Faculty Bibliography

OBJECTIVE. The purposes of this study were to evaluate the outcome of new arterial phase enhancing nodules at MRI of cirrhotic livers, including clinical and imaging factors that affect progression to hepatocellular carcinoma (HCC), and to assess the diagnostic performance of Liver Imaging Reporting and Data System version 2018 (LI-RADSv2018) versus version 2017 (LI-RADSv2017) in categorizing these nodules. MATERIALS AND METHODS. A database search identified 129 new arterial phase enhancing, round, solid, space-occupying nodules in 79 patients with cirrhosis who underwent surveillance MRI. Three readers assessed the nodules for LI-RADS findings and made assessments based on the 2017 and 2018 criteria. Clinical information and laboratory values were collected. Outcome data were assessed on the basis of follow-up imaging and pathology results. Interreader agreement was assessed. Logistic regression and ROC curve analyses were used to assess the utility of the features for prediction of progression to HCC. RESULTS. Of the 129 nodules, 71 (55%) progressed to HCC. LI-RADSv2017 score, LIRADSv2018 score, and mild-to-moderate T2 hyperintensity were significant independent predictors of progression to HCC in univariate analyses. Serum α-fetoprotein level, hepatitis B or C virus infection as the cause of liver disease, and presence of other HCCs were significant predictors of progression to HCC in multivariate analyses. The rates of progression of LI-RADS category 3 and 4 observations were 38.1% and 57.6%, respectively, for LI-RADSv2017 and 44.4% and 69.9%, respectively, for LI-RADSv2018. CONCLUSION. New arterial phase enhancing nodules in patients with cirrhosis frequently progress to HCC. Factors such as serum α-fetoprotein level and presence of other HCCs are strong predictors of progression to HCC.

OBJECTIVE:Guideline-concordant follow-up of incidental lung nodules (ILNs) is suboptimal. We aimed to improve communication and tracking for follow-up of these common incidental findings detected on imaging examinations. METHODS:We implemented a process improvement program for reporting and tracking ILNs at a large urban academic health care system. A multidisciplinary committee designed, tested, and implemented a multipart tracking system in the electronic health record (EHR) that included Fleischner Society management recommendations for each patient. Plan-do-study-act cycles addressed gaps in the follow-up of ILNs, broken into phases of developing and testing components of the conceived EHR toolkit. RESULTS:The program resulted in standardized text macros with discrete categories and recommendations for ILNs, with ability to track each case in a work list within the EHR. The macros incorporated evidence-based guidelines and also input of collaborating clinical referrers in the respective specialty. The ILN macro was used 3,964 times over the first 2 years, increasing from 104 to over 300 uses per month. Usage spread across all subspecialty divisions, with nonthoracic radiologists currently accounting for 80% (56 of 70) of the radiologists using the system and 31% (1,230 of 3,964) of all captured ILNs. When radiologists indicated ILNs as warranting telephone communication to provider offices, completion was documented in 100% of the cases captured in the EHR-embedded tracking report. CONCLUSION/CONCLUSIONS:An EHR-based system for managing incidental nodules enables case tracking with exact recommendations, provider communication, and completion of follow-up testing. Future efforts will target consistent radiologist use of the system and follow-up completion.

INTRODUCTION/BACKGROUND:Communication and physician burn out are major issues within Radiology. This study is designed to determine the utilization and cost benefit of a hybrid computer/human communication tool to aid in relay of clinically important imaging findings. MATERIAL AND METHODS/METHODS:Analysis of the total number of tickets, (requests for assistance) placed, the type of ticket and the turn-around time was performed. Cost analysis of a hybrid computer/human communication tool over a one-year period was based on human costs as a multiple of the time to close the ticket. Additionally, we surveyed a cohort of radiologists to determine their use of and satisfaction with this system. RESULTS:14,911 tickets were placed in the 6-month period, of which 11,401 (76.4%) were requests to "Get the Referring clinician on the phone." The mean time to resolution (TTR) of these tickets was 35.3 (±17.4) minutes. Ninety percent (72/80) of radiologists reported being able to interpret a new imaging study instead of waiting to communicate results for the earlier study, compared to 50% previously. 87.5% of radiologists reported being able to read more cases after this system was introduced. The cost analysis showed a cost savings of up to $101.12 per ticket based on the length of time that the ticket took to close and the total number of placed tickets. CONCLUSIONS:A computer/human communication tool can be translated to significant time savings and potentially increasing productivity of radiologists. Additionally, the system may have a cost savings by freeing the radiologist from tracking down referring clinicians prior to communicating findings.

PURPOSE/OBJECTIVE:To determine the utility of an automated radiology-pathology feedback tool. METHODS:We previously developed a tool that automatically provides radiologists with pathology results related to imaging examinations they interpreted. The tool also allows radiologists to mark the results as concordant or discordant. Five abdominal radiologists prospectively scored their own discordant results related to their previously interpreted abdominal ultrasound, CT, and MR interpretations between August 2017 and June 2018. Radiologists recorded whether they would have followed up on the case if there was no automated alert, reason for the discordance, whether the result required further action, prompted imaging rereview, influenced future interpretations, enhanced teaching files, or inspired a research idea. RESULTS:There were 234 total discordances (range 30-66 per radiologist), and 70.5% (165 of 234) of discordances would not have been manually followed up in the absence of the automated tool. Reasons for discordances included missed findings (10.7%; 25 of 234), misinterpreted findings (29.1%; 68 of 234), possible biopsy sampling error (13.3%; 31 of 234), and limitations of imaging techniques (32.1%; 75/234). In addition, 4.7% (11 of 234) required further radiologist action, including report addenda or discussion with referrer or pathologist, and 93.2% (218 of 234) prompted radiologists to rereview the images. Radiologists reported that they learned from 88% (206 of 234) of discordances, 38.6% (90 of 233) of discordances probably or definitely influenced future interpretations, 55.6% (130 of 234) of discordances prompted the radiologist to add the case to his or her teaching files, and 13.7% (32 of 233) inspired a research idea. CONCLUSION/CONCLUSIONS:Automated pathology feedback provides a valuable opportunity for radiologists across experience levels to learn, increase their skill, and improve patient care.

OBJECTIVE. The objective of this article is to show how artificial intelligence (AI) has impacted different components of the imaging value chain thus far as well as to describe its potential future uses. CONCLUSION. The use of AI has the potential to greatly enhance every component of the imaging value chain. From assessing the appropriateness of imaging orders to helping predict patients at risk for fracture, AI can increase the value that musculoskeletal imagers provide to their patients and to referring clinicians by improving image quality, patient centricity, imaging efficiency, and diagnostic accuracy.

This article proposes a consensus nomenclature for fat-containing renal and adrenal masses at MRI to reduce variability, improve understanding, and enhance communication when describing imaging findings. The MRI appearance of "macroscopic fat" occurs due to a sufficient number of aggregated adipocytes and results in one or more of: 1) intratumoral signal intensity (SI) loss using fat-suppression techniques, or 2) chemical shift artifact of the second kind causing linear or curvilinear India-ink (etching) artifact within or at the periphery of a mass at macroscopic fat-water interfaces. "Macroscopic fat" is most commonly observed in adrenal myelolipoma and renal angiomyolipoma (AML) and only rarely encountered in other adrenal cortical tumors and renal cell carcinomas (RCC). Nonlinear noncurvilinear signal intensity loss on opposed-phase (OP) compared with in-phase (IP) chemical shift MRI (CSI) may be referred to as "microscopic fat" and is due to: a) an insufficient amount of adipocytes, or b) the presence of fat within tumor cells. Determining whether the signal intensity loss observed on CSI is due to insufficient adipocytes or fat within tumor cells cannot be accomplished using CSI alone; however, it can be inferred when other imaging features strongly suggest a particular diagnosis. Fat-poor AML are homogeneously hypointense on T₂ -weighted (T₂ W) imaging and avidly enhancing; signal intensity loss at OP CSI is uncommon, but when present is usually focal and is caused by an insufficient number of adipocytes within adjacent voxels. Conversely, clear-cell RCC are heterogeneously hyperintense on T₂ W imaging and avidly enhancing, with the signal intensity loss observed on OP CSI being typically diffuse and due to fat within tumor cells. Adrenal adenomas, adrenal cortical carcinoma, and adrenal metastases from fat-containing primary malignancies also show signal intensity loss on OP CSI due to fat within tumor cells and not from intratumoral adipocytes. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019.

PURPOSE/OBJECTIVE:To determine the need for a standardized renal mass reporting template by analyzing reports of indeterminate renal masses and comparing their contents to stated preferences of radiologists and urologists. METHODS:The host IRB waived regulatory oversight for this multi-institutional HIPAA-compliant quality improvement effort. CT and MRI reports created to characterize an indeterminate renal mass were analyzed from 6 community (median: 17 reports/site) and 6 academic (median: 23 reports/site) United States practices. Report contents were compared to a published national survey of stated preferences by academic radiologists and urologists from 9 institutions. Descriptive statistics and Chi-square tests were calculated. RESULTS:Of 319 reports, 85% (271; 192 CT, 79 MRI) reported a possibly malignant mass (236 solid, 35 cystic). Some essential elements were commonly described: size (99% [269/271]), mass type (solid vs. cystic; 99% [268/271]), enhancement (presence vs. absence; 92% [248/271]). Other essential elements had incomplete penetrance: the presence or absence of fat in solid masses (14% [34/236]), size comparisons when available (79% [111/140]), Bosniak classification for cystic masses (54% [19/35]). Preferred but non-essential elements generally were described in less than half of reports. Nephrometry scores usually were not included for local therapy candidates (12% [30/257]). Academic practices were significantly more likely than community practices to include mass characterization details, probability of malignancy, and staging. Community practices were significantly more likely to include management recommendations. CONCLUSIONS:Renal mass reporting elements considered essential or preferred often are omitted in radiology reports. Variation exists across radiologists and practice settings. A standardized template may mitigate these inconsistencies.

The original version of this article contained an error in author name. The co-author's name was published as Ivan M. Pedrosa, instead it should be Ivan Pedrosa. The original article has been corrected.

Radiologists are facing increasing workplace pressures that can lead to decreased job satisfaction and burnout. The increasing complexity and volumes of cases and increasing numbers of noninterpretive tasks, compounded by decreasing reimbursements and visibility in this digital age, have created a critical need to develop innovations that optimize workflow, increase radiologist engagement, and enhance patient care. During their workday, radiologists often must navigate through multiple software programs, including picture archiving and communication systems, electronic health records, and dictation software. Furthermore, additional noninterpretive duties can interrupt image review. Fragmented data and frequent task switching can create frustration and potentially affect patient care. Despite the current successful technological advancements across industries, radiology software systems often remain nonintegrated and not leveraged to their full potential. Each step of the imaging process can be enhanced with use of information technology (IT). Successful implementation of IT innovations requires a collaborative team of radiologists, IT professionals, and software programmers to develop customized solutions. This article includes a discussion of how IT tools are used to improve many steps of the imaging process, including examination protocoling, image interpretation, reporting, communication, and radiologist feedback. ^©RSNA, 2018.

The disease-focused panel (DFP) program was created by the Society of Abdominal Radiology (SAR) as a mechanism to "improve patient care, education, and research" in a "particular disease or a particular aspect of a disease". The DFP on renal cell carcinoma (RCC) was proposed in 2014 and has been functional for 4 years. Although nominally focused on RCC, the scope of the DFP has included indeterminate renal masses because many cannot be assigned a specific diagnosis when detected. Since its founding, the DFP has been active in a variety of clinical, research, and educational projects to optimize the care of patients with known or suspected RCC. The DFP is utilizing multi-institutional and cross-disciplinary collaboration to differentiate benign from malignant disease, optimize the management of early stage RCC, and ultimately to differentiate indolent from aggressive cancers. Several additional projects have worked to develop a quantitative biomarker that predicts metastatic RCC response to anti-angiogenic therapy. While disease focus is the premise by which all DFPs are created, it is likely that in the future the RCC DFP will need to expand or create new panels that will focus on other specific aspects of RCC-a result that the program's founders envisioned. New knowledge creates a need for more focus.