The Environmental, Social, Governance Movement and Radiology: Opportunities and Strategy

The environmental, social, governance (ESG) movement has come to health care organizations, in part through the Biden administration's challenge to them to reduce greenhouse gas emissions by 50% by 2030 and achieve net zero emissions by 2050, in support of more robust environmental sustainability. Radiology practices should become knowledgeable about ESG concepts and look for opportunities that are meaningful and achievable to support their host organizations' ESG efforts. Examples of initiatives to support improved environmental sustainability include selecting the least energy intensive imaging method for a given diagnosis, shutting down equipment in standby mode, sourcing energy from renewable sources, and reducing waste through recycling. Optimizing imaging protocols can reduce radiation exposure to patients, energy used per examination, and the use of other resources such as iodinated contrast media, an environmental pollutant. Achieving socially equitable access to services for ethnic and racial minorities remains a challenge in the US health care system. Extending hours of operation for screening services to include nights and weekends can provide options for patients who otherwise must take time away from work with loss of income. With respect to governance, more transparency in leadership selection and greater opportunities for participation by women and racial/ethnic minorities in the leadership of professional organizations should be supported in radiology. To succeed in ESG initiatives, radiology practice leaders should consider appointing a lead person and a multifunctional team that includes broad representation from the radiology workplace. The team should work to identify opportunities that are realistic and achievable within their institutional contexts.

A Novel Design-Thinking, Hospital Innovation Core Certificate Curriculum for Radiologists and Trainees: Creation, Implementation, and Multiyear Results

RATIONALE AND OBJECTIVES

Innovation is a crucial skill for physicians and researchers, yet traditional medical education does not provide instruction or experience to cultivate an innovative mindset. This study evaluates the effectiveness of a novel course implemented in an academic radiology department training program over a 5-year period designed to educate future radiologists on the fundamentals of medical innovation.

MATERIALS AND METHODS

A pre- and post-course survey and examination were administered to residents who participated in the innovation course (MESH Core) from 2018 to 2022. Respondents were first evaluated on their subjective comfort level, understanding, and beliefs on innovation-related topics using a 5-point Likert-scale survey. Respondents were also administered a 21-question multiple-choice exam to test their objective knowledge of innovation-related topics.

RESULTS

Thirty-eight residents participated in the survey (response rate 95%). Resident understanding, comfort and belief regarding innovation-related topics improved significantly (P < .0001) on all nine Likert-scale questions after the course. After the course, a significant majority of residents either agreed or strongly agreed that technological innovation should be a core competency for the residency curriculum, and that a workshop to prototype their ideas would be beneficial. Performance on the course exam showed significant improvement (48% vs 86%, P < .0001). The overall course experience was rated 5 out of 5 by all participants.

CONCLUSION

MESH Core demonstrates long-term success in educating future radiologists on the basic concepts of medical technological innovation. Years later, residents used the knowledge and experience gained from MESH Core to successfully pursue their own inventions and innovative projects. This innovation model may serve as an approach for other institutions to implement training in this domain.

A Multimedia Strategy to Integrate Introductory Broad-Based Radiation Science Education in US Medical Schools

US physicians in multiple specialties who order or conduct radiological procedures lack formal radiation science education and thus sometimes order procedures of limited benefit or fail to order what is necessary. To this end, a multidisciplinary expert group proposed an introductory broad-based radiation science educational program for US medical schools. Suggested preclinical elements of the curriculum include foundational education on ionizing and nonionizing radiation (eg, definitions, dose metrics, and risk measures) and short- and long-term radiation-related health effects as well as introduction to radiology, radiation therapy, and radiation protection concepts. Recommended clinical elements of the curriculum would impart knowledge and practical experience in radiology, fluoroscopically guided procedures, nuclear medicine, radiation oncology, and identification of patient subgroups requiring special considerations when selecting specific ionizing or nonionizing diagnostic or therapeutic radiation procedures. Critical components of the clinical program would also include educational material and direct experience with patient-centered communication on benefits of, risks of, and shared decision making about ionizing and nonionizing radiation procedures and on health effects and safety requirements for environmental and occupational exposure to ionizing and nonionizing radiation. Overarching is the introduction to evidence-based guidelines for procedures that maximize clinical benefit while limiting unnecessary risk. The content would be further developed, directed, and integrated within the curriculum by local faculties and would address multiple standard elements of the Liaison Committee on Medical Education and Core Entrustable Professional Activities for Entering Residency of the Association of American Medical Colleges.

Radiology 2040

A translation of this article in Spanish is available in the supplement. Una traducción de este artículo en español está disponible en el suplemento.

Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?

As the role of artificial intelligence (AI) in clinical practice evolves, governance structures oversee the implementation, maintenance, and monitoring of clinical AI algorithms to enhance quality, manage resources, and ensure patient safety. In this article, a framework is established for the infrastructure required for clinical AI implementation and presents a road map for governance. The road map answers four key questions: Who decides which tools to implement? What factors should be considered when assessing an application for implementation? How should applications be implemented in clinical practice? Finally, how should tools be monitored and maintained after clinical implementation? Among the many challenges for the implementation of AI in clinical practice, devising flexible governance structures that can quickly adapt to a changing environment will be essential to ensure quality patient care and practice improvement objectives.

Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging

Medical imaging is a central part of clinical diagnosis and treatment guidance. Machine learning has increasingly gained relevance because it captures features of disease and treatment response that are relevant for therapeutic decision-making. In clinical practice, the continuous progress of image acquisition technology or diagnostic procedures, the diversity of scanners, and evolving imaging protocols hamper the utility of machine learning, as prediction accuracy on new data deteriorates, or models become outdated due to these domain shifts. We propose a continual learning approach to deal with such domain shifts occurring at unknown time points. We adapt models to emerging variations in a continuous data stream while counteracting catastrophic forgetting. A dynamic memory enables rehearsal on a subset of diverse training data to mitigate forgetting while enabling models to expand to new domains. The technique balances memory by detecting pseudo-domains, representing different style clusters within the data stream. Evaluation of two different tasks, cardiac segmentation in magnetic resonance imaging and lung nodule detection in computed tomography, demonstrate a consistent advantage of the method.

Trends in cancer imaging by indication, care setting, and hospital type during the COVID-19 pandemic and recovery at four hospitals in Massachusetts

Background

We aimed to investigate the effects of COVID‐19 on computed tomography (CT) imaging of cancer.

Methods

Cancer‐related CTs performed at one academic hospital and three affiliated community hospitals in Massachusetts were retrospectively analyzed. Three periods of 2020 were considered as follows: pre‐COVID‐19 (1/5/20–3/14/20), COVID‐19 peak (3/15/20–5/2/20), and post‐COVID‐19 peak (5/3/20–11/14/20). 15 March 2020 was the day a state of emergency was declared in MA; 3 May 2020 was the day our hospitals resumed to non‐urgent imaging. The volumes were assessed by (1) Imaging indication: cancer screening, initial workup, active cancer, and surveillance; (2) Care setting: outpatient and inpatient, ED; (3) Hospital type: quaternary academic center (QAC), university‐affiliated community hospital (UACH), and sole community hospitals (SCHs).

Results

During the COVID‐19 peak, a significant drop in CT volumes was observed (−42.2%, p < 0.0001), with cancer screening, initial workup, active cancer, and cancer surveillance declining by 81.7%, 54.8%, 30.7%, and 44.7%, respectively (p < 0.0001). In the post‐COVID‐19 peak period, cancer screening and initial workup CTs did not recover (−11.7%, p = 0.037; −20.0%, p = 0.031), especially in the outpatient setting. CT volumes for active cancer recovered, but inconsistently across hospital types: the QAC experienced a 9.4% decline (p = 0.022) and the UACH a 41.5% increase (p < 0.001). Outpatient CTs recovered after the COVID‐19 peak, but with a shift in utilization away from the QAC (−8.7%, p = 0.020) toward the UACH (+13.3%, p = 0.013). Inpatient and ED‐based oncologic CTs increased post‐peak (+20.0%, p = 0.004 and +33.2%, p = 0.009, respectively).

Conclusions

Cancer imaging was severely impacted during the COVID‐19 pandemic. CTs for cancer screening and initial workup did not recover to pre‐COVID‐19 levels well into 2020, a finding that suggests more patients with advanced cancers may present in the future. A redistribution of imaging utilization away from the QAC and outpatient settings, toward the community hospitals and inpatient setting/ED was observed.

Increased per-patient imaging utilization in an emergency department setting during COVID-19

Introduction

COVID-19 has resulted in decreases in absolute imaging volumes, however imaging utilization on a per-patient basis has not been reported. Here we compare per-patient imaging utilization, characterized by imaging studies and work relative value units (wRVUs), in an emergency department (ED) during a COVID-19 surge to the same period in 2019.

Methods

This retrospective study included patients presenting to the ED from April 1–May 1, 2020 and 2019. Patients were stratified into three primary subgroups: all patients (n = 9580, n = 5686), patients presenting with respiratory complaints (n = 1373, n = 2193), and patients presenting without respiratory complaints (n = 8207, n = 3493). The primary outcome was imaging studies/patient and wRVU/patient. Secondary analysis was by disposition and COVID status. Comparisons were via the Wilcoxon rank-sum or Chi-squared tests.

Results

The total patients, imaging exams, and wRVUs during the 2020 and 2019 periods were 5686 and 9580 (−41%), 6624 and 8765 (−24%), and 4988 and 7818 (−36%), respectively, and the percentage patients receiving any imaging was 67% and 51%, respectively (p < .0001). In 2020 there was a 170% relative increase in patients presenting with respiratory complaints. In 2020, patients without respiratory complaints generated 24% more wRVU/patient (p < .0001) and 33% more studies/patient (p < .0001), highlighted by 38% more CTs/patient.

Conclusion

We report increased per-patient imaging utilization in an emergency department during COVID-19, particularly in patients without respiratory complaints.

Radiology in the Era of Value-Based Healthcare: A Multi Society Expert Statement From the ACR, CAR, ESR, IS3R, RANZCR, and RSNA

BACKGROUND

The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation.

METHODS, FINDINGS AND INTERPRETATION

This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.

Practical Tips for Creating a Diversity, Equity, and Inclusion Committee: Experience From a Multicenter, Academic Radiology Department

PURPOSE

Coronavirus disease 2019 and the publicly documented deaths of countless Black individuals have highlighted the need to confront systemic racism, address racial/ethnic disparities, and improve diversity and inclusion in radiology. Several radiology departments have begun to create diversity, equity, and inclusion (DEI) committees to systematically address DEI issues in radiology. However, there are few articles that provide departments with guidance on how to create DEI committees to comprehensively address DEI issues in radiology. The purpose of this review is to provide readers with a framework and practical tips for creating a comprehensive, institutionally aligned radiology DEI committee.

METHODS

The authors describe key components of the strategic planning process and lessons learned in the creation of a radiology DEI committee, on the basis of the experience of an integrated, academic northeastern radiology department.

RESULTS

A hospital-based strategic planning process defining the DEI vision, mission, goals, and strategies was used to inform the formation of the radiology department DEI committee. The radiology department performed gap analyses by conducting internal and external research. Strengths, weaknesses, opportunities, and threats analyses were performed on the basis of consultations with institutional and other departmental DEI leaders as well as DEI leaders from other academic medical centers. This framework served as the basis for the creation of the radiology departmental DEI committee, including a steering committee and four task forces (education, research, patient experience, and workforce development), each charged with addressing specific institutional goals and strategies.

CONCLUSIONS

This review provides academic radiology departments with a blueprint to create a comprehensive, institutionally aligned radiology DEI committee.

Medical imaging and nuclear medicine: a Lancet Oncology Commission

The diagnosis and treatment of patients with cancer requires access to imaging to ensure accurate management decisions and optimal outcomes. Our global assessment of imaging and nuclear medicine resources identified substantial shortages in equipment and workforce, particularly in low-income and middle-income countries (LMICs). A microsimulation model of 11 cancers showed that the scale-up of imaging would avert 3·2% (2·46 million) of all 76·0 million deaths caused by the modelled cancers worldwide between 2020 and 2030, saving 54·92 million life-years. A comprehensive scale-up of imaging, treatment, and care quality would avert 9·55 million (12·5%) of all cancer deaths caused by the modelled cancers worldwide, saving 232·30 million life-years. Scale-up of imaging would cost US$6·84 billion in 2020-30 but yield lifetime productivity gains of $1·23 trillion worldwide, a net return of $179·19 per $1 invested. Combining the scale-up of imaging, treatment, and quality of care would provide a net benefit of $2·66 trillion and a net return of $12·43 per $1 invested. With the use of a conservative approach regarding human capital, the scale-up of imaging alone would provide a net benefit of $209·46 billion and net return of $31·61 per $1 invested. With comprehensive scale-up, the worldwide net benefit using the human capital approach is $340·42 billion and the return per dollar invested is $2·46. These improved health and economic outcomes hold true across all geographical regions. We propose actions and investments that would enhance access to imaging equipment, workforce capacity, digital technology, radiopharmaceuticals, and research and training programmes in LMICs, to produce massive health and economic benefits and reduce the burden of cancer globally.

Radiology in the Era of Value-Based Healthcare: A Multi-Society Expert Statement From the ACR, CAR, ESR, IS3R, RANZCR, and RSNA

BACKGROUND

The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation.

METHODS, FINDINGS AND INTERPRETATION

This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.

Radiology in the era of value-based healthcare: a multi-society expert statement from the ACR, CAR, ESR, IS3R, RANZCR, and RSNA

Background

The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology’s central role; this may have future negative consequences for resource allocation.

Methods, findings and interpretation

This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the healthcare value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.

Radiology in the era of value-based healthcare: A multi-society expert statement from the ACR, CAR, ESR, IS3R, RANZCR and RSNA

BACKGROUND

The value-based healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation.

METHODS, FINDINGS AND INTERPRETATION

This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia and New Zealand, describes the place of radiology in VBH models and the healthcare value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.

Radiology in the Era of Value-based Healthcare: A Multi-Society Expert Statement from the ACR, CAR, ESR, IS3R, RANZCR, and RSNA

Background The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation. Methods, findings and interpretation This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined. Published under a CC BY 4.0 license.

Analysis of the Effects of a Patient-Centered Rideshare Program on Missed Appointments and Timeliness for MRI Appointments at an Academic Medical Center

PURPOSE

The aim of this study was to assess the differences in timeliness to MRI appointments and missed MRI appointment rates before and after the implementation of a rideshare program.

METHODS

Retrospective analysis of a rideshare program was performed 9 months after implementation to compare the effects before and after implementation. Variables obtained included demographics, MRI appointment variables, and data related to rideshare use. Descriptive statistics and linear and logistic regression analyses were used to compare demographic characteristics among patients using the rideshare program with (1) those who did not use the rideshare program after implementation and (2) patients before rideshare implementation. Rates of missed appointments derived from patient-related, same-day appointment cancellations were analyzed using logistic regression analyses. Timeliness was analyzed using linear regression analyses. All analyses were adjusted for potential confounders.

RESULTS

Of 7,707 patients scheduled for MRI appointments during the postintervention period, 151 patients used the rideshare service (1.95%). There were no statistically significant differences in missed appointment rates after rideshare implementation (adjusted odds ratio, 1.09; 95% confidence interval, 0.93-1.27; P = .275). Patients using the rideshare service were more likely to be on time (adjusted coefficient = 13.0; 95% confidence interval, 5.4-20.5; P = .001). Older patients (P = .001), unemployed patients (P < .001), and patients without commercial insurance (P < .001) were more likely to use the rideshare service.

CONCLUSIONS

Implementation of a rideshare program did not significantly decrease missed appointment rates, but it significantly improved timeliness to MRI appointments while assisting at-risk patient populations reporting transportation barriers.

Early-Stage Radiology Volume Effects and Considerations with the Coronavirus Disease 2019 (COVID-19) Pandemic: Adaptations, Risks, and Lessons Learned

Objective

The coronavirus disease 2019 (COVID-19) pandemic resulted in significant loss of radiologic volume as a result of shelter-at-home mandates and delay of non-time-sensitive imaging studies to preserve capacity for the pandemic. We analyze the volume-related impact of the COVID-19 pandemic on six academic medical systems (AMSs), three in high COVID-19 surge (high-surge) and three in low COVID-19 surge (low-surge) regions, and a large national private practice coalition. We sought to assess adaptations, risks of actions, and lessons learned.

Methods

Percent change of 2020 volume per week was compared with the corresponding 2019 volume calculated for each of the 14 imaging modalities and overall total, outpatient, emergency, and inpatient studies in high-surge AMSs and low-surge AMSs and the practice coalition.

Results

Steep examination volume drops occurred during week 11, with slow recovery starting week 17. The lowest total AMS volume drop was 40% compared with the same period the previous year, and the largest was 70%. The greatest decreases were seen with screening mammography and dual-energy x-ray absorptiometry scans, and the smallest decreases were seen with PET/CT, x-ray, and interventional radiology. Inpatient volume was least impacted compared with outpatient or emergency imaging.

Conclusion

Large percentage drops in volume were seen from weeks 11 through 17, were seen with screening studies, and were larger for the high-surge AMSs than for the low-surge AMSs. The lowest drops in volume were seen with modalities in which delays in imaging had greater perceived adverse consequences.

Implementing the DICOM Standard for Digital Pathology

Background:

Digital Imaging and Communications in Medicine (DICOM^®) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network.

Methods:

We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software.

Results:

Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed.

Conclusion:

Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.

Current Applications and Future Impact of Machine Learning in Radiology

Recent advances and future perspectives of machine learning techniques offer promising applications in medical imaging. Machine learning has the potential to improve different steps of the radiology workflow including order scheduling and triage, clinical decision support systems, detection and interpretation of findings, postprocessing and dose estimation, examination quality control, and radiology reporting. In this article, the authors review examples of current applications of machine learning and artificial intelligence techniques in diagnostic radiology. In addition, the future impact and natural extension of these techniques in radiology practice are discussed.

What Patients Want to Know about Imaging Examinations: A Multiinstitutional U.S. Survey in Adult and Pediatric Teaching Hospitals on Patient Preferences for Receiving Information before Radiologic Examinations

Purpose To identify what information patients and parents or caregivers found useful before an imaging examination, from whom they preferred to receive information, and how those preferences related to patient-specific variables including demographics and prior radiologic examinations. Materials and Methods A 24-item survey was distributed at three pediatric and three adult hospitals between January and May 2015. The χ² or Fisher exact test (categorical variables) and one-way analysis of variance or two-sample t test (continuous variables) were used for comparisons. Multivariate logistic regression was used to determine associations between responses and demographics. Results Of 1742 surveys, 1542 (89%) were returned (381 partial, 1161 completed). Mean respondent age was 46.2 years ± 16.8 (standard deviation), with respondents more frequently female (1025 of 1506, 68%) and Caucasian (1132 of 1504, 75%). Overall, 78% (1117 of 1438) reported receiving information about their examination most commonly from the ordering provider (824 of 1292, 64%), who was also the most preferred source (1005 of 1388, 72%). Scheduled magnetic resonance (MR) imaging or nuclear medicine examinations (P < .001 vs other examination types) and increasing education (P = .008) were associated with higher rates of receiving information. Half of respondents (757 of 1452, 52%) sought information themselves. The highest importance scores for pre-examination information (Likert scale ≥4) was most frequently assigned to information on examination preparation and least frequently assigned to whether an alternative radiation-free examination could be used (74% vs 54%; P < .001). Conclusion Delivery of pre-examination information for radiologic examinations is suboptimal, with half of all patients and caregivers seeking information on their own. Ordering providers are the predominant and preferred source of examination-related information, with respondents placing highest importance on information related to examination preparation. ^© RSNA, 2018 Online supplemental material is available for this article.

NCRP Program Area Committee 4: Radiation Protection in Medicine

Program Area Committee 4 (PAC 4) addresses radiation protection issues in health care environments. Reports from two scientific committees (SC 4-5 and SC 4-7) are soon to be released and have entered council review, respectively. A report from SC 4-8 will be submitted for PAC 4 review in July 2017. Five additional proposals for potential PAC 4 publications are under consideration.

Bits and bytes: the future of radiology lies in informatics and information technology

Advances in informatics and information technology are sure to alter the practice of medical imaging and image-guided therapies substantially over the next decade. Each element of the imaging continuum will be affected by substantial increases in computing capacity coincident with the seamless integration of digital technology into our society at large. This article focuses primarily on areas where this IT transformation is likely to have a profound effect on the practice of radiology.

KEY POINTS

• Clinical decision support ensures consistent and appropriate resource utilization. • Big data enables correlation of health information across multiple domains. • Data mining advances the quality of medical decision-making. • Business analytics allow radiologists to maximize the benefits of imaging resources.