Faculty Bibliography

RATIONALE AND OBJECTIVES: Correlation of imaging studies and reference standard outcomes is a significant challenge in radiology. This study evaluates the effectiveness of a new communication tool by assessing the ability of this system to correctly match the imaging studies to arthroscopy reports and qualitatively assessing radiologist behavior before and after the implementation of this system. MATERIALS AND METHODS: Using a commercially available communication or educational tool and applying a novel matching rule algorithm, radiology and arthroscopy reports were matched from January 17, 2017 to March 1, 2017 based on anatomy. The interpreting radiologist was presented with email notifications containing the impression of the imaging report and the entire arthroscopy report. Total correlation rate of appropriate report pairings, modality-specific correlation rate, and the anatomy-specific correlation rate were calculated. Radiologists using the system were given a survey. RESULTS: Overall correlation rate for all musculoskeletal imaging was 83.1% (433 or 508). Low correlation was found in fluoroscopic procedures at 74.4%, and the highest correlation was found with ultrasound at 88.4%. Anatomic location varied from 51.6% for spine to 98.8% for hips and pelvis studies. Survey results revealed 87.5% of the respondents reporting being either satisfied or very satisfied with the new communication tool. The survey also revealed that some radiologists reviewed more cases than before. CONCLUSIONS: Matching of radiology and arthroscopy reports by anatomy allows for excellent report correlation (83.1%). Automated correlation improves the quality and efficiency of feedback to radiologists, providing important opportunities for learning and improved accuracy.

Radiology has historically been at the forefront of innovation and the advancement of technology for the benefit of patient care. However, challenges to early implementation prevented most radiologists from adopting and integrating certified electronic health record technology (CEHRT) into their daily workflow despite the early and potential advantages it offered. This circumstance places radiology at a disadvantage in the two payment pathways of the Medicare Access and CHIP Reauthorization Act of 2015: the Merit-Based Incentive Payment System (MIPS) and advanced alternative payment models (APMs). Specifically, not integrating CEHRT hampers radiology's ability to receive bonus points in the quality performance category of the MIPS and in parallel threatens certain threshold requirements for advanced APMs under the new Quality Payment Program. Radiology must expand the availability and use of CEHRT to satisfy existing performance measures while creating new performance measures that create value for the health care system. In addition, radiology IT vendors will need to ensure their products (eg, radiology information systems, PACS, and radiology reporting systems) are CEHRT compliant and approved. Such collective efforts will increase radiologists' quality of patient care, contribution to value driven activities, and overall health care relevance.

OBJECTIVE:Radiologic technologists may repeat images within a radiographic examination because of perceived suboptimal image quality, excluding these original images from submission to a PACS. This study assesses the appropriateness of technologists' decisions to repeat musculoskeletal and chest radiographs as well as the utility of repeat radiographs in addressing examinations' clinical indication. MATERIALS AND METHODS/METHODS:We included 95 musculoskeletal and 87 chest radiographic examinations in which the technologist repeated one or more images because of perceived image quality issues, rejecting original images from PACS submission. Rejected images were retrieved from the radiograph unit and uploaded for viewing on a dedicated server. Musculoskeletal and chest radiologists reviewed rejected and repeat images in their timed sequence, in addition to the studies' remaining images. Radiologists answered questions regarding the added value of repeat images. RESULTS:The reviewing radiologist agreed with the reason for rejection for 64.2% of musculoskeletal and 60.9% of chest radiographs. For 77.9% and 93.1% of rejected radiographs, the clinical inquiry could have been satisfied without repeating the image. For 75.8% and 64.4%, the repeated images showed improved image quality. Only 28.4% and 3.4% of repeated images were considered to provide additional information that was helpful in addressing the clinical question. CONCLUSION/CONCLUSIONS:Most repeated radiographs (chest more so than musculoskeletal radiographs) did not add significant clinical information or alter diagnosis, although they did increase radiation exposure. The decision to repeat images should be made after viewing the questionable image in context with all images in a study and might best be made by a radiologist rather than the performing technologist.

The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiology. But rather than being a significant threat to radiologists, we believe these changes, particularly machine learning/artificial intelligence, will be a boon to radiologists by increasing their value, efficiency, accuracy, and personal satisfaction.

OBJECTIVE: The purpose of this article is to review current and emerging techniques and strategies that can be used to accelerate acquisition times in routine knee MRI. CONCLUSION: Specific techniques reviewed include 3D fast spin-echo imaging as well as new approaches to rapid image acquisition techniques (parallel imaging, compressed sensing, simultaneous multislice, and neural network reconstruction techniques) and their potential application to knee MRI.

RATIONALE AND OBJECTIVES: This study aims to assess the impact of off-campus facility expansion by a large academic health system on patient travel times for screening mammography. MATERIALS AND METHODS: Screening mammograms performed from 2013 to 2015 and associated patient demographics were identified using the NYU Langone Medical Center Enterprise Data Warehouse. During this time, the system's number of mammography facilities increased from 6 to 19, reflecting expansion beyond Manhattan throughout the New York metropolitan region. Geocoding software was used to estimate driving times from patients' homes to imaging facilities. RESULTS: For 147,566 screening mammograms, the mean estimated patient travel time was 19.9 +/- 15.2 minutes. With facility expansion, travel times declined significantly (P < 0.001) from 26.8 +/- 18.9 to 18.5 +/- 13.3 minutes (non-Manhattan residents: from 31.4 +/- 20.3 to 18.7 +/- 13.6). This decline occurred consistently across subgroups of patient age, race, ethnicity, payer status, and rurality, leading to decreased variation in travel times between such subgroups. However, travel times to pre-expansion facilities remained stable (initial: 26.8 +/- 18.9 minutes, final: 26.7 +/- 18.6 minutes). Among women undergoing mammography before and after expansion, travel times were shorter for the postexpansion mammogram in only 6.3%, but this rate varied significantly (all P < 0.05) by certain demographic factors (higher in younger and non-Hispanic patients) and was as high as 18.2%-18.9% of patients residing in regions with the most active expansion. CONCLUSIONS: Health system mammography facility geographic expansion can improve average patient travel burden and reduce travel time variation among sociodemographic populations. Nonetheless, existing patients strongly tend to return to established facilities despite potentially shorter travel time locations, suggesting strong site loyalty. Variation in travel times likely relates to various factors other than facility proximity.

RATIONALE AND OBJECTIVES: Patients' willingness to travel farther distances for certain imaging services may reflect their perceptions of the degree of differentiation of such services. We compare patients' travel times for a range of imaging examinations performed across a large academic health system. MATERIALS AND METHODS: We searched the NYU Langone Medical Center Enterprise Data Warehouse to identify 442,990 adult outpatient imaging examinations performed over a recent 3.5-year period. Geocoding software was used to estimate typical driving times from patients' residences to imaging facilities. Variation in travel times was assessed among examination types. RESULTS: The mean expected travel time was 29.2 +/- 20.6 minutes, but this varied significantly (p < 0.001) among examination types. By modality, travel times were shortest for ultrasound (26.8 +/- 18.9) and longest for positron emission tomography-computed tomography (31.9 +/- 21.5). For magnetic resonance imaging, travel times were shortest for musculoskeletal extremity (26.4 +/- 19.2) and spine (28.6 +/- 21.0) examinations and longest for prostate (35.9 +/- 25.6) and breast (32.4 +/- 22.3) examinations. For computed tomography, travel times were shortest for a range of screening examinations [colonography (25.5 +/- 20.8), coronary artery calcium scoring (26.1 +/- 19.2), and lung cancer screening (26.4 +/- 14.9)] and longest for angiography (32.0 +/- 22.6). For ultrasound, travel times were shortest for aortic aneurysm screening (22.3 +/- 18.4) and longest for breast (30.1 +/- 19.2) examinations. Overall, men (29.9 +/- 21.6) had longer (p < 0.001) travel times than women (27.8 +/- 20.3); this difference persisted for each modality individually (p