Text Report Analysis to Identify Opportunities for Optimizing Target Selection for Chest Radiograph Artificial Intelligence Models.

Our goal was to analyze radiology report text for chest radiographs (CXRs) to identify imaging findings that have the most impact on report length and complexity. Identifying these imaging findings can highlight opportunities for designing CXR AI systems which increase radiologist efficiency. We retrospectively analyzed text from 210,025 MIMIC-CXR reports and 168,949 reports from our local institution collected from 2019 to 2022. Fifty-nine categories of imaging finding keywords were extracted from reports using natural language processing (NLP), and their impact on report length was assessed using linear regression with and without LASSO regularization. Regression was also used to assess the impact of additional factors contributing to report length, such as the signing radiologist and use of terms of perception. For modeling CXR report word counts with regression, mean coefficient of determination, R2, was 0.469 ± 0.001 for local reports and 0.354 ± 0.002 for MIMIC-CXR when considering only imaging finding keyword features. Mean R2 was significantly less at 0.067 ± 0.001 for local reports and 0.086 ± 0.002 for MIMIC-CXR, when only considering use of terms of perception. For a combined model for the local report data accounting for the signing radiologist, imaging finding keywords, and terms of perception, the mean R2 was 0.570 ± 0.002. With LASSO, highest value coefficients pertained to endotracheal tubes and pleural drains for local data and masses, nodules, and cavitary and cystic lesions for MIMIC-CXR. Natural language processing and regression analysis of radiology report textual data can highlight imaging targets for AI models which offer opportunities to bolster radiologist efficiency.

Medical Malpractice and Diagnostic Radiology: Challenges and Opportunities.

Medicolegal challenges in radiology are broad and impact both radiologists and patients. Radiologists may be affected directly by malpractice litigation or indirectly due to defensive imaging ordering practices. Patients also could be harmed physically, emotionally, or financially by unnecessary tests or procedures. As technology advances, the incorporation of artificial intelligence into medicine will bring with it new medicolegal challenges and opportunities. This article reviews the current and emerging direct and indirect effects of medical malpractice on radiologists and summarizes evidence-based solutions.

Perspectives on lung visualization: Three-dimensional anatomical modeling of computed and micro-computed tomographic data in comparative evolutionary morphology and medicine with applications for COVID-19.

The vertebrate respiratory system is challenging to study. The complex relationship between the lungs and adjacent tissues, the vast structural diversity of the respiratory system both within individuals and between taxa, its mobility (or immobility) and distensibility, and the difficulty of quantifying and visualizing functionally important internal negative spaces have all impeded descriptive, functional, and comparative research. As a result, there is a relative paucity of three-dimensional anatomical information on this organ system in all vertebrate groups (including humans) relative to other regions of the body. We present some of the challenges associated with evaluating and visualizing the vertebrate respiratory system using computed and micro-computed tomography and its subsequent digital segmentation. We discuss common mistakes to avoid when imaging deceased and live specimens and various methods for merging manual and threshold-based segmentation approaches to visualize pulmonary tissues across a broad range of vertebrate taxa, with a particular focus on sauropsids (reptiles and birds). We also address some of the recent work in comparative evolutionary morphology and medicine that have used these techniques to visualize respiratory tissues. Finally, we provide a clinical study on COVID-19 in humans in which we apply modeling methods to visualize and quantify pulmonary infection in the lungs of human patients.

Computed Tomography Coronary Angiography on a Detector-Based Spectral Computed Tomography Platform: Evaluation of Patients With Coronary Artery Disease Reporting and Data System Score of 3 and Higher.

PURPOSE: Computed tomography (CT) coronary angiography performed on a detector-based spectral scanner helps more closely approximate severity of stenosis with nuclear medicine and cardiac catheterization tests compared with single-energy CT (SECT) in patients with an original CAD-RADS score of 3 and higher. METHODS: This retrospective trial was conducted between January 2017 and December 2019 and included 52 patients with a CAD-RADS score of 3 and higher. Two reading sessions were performed 6 weeks apart. The first reading session was performed using only conventional images and the second reading session was performed using spectral results. Detector-based spectral CT CAD-RADS scores were compared with cardiac stress test and/or cardiac catheterization results for final characterization of stenosis in 41 segments from 32 patients. The mean CAD-RADS score was calculated for both the conventional images and spectral images. RESULTS: The CAD-RADS score for SECT and the score for spectral CT for the 41 segments were compared. Available associated stress test and/or cardiac catheterization results were also compared with CAD-RADS scores. In 51% (21/41), a diagnosis concordant with best practices results was achieved with the help of spectral CT results. A mean CAD-RADS score of 3.56 was obtained using spectral results, compared with 3.93 using conventional images. A 2-tailed paired t test determined the difference to be significant with a P value of 0.007. CONCLUSIONS: Computed tomography coronary angiography is feasible on a detector-based spectral CT scanner and can improve diagnostic confidence over SECT angiography in patients with an original CAD-RADS score of 3 and higher.

Practical Tips and a Template for Developing Your Curriculum Vitae.

The Alliance of Leaders in Academic Affairs in Radiology (ALAAR) advocates for a Universal Curriculum Vitae for all medical institutions and to that end, we have developed a template that can be downloaded on the AUR website (ALAAR CV template) that includes all of the elements required by many academic institutions. Members of ALAAR represent multiple academic institutions and have spent many hours reviewing and providing input on radiologists' curricula vitae. The purpose of this review is to help academic radiologists accurately maintain and optimize their CVs with minimal effort and to clarify common questions that arise at many different institutions in the process of constructing a CV.

A Problem of Gender Representation: Adapting the Bechdel Test to Evaluate the Social Media Presence of Radiology Residency Programs.

RATIONALE AND OBJECTIVES: Social media serves as recruitment tools for residency programs, allowing programs to "brand" themselves in an era of virtual interviews. For female applicants, viewing their gender represented on Instagram may influence their pursuit of a program. Our study's goal is to quantify how female-presenting professionals are represented on radiology residency (RR) Instagram pages, as these are increasingly important platforms for resident recruitment. MATERIALS AND METHODS: The Bechdel test is a well-known measure of the representation of women in fiction that requires at least 2 women speak to each other about a topic other than a man. We modified this test to evaluate the portrayal of female-presenting professionals on public Instagram galleries of RR programs. For a photo to pass our test, female-presenting persons are shown physically together, without male-presenting professionals, and in a professional setting. To compare gender depiction, a Male Bechdel Test was also used. RR Instagram pages were identified using the Fellowship and Residency Electronic Interactive Database Access (n = 87) and examined with an adapted framework approach to count female and male-presenting individuals in 1044 images. Results were assessed using paired t-tests and a chi-square with McNemar's test. RESULTS: Approximately 50% of the RR Instagrams passed the Male Bechdel Test while only 21.3% passed the Female Bechdel Test, a significant difference in gender representation (χ2(1) = 13.255, P = 0.022). Paired sample t-tests revealed that RR Instagram pages are significantly more likely to feature male-presenting professionals in a professional setting (P < 0.0001), feature them with other male-presenting professionals (P = 0.001), and feature them without female-presenting professionals (P = 0.003). CONCLUSION: Our results suggest female-presenting radiologists are under-represented on the Instagram profiles of RR programs. While this reflects the dearth of females in this field, programs may improve gender inclusion by more prominently displaying females on social media. This may assist in recruiting minority applicants.

Continuing to Thrive in Academic Radiology Despite Decreasing Reimbursement.

Decreasing radiology reimbursement is a major challenge faced by academic radiology practices in the United States. The consequent increased workload from reading more radiological studies can lead to job dissatisfaction, burnout and adverse impact on research, innovation, and education. Thriving successfully in an academic practice despite low reimbursement requires modification of radiology business models and culture of the practice. In this article, we review the financial and operational strategies to mitigate low reimbursement and strategies for thriving in academic radiology without burnout.

Radiomics in Abdominopelvic Solid-Organ Oncologic Imaging: Current Status.

Radiomics is the process of extraction of high-throughput quantitative imaging features from medical images. These features represent noninvasive quantitative biomarkers that go beyond the traditional imaging features visible to the human eye. This article first reviews the steps of the radiomics pipeline, including image acquisition, ROI selection and image segmentation, image preprocessing, feature extraction, feature selection, and model development and application. Current evidence for the application of radiomics in abdominopelvic solid-organ cancers is then reviewed. Applications including diagnosis, subtype determination, treatment response assessment, and outcome prediction are explored within the context of hepatobiliary and pancreatic cancer, renal cell carcinoma, prostate cancer, gynecologic cancer, and adrenal masses. This literature review focuses on the strongest available evidence, including systematic reviews, meta-analyses, and large multicenter studies. Limitations of the available literature are highlighted, including marked heterogeneity in radiomics methodology, frequent use of small sample sizes with high risk of overfitting, and lack of prospective design, external validation, and standardized radiomics workflow. Thus, although studies have laid a foundation that supports continued investigation into radiomics models, stronger evidence is needed before clinical adoption.

Influences of the Social Media Continuum Model in Radiology: Theory and Reality.

Social media utilization has been growing exponentially worldwide and has created a thriving venue for radiologists and the profession of radiology to engage in on both the academic and social levels. The aim of this article is to conduct updated literature review and address a gap in the literature by introducing a simple classification for social media utilization and a new theoretical model to outline the role and potential value of social media in the realm of radiology. We propose classifying social media through usage-driven and access-driven indices. Furthermore, we discuss the interdependency of radiologists, other physicians and non-physician stakeholders, scientific journals, conferences/meetings and the general public in an integrated social media continuum model. With the ongoing sub-specialization of radiology, social media helps mitigate the physical barriers of making connections with peers and audiences which would have otherwise been unfeasible. The constant evolution and diversification of social media platforms necessitates a novel approach to better understand its role through a radiological lens. With the looming fear of 'ancillary service' labelling, social media could be the golden plate to halt the path towards commoditization of radiology.

A Framework for the Virtual Medical Interview Process: Considerations for the Applicant and the Interviewer.

Background: Videoconferencing platforms are being used for the purposes of interviewing in academic medicine because of the coronavirus disease 2019 pandemic. We present considerations applicable to interviewers and interviewees in the virtual space, with a focus on medical school and residency applicants. Methods: We reviewed the literature regarding the virtual interview process for medical school and residency by searching PubMed using the following keywords and terms: "interview," "academic medicine," "medical school application," "residency application," "virtual interviews," and "videoconferencing." Our search identified 701 results, from which we selected 36 articles for review. Results: The garnered information focuses on strategies for optimizing the virtual interview process from the standpoint of both the interviewer and the interviewee. We discuss the advantages and disadvantages of the virtual interview process and present recommendations. Conclusion: While the future of the interview process for medical school and residency is uncertain, virtual interviewing is a common and growing practice that will continue to be at least part of the medical interview process for years to come. Interviewers and interviewees should prepare to adapt to the evolving changes in the process.

Burnout: A Mindful Framework for the Radiologist.

Burnout, the outcome of prolonged stress or frustration, manifests as both mental and physical fatigue affecting over half of healthcare workers. This article will discuss the etiologies, problems, and potential solutions to burnout related issues that are impacting radiologists. Factors placing radiologists at risk for burnout as well the impact of burnout upon the radiologist, the department, staff, and patients they serve will also be discussed. An emphasis will also be placed upon recognition, solutions, and a collective response to burnout. Readers should be able to perform a self-assessment of their own risk for burnout and understand what can be done to dissolve and prevent burnout amongst their colleagues. In doing so, our hope is that radiologists will develop greater insight, awareness, and ultimately empathy for the unique challenges that others in the radiology community may face.

Coronavirus Disease (COVID-19): The Value of Chest Radiography for Patients Greater Than Age 50 Years at an Earlier Timepoint of Symptoms Compared With Younger Patients.

Background: A relative paucity of data exists regarding chest radiography (CXR) in diagnosis of coronavirus disease (COVID-19) compared to computed tomography. We address the use of a strict pattern of CXR findings for COVID-19 diagnosis, specifically during early onset of symptoms with respect to patient age. Methods: We performed a retrospective study of patients under investigation for COVID-19 who presented to the emergency department during the COVID-19 outbreak of 2020 and had CXR within 1 week of symptoms. Only reverse transcription polymerase chain reaction (RT-PCR)-positive patients were included. Two board-certified radiologists, blinded to RT-PCR results, assessed 60 CXRs in consensus and assigned 1 of 3 patterns: characteristic, atypical, or negative. Atypical patterns were subdivided into more suspicious or less suspicious for COVID-19. Results: Sixty patients were included: 30 patients aged 52 to 88 years and 30 patients aged 19 to 48 years. Ninety-three percent of the older group demonstrated an abnormal CXR and were more likely to have characteristic and atypical-more suspicious findings in the first week after symptom onset than the younger group. The relationship between age and CXR findings was statistically significant (χ2 [2, n=60]=15.70; P=0.00039). The relationship between negative and characteristic COVID-19 CXR findings between the 2 age cohorts was statistically significant with Fisher exact test resulting in a P value of 0.001. Conclusion: COVID-19 positive patients >50 years show earlier, characteristic patterns of statistically significant CXR changes than younger patients, suggesting that CXR is useful in the early diagnosis of infection. CXR can be useful in early diagnosis of COVID-19 in patients older than 50 years.

Artificial Intelligence in Imaging of Chronic Liver Diseases: Current Update and Future Perspectives.

Here we review artificial intelligence (AI) models which aim to assess various aspects of chronic liver disease. Despite the clinical importance of hepatocellular carcinoma in the setting of chronic liver disease, we focus this review on AI models which are not lesion-specific and instead review models developed for liver parenchyma segmentation, evaluation of portal circulation, assessment of hepatic fibrosis, and identification of hepatic steatosis. Optimization of these models offers the opportunity to potentially reduce the need for invasive procedures such as catheterization to measure hepatic venous pressure gradient or biopsy to assess fibrosis and steatosis. We compare the performance of these AI models amongst themselves as well as to radiomics approaches and alternate modality assessments. We conclude that these models show promising performance and merit larger-scale evaluation. We review artificial intelligence models that aim to assess various aspects of chronic liver disease aside from hepatocellular carcinoma. We focus this review on models for liver parenchyma segmentation, evaluation of portal circulation, assessment of hepatic fibrosis, and identification of hepatic steatosis. We conclude that these models show promising performance and merit a larger scale evaluation.

Can Radiographic Tumor Volume of Oral Squamous Cell Carcinoma Help Predict Clinical and Pathological Tumor Features?

PURPOSE: Radiographic tumor volume (RTV) of oral squamous cell carcinoma (SCC) is seldom measured in practice. Aims of the study are to estimate RTV of SCC and to investigate its relationship with clinical and pathological stage, tumor margin status, recurrence, and need for chemo/radiation. METHODS: The design is a retrospective cohort study. The predictor variable is SCC RTV. The primary outcome variables are clinical and pathological tumor size. The secondary outcomes are margin status and postoperative chemo/radiation. Tumor dimensions were measured on preoperative maxillofacial or neck computer tomography images with contrast. Information on patient and tumor characteristics was obtained. Pearson correlation, t test, ANOVA and log rank test were used for statistical analysis. The significance level was set at .05. RESULTS: Thirty-six subjects aged 36 to 86 were included in the study. Positive association was found between clinical T stage and RTV (P = .0003) and between pathologic T stage and RTV (P = .002). Mean value of RTV was significantly higher in the group with positive margins (P = .0004). RTV was significantly higher in cancers requiring adjuvant chemo/radiation (P = .033). Mean RTV for patients with recurrence was 1.86 cm3 as compared to 1.29 cm3 for patients with no recurrence. Higher tumor volumes were more likely to be associated with recurrence. CONCLUSIONS: RTV is a variable that is readily available to head and neck surgeons. RTV is associated with clinical and pathological tumor sizes, margin status, need for adjuvant chemo/radiation and tumor recurrence.

LI-RADS treatment response assessment of combination locoregional therapy for HCC.

HCC incidence continues to increase worldwide and is most frequently discovered at an advanced stage when limited curative options are available. Combination locoregional therapies have emerged to improve patient survival and quality of life or downstage patients to curative options. The increasing options for locoregional therapy combinations require an understanding of the expected post-treatment imaging appearance in order to assess treatment response. This review aims to describe the synergy between TACE combined with thermal ablation and TACE combined with SBRT. We will also illustrate expected imaging findings that determine treatment efficacy based on the mechanism of tissue injury using the LI-RADS Treatment Response Algorithm.