Improving Performance by Using a Radiology Extender

Laws That Have Shaped Radiology: Part I

Radiology began as a translation of quantum physics to clinical medicine. Advances in computing and engineering enabled the differentiation of the field into diagnostic radiology, interventional radiology, and radiation oncology as practical responses to rapidly proliferating medical knowledge. Radiology has itself transformed modern medicine, helping clinicians identify, track, and intervene on multiple once deadly diseases. It is practiced in academic departments and hospital based, outpatient center based, or fully remote private groups of varying sizes, often with direct physicist support to optimize the use of complicated equipment. Importantly, radiology was guided to its current form not just by scientific advances, but by the interplay of cultural and governmental forces, as well as hard lessons, the results of constantly shifting balances of competing interests as follows: insurance, pharmaceutical, medical device, hospital, physician, physician extender, and patient. The purpose of this review is to describe the historical legal landscape of diagnostic radiology in the context of ethics, public health initiatives, and patient protections. For clarity, the review is divided into two parts.

Rethinking Clinical Trial Radiology Workflows and Student Training: Integrated Virtual Student Shadowing Experience, Education, and Evaluation

There is consistent demand for clinical exposure from students interested in radiology; however, the COVID-19 pandemic resulted in fewer available options and limited student access to radiology departments. Additionally, there is increased demand for radiologists to manage more complex quantification in reports on patients enrolled in clinical trials. We present an online educational curriculum that addresses both of these gaps by virtually immersing students (radiology preprocessors, or RPs) into radiologists' workflows where they identify and measure target lesions in advance of radiologists, streamlining report quantification. RPs switched to remote work at the beginning of the COVID-19 pandemic in our National Institutes of Health (NIH). We accommodated them by transitioning our curriculum on cross-sectional anatomy and advanced PACS tools to a publicly available online curriculum. We describe collaborations between multiple academic research centers and industry through contributions of academic content to this curriculum. Further, we describe how we objectively assess educational effectiveness with cross-sectional anatomical quizzes and decreasing RP miss rates as they gain experience. Our RP curriculum generated significant interest evidenced by a dozen academic and research institutes providing online presentations including radiology modality basics and quantification in clinical trials. We report a decrease in RP miss rate percentage, including one virtual RP over a period of 1 year. Results reflect training effectiveness through decreased discrepancies with radiologist reports and improved tumor identification over time. We present our RP curriculum and multicenter experience as a pilot experience in a clinical trial research setting. Students are able to obtain useful clinical radiology experience in a virtual learning environment by immersing themselves into a clinical radiologist's workflow. At the same time, they help radiologists improve patient care with more valuable quantitative reports, previously shown to improve radiologist efficiency. Students identify and measure lesions in clinical trials before radiologists, and then review their reports for self-evaluation based on included measurements from the radiologists. We consider our virtual approach as a supplement to student education while providing a model for how artificial intelligence will improve patient care with more consistent quantification while improving radiologist efficiency.

WITHDRAWN: Radiology Extenders: Impact on Throughput and Accuracy for Routine Chest Radiographs

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Assessing the Training Costs and Work of Diagnostic Radiology Residents Using Key Performance Indicators - An Observational Study

RATIONALE AND OBJECTIVES

To quantify the costs and work of diagnostic radiology (DR) residents using the radiology key performance indicator turn-around time (TAT) as the outcome measure.

MATERIALS AND METHODS

In an Institutional Review Board-approved study, the annual cost of a DR resident was determined using salary, benefits, and a cost allocation of faculty effort. The volume of cases reported in the 2015-16 academic year and median and interquartile range (IQR) TAT for a trainee preliminary (Complete to Prelim, C-P) or an attending final (Complete to Final, C-F) radiology report were measured and stratified by time of day and patient location. Wilcoxon rank-sum tests were used (significance, p values < 0.05).

RESULTS

The annual cost of a DR resident was $99,109, 34% greater than direct salary/benefits and 27% of the direct salary/benefits cost of an attending. The total per minute cost of rendering care was $4.36 with both trainee ($0.70/minute) and faculty ($3.66/minute). Residents participated in 139,084/235,417 (59%) imaging studies. The C-P TAT was 74 (IQR, 27-180) minutes compared to 51 (IQR, 18-129) minutes C-F TAT of faculty working alone and C-F TAT of 213 (IQR, 71-469) minutes with a resident (p < 0.001). The C-P TAT vs C-F TAT between 4 pm-9 am and weekends with residents is 44 (IQR, 18-119) minutes vs 60 (IQR, 18-179) minutes without.

CONCLUSION

The cost of training DR residents exceeds the salary and benefits allocated to their training. Residents increase the absolute professional labor cost of caring for a patient. Overall TAT is slower with residents but the care delivered by residents after-hours is faster.

Augmented Radiologist Workflow Improves Report Value and Saves Time: A Potential Model for Implementation of Artificial Intelligence

RATIONALE AND OBJECTIVES

Our primary aim was to improve radiology reports by increasing concordance of target lesion measurements with oncology records using radiology preprocessors (RP). Faster notification of incidental actionable findings to referring clinicians and clinical radiologist exam interpretation time savings with RPs quantifying tumor burden were also assessed.

MATERIALS AND METHODS

In this prospective quality improvement initiative, RPs annotated lesions before radiologist interpretation of CT exams. Clinical radiologists then hyperlinked approved measurements into interactive reports during interpretations. RPs evaluated concordance with our tumor measurement radiologist, the determinant of tumor burden. Actionable finding detection and notification times were also deduced. Clinical radiologist interpretation times were calculated from established average CT chest, abdomen, and pelvis interpretation times.

RESULTS

RPs assessed 1287 body CT exams with 812 follow-up CT chest, abdomen, and pelvis studies; 95 (11.7%) of which had 241 verified target lesions. There was improved concordance (67.8% vs. 22.5%) of target lesion measurements. RPs detected 93.1% incidental actionable findings with faster clinician notification by a median time of 1 hour (range: 15 minutes-16 hours). Radiologist exam interpretation times decreased by 37%.

CONCLUSIONS

This workflow resulted in three-fold improved target lesion measurement concordance with oncology records, earlier detection and faster notification of incidental actionable findings to referring clinicians, and decreased exam interpretation times for clinical radiologists. These findings demonstrate potential roles for automation (such as AI) to improve report value, worklist prioritization, and patient care.

An Initiative to Reduce Unnecessary Gadolinium-Based Contrast in Multiple Sclerosis Patients

OBJECTIVE

Patients with multiple sclerosis (MS) routinely undergo serial contrast-enhanced MRIs. Given concerns regarding tissue deposition of gadolinium-based contrast agents (GBCAs) and evidence that enhancement of lesions is only seen in patients with new disease activity on noncontrast imaging, we set out to implement a prospective quality improvement project whereby intravenous contrast would be reserved only for patients with evidence of new disease activity on noncontrast images.

METHODS

To prospectively implement such a protocol, we leveraged our in-house computer-assisted detection (CAD) software and 3-D laboratory radiology technologists to perform real-time preliminary assessments of the CAD-processed T2 fluid attenuated inversion recovery (FLAIR) noncontrast images as a basis for deciding whether to inject contrast. Before implementation, we held multidisciplinary meetings with neurology, neuroradiology, and MR technologists and distributed surveys to objectively assess opinions and obstacles to clinical implementation. We evaluated reduction in GBCA utilization and technologist performance relative to final neuroradiologist interpretations.

RESULTS

During a 2-month trial period, 153 patients were imaged under the new protocol. Technologists using the CAD software were able to identify patients with new or enlarging lesions on FLAIR images with 95% accuracy and 97% negative predictive value relative to final neuroradiologist interpretations, which allowed us to avoid the use of contrast and additional imaging sequences in 87% of patients.

DISCUSSION

A multidisciplinary effort to implement a quality improvement project to limit contrast in MS patients receiving follow-up MRIs allowed for improved safety and cost by targeting patients that would benefit from the use of intravenous contrast in real-time.