Diagnostic performance of US for suspected appendicitis: Does multi-categorical reporting provide better estimates of disease in adults, and what factors are associated with false or indeterminate results?

PURPOSE

To identify factors associated with false or indeterminate US result for suspected appendicitis, and assess whether multi-categorical reporting of US yields more precise estimates regarding the probability of appendicitis.

METHODS

562 US examinations for suspected appendicitis between May 2013-April 2015 were categorized as true (77/562 true positives or true negatives) or false/indeterminate (485/562 false negatives, false positives or indeterminates) based on results from a prior study. Of 541 examinations with images available retrospectively, a category of A-E was assigned as follows: non-visualized appendix with secondary findings (A) absent or (B) present; appendix visualized and considered (C) negative, (D) equivocal, or (E) positive for appendicitis. The following factors were recorded: age; sex; scan time (daytime vs. off-hours); resident/fellow involvement; abdominal subspecialty radiologist; radiologist experience (>5 years or not); and tenderness on interrogation. Associations between factors and US result were assessed (t-tests, Fisher's exact test and multivariate logistic regression).

RESULTS

The true group had proportionally more males (18/77 (23.4%) vs. 66/485 (13.6%), p = 0.04) and patients with sonographic tenderness (43/77 (55.8%) vs. 132/353 (27.3%), p < 0.0001). There was no significant difference or association with other factors. On multivariate logistic regression, false/indeterminate results were 1.9 times (95% CIs 1.0-3.5) more likely among females and 3.8 times more likely in the absence of tenderness (95% CIs 2.3-6.4). The proportion of patients with appendicitis in categories A-E was 34/410 (8.3%), 24/44 (54.5%), 0/18 (0%), 0/3 (0%) and 61/66 (92.4%), respectively.

CONCLUSIONS

Females and absence of tenderness were associated with a false/indeterminate US. Categorical reporting provides more granular estimates of the post-test probability of appendicitis.

Using Facebook Live to Advocate Breast Cancer Screening

With current conflicting and confusing screening mammography guidelines between major medical organizations, radiologists have an opportunity to educate and advocate for patients using the power of social media. The authors provide a brief overview on the impact of social media in radiology, in particular Facebook, as well as challenges encountered by radiologists as they establish an online presence, and how to effectively use Facebook Live to advocate for screening mammography.

[Image and report quality of outpatient MRI examinations : Evaluation of organizational, technical and report-related parameters in patients with arthroscopically secured rotator cuff rupture]

BACKGROUND

MRI is commonly used to diagnose and assess prognosis for rotator cuff (RM) pathology in addition to history and clinical examination.

AIM

This study investigates the image and report quality of shoulder MRIs with regard to prognosis-relevant parameters in outpatients who subsequently underwent surgical treatment for RM rupture.

MATERIALS AND METHODS

Using a defined questionnaire, both the MR images and the original reports of 94 patients were evaluated by an experienced radiologist with regard to referral information, MRI technology and quality of the MRI reports.

RESULTS

Questions or comments on RC were noted in 39% (general practitioners) and 48% (orthopaedics/UCH) of referrals. In MRI reports with the diagnosis "complete rupture of the RC", no information on the size of the defect was available in 47% of cases. In 18 and 30% of the reports, respectively, a fatty infiltration of the RM musculature or atrophy of the musculature was mentioned. When a partial RC rupture (n = 25) was diagnosed; the depth diameter (< or > 50% of the tendon thickness) was determined in only one case. The protocol recommendations valid today for MRI diagnostics of the shoulder were implemented in 60% of the examinations. According to the evaluating radiologist, 93-97% of the available MRI examinations were able to answer prognostic-relevant questions of an RC rupture.

DISCUSSION

The questions by physicians referring to the MRI examination of a shoulder with a subsequently arthroscopically verified RC rupture were predominantly unspecific or insufficient. In the radiological reports of these MRI examinations, prognosis-relevant parameters could not be extracted in sufficient form and number, although the MRI technique would have allowed this.

Inter-modality assessment of medial temporal lobe atrophy in a non-demented population: application of a visual rating scale template across radiologists with varying clinical experience

OBJECTIVES

To assess inter-modality agreement and accuracy for medial temporal lobe atrophy (MTA) ratings across radiologists with varying clinical experience in a non-demented population.

METHODS

Four raters (two junior radiologists and two senior neuroradiologists) rated MTA on CT and MRI scans using Scheltens' MTA scale. Ratings were compared to a consensus rating by two experienced neuroradiologists for estimation of true positive and negative rates (TPR and TNR) and over- and underestimation of MTA. Inter-modality agreement expressed as Cohen's κ (dichotomized data), Cohen's κ_w, and two-way mixed, single measures, consistency ICC (ordinal data) were determined. Adequate agreement was defined as κ/κ_w ≥ 0.80 and ICC ≥ 0.80 (significance level at 95% CI ≥ 0.65).

RESULTS

Forty-nine subjects (median age 72 years, 27% abnormal MTA) with cognitive impairment were included. Only junior radiologists achieved adequate agreement expressed as Cohen's κ. All raters achieved adequate agreement expressed as Cohen's κ_w and ICC. True positive rates varied from 69 to 100% and TNR varied from 85 to 100%. No under- or overestimation of MTA was observed. Ratings did not differ between radiologists.

CONCLUSION

We conclude that radiologists with varying experience achieve adequate inter-modality agreement and similar accuracy when Scheltens' MTA scale is used to rate MTA on a non-demented population. However, TPR varied between radiologists which could be attributed to rating style differences.

KEY POINTS

• Radiologists with varying experience achieve adequate inter-modality agreement with similar accuracy when Scheltens' MTA scale is used to rate MTA on a non-demented population. • Differences in rating styles might affect accuracy, this was most evident for senior neuroradiologists, and only junior radiologists achieved adequate agreement on dichotomized (abnormal/normal) ratings. • The use of an MTA scale template might compensate for varying clinical experience which could make it applicable for clinical use.

What does the orthopaedic surgeon want in the radiology report?

Complementary imaging is crucial in the diagnosis and management of the spectrum of Musculoskeletal (MSK) pathologies. Like in all medical specialities, its role in trauma and orthopaedic conditions has evolved. A radiology report following an imaging study should provide an accurate, timely interpretation of images and be presented in a format that allows formal analysis or clarification of a patient's diagnostic dilemma. It is essential that it is descriptive enough to allow clinico-pathological correlation to a patient's condition. A high-quality report follows clinical governance processes, provides clinical feedback, and when appropriate, incorporates advice regarding differential diagnosis or further investigation/management that can be undertaken, permitting the attending clinician to formulate a suitable treatment plan for their patient. In this narrative we explore common radiological investigations and reporting information in trauma and orthopaedic conditions, which would be useful to the attending surgeon.

Workload of diagnostic radiologists in the foreseeable future based on recent scientific advances: growth expectations and role of artificial intelligence

Objective

To determine the anticipated contribution of recently published medical imaging literature, including artificial intelligence (AI), on the workload of diagnostic radiologists.

Methods

This study included a random sample of 440 medical imaging studies published in 2019. The direct contribution of each study to patient care and its effect on the workload of diagnostic radiologists (i.e., number of examinations performed per time unit) was assessed. Separate analyses were done for an academic tertiary care center and a non-academic general teaching hospital.

Results

In the academic tertiary care center setting, 65.0% (286/440) of studies could directly contribute to patient care, of which 48.3% (138/286) would increase workload, 46.2% (132/286) would not change workload, 4.5% (13/286) would decrease workload, and 1.0% (3/286) had an unclear effect on workload. In the non-academic general teaching hospital setting, 63.0% (277/240) of studies could directly contribute to patient care, of which 48.7% (135/277) would increase workload, 46.2% (128/277) would not change workload, 4.3% (12/277) would decrease workload, and 0.7% (2/277) had an unclear effect on workload. Studies with AI as primary research area were significantly associated with an increased workload (p < 0.001), with an odds ratio (OR) of 10.64 (95% confidence interval (CI) 3.25–34.80) in the academic tertiary care center setting and an OR of 10.45 (95% CI 3.19–34.21) in the non-academic general teaching hospital setting.

Conclusions

Recently published medical imaging studies often add value to radiological patient care. However, they likely increase the overall workload of diagnostic radiologists, and this particularly applies to AI studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-021-01031-4.

Communication and empathy skills: Essential requisites for patient-centered radiology care

PURPOSE

To investigate how patients value radiologists, using data from the Dutch healthcare assessment website.

METHOD

The Dutch healthcare assessment website was searched for patient reviews about radiologists in The Netherlands. The scores (scale of 1-10) assigned to the most recent review of each radiologist were extracted. All written reviews were assessed using standardized coding taxonomy, in the domains "clinical competencies" (including quality and safety of clinical care) and "relationships" (including communication with patients and humaneness/caring). For each category, it was assessed whether the review was positive or negative with regard to the performance of the radiologist.

RESULTS

217 of 941 radiologists (23 %) had been reviewed between 2017 and 2021. The total number of institutions to which these radiologists were affiliated was 75 (6 academic and 69 non-academic institutions). Median score assigned to each review was 9.6 (interquartile range 1.3, range 1-10). 74 of 217 radiologists (34 %) were given a maximum review score of 10. 29 of 217 radiologists (13 %) were given a review score of 5 or lower. The far majority of reviews concerned the categories communication (36 % of all positive patient reviews and 30 % of all negative patient reviews) and humaneness/caring (45 % of all positive patient reviews and 49 % of all negative patient reviews).

CONCLUSION

Radiologists are generally highly valued by patients, although there is room for improvement to decrease the number of negative patient experiences. Communication and empathy appear to be the most important skills on which radiologists are judged from a patient's perspective.

Direct communication between radiologists and patients improves the quality of imaging reports

OBJECTIVES

We investigate in what percentage of cases and to what extent radiological reports change when radiologists directly communicate with patients after imaging examinations.

METHODS

One hundred twenty-two consecutive outpatients undergoing MRI examinations at a single center were prospectively included. Radiological reports of the patients were drafted by two radiologists in consensus using only the clinical information that was made available by the referring physicians. Thereafter, one radiologist talked directly with the patient and recorded the duration of the conversation. Afterwards, the additional information from the patient was used to reevaluate the imaging studies in consensus. The radiologists determined whether the radiological report changed based on additional information and, if yes, to what extent. The degree of change was graded on a 4-point Likert scale (1, non-relevant findings, to 4, highly relevant findings).

RESULTS

Following direct communication (duration 170.9 ± 53.9 s), the radiological reports of 52 patients (42.6%) were changed. Of the 52 patients, the degree of change was classified as grade 1 for 8 patients (15.4 %), grade 2 for 27 patients (51.9%), grade 3 for 13 patients (25%), and grade 4 for 4 patients (7.7%). The reasons leading to changes were missing clinical information in 50 cases (96.2%) and the lack of additional external imaging in 2 cases (3.8%).

CONCLUSIONS

Radiologists should be aware that a lack of accurate information from the clinician can lead to incorrect radiological reports or diagnosis. Radiologists should communicate directly with patients, especially when the provided information is unclear, as it may significantly alter the radiological report.

KEY POINTS

• Direct communication between radiologists and patients for an average of 170's resulted in a change in the radiological reports of 52 patients (42.6%). • Of the 42.6% of cases where the reports were changed, the alterations were highly relevant (grades 3 and 4) in 32.7%, indicating major changes with significant impact towards patient management.

Interventional radiologists have a higher rate of chromosomal damage due to occupational radiation exposure: a dicentric chromosome assay

OBJECTIVES

There are growing concerns regarding radiation exposure in medical workers who perform interventional fluoroscopy procedures. Owing to the nature of certain interventional procedures, workers may be subjected to partial-body radiation exposure that is high enough to cause local damage. We aimed to investigate the level of radiation exposure in interventional radiologists in South Korea by performing cytogenetic biodosimetry, particularly focusing on partial-body exposure.

METHODS

Interventional radiologists (n = 52) completed a questionnaire, providing information about their work history and practices. Blood samples were collected and processed for a dicentric chromosome assay. We determined Papworth's U-value to assess the conformity of dicentrics with the Poisson distribution to estimate the partial-body exposures of the radiologists.

RESULTS

Radiologists had a higher number of dicentrics than the normal population and industrial radiographers. Indeed, subjects with a U-value of > 1.96, an indicator of heterogeneous exposure, were observed more frequently; 4.67 ± 0.81% of their body was irradiated at an average dose of 4.64 ± 0.67 Gy. Logistic regression analysis revealed that the total duration of all interventional procedures per week was associated with partial-body exposure levels.

CONCLUSIONS

Our findings suggest that interventional radiologists had greater chromosomal damages than those in other occupational groups, and their partial-body exposure levels might be high enough to cause local damage. Use of special dosimeters to monitor partial-body exposure, as well as restricting the time and frequency of interventional procedures, could help reduce occupational radiation exposure.

KEY POINTS

• Interventional radiologists had a higher number of dicentrics than the normal population and industrial radiographers. • The level of partial-body exposure of interventional radiologists might be high enough to cause occupational local damage such as a skin cancer in fingers. • Restricting the duration and frequency of interventional procedures might be helpful in reducing occupational radiation exposure.

Radiologists in the loop: the roles of radiologists in the development of AI applications

Objectives

To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications.

Materials and methods

Through the case study of eight companies active in developing AI applications for radiology, in different regions (Europe, Asia, and North America), we conducted 17 semi-structured interviews and collected data from documents. Based on systematic thematic analysis, we identified various roles of radiologists. We describe how each role happens across the companies and what factors impact how and when these roles emerge.

Results

We identified 9 roles that radiologists play in different steps of developing AI applications: (1) problem finder (in 4 companies); (2) problem shaper (in 3 companies); (3) problem dominator (in 1 company); (4) data researcher (in 2 companies); (5) data labeler (in 3 companies); (6) data quality controller (in 2 companies); (7) algorithm shaper (in 3 companies); (8) algorithm tester (in 6 companies); and (9) AI researcher (in 1 company).

Conclusions

Radiologists can play a wide range of roles in the development of AI applications. How actively they are engaged and the way they are interacting with the development teams significantly vary across the cases. Radiologists need to become proactive in engaging in the development process and embrace new roles.

Key Points

• Radiologists can play a wide range of roles during the development of AI applications.

• Both radiologists and developers need to be open to new roles and ways of interacting during the development process.

• The availability of resources, time, expertise, and trust are key factors that impact how actively radiologists play roles in the development process.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-07879-w.

The value of the Demetics ultrasound-assisted diagnosis system in the differential diagnosis of benign from malignant thyroid nodules and analysis of the influencing factors

OBJECTIVES

To evaluate the value of Demetics and to explore whether Demetics can help radiologists with varying years of experience in the differential diagnosis of benign from malignant thyroid nodules.

METHODS

The clinical application value of Demetics was assessed by comparing the diagnostic accuracy of radiologists before and after applying Demetics. This retrospective analysis included 284 thyroid nodules that underwent pathological examinations. Two different combined methods were applied. Using method 1: the original TI-RADS classification was forcibly upgraded or downgraded by one level when Demetics classified the thyroid nodules as malignant or benign. Using method 2: the TI-RADS and benign or malignant classification of the thyroid nodules were flexibly adjusted after the physician learned the Demetics' results.

RESULTS

Demetics exhibited a higher sensitivity than did junior radiologist 1 (p_D1 = 0.029) and was similar in sensitivity to the two senior radiologists. Demetics had a higher AUC than both junior radiologists (p_D1 = 0.042, p_D2 = 0.038) and an AUC similar to that of the senior radiologists. The sensitivity (p = 0.035) and AUC (p = 0.031) of junior radiologist 1 and the specificity (p < 0.001) and AUC (p = 0.026) of junior radiologist 2 improved with combined method 1. The AUC of junior radiologist 2 improved with combined method 2 (p = 0.045). The factors influencing the diagnostic results of Demetics include sonographic signs (echogenicity and echogenic foci), contrast of the image, and nodule size.

CONCLUSION

Demetics exhibited high sensitivity and accuracy in the differential diagnosis of benign from malignant thyroid nodules. Demetics could improve the diagnostic accuracy of junior radiologists.

KEY POINTS

• Demetics exhibited a high sensitivity and accuracy in the differential diagnosis of benign from malignant thyroid nodules. • Demetics could improve the diagnostic accuracy of junior radiologists in the differential diagnosis of benign from malignant thyroid nodules. • Factors influencing the diagnostic results of Demetics include the sonographic signs (echogenicity and echogenic foci), contrast of the image, and nodule size.

Implementation of a Software Distribution Intervention to Improve Workload Balance in an Academic Pediatric Radiology Department

In our pediatric radiology department, radiographs (XR) are the shared responsibility of the body section and interpreted in addition to modality or site-specific assignments. Given an unequal contribution amongst radiologists to the XR workload, a software solution was developed to distribute radiographs and improve workload balance. Metrics to evaluate the intervention's effectiveness were compared before and after the intervention. Data was retrieved from the radiology analytics platform, scheduling software, and the peer learning database. Metrics were compared 12 months pre (March 2018-February 2019) and 6 months post (March 2019-August 2019) intervention on non-holiday weekdays, 7 am-5 pm. To evaluate the intervention's effectiveness, variance between radiologists' contributions to XR volume was assessed using Levene's and Fisher's tests. Changes in turnaround times (TATs) and error rates pre- and post-intervention were evaluated as secondary metrics. Following the intervention, the average number of XR interpreted on target rotations increased by 8.9% (p = 0.011) while the departmental volume of radiographs increased only 4.5%. The variance between radiologists' daily XR contribution was 21.3% (p < 0.0001) higher prior to the intervention. Days where target rotations read fewer than 5 XR decreased from 17.8 to 1.1% (p < 0.0001) after the intervention. Days in which more than 75% of all XR had a TAT less than 60 min improved from 26.8 to 39.7% (p = 0.017) after the intervention. There was no statistically significant difference in error frequency (error rate 2.49% pre and 2.72% post, p = 0.636). In conclusion, the software intervention improved XR workload contribution with decreased variability. Despite increased volumes, there was an improvement in turnaround times with no effect on error rates.

Training opportunities of artificial intelligence (AI) in radiology: a systematic review

OBJECTIVES

The aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists.

METHODS

Deductive thematic analysis of 100 training programs offered in 2019 and 2020 (until June 30). We analyze the public data about the training programs based on their "contents," "target audience," "instructors and offering agents," and "legitimization strategies."

RESULTS

There are many AI training programs offered to radiologists, yet most of them (80%) are short, stand-alone sessions, which are not part of a longer-term learning trajectory. The training programs mainly (around 85%) focus on the basic concepts of AI and are offered in passive mode. Professional institutions and commercial companies are active in offering the programs (91%), though academic institutes are limitedly involved.

CONCLUSIONS

There is a need to further develop systematic training programs that are pedagogically integrated into radiology curriculum. Future training programs need to further focus on learning how to work with AI at work and be further specialized and customized to the contexts of radiology work.

KEY POINTS

• Most of AI training programs are short, stand-alone sessions, which focus on the basics of AI. • The content of training programs focuses on medical and technical topics; managerial, legal, and ethical topics are marginally addressed. • Professional institutions and commercial companies are active in offering AI training; academic institutes are limitedly involved.

Bridging the divide between medical school and clinical practice: identification of six key learning outcomes for an undergraduate preparatory course in radiology

BACKGROUND

There exists a significant divide between what is learnt in medical school and subsequently what is required to practice medicine effectively. Despite multiple strategies to remedy this discordance, the problem persists. Here, we describe the identification of a comprehensive set of learning outcomes for a preparation for practice course in radiology.

METHODS

Assessment of interns' readiness to interact with the radiology department was conducted using a national survey of both interns and radiologists. In parallel, group concept mapping (GCM) which involves a combination of qualitative and quantitative techniques was used to identify the shared understanding of participants from a diverse range of medical specialties regarding what topics should be included in an intern preparatory course for interacting with the radiology department.

RESULTS

The survey demonstrated that most interns and radiologists felt that undergraduate medical training did not prepare interns to interact with the radiology department. GCM identified six learning outcomes that should be targeted when designing a preparatory module: requesting investigations; clinical decision support; radiology department IT and communication; adverse reactions and risks; interpretation of radiology results and urgent imaging. The thematic clusters from the group concept mapping corroborated the deficiencies identified in the national survey.

CONCLUSION

We have identified six key learning outcomes that should be included in a preparation for practice module in radiology. Future courses targeting these thematic clusters may facilitate a smoother transition from theory to practice for newly graduated doctors.

Three-dimensional imaging and three-dimensional printing for plastic preparation of medical interventions

Three-dimensional (3D) imaging has been available for nearly four decades and is regarded as state of the art for visualization of anatomy and pathology and for procedure planning in many clinical fields. Together with 3D image reconstructions in the form of rendered virtual 3D models, it has helped to better perceive complex anatomic and pathologic relations, improved preprocedural measuring and sizing of implants, and nowadays enables even photorealistic quality. However, presentation on 2D displays limits the 3D experience. Novel 3D printing technologies can transfer virtual anatomic models into true 3D space and produce both patient-specific models and medical devices constructed by computer-aided design. Individualized anatomic models hold great potential for medical and patient education, research, device development and testing, procedure training, preoperative planning, and fabrication of individualized instruments and implants. Hand in hand with 3D imaging, medical 3D printing has started to revolutionize medicine in certain fields and new applications are developed and introduced regularly. The demand for medical 3D printing will likely continue to rise, as it is a promising tool for plastic preparation of medical interventions. However, there is ongoing debate on the appropriateness of medical 3D printing and further research on its efficiency is needed. As experts in 3D imaging, radiologists are not only capable of advising on adequate imaging parameters, but should also become adept in 3D printing to participate in on-site 3D printing facilities and randomized controlled trials on the topic, thus contributing to improving patient outcomes via personalized medicine through patient-specific preparation of medical interventions.

Automated quantitative MRI volumetry reports support diagnostic interpretation in dementia: a multi-rater, clinical accuracy study

Objectives

We examined whether providing a quantitative report (QReport) of regional brain volumes improves radiologists’ accuracy and confidence in detecting volume loss, and in differentiating Alzheimer’s disease (AD) and frontotemporal dementia (FTD), compared with visual assessment alone.

Methods

Our forced-choice multi-rater clinical accuracy study used MRI from 16 AD patients, 14 FTD patients, and 15 healthy controls; age range 52–81. Our QReport was presented to raters with regional grey matter volumes plotted as percentiles against data from a normative population (n = 461). Nine raters with varying radiological experience (3 each: consultants, registrars, ‘non-clinical image analysts’) assessed each case twice (with and without the QReport). Raters were blinded to clinical and demographic information; they classified scans as ‘normal’ or ‘abnormal’ and if ‘abnormal’ as ‘AD’ or ‘FTD’.

Results

The QReport improved sensitivity for detecting volume loss and AD across all raters combined (p = 0.015* and p = 0.002*, respectively). Only the consultant group’s accuracy increased significantly when using the QReport (p = 0.02*). Overall, raters’ agreement (Cohen’s κ) with the ‘gold standard’ was not significantly affected by the QReport; only the consultant group improved significantly (κ_s 0.41➔0.55, p = 0.04*). Cronbach’s alpha for interrater agreement improved from 0.886 to 0.925, corresponding to an improvement from ‘good’ to ‘excellent’.

Conclusion

Our QReport referencing single-subject results to normative data alongside visual assessment improved sensitivity, accuracy, and interrater agreement for detecting volume loss. The QReport was most effective in the consultants, suggesting that experience is needed to fully benefit from the additional information provided by quantitative analyses.

Key Points

• The use of quantitative report alongside routine visual MRI assessment improves sensitivity and accuracy for detecting volume loss and AD vs visual assessment alone.

• Consultant neuroradiologists’ assessment accuracy and agreement (kappa scores) significantly improved with the use of quantitative atrophy reports.

• First multi-rater radiological clinical evaluation of visual quantitative MRI atrophy report for use as a diagnostic aid in dementia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-020-07455-8.

Evaluation of stress and anxiety caused by the coronavirus disease 2019 (COVID-19) pandemic in pediatric radiology

BACKGROUND

Work-related stress and burnout were documented to be high among pediatric radiologists prior to the coronavirus disease 2019 (COVID-19) pandemic. New challenges arose from the COVID-19 pandemic, potentially introducing new stressors and anxieties.

OBJECTIVE

To evaluate potential sources of stress and anxiety for pediatric radiology faculty during the early phase of the COVID-19 pandemic.

MATERIALS AND METHODS

We conducted a survey of attending physician members of the Society for Pediatric Radiology in North America from April 27, 2020, to May 22, 2020. The response rate was 21% (251/1,206). Survey questions included demographic information and questions regarding working remotely, personal protective equipment, redeployment, personal wellness, wellness resources and financial concerns. A psychometrician reviewed the questions to ensure minimal risk of misinterpretation.

RESULTS

Median age of respondents was 48 years (range 33-70 years) with median number of years in practice of 14 (range 1-45 years). Fifty-three percent of respondents were women and 46% were men. Because of an increase in remote work, 69% of respondents endorsed feeling more isolated from a lack of regular interaction with colleagues. Fifty-three percent of respondents indicated that it is challenging to work remotely while overseeing home schooling for children. In comparison to men, women reported overall higher work-related stress and anxiety (P=0.02), higher feelings of guilt from radiology staff (i.e. technologists and nurses) being more exposed to COVID-19 (P=0.02) and higher levels of stress providing for dependents (P=0.04). Most respondents thought that departmental leadership was effective and respondents were not concerned about meeting financial obligations or job loss.

CONCLUSION

The early phase of the COVID-19 pandemic caused additional stress and anxiety for pediatric radiology faculty and disproportionally affected women. Given the continuously evolving state of the COVID-19 pandemic, these results could aid in planning and implementation of future strategies to combat burnout in radiology. Specific attention should be directed to different stressors experienced by female versus male radiologists, especially in regard to dependent care.

Concordance between a neuroradiologist, a consultant radiologist and trained reporting radiographers interpreting MRI head examinations: An empirical study

INTRODUCTION

This study assessed agreement between MRI reporting radiographers and a consultant radiologist compared with an index neuroradiologist when reporting MRI head (brain/internal auditory meati [IAMs]) examinations. The effect on patient management of any discordant reports was also examined.

METHODS

Two trained MRI reporting radiographers (RRs), a consultant radiologist (CR) and an index neuroradiologist (INR) reported on a random sample of 210 MRI examinations. The radiographers reported during clinical practice and the radiologists in clinical practice conditions. Two independent consultant physicians (neuro-rehabilitation and neuropsychiatry) compared these reports with the index neuroradiologist report for agreement and the clinical importance of discrepant reports.

RESULTS

Overall observer agreement between the RRs and CR was comparable in relation to agreement with the INR: RR; 93/210 (44.3%); and the CR; 83/210 (39.4%) for all head MRI examinations (p = 0.32). For brain examinations the difference was similar: RR; 64/180 (35.6%); and CR; 54/190 (30.0%), p = 0.26. Agreement rates for the IAMs examinations were identical, 29/30 (97.7%). For all head MRI examinations (n = 210) there was a very small observed difference of <0.5% in mean agreement between the reporting radiographers and the consultant radiologist (p = 0.92) for examinations where a major disagreement would have been likely to have led to a change in patient management.

CONCLUSION

MRI reporting radiographers reported during clinical practice on MRI head examinations to a level of agreement comparable with a consultant radiologist.

IMPLICATIONS FOR PRACTICE

This is an area in which radiographers could provide additional reporting roles to the reporting service to increase capacity. Wider potential benefits include cost-effectiveness and role development/retention of radiographers.

Prediction of visceral pleural invasion in lung cancer on CT: deep learning model achieves a radiologist-level performance with adaptive sensitivity and specificity to clinical needs

OBJECTIVES

To develop and validate a preoperative CT-based deep learning model for the prediction of visceral pleural invasion (VPI) in early-stage lung cancer.

METHODS

In this retrospective study, dataset 1 (for training, tuning, and internal validation) included 676 patients with clinical stage IA lung adenocarcinomas resected between 2009 and 2015. Dataset 2 (for temporal validation) included 141 patients with clinical stage I adenocarcinomas resected between 2017 and 2018. A CT-based deep learning model was developed for the prediction of VPI and validated in terms of discrimination and calibration. An observer performance study and a multivariable regression analysis were performed.

RESULTS

The area under the receiver operating characteristic curve (AUC) of the model was 0.75 (95% CI, 0.67-0.84), which was comparable to those of board-certified radiologists (AUC, 0.73-0.79; all p > 0.05). The model had a higher standardized partial AUC for a specificity range of 90 to 100% than the radiologists (all p < 0.05). The high sensitivity cutoff (0.245) yielded a sensitivity of 93.8% and a specificity of 31.2%, and the high specificity cutoff (0.448) resulted in a sensitivity of 47.9% and a specificity of 86.0%. Two of the three radiologists provided highly sensitive (93.8% and 97.9%) but not specific (48.4% and 40.9%) diagnoses. The model showed good calibration (p > 0.05), and its output was an independent predictor for VPI (adjusted odds ratio, 1.07; 95% CI, 1.03-1.11; p < 0.001).

CONCLUSIONS

The deep learning model demonstrated a radiologist-level performance. The model could achieve either highly sensitive or highly specific diagnoses depending on clinical needs.

KEY POINTS

• The preoperative CT-based deep learning model demonstrated an expert-level diagnostic performance for the presence of visceral pleural invasion in early-stage lung cancer. • Radiologists had a tendency toward highly sensitive, but not specific diagnoses for the visceral pleural invasion.

To repeat or not to repeat: Radiologists demonstrated more decisiveness than their fellow radiographers in reducing the repeat rate during mobile chest radiography

INTRODUCTION

Radiologists and radiographers play a complementary role in providing an optimal image quality with decrease radiation dose and proper diagnosis during chest radiographs. We aim Investigate years of experience among radiologists and radiographers on perception of image quality and its impact on repeat rate when evaluating portable pediatric chest radiographs.

METHODS

IRB approved retrospective study consisted of randomly selected images (n = 131) of pediatric portable chest radiographs. Images were blindly assessed by four radiologists and four radiographers. Readers were asked to assess qualitative and quantitative image quality by rating: image quality, decision to repeat and image technique. All data was compared employing Pearson's Correlation, Visual grading characteristic (VGC) and Cohens' kappa analyses.

RESULTS

Image quality: Radiologists (88.4%) rated images as excellent significantly more than radiographers (11.6%), and radiographers (90.1%) as poor significantly more than radiologists (9.9%) (p < 0.05). Repeat: Radiologists (57%) decided not to repeat images significantly more than radiographers (43%) (p < 0.05). Image technique: Radiologists rated images as acceptable (65%) and excellent (97.7%) significantly more than radiographers (35% and 2.3% respectively) (p < 0.05), whereas radiographers (84%) assessed image technique as poor significantly more than radiologists (16%) (p < 0.05). VGC: radiographers had slightly better qualitative evaluation of image quality than radiologists. An association between image quality (p < 0.002) and repeat decision (p < 0.044) with years of experience was established when comparing years of experience with image assessment rubric, while no association was noted with image technique (p < 0.9).

CONCLUSION

Radiologists demonstrated more decisiveness than their fellow radiographers in reducing the repeat rate of portable pediatric chest radiographs. Interestingly, years of experience only seem to affect image technique and image quality assessment among radiologists.

IMPLICATIONS FOR PRACTICE

Continuous education of radiographers and close collaboration with radiologists is crucial to achieve optimal image quality and low radiation doses.

Minimum perceivable size difference: how well can radiologists visually detect a change in lung nodule size from CT images?

OBJECTIVE

The purpose of this study was to determine how well radiologists could visually detect a change in lung nodule size on the basis of visual image perception alone.

SUBJECTS AND METHODS

Under IRB approval, 109 standard chest CT image series were anonymized and exported from PACS. Nine hundred forty virtual lung nodule pairs (six baseline diameters, six relative volume differences, two nodule types-solid and ground glass-and 14 repeats) were digitally inserted into the chest CT image series (same location, different sizes between the pair). These digitally altered CT image pairs were shown to nine radiologists who were tasked to visually determine which image contained the larger nodule using a two-alternative forced-choice perception experimental design. These data were statistically analyzed using a generalized linear mixed effects model to determine how accurately the radiologists were able to correctly identify the larger nodule.

RESULTS

Nominal baseline nodule diameter, relative volume difference, and nodule type were found to be statistically significant factors (p < 0.001) in influencing the radiologists' accuracy. For solid (ground-glass) nodules, the baseline diameter needed to be at least 6.3 mm (13.2 mm) to be able to visually detect a 25% change in volume with 95 ± 1.4% accuracy. Accuracy was lowest for the nodules with the smallest baseline diameters and smallest relative volume differences. Additionally, accuracy was lower for ground-glass nodules compared to solid nodules.

CONCLUSIONS

Factors that impacted visual size assessment were baseline nodule diameter, relative volume difference, and solid versus non-solid nodule type, with larger and more solid lesions offering a more precise assessment of change.

KEY POINTS

• For solid nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 6.3-mm baseline diameter. • For ground-glass nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 13.2-mm baseline diameter. • Accuracy in detecting a change in nodule size began to stabilize around 90-100% for nodules with larger baseline diameters (> 8 mm for solid nodules, > 12 mm for ground-glass nodules) and larger relative volume differences (>15% for solid nodules, > 25% for ground-glass nodules).

Interobserver variability in quality assessment of magnetic resonance images

Background

The perceptual quality of magnetic resonance (MR) images influences diagnosis and may compromise the treatment. The purpose of this study was to evaluate how the image quality changes influence the interobserver variability of their assessment.

Methods

For the variability evaluation, a dataset containing distorted MRI images was prepared and then assessed by 31 experienced medical professionals (radiologists). Differences between observers were analyzed using the Fleiss’ kappa. However, since the kappa evaluates the agreement among radiologists taking into account aggregated decisions, a typically employed criterion of the image quality assessment (IQA) performance was used to provide a more thorough analysis. The IQA performance of radiologists was evaluated by comparing the Spearman correlation coefficients, ρ, between individual scores with the mean opinion scores (MOS) composed of the subjective opinions of the remaining professionals.

Results

The experiments show that there is a significant agreement among radiologists (κ=0.12; 95% confidence interval [CI]: 0.118, 0.121; P<0.001) on the quality of the assessed images. The resulted κ is strongly affected by the subjectivity of the assigned scores, separately presenting close scores. Therefore, the ρ was used to identify poor performance cases and to confirm the consistency of the majority of collected scores (ρ_mean = 0.5706). The results for interns (ρ_mean = 0.6868) supports the finding that the quality assessment of MR images can be successfully taught.

Conclusions

The agreement observed among radiologists from different imaging centers confirms the subjectivity of the perception of MR images. It was shown that the image content and severity of distortions affect the IQA. Furthermore, the study highlights the importance of the psychosomatic condition of the observers and their attitude.

Applications of artificial intelligence (AI) in diagnostic radiology: a technography study

Objectives

Why is there a major gap between the promises of AI and its applications in the domain of diagnostic radiology? To answer this question, we systematically review and critically analyze the AI applications in the radiology domain.

Methods

We systematically analyzed these applications based on their focal modality and anatomic region as well as their stage of development, technical infrastructure, and approval.

Results

We identified 269 AI applications in the diagnostic radiology domain, offered by 99 companies. We show that AI applications are primarily narrow in terms of tasks, modality, and anatomic region. A majority of the available AI functionalities focus on supporting the “perception” and “reasoning” in the radiology workflow.

Conclusions

Thereby, we contribute by (1) offering a systematic framework for analyzing and mapping the technological developments in the diagnostic radiology domain, (2) providing empirical evidence regarding the landscape of AI applications, and (3) offering insights into the current state of AI applications. Accordingly, we discuss the potential impacts of AI applications on the radiology work and we highlight future possibilities for developing these applications.

Key Points

• Many AI applications are introduced to the radiology domain and their number and diversity grow very fast.

• Most of the AI applications are narrow in terms of modality, body part, and pathology.

• A lot of applications focus on supporting “perception” and “reasoning” tasks.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07230-9) contains supplementary material, which is available to authorized users.