver in adult patients at risk for developing this malignancy, such as those with cirrhosis and some patients with chronic hepatitis B infection. However, cirrhosis and a large body habitus, both of which are increasingly prevalent in the United States and the rest of the world, may impair US visualization of liver lesions and reduce the sensitivity of surveillance with this modality. The low sensitivity of US for detection of early-stage HCC contributes to delayed diagnosis and increased mortality. Abbreviated MRI, a shortened MRI protocol tailored for early-stage detection of HCC, has been proposed as an alternative surveillance option that provides high sensitivity and specificity. Abbreviated MRI protocols include fewer sequences than a complete multiphase MRI examination and are specifically designed to identify small potentially curable HCCs that may be missed at US. Three abbreviated MRI strategies have been studied: (a) nonenhanced, (b) dynamic contrast material-enhanced, and (c) hepatobiliary phase contrast-enhanced abbreviated MRI. Retrospective studies have shown that simulated abbreviated MRI provides high sensitivity and specificity for early-stage HCC, mostly in nonsurveillance cohorts. If it is supported by scientific evidence in surveillance populations, adoption of abbreviated MRI could advance clinical practice by increasing early detection of HCC, allowing effective treatment and potentially prolonging life in the growing number of individuals with this cancer. Online supplemental material is available for this article. © RSNA, 2020.

Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown. Purpose To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers. Materials and Methods This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2-5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range. Results The authors evaluated 3449 men (mean age, 65 years ± 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%-44% and 27%-48%, respectively. Conclusion The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Milot in this issue.

Purpose: To investigate the national coverage landscape for prostate MRI services, assessing the presence of updated and accurate coverage requirements by private payers., Methods: The database Policy Reporter was used to evaluate private payer coverage related to prostate MRI for 81 plans covering 149 million people in the United States. Both the indications and requirements for prostate MRI coverage were recorded in a variety of clinical scenarios, including initial diagnosis, staging, active surveillance, and suspected recurrence., Results: Overall, 11.1% of payers cover prostate MRI in biopsy-naïve patients with suspected prostate cancer, with the remaining 88.9% requiring a prior negative biopsy. Nearly all payers also require either a rising prostate-specific antigen (PSA) or abnormal digital rectal examination (DRE). Rarely, a planned future MRI-targeted biopsy serves as a basis for MRI coverage. Initial staging is covered by most payers, although typically with stringent indications (eg, PSA ≥ 20 ng/mL, Gleason score ≥7 or 8, stage T3 or T4, or ≥20% risk of nodal metastases). Only 10 payers discuss active surveillance, with 8 of these requiring a repeat biopsy before MRI. Coverage for detection of post-treatment recurrence often requires a rising PSA or abnormal DRE, and occasionally only if a CT is first performed; only 10 of 81 payers address coverage after androgen deprivation treatment., Conclusion: Prostate MRI coverage varies widely among private payers, fails to recognize major clinical scenarios, is overly restrictive, and is often not reflective of current clinical practice. This creates challenges for patients and referring physicians seeking to obtain ready access to prostate MRI services., (Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: Optimizing the utilization of CT pulmonary angiogram (CTPA) for the diagnosis and workup of acute chest pain can provide an opportunity to reduce unnecessary radiation and health care system expense., Methods: An attempt to improve CTPA utilization began by measuring overall department and clinician-specific utilization. This was bolstered by retrospectively evaluating patient charts for pulmonary embolism scoring criteria and D-dimer utilization so as to better understand gaps in diagnostic workup. The department-wide and individualized metrics were then provided to each emergency department clinician and differences between the pre- and postintervention data were evaluated., Results: The percentage of positive CTPAs did not change significantly at 8.7% and 9.2% in the pre- and postintervention groups, respectively. Similarly, the workup of patients based on retrospective PERC and Wells-score criteria did not significantly improve after the intervention. However, the percentage of CTPAs ordered on low D-dimer patients did decrease significantly post-intervention. Further observational analysis uncovered marked variability in clinician ordering behavior and diagnostic rates., Conclusions: Overall, such an intervention seems to have a limited, though not insignificant, impact on the workup of suspected pulmonary embolism. Calculating provider-specific utilization metrics allows both the radiologist and clinician to better understand opportunities to improve health care delivery., (Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

The application of simulation software in health care has transformed quality and process improvement. Specifically, software based on discrete-event simulation (DES) has shown the ability to improve radiology workflows and systems. Nevertheless, despite the successful application of DES in the medical literature, the power and value of simulation remains underutilized. For this reason, the basics of DES modeling are introduced, with specific attention to medical imaging. In an effort to provide readers with the tools necessary to begin their own DES analyses, the practical steps of choosing a software package and building a basic radiology model are discussed. In addition, three radiology system examples are presented, with accompanying DES models that assist in analysis and decision making. Through these simulations, we provide readers with an understanding of the theory, requirements, and benefits of implementing DES in their own radiology practices., (Copyright © 2016 American College of Radiology. All rights reserved.)

The quantitative, multiparametric assessment of brain lesions requires coregistering different parameters derived from MRI sequences. This will be followed by analysis of the voxel values of the ROI within the sequences and calculated parametric maps, and deriving multiparametric models to classify imaging data. There is a need for an intuitive, automated quantitative processing framework that is generalized and adaptable to different clinical and research questions. As such flexible frameworks have not been previously described, we proceeded to construct a quantitative post-processing framework with commonly available software components. Matlab was chosen as the programming/integration environment, and SPM was chosen as the coregistration component. Matlab routines were created to extract and concatenate the coregistration transforms, take the coregistered MRI sequences as inputs to the process, allow specification of the ROI, and store the voxel values to the database for statistical analysis. The functionality of the framework was validated using brain tumor MRI cases. The implementation of this quantitative post-processing framework enables intuitive creation of multiple parameters for each voxel, facilitating near real-time in-depth voxel-wise analysis. Our initial empirical evaluation of the framework is an increased usage of analysis requiring post-processing and increased number of simultaneous research activities by clinicians and researchers with non-technical backgrounds. We show that common software components can be utilized to implement an intuitive real-time quantitative post-processing framework, resulting in improved scalability and increased adoption of post-processing needed to answer important diagnostic questions.

Although conventional contrast-enhanced MR imaging remains the standard-of-care imaging method in the posttreatment evaluation of gliomas, recent developments in therapeutic options such as chemoradiation and antiangiogenic agents have caused the neuro-oncology community to rethink traditional imaging criteria. This article highlights the latest recommendations. These recommendations should be viewed as works in progress. As more is learned about the pathophysiology of glioma treatment response, quantitative imaging biomarkers will be validated within this context. There will likely be further refinements to glioma response criteria, although the lack of technical standardization in image acquisition, postprocessing, and interpretation also need to be addressed., (Copyright © 2013 Elsevier Inc. All rights reserved.)