Medico-Legal Cases in Breast Imaging in Canada: A Trend Analysis

Purpose: Breast imaging accounts for a large proportion of medico-legal cases involving radiologists in several countries and may be a disincentive to breast imaging. As this has not been well studied in Canada, we evaluated the key medico-legal issues of breast imaging in Canada and their implications for health care providers and patient safety. Methods: In collaboration with Canadian Medical Protective Association (CMPA), we obtained information from the medico-legal repository, including civil-legal, medical regulatory authority (College) and hospital complaints occurring between 2002-2021. Canadian Classification of Health Interventions (CCI) codes were used for breast imaging and biopsy. Trend analysis was done comparing cases involving breast imaging/biopsy to all cases where a radiologist was named. Results: Radiologists were named in 3108 medico-legal cases, 188 (6%, 188/3108) of which were CCI coded for breast imaging or biopsy. Factors related to radiologists were most frequent (64%, 120/188), followed by team (23.4%, 44/188) and system (6.9%, 13/188). Equal representation of male and female radiologists was found (IRR = 1.22; 95% CI: .89, 1.56). In a 10-year test window from 2006 - 2015 we identified an increasing trend for all cases involving radiologists (P = 0,0128) but a decreasing trend for cases coded with breast imaging or biopsy (P = 0,0099). Conclusions: A significant decrease in cases involving breast imaging were found from 2006-2015, accounting for 6% of the medico-legal cases. The lower risk of breast imaging medico-legal issues may encourage more radiologists in breast imaging.

Mounier-Kuhn syndrome in poorly controlled asthma

INTRODUCTION

Mounier-Kuhn syndrome or tracheobronchomegaly, is a rare condition that consists of abnormal dilation of the trachea and main bronchi due to a pathological arrangement of smooth muscle fibers in this area.

CASE REPORT

We present the case of a 46-year-old woman with poorly controlled asthma and recurrent infections, who was diagnosed with Mounier-Kuhn syndrome through a computed tomography scan revealing an unusual enlargement of the trachea with associated bronchiectasis.

RESULTS

The diagnosis of Mounier-Kuhn syndrome is radiological, involving measurement of the trachea where a diameter >25 mm in men and >21 mm in women is observed. While diagnosis is sometimes incidental, there is an association with respiratory diseases such as asthma or COPD, hence clinical suspicion is important in patients with poorly controlled underlying conditions who present with recurrent infections, inadequate secretion management, or even hemoptysis.

CONCLUSIONS

Despite its rarity, this syndrome significantly impacts patients' quality of life. Diagnosis and management involve comprehensive evaluations including computed tomography, with a multidisciplinary approach including pulmonologists and radiologists. Exploring its clinical features, associations with other respiratory diseases and treatment options is crucial in managing this rare respiratory condition.

Applying machine-learning models to differentiate benign and malignant thyroid nodules classified as C-TIRADS 4 based on 2D-ultrasound combined with five contrast-enhanced ultrasound key frames

Objectives

To apply machine learning to extract radiomics features from thyroid two-dimensional ultrasound (2D-US) combined with contrast-enhanced ultrasound (CEUS) images to classify and predict benign and malignant thyroid nodules, classified according to the Chinese version of the thyroid imaging reporting and data system (C-TIRADS) as category 4.

Materials and methods

This retrospective study included 313 pathologically diagnosed thyroid nodules (203 malignant and 110 benign). Two 2D-US images and five CEUS key frames ("2nd second after the arrival time" frame, "time to peak" frame, "2nd second after peak" frame, "first-flash" frame, and "second-flash" frame) were selected to manually label the region of interest using the "Labelme" tool. A total of 7 images of each nodule and their annotates were imported into the Darwin Research Platform for radiomics analysis. The datasets were randomly split into training and test cohorts in a 9:1 ratio. Six classifiers, namely, support vector machine, logistic regression, decision tree, random forest (RF), gradient boosting decision tree and extreme gradient boosting, were used to construct and test the models. Performance was evaluated using a receiver operating characteristic curve analysis. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy (ACC), and F1-score were calculated. One junior radiologist and one senior radiologist reviewed the 2D-US image and CEUS videos of each nodule and made a diagnosis. We then compared their AUC and ACC with those of our best model.

Results

The AUC of the diagnosis of US, CEUS and US combined CEUS by junior radiologist and senior radiologist were 0.755, 0.750, 0.784, 0.800, 0.873, 0.890, respectively. The RF classifier performed better than the other five, with an AUC of 1 for the training cohort and 0.94 (95% confidence interval 0.88-1) for the test cohort. The sensitivity, specificity, accuracy, PPV, NPV, and F1-score of the RF model in the test cohort were 0.82, 0.93, 0.90, 0.85, 0.92, and 0.84, respectively. The RF model with 2D-US combined with CEUS key frames achieved equivalent performance as the senior radiologist (AUC: 0.94 vs. 0.92, P = 0.798; ACC: 0.90 vs. 0.92) and outperformed the junior radiologist (AUC: 0.94 vs. 0.80, P = 0.039, ACC: 0.90 vs. 0.81) in the test cohort.

Conclusions

Our model, based on 2D-US and CEUS key frames radiomics features, had good diagnostic efficacy for thyroid nodules, which are classified as C-TIRADS 4. It shows promising potential in assisting less experienced junior radiologists.

Synergy between formal and informal education

The informal components of education can shape a person's capacity to contribute. Such informal components might include cultural backgrounds, work experiences, and extracurricular pursuits. To appreciate the synergy between formal and informal education it can be helpful to explore a particular case of someone who actually combined the two to make the whole more than the sum of its parts.

Radiologists' experiences and perceptions regarding the use of teleradiology in South Africa

Background

Teleradiology was implemented in South Africa in 1999, but the subsequent uptake was low and slow. The onset of the coronavirus disease 2019 (COVID-19) pandemic catapulted South African healthcare into the arena of teleradiology. This created the environment for re-examining the factors that enable or inhibit the uptake of teleradiology in both the public and private sectors.

Objectives

This article reports on a study of a select sample of private and public sector radiologists' experiences with, and perceptions of, the benefits, opportunities, challenges and barriers to the implementation of teleradiology in the South African context.

Method

Qualitative data on the perceived benefits and challenges of teleradiology, as well as on its enablers and the barriers to its implementation, were collected and analysed.

Results

The uptake of teleradiology in the sample increased by 15.9% during the COVID-19 pandemic. The results demonstrated that teleradiology was perceived to have clear benefits on operational, personal and societal levels.

Conclusion

It is important to address structural barriers to the implementation of teleradiology. Clear communication strategies and multistakeholder engagement are also required.

Contribution

By investigating radiologists' experience with teleradiology, this study provides an understanding of the benefits, opportunities, challenges and barriers to implementation of services. These insights enable informed decision-making and stakeholder engagement and provide a foundation for establishing recommendations for the viable implementation of teleradiology in South Africa and other lower- and middle-income countries to promote access to healthcare.

Towards equality: gender representation at the Royal College of Radiologists' Annual Scientific Meeting 2014-2021

Background: Conferences facilitate career advancement, but gender imbalances in public fora may negatively impact both women and men, and society. We aimed to describe the gender distribution of presenters at the UK's 2014-2021 Royal College of Radiologists' (RCR) Annual Scientific Meeting. Methods: We extracted data on presenter name, role and session type from meeting programmes. We classified gender as male or female using names, records or personal pronouns, accepting the limitations of these categories. We classified roles by prestige: lead, other (speakers and workshop faculty), proffered paper or poster presenters. We calculated odds ratios (OR) and 95% confidence intervals (CI) for associations between gender and binary outcomes using logistic regression.  Results: Women held 1,059 (37.5%) of 2,826 conference roles and presented 9/27 keynotes. Compared to men, women were less likely to hold other roles such as speakers and workshop faculty (OR 0.72 95% CI 0.61-0.83), and more likely to present posters (OR 1.49 95% CI 1.27-1.76). There were 60 male-only and eight women-only multi-presenter sessions. Sessions led by women had higher proportions of women speakers. The odds of roles being held by women increased during online meetings during COVID in 2020 and 2021 (OR 1.61, 95% CI 1.36-1.91) compared to earlier years. Conclusion: The proportion of women presenters and keynote speakers reflects that of RCR membership, but not of wider society. Disadvantage starts from the earliest career stages, prejudicing career opportunities. Efforts to improve inclusion and diversity are needed; focusing on lead roles and hybrid online/in-person formats may accelerate change.

[Role of Interventional Radiologists in Trauma Centers]

Based on statistics available in Korea, trauma centers play a critical role in treatment of patients with trauma. Interventional radiologists in trauma centers perform various procedures, including embolization, which constitutes the basic treatment for control of hemorrhage, although interventions such as stent graft insertion may also be used. Although emergency interventional procedures have been used conventionally, rapid and effective hemorrhage control is important in patients with trauma. Therefore, it is important to accurately understand and implement the concept of damage control interventional radiology, which has gained attention in recent times, to reduce preventable trauma-induced mortality rates.

Developing a Supplementary Diagnostic Tool for Breast Cancer Risk Estimation Using Ensemble Transfer Learning

Breast cancer is the most prevalent cancer worldwide. Thus, it is necessary to improve the efficiency of the medical workflow of the disease. Therefore, this study aims to develop a supplementary diagnostic tool for radiologists using ensemble transfer learning and digital mammograms. The digital mammograms and their associated information were collected from the department of radiology and pathology at Hospital Universiti Sains Malaysia. Thirteen pre-trained networks were selected and tested in this study. ResNet101V2 and ResNet152 had the highest mean PR-AUC, MobileNetV3Small and ResNet152 had the highest mean precision, ResNet101 had the highest mean F1 score, and ResNet152 and ResNet152V2 had the highest mean Youden J index. Subsequently, three ensemble models were developed using the top three pre-trained networks whose ranking was based on PR-AUC values, precision, and F1 scores. The final ensemble model, which consisted of Resnet101, Resnet152, and ResNet50V2, had a mean precision value, F1 score, and Youden J index of 0.82, 0.68, and 0.12, respectively. Additionally, the final model demonstrated balanced performance across mammographic density. In conclusion, this study demonstrates the good performance of ensemble transfer learning and digital mammograms in breast cancer risk estimation. This model can be utilised as a supplementary diagnostic tool for radiologists, thus reducing their workloads and further improving the medical workflow in the screening and diagnosis of breast cancer.

Effectiveness of ultrasound screening in right upper quadrant pain: A comparative study in a basic emergency service

Background and Aims

The use of ultrasound screening is primarily facilitated by point-of-care ultrasound (POCUS) and its integration into healthcare systems is a result of the versatility of this imaging technique. This study intends to compare the accuracy and pertinence of sonographic findings obtained by a sonographer in a Basic Emergency Service (BES) with that of radiologists at referral hospital (RH) in Portugal.

Methods

Twenty patients with right upper quadrant (RUQ) pain and suspected cholecystitis or biliary pathology underwent sonography screening using POCUS in the BES. They were then forwarded to the RH where a radiologist performed a conventional ultrasound exam on the same patients. The results of both exams were compared to determine if the findings obtained in the BES were confirmed by the radiologist in the RH.

Results

In our sample, 60% of cases were related to biliary pathology, 20% were liver-related, 10% had hepatopancreatic biliary etiology, and 10% had unknown etiology. A strong association between the sonographic findings in the BES and the RH was found in the variables "Sonographic Murphy sign" (V = 0.859; p = 0.001), "Cholelithiasis/Gallbladder sludge" (V = 0.840; p = 0.001), and "Intrahepatic biliary tract dilatation" (V = 0.717; p = 0.006). Adequate measures of agreement between the findings of the radiographer and radiologist were obtained for the "Sonographic Murphy sign" (k = 0.664; p = 0.001) and the presence of "Cholelithiasis/Gallbladder sludge" (k = 0.712; p = 0.000).

Conclusion

Major biliary abnormalities were detected in patients with RUQ pain in BES using sonography. The correlation between the sonographic findings obtained by the sonographers at BES and those obtained by radiologists at the RH in Portugal was strong, showing that POCUS screening could be extended to other similar settings; however, more studies are needed.

Awareness of Artificial Intelligence in Medical Imaging Among Radiologists and Radiologic Technologists

BACKGROUND

Current technological developments in medical imaging are primarily focused on increasing the integration of artificial intelligence (AI) into all medical imaging modalities. They are already considered capable of handling tasks such as image reconstruction, processing (denoising, segmentation), analysis, and predictive modeling. The purpose of this study is to assess the awareness (knowledge, attitudes, and practices) of radiologists and radiologic technologists regarding AI in medical imaging.

MATERIALS AND METHODS

This cross-sectional, qualitative study focuses on radiologists and radiologic technologists in Saudi Arabia, Sudan, and Yemen. A self-administered questionnaire based on published studies was used to collect primary data. Version 25.0 of IBM SPSS Statistics (IBM Corp., Armonk, NY) was used for the statistical analysis. The demographics were summarized as frequency and percentage. Independent samples t-tests and ANOVA tests were used to evaluate and compare the degree of AI awareness among the study groups.

RESULTS

A total of 210 individuals completed the survey. According to demographic information, there were 134 (63.8%) radiologic technologists and 76 radiologists (36.2%). Of the participants, 131 (62%) were male, while 79 (37.6%) were female. A total of 130 (61.9%) of the targeted respondents had a positive attitude, 105 (50%) had appropriate practice, and 122 (58.1%) of them were informed (knowledgeable) about AI in medical imaging. There was a significant difference in knowledge awareness between radiologists and radiologic technologists (p-value: <0.05). Radiologists were more knowledgeable than radiologic technologists, and females were more knowledgeable than males (p-value: 0.049). For attitude awareness, there were no significant differences regarding specialization, gender, age, academic qualification, and experience (p-value > 0.05). Regarding practice awareness, it turned out that females are more knowledgeable than males (p-value: 0.007). Additionally, it was discovered that significant differences indicated that bachelor's degree holders have a higher level of practice awareness than diploma holders (p-value: <0.05).

CONCLUSION

Significant differences between the respondent's knowledge awareness regarding specialization, gender, and experience are linked with relatively sufficient AI-basic knowledge and positive attitude awareness among radiologists and radiologic technologists. Only half of the study participants had appropriate practical awareness; therefore, additional training could enhance practical awareness.

Assessment of the statistical optimization strategies and clinical evaluation of an artificial intelligence-based automated diagnostic system for thyroid nodule screening

Background

Thyroid cancer is the most common endocrine cancer in the world. Accurately distinguishing between benign and malignant thyroid nodules is particularly important for the early diagnosis and treatment of thyroid cancer. This study aimed to investigate the best possible optimization strategies for an already-trained artificial intelligence (AI)-based automated diagnostic system for thyroid nodule screening and, in addition, to scrutinize the clinically relevant limitations using stratified analysis to better standardize the application in clinical workflows.

Methods

We retrospectively reviewed a total of 1,092 ultrasound images associated with 397 thyroid nodules collected from 287 patients between April 2019 and January 2021, applying postoperative pathology as the gold standard. We applied different statistical approaches, including averages, maximums, and percentiles, to estimate per-nodule-based malignancy scores from the malignancy scores per image predicted by AI-SONIC Thyroid v. 5.3.0.2 (Demetics Medical Technology Ltd., Hangzhou, China) system, and we assessed its diagnostic efficacy on nodules of different sizes or tumor types with per-nodule analysis using performance metrics.

Results

Of the 397 thyroid nodules, 272 thyroid nodules were overrepresented by malignant nodules according to the results of the surgical pathological examinations. Taking the median of the malignancy scores per image to estimate the nodule-based score with a cutoff value of 0.56 optimized for the means of sensitivity and specificity, the AI-based automated detection system demonstrated slightly lower sensitivity, significantly higher specificity (almost independent of nodule size), and similar accuracy to that of the senior radiologist. Both the AI system and the senior radiologist demonstrated higher sensitivity in diagnosing smaller nodules (≤25 mm) and comparable diagnostic performances for larger nodules. The mean diagnostic time per nodule of the AI system was 0.146 s, which was in sharp contrast to the 2.8 to 4.5 min of the radiologists.

Conclusions

Using our optimization strategy to achieve nodule-based diagnosis, the AI-SONIC Thyroid automated diagnostic system demonstrated an overall diagnostic accuracy equivalent to that of senior radiologists. Thus, it is expected that it can be used as a reliable auxiliary diagnostic method by radiologists for the screening and preoperative evaluation of malignant thyroid nodules.

Visual hindsight bias for abnormal mammograms in radiologists

Purpose

Hindsight bias-where people falsely believe they can accurately predict something once they know about it-is a pervasive decision-making phenomenon, including in the interpretation of radiological images. Evidence suggests it is not only a decision-making phenomenon but also a visual perception one, where prior information about an image enhances our visual perception of the contents of that image. The current experiment investigates to what extent expert radiologists perceive mammograms with visual abnormalities differently when they know what the abnormality is (a visual hindsight bias), above and beyond being biased at a decision level.

Approach

N=40 experienced mammography readers were presented with a series of unilateral abnormal mammograms. After each case, they were asked to rate their confidence on a 6-point scale that ranged from confident mass to confident calcification. We used the random image structure evolution method, where the images repeated in an unpredictable order and with varied noise, to ensure any biases were visual, not cognitive.

Results

Radiologists who first saw an original image with no noise were more accurate in the max noise level condition [area under the curve (AUC)=0.60] than those who first saw the degraded images (AUC=0.55; difference: p=0.005), suggesting that radiologists' visual perception of medical images is enhanced by prior visual experience with the abnormality.

Conclusions

Overall, these results provide evidence that expert radiologists experience not only decision level but also visual hindsight bias, and have potential implications for negligence lawsuits.

Comparison of Diagnostic Performance in Mammography Assessment: Radiologist with Reference to Clinical Information Versus Standalone Artificial Intelligence Detection

We compared diagnostic performances between radiologists with reference to clinical information and standalone artificial intelligence (AI) detection of breast cancer on digital mammography. This study included 392 women (average age: 57.3 ± 12.1 years, range: 30−94 years) diagnosed with malignancy between January 2010 and June 2021 who underwent digital mammography prior to biopsy. Two radiologists assessed mammographic findings based on clinical symptoms and prior mammography. All mammographies were analyzed via AI. Breast cancer detection performance was compared between radiologists and AI based on how the lesion location was concordant between each analysis method (radiologists or AI) and pathological results. Kappa coefficient was used to measure the concordance between radiologists or AI analysis and pathology results. Binominal logistic regression analysis was performed to identify factors influencing the concordance between radiologists’ analysis and pathology results. Overall, the concordance was higher in radiologists’ diagnosis than on AI analysis (kappa coefficient: 0.819 vs. 0.698). Impact of prior mammography (odds ratio (OR): 8.55, p < 0.001), clinical symptom (OR: 5.49, p < 0.001), and fatty breast density (OR: 5.18, p = 0.008) were important factors contributing to the concordance of lesion location between radiologists’ diagnosis and pathology results.

Inter- and Intra-Observer Agreement When Using a Diagnostic Labeling Scheme for Annotating Findings on Chest X-rays-An Early Step in the Development of a Deep Learning-Based Decision Support System

Consistent annotation of data is a prerequisite for the successful training and testing of artificial intelligence-based decision support systems in radiology. This can be obtained by standardizing terminology when annotating diagnostic images. The purpose of this study was to evaluate the annotation consistency among radiologists when using a novel diagnostic labeling scheme for chest X-rays. Six radiologists with experience ranging from one to sixteen years, annotated a set of 100 fully anonymized chest X-rays. The blinded radiologists annotated on two separate occasions. Statistical analyses were done using Randolph's kappa and PABAK, and the proportions of specific agreements were calculated. Fair-to-excellent agreement was found for all labels among the annotators (Randolph's Kappa, 0.40-0.99). The PABAK ranged from 0.12 to 1 for the two-reader inter-rater agreement and 0.26 to 1 for the intra-rater agreement. Descriptive and broad labels achieved the highest proportion of positive agreement in both the inter- and intra-reader analyses. Annotating findings with specific, interpretive labels were found to be difficult for less experienced radiologists. Annotating images with descriptive labels may increase agreement between radiologists with different experience levels compared to annotation with interpretive labels.

Early stage of radiological expertise modulates resting-state local coherence in the inferior temporal lobe

Background

The visual system and its inherent functions undergo experience-dependent changes through the lifespan, enabling acquisition of new skills. Previous fMRI studies using tasks reported increased specialization in a number of cortical regions subserving visual expertise. Although ample studies focused on representation of long-term visual expertise in the brain, i.e. in terms of year, monthly-based early-stage representation of visual expertise remains unstudied. Given that spontaneous neuronal oscillations actively encode previous experience, we propose brain representations in the resting state is fundamentally important.

Objective

The current study aimed to investigate how monthly-based early-stage visual expertise are represented in the resting state using the expertise model of radiologists.

Methods

In particular, we investigated the altered local clustering pattern of spontaneous brain activity using regional homogeneity (ReHo). A cohort group of radiology interns (n = 22) after one-month training in X-ray department and matched laypersons (n = 22) were recruited after rigorous behavioral assessment.

Results

The results showed higher ReHo in the right hippocampus (HIP) and the right ventral anterior temporal lobe (vATL) (corrected by Alphasim correction, P < 0.05). Moreover, ReHo in the right HIP correlated with the number of cases reviewed during intern radiologists' training (corrected by Alphasim correction, P < 0.05).

Conclusions

In sum, our results demonstrated that the early stage of visual expertise is more concerned with stabilizing visual feature and domain-specific knowledge into long-term memory. The results provided novel evidence regarding how early-stage visual expertise is represented in the resting brain, which help further elaborate how human visual expertise is acquired. We propose that our current study may provide novel ideas for developing new training protocols in medical schools.

Canadian Radiology Gender Pay Gap-Reality or Myth?

Introduction: Prior studies on Canadian physicians' income have demonstrated a gender pay gap (GPG); however, there is a paucity of data in the Radiology specialty. A cross-sectional study was conducted to determine if practicing Canadian radiologists' self-reported income is related to gender, controlling for demographic and work variables. Methods: English and French online surveys were distributed by email and social media to radiologists and trainees (May-July 2021). The association between Gender (controlling for Ethnicity variables, Region, having Children, Full-/Part-Time work, and Academic position) and Self-Reported Income was examined using chi-square tests. Pearson correlations examined relationships between opinion variables. Analyses were conducted using SPSS V28.0. A priori significance was P < .05. Study had ethics approval. Results: Four hundred and fifty-four practicing Canadian radiologists responded. Majority were women (51.2%, n = 227), a non-visible Minority (71.7%, n = 317), and from Western Provinces (67.8%, n = 308). Significant relationship was established between Self-Reported Income and Gender (χ2 = 10.44, df = 2, P < .05). More men (70.6%, n = 120) than women (56.4%, n = 110), reported income "greater than $500 000"; fewer men (20.6%, n = 35) than women (35.9%, n = 70) reported "$300 000-$500 000"; a similar percent of men (8.8%, n = 15) and women (7.7%, n = 15) reported "less than $300 000." No relationship was found between self-reported income and gender for ethnicity variables, those without children, part-time, or non-academic radiologists. The opinion "Addressing the GPG is important" correlated to "Canadian Association of Radiologists should collect demographic data" (r = 0.63). Responses were low for ethnic minorities and non-western provinces. Conclusion: Our results suggest a GPG exists in Canadian radiology and is an important first step for future studies.

Geographic Variations in Growth of Radiologists and Medicare Enrollees From 2012 to 2019

OBJECTIVE

Analyze changes in the number of Medicare-serving radiologists and Medicare enrollees nationwide and by geographic region and state from 2012 to 2019 to understand variations in allocation of imaging health care services over the past decade.

METHODS

The number of radiologists submitting claims to Medicare was extracted from the CMS Physician and Other Supplier Public Use File Database. The number of Medicare enrollees by state was obtained from the Kaiser Family Foundation. National-, regional-, and state-level changes in rates of growth of radiologists, Medicare enrollees, and radiologists per 100,000 Medicare enrollees from 2012 to 2019 were tabulated.

RESULTS

The overall number of radiologists per 100,000 Medicare enrollees was 79.7 in 2012, increasing to 79.9 in 2019. In 2012, the number of radiologists per 100,000 enrollees was lower than the national average in the South (66.9; 16% lower) and Midwest (79.1; 0.7% lower) and higher in the Northeast (98.3; 23% higher) and West (88.8; 11% higher). In 2019, the number of radiologists per 100,000 enrollees was lower than the national average in the South (69.8; 12% lower) only and was higher in the Midwest (81.4; 1.9% higher), Northeast (99.3; 24% higher), and West (80.2; 0.4% higher). By state, there was a 4.2-fold variation in the number of radiologists per 100,000 Medicare enrollees, ranging from 38.8 in Wyoming to 161.4 in Minnesota (200.5 in Washington, DC).

DISCUSSION

The growth of Medicare-serving radiologists and Medicare enrollees was stable nationally and demonstrated tremendous variations by US region and state. These variations bring to light potential implications for patient access to care and distribution of health care resources.

[Burnout among Radiologists in Korea: Prevalence, Risk Factors, and Remedies]

Burnout among radiologists has recently emerged as an issue that poses a threat to patient safety. Burnout adversely effects the quality of patient care and may lead to health problems in physicians. Approximately 84% of board-certified radiologists working in large hospitals in Korea responded that they had experienced burnout at least once. To overcome this, the standardization of physicians' workloads, as well as improvements in the professional workflow are necessary to ensure a healthy lifestyle balance.

A Comparison of Central Venous Access to the Internal Jugular Vein and Two Standard Approaches to the Subclavian Vein: A Study of Cross-Sectional Areas Using Computed Tomography Scans

Introduction The supraclavicular approach to the subclavian vein has been cited as having many advantages to the infraclavicular approach, including a larger short-axis cross-sectional area, a greater margin of safety, and fewer complications. Methods To examine whether a larger short-axis cross-sectional area of the subclavian vein at the supraclavicular fossa is a potential explanation for the reduction in attempts with the supraclavicular approach seen in a previous study, we examined computed tomography scans from 50 patients (24 M, 26 F). The short-axis cross-sectional areas of the subclavian vein at the mid-clavicular line, the subclavian vein in the supraclavicular fossa, and the internal jugular vein at the level of the thyroid cartilage were calculated. Results The internal jugular vein short-axis cross-sectional area was significantly larger than the subclavian vein short-axis cross-sections measured at each location. We found no difference between the short-axis cross-sectional areas of the subclavian vein or when comparing measurements as a factor of gender, age, or race. Weight had a significant relationship to the short-axis cross-sectional area of the internal jugular vein and subclavian vein at the mid-clavicular vein. Conclusions On supine computed tomographic imaging, the subclavian vein short-axis cross-section was not larger in the supraclavicular fossa than the mid-clavicular line. The short-axis cross-sectional area of the subclavian vein at the supraclavicular fossa does not appear to contribute to the decrease in attempts to access it. Weight, but not necessarily height, appears to be correlated with central vein size.

Convolutional Neural Network-Based Computer-Assisted Diagnosis of Hashimoto's Thyroiditis on Ultrasound

PURPOSE

This study investigates the efficiency of deep learning models in the automated diagnosis of Hashimoto's thyroiditis (HT) using real-world ultrasound data from ultrasound examinations by computer-assisted diagnosis (CAD) with artificial intelligence.

METHODS

We retrospectively collected ultrasound images from patients with and without HT from 2 hospitals in China between September 2008 and February 2018. Images were divided into a training set (80%) and a validation set (20%). We ensembled 9 convolutional neural networks (CNNs) as the final model (CAD-HT) for HT classification. The model's diagnostic performance was validated and compared to 2 hospital validation sets. We also compared the accuracy of CAD-HT against seniors/junior radiologists. Subgroup analysis of CAD-HT performance for different thyroid hormone levels (hyperthyroidism, hypothyroidism, and euthyroidism) was also evaluated.

RESULTS

39 280 ultrasound images from 21 118 patients were included in this study. The accuracy, sensitivity, and specificity of the HT-CAD model were 0.892, 0.890, and 0.895, respectively. HT-CAD performance between 2 hospitals was not significantly different. The HT-CAD model achieved a higher performance (P < 0.001) when compared to senior radiologists, with a nearly 9% accuracy improvement. HT-CAD had almost similar accuracy (range 0.87-0.894) for the 3 subgroups based on thyroid hormone level.

CONCLUSION

The HT-CAD strategy based on CNN significantly improved the radiologists' diagnostic accuracy of HT. Our model demonstrates good performance and robustness in different hospitals and for different thyroid hormone levels.

Evaluation of Breast Cancer Size Measurement by Computer-Aided Diagnosis (CAD) and a Radiologist on Breast MRI

Purpose: This study aimed to evaluate cancer size measurement by computer-aided diagnosis (CAD) and radiologist on breast magnetic resonance imaging (MRI) relative to histopathology and to determine clinicopathologic and MRI factors that may affect measurements. Methods: Preoperative MRI of 208 breast cancers taken between January 2017 and March 2021 were included. We evaluated correlation between CAD-generated size and pathologic size as well as that between radiologist-measured size and pathologic size. We classified size discrepancies into accurate and inaccurate groups. For both CAD and radiologist, clinicopathologic and imaging factors were compared between accurate and inaccurate groups. Results: The mean sizes as predicted by CAD, radiologist and pathology were 2.66 ± 1.68 cm, 2.54 ± 1.68 cm, and 2.30 ± 1.61 cm, with significant difference (p < 0.001). Correlation coefficients of cancer size measurement by radiologist and CAD in reference to pathology were 0.898 and 0.823. Radiologist’s measurement was more accurate than CAD, with statistical significance (p < 0.001). CAD-generated measurement was significantly more inaccurate for cancers of larger pathologic size (>2 cm), in the presence of an extensive intraductal component (EIC), with positive progesterone receptor (PR), and of non-mass enhancement (p = 0.045, 0.045, 0.03 and 0.002). Radiologist-measured size was significantly more inaccurate for cancers in presence of an in situ component, EIC, positive human epidermal growth factor receptor 2 (HER2), and non-mass enhancement (p = 0.017, 0.008, 0.003 and <0.001). Conclusion: Breast cancer size measurement showed a very strong correlation between CAD and pathology and radiologist and pathology. Radiologist-measured size was significantly more accurate than CAD size. Cancer size measurement by CAD and radiologist can both be inaccurate for cancers with EIC or non-mass enhancement.

Saudi Radiology Personnel's Perceptions of Artificial Intelligence Implementation: A Cross-Sectional Study

PURPOSE

Artificial intelligence (AI) in radiology has been a subject of heated debate. The external perception is that algorithms and machines cannot offer better diagnosis than radiologists. Reluctance to implement AI maybe due to the opacity in how AI applications work and the challenging and lengthy validation process. In this study, Saudi radiology personnel's familiarity with AI applications and its usefulness in clinical practice were investigated.

METHODS

A cross-sectional study was conducted in Saudi Arabia among radiology personnel from March to April 2021. Radiology personnel nationwide were surveyed electronically using Google form. The questionnaire included 12-questions related to AI usefulness in clinical practice and participants' knowledge about AI and their acceptance level to learn and implement this technology into clinical practice. Participants' trust level was also measured; Kruskal-Wallis test was used to examine differences between groups.

RESULTS

A total of 224 respondents from various radiology-related occupations participated in the survey. The lowest trust level in AI applications was shown by radiologists (p = 0.033). Eighty-two percent of participants (n = 184) had never used AI in their departments. Most respondents (n = 160, 71.4%) reported lack of formal education regarding AI-based applications. Most participants (n = 214, 95.5%) showed strong interest in AI education and are willing to incorporate it into the clinical practice of radiology. Almost half of radiography students (22/46, 47.8%) believe that their job might be at risk due to AI application (p = 0.038).

CONCLUSION

Radiology personnel's knowledge of AI has a significant impact on their willingness to learn, use and adapt this technology in clinical practice. Participants demonstrated a positive attitude towards AI, showed a reasonable understanding and are highly motivated to learn and incorporate it into clinical practice. Some participants felt that their jobs were threatened by AI adaptation, but this belief might change with good training and education programmes.

Interpretation of Thoracic Radiography Shows Large Discrepancies Depending on the Qualification of the Physician-Quantitative Evaluation of Interobserver Agreement in a Representative Emergency Department Scenario

(1) Background: Chest radiography (CXR) is still a key diagnostic component in the emergency department (ED). Correct interpretation is essential since some pathologies require urgent treatment. This study quantifies potential discrepancies in CXR analysis between radiologists and non-radiology physicians in training with ED experience. (2) Methods: Nine differently qualified physicians (three board-certified radiologists [BCR], three radiology residents [RR], and three non-radiology residents involved in ED [NRR]) evaluated a series of 563 posterior-anterior CXR images by quantifying suspicion for four relevant pathologies: pleural effusion, pneumothorax, pneumonia, and pulmonary nodules. Reading results were noted separately for each hemithorax on a Likert scale (0–4; 0: no suspicion of pathology, 4: safe existence of pathology) adding up to a total of 40,536 reported pathology suspicions. Interrater reliability/correlation and Kruskal–Wallis tests were performed for statistical analysis. (3) Results: While interrater reliability was good among radiologists, major discrepancies between radiologists’ and non-radiologists’ reading results could be observed in all pathologies. Highest overall interrater agreement was found for pneumothorax detection and lowest agreement in raising suspicion for malignancy suspicious nodules. Pleural effusion and pneumonia were often suspected with indifferent choices (1–3). In terms of pneumothorax detection, all readers mainly decided for a clear option (0 or 4). Interrater reliability was usually higher when evaluating the right hemithorax (all pathologies except pneumothorax). (4) Conclusions: Quantified CXR interrater reliability analysis displays a general uncertainty and strongly depends on medical training. NRR can benefit from radiology reporting in terms of time efficiency and diagnostic accuracy. CXR evaluation of long-time trained ED specialists has not been tested.

Value of a breast imaging unit in the detection of breast cancer in Mexico

The screening breast cancer detection rate in Mexico is low. The main objective of this study was to determine the breast cancer detection rate in a Mexican population that attended a breast imaging unit, in which the same radiologist comprehensively evaluated and interpreted breast imaging studies. A total of 5,429 mammograms performed between 2015 and 2016 were evaluated. Rates for biopsy indication, biopsies performed and positive biopsies for cancer were determined. The malignancy detection rate, after a comprehensive imaging evaluation in a breast imaging unit, was 24.3 per 1,000 mammograms. In symptomatic women was 52.9 per 1,000 mammograms, and in screening women was 11.1 per 1,000 mammograms. Breast imaging units in which a comprehensive imaging approach is performed represent an opportunity for low- and middle-income countries without population-based screening programs to achieve a more efficient detection of breast cancer, without generating a higher cost.

Breast Arterial Calcifications on Mammography: A Survey of Practicing Radiologists

OBJECTIVE

To explore current practice patterns of reporting and issuing recommendations based on the presence of breast arterial calcifications on mammography and existing knowledge of their prevalence and associated factors.

METHODS

An online anonymous 19-question survey was distributed to 2583 practicing radiologists who were members of the Society of Breast Imaging. Questions covered demographics, breast imaging training, practice type, and knowledge regarding the epidemiology and potential clinical significance of breast arterial calcifications detected on mammograms. Differences between groups were calculated using the chi-square test or Fisher exact test. An α level of 0.05 was used to determine statistical significance.

RESULTS

Response rate was 22% (364/1662). The median age of respondents was 51 years (range: 29-76) and most were female (248/323, 77%). The most prevalent characteristics among respondents were as follows: 69% (223/323) had completed a breast imaging fellowship, 55% (179/323) were in private practice, 49% (158/323) practiced dedicated breast imaging, and 38% (124/323) had been in practice for more than 20 years. The prevalence of breast arterial calcifications was correctly estimated to be 1%-30% by 39% (125/323) of respondents. Most respondents correctly recognized the growing evidence of an association between breast arterial calcifications and coronary artery disease (275/323, 85%). However, only 15% (48/323) always reported the presence of these calcifications, and of those who report them at any time, only 0.7% (2/274) always issued recommendations.

CONCLUSION

There are differences in both knowledge of the epidemiology of breast arterial calcifications and practices around their reporting amongst breast radiologists.

Implications of the revised cervical cancer FIGO staging system

The 2018 revised International Federation of Gynaecology and Obstetrics (FIGO) staging of cervical cancer has brought about a paradigm shift by offering the option of adding imaging and pathology to clinical staging. This makes it applicable to all types of resource situations across geographies with implications for all stakeholders, including gynaecologists, gynaecologic oncologists, radiologists, pathologists and radiation and medical oncologists. The new staging classification has more granularity, with three sub-stages of stage IB and a new category of stage IIIC for all cases with lymph node (LN) involvement. The major limitations of clinical staging were inaccurate assessment of tumour size and inability to assess pelvic and para-aortic LNs with the limited investigations permitted by FIGO to change the stage. This resulted in understaging of stages IB-III, and overstaging of stage IIIB, which has been largely overcome by incorporating imaging findings. Although any imaging modality can be used, magnetic resonance imaging appears to be the best imaging modality for early-stage disease owing to its better soft-tissue resolution. However, the use of contrast-enhanced computed tomography or ultrasonography are also feasible options, depending on the availability and resources. But wherever pathological evaluation is possible, it supersedes clinical and radiological findings.

Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

Visual experience modulates whole-brain connectivity dynamics: A resting-state fMRI study using the model of radiologists

Visual expertise refers to proficiency in visual recognition. It is attributed to accumulated visual experience in a specific domain and manifests in widespread neural activities that extend well beyond the visual cortex to multiple high‐level brain areas. An extensive body of studies has centered on the neural mechanisms underlying a distinctive domain of visual expertise, while few studies elucidated how visual experience modulates resting‐state whole‐brain connectivity dynamics. The current study bridged this gap by modeling the subtle alterations in interregional spontaneous connectivity patterns with a group of superior radiological interns. Functional connectivity analysis was based on functional brain segmentation, which was derived from a data‐driven clustering approach to discriminate subtle changes in connectivity dynamics. Our results showed there was radiographic visual experience accompanied with integration within brain circuits supporting visual processing and decision making, integration across brain circuits supporting high‐order functions, and segregation between high‐order and low‐order brain functions. Also, most of these alterations were significantly correlated with individual nodule identification performance. Our results implied that visual expertise is a controlled, interactive process that develops from reciprocal interactions between the visual system and multiple top‐down factors, including semantic knowledge, top‐down attentional control, and task relevance, which may enhance participants' local brain functional integration to promote their acquisition of specific visual information and modulate the activity of some regions for lower‐order visual feature processing to filter out nonrelevant visual details. The current findings may provide new ideas for understanding the central mechanism underlying the formation of visual expertise.

Today's radiologists meet tomorrow's AI: the promises, pitfalls, and unbridled potential

Advances in information technology have improved radiologists' abilities to perform an increasing variety of targeted diagnostic exams. However, due to a growing demand for imaging from an aging population, the number of exams could soon exceed the number of radiologists available to read them. However, artificial intelligence has recently resounding success in several case studies involving the interpretation of radiologic exams. As such, the integration of AI with standard diagnostic imaging practices to revolutionize medical care has been proposed, with the ultimate goal being the replacement of human radiologists with AI 'radiologists'. However, the complexity of medical tasks is often underestimated, and many proponents are oblivious to the limitations of AI algorithms. In this paper, we review the hype surrounding AI in medical imaging and the changing opinions over the years, ultimately describing AI's shortcomings. Nonetheless, we believe that AI has the potential to assist radiologists. Therefore, we discuss ways AI can increase a radiologist's efficiency by integrating it into the standard workflow.

Which Aspects of the CanMEDS Competencies are Most Valued in Radiologists? Perspectives of Trainees From Other Specialties

PURPOSE

Radiologists work primarily in collaboration with other healthcare professionals. As such, these stakeholder perspectives are of value to the development and assessment of educational outcomes during the transition to competency-based medical education. Our aim in this study was to determine which aspects of the Royal College CanMEDS competencies for diagnostic radiology are considered most important by future referring physicians.

METHODS

Institutional ethics approval was obtained. After pilot testing, an anonymous online survey was sent to all residents and clinical fellows at our university. Open-ended questions asked respondents to describe the aspects of radiologist service they felt were most important. Thematic analysis of the free-text responses was performed using a grounded theory approach. The resulting themes were mapped to the 2015 CanMEDS Key Competencies.

RESULTS

115 completed surveys were received from residents and fellows from essentially all specialties and years of training (out of 928 invited). Major themes were 1) timeliness and accessibility of service, 2) quality of reporting, and 3) acting as a valued team member. The competencies identified as important by resident physicians were largely consistent with the CanMEDS framework, although not all key competencies were covered in the responses.

CONCLUSIONS

This study illustrates how CanMEDS roles and competencies may be exemplified in a concrete and specialty-specific manner from the perspective of key stakeholders. Our survey results provide further insight into specific objectives for teaching and assessing these competencies in radiology residency training, with the ultimate goal of improving patient care through strengthened communication and working relationships.

Ultrasound-guided assessment of gastric residual volume in patients receiving three types of clear fluids: A randomised blinded study

Background and Aims:

Ultrasonography (USG) is used to evaluate gastric residual volume (GRV); however, this technique may have inter-assessor variability. This study aimed to measure GRV in three groups of fasted patients 2 h after they received 200 mL of water, clear apple juice or apple-flavoured oral rehydration solution (ORS) and to determine inter-assessor reliability of USG-guided GRV measurement.

Methods:

We randomised 90 adult patients planned for elective cancer surgery, with no risk factors for delayed gastric emptying, to receive 200 mL of water, clear apple juice or apple-flavoured ORS after overnight fasting. Two hours later, two blinded assessors (a trained anaesthesiologist and a radiologist) independently determined USG-guided GRV. The primary outcome was GRV measured by the radiologist. The secondary outcome was inter-assessor correlation and agreement in GRV measurements.

Results:

There was no statistically significant difference in median GRV between groups (apple-flavoured ORS 74.8 mL, apple juice 63.7 mL, and water 62.1 mL, P = 0.11). We found poor correlation between measurements of radiologist and anaesthesiologist (Intra-class correlation coefficient 0.3, 95% confidence intervals 0.09 to 0.48, P value 0.002). The average (mean) bias was 5.4 mL (standard deviation 42.3 mL) and the 95% limits of agreement were -79.2 ml to +90 ml.

Conclusion:

Patients receiving 200 mL of water, clear apple juice or apple-flavoured ORS had comparable GRV after 2 h. There was poor correlation and agreement between GRV measurements of different assessors, indicating that more training may be required for anaesthesiologists to attain proficiency in the quantitative assessment of GRV.

The adequacy of fluoroscopic upper gastrointestinal studies for suspected intestinal volvulus in a tertiary care centre vs. secondary centres: A regional multicentre study

INTRODUCTION

Early diagnosis and treatment of intestinal volvulus are important to reduce morbidity. A fluoroscopic upper GI study is the gold standard for diagnosis and may be performed in a secondary or tertiary care centre prior to surgery. It is important the reporting radiologist is confident in the findings. We aim to assess whether there is any difference in confidence and study quality between paediatric and general radiologists who work in secondary or tertiary care centres.

METHODS

Retrospective review of initial radiology reports and blinded review of the study images by paediatric radiologists.

RESULTS

A total of 277 children underwent a fluoroscopic study for intestinal volvulus over a four-year period. The majority were performed at a tertiary care centre, by paediatric radiologists. The confidence of initial reporting was higher in paediatric than general radiologists despite whether they worked in a secondary or tertiary care centre (P-value < 0.001). On retrospective review, studies performed by paediatric radiologists were rated as having a higher confidence in identifying the location of the duodenojejunal flexure. General radiologists tended to have a slightly higher rate of repeat studies but still low at 2.2%. Despite this, there was no significant difference in the diagnosis rates and secondary centre general radiologists excluded malrotation in 62% of studies likely reducing transfer rates.

CONCLUSION

Confidence in initial reporting and on review of the duodenojejunal flexure location in suspected intestinal volvulus is higher in paediatric radiologists compared with general radiologists, although diagnosis rates are no different.

The Need for an Ecologic Understanding of Radiology Practice

OBJECTIVE. Many models have been used to understand radiology practice, including economics, engineering, and information technology. Each has advantages, but each also has drawbacks, failing to illuminate important aspects of radiologists' work. A model that offers additional insights is ecology. CONCLUSION. By looking at radiology practice through the ecologic concept of symbiosis, radiologists can gain new understanding and appreciation of aspects of their work that can render it more fruitful and sustainable.

Online Liver Imaging Course; Pivoting to Transform Radiology Education During the SARS-CoV-2 Pandemic

PURPOSE

The SARS-CoV-2 pandemic has drastically disrupted radiology in-person education. The purpose of this study was to assess the implementation of a virtual teaching method using available technology and its role in the continuity of education of practicing radiologists and trainees during the pandemic.

METHODS

The authors created the Online Liver Imaging Course (OLIC) that comprised 28 online comprehensive lectures delivered in real-time and on-demand over six weeks. Radiologists and radiology trainees were asked to register to attend the live sessions. At the end of the course, we conducted a 46-question survey among registrants addressing their training level, perception of virtual conferencing, and evaluation of the course content.

RESULTS

One thousand four hundred and thirty four radiologists and trainees completed interest sign up forms before the start of the course with the first webinar having the highest number of live attendees (343 people). On average, there were 89 live participants per session and 750 YouTube views per recording (as of July 9, 2020). After the end of the course, 487 attendees from 37 countries responded to the postcourse survey for an overall response rate of (33%). Approximately (63%) of participants were practicing radiologists while (37%) were either fellows or residents and rarely medical students. The overwhelming majority (97%) found the OLIC webinar series to be beneficial. Essentially all attendees felt that the webinar sessions met (43%) or exceeded (57%) their expectations. When asked about their perception of virtual conferences after attending OLIC lectures, almost all attendees (99%) enjoyed the virtual conference with a majority (61%) of the respondents who enjoyed the virtual format more than in-person conferences, while (38%) enjoyed the webinar format but preferred in-person conferences. When asked about the willingness to attend virtual webinars in the future, (84%) said that they would attend future virtual conferences even if in-person conferences resume while (15%) were unsure.

CONCLUSION

The success of the OLIC, attributed to many factors, indicates that videoconferencing technology provides an inexpensive alternative to in-person radiology conferences. The positive responses to our postcourse survey suggest that virtual education will remain to stay. Educational institutions and scientific societies should foster such models.

Deep learning assistance for tuberculosis diagnosis with chest radiography in low-resource settings

Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous researches of artificial intelligence (AI) have been conducted targeting at TB to reduce the diagnostic burden. However, most researches are conducted in the developed urban areas. The feasibility of applying AI in low-resource settings remains unexplored. In this study, we apply an automated detection (AI) system to screen a large population in an underdeveloped area and evaluate feasibility and contribution of applying AI to help local radiologists detect and diagnose TB using chest X-ray (CXR) images. First, we divide image data into one training dataset including 2627 TB-positive cases and 7375 TB-negative cases and one testing dataset containing 276 TB-positive cases and 619 TB-negative cases, respectively. Next, in building AI system, the experiment includes image labeling and preprocessing, model training and testing. A segmentation model named TB-UNet is also built to detect diseased regions, which uses ResNeXt as the encoder of U-Net. We use AI-generated confidence score to predict the likelihood of each testing case being TB-positive. Then, we conduct two experiments to compare results between the AI system and radiologists with and without AI assistance. Study results show that AI system yields TB detection accuracy of 85%, which is much higher than detection accuracy of radiologists (62%) without AI assistance. In addition, with AI assistance, the TB diagnostic sensitivity of local radiologists is improved by 11.8%. Therefore, this study demonstrates that AI has great potential to help detection, prevention, and control of TB in low-resource settings, particularly in areas with more scant doctors and higher rates of the infected population.

Balancing Narrow and Broad Perspectives in Radiology

OBJECTIVE. The purpose of this article is to help radiologists achieve a balance between narrow and broad perspectives in their work. CONCLUSION. There are two fundamentally different perspectives from which radiologists can work: narrow and broad. Both have important roles, yet if the balance between these perspectives shifts excessively in one direction or the other, problems can arise. By understanding the respective strengths and weaknesses of each perspective, radiologists can achieve a more appropriate balance between them.

PI-RADS Versions 2 and 2.1: Interobserver Agreement and Diagnostic Performance in Peripheral and Transition Zone Lesions Among Six Radiologists

BACKGROUND. PI-RADS version 2.1 (v2.1) modifications primarily address transition zone (TZ) interpretation. The revisions also impact peripheral zone (PZ) interpretation, which has received less attention. OBJECTIVE. The purpose of this study was to compare interobserver agreement of PI-RADS version 2 (v2) and v2.1 in the prostate PZ and TZ and perform a pilot comparison of their diagnostic performance in the two zones. METHODS. Six radiologists with varying experience retrospectively assessed 80 prostate lesions (40 PZ, 40 TZ) on MRI in separate sessions for PI-RADS v2 and v2.1. Interobserver agreement was assessed using Conger kappa (κ). For 50 lesions with pathology data, average AUC for detecting clinically significant cancer was compared between versions using multireader multicase statistical methods. Error variance and covariance results informed post hoc power analysis. RESULTS. Interobserver agreement for PI-RADS category 4 or greater was higher for version 2.1 (κ = 0.64) than version 2 (κ = 0.51) in the PZ, but similar for version 2 (κ = 0.64) and version 2.1 (κ = 0.60) in the TZ. The PI-RADS v2.1 DWI descriptor "linear/wedge-shaped" had higher agreement than its predecessor version 2 descriptor "indistinct hypointense" (κ = 0.52 vs κ = 0.18) and yielded 14 more true-negative versus five more false-negative interpretations. The ADC signal descriptor "markedly hypointense," for which only version 2.1 provides a specific definition, had lower agreement in version 2.1 (κ = 0.26) than version 2 (κ = 0.52). Modified TZ T2-weighted category 2 descriptors in version 2.1 had fair agreement (κ = 0.21), and agreement for PI-RADS category 2 in the TZ was lower in version 2.1 (κ = 0.31) than version 2 (κ = 0.57). DWI upgraded a TZ lesion category from 2 to 3 in four patients, detecting two additional cancers. Average AUC was not different between versions 2 and 2.1 for the PZ (AUC, 0.81 vs 0.85; p = .24) or the TZ (AUC, 0.69 vs 0.69; p = .94), though among experienced readers AUC was higher for version 2.1 than version 2 for the PZ (0.91 vs 0.82; p = .001). Overall performance comparison had sufficient power (0.8) to detect a 0.085 difference in AUC. CONCLUSION. Interobserver agreement improved using PI-RADS v2.1 in the PZ but not the TZ. Diagnostic performance improved using version 2.1 only in the PZ for experienced readers. Specific version 2.1 modifications yielded mixed results. CLINICAL IMPACT. The impact of PI-RADS v2.1 in the PZ is notable given the emphasis on version 2.1 TZ modifications. The findings suggest areas in which additional modification could further improve interobserver agreement and performance.

Comparison of breast density assessments according to BI-RADS 4th and 5th editions and experience level

Background

Breast density is an important variable that can change the sensitivity of mammography. It can be analyzed with using the 4th and 5th editions of the Breast Imaging and Reporting Data System (BI-RADS) recommendations from the American College of Radiology (ACR).

Purpose

To define the intra- and inter-reader agreement levels of breast density assignments performed by readers with different experience levels using two versions of BI-RADS.

Material and Methods

The breast density assessments of 330 women were conducted by two readers with different levels of experience (one breast radiologist and one resident). Each reader independently defined the breast density four times-twice using the 4th edition and twice using the 5th edition. Assessments were analyzed on four- and two-category scales.

Results

The intra-reader agreement of the breast radiologist for the 4th and 5th editions of BI-RADS was almost perfect (k = 0.90 and k = 0.87, respectively.) The resident had similar results (k = 0.88 and k = 0.87, respectively). The agreement between the breast radiologist and resident for the 4th and 5th edition of BI-RADS was substantial (k = 0.70 and k = 0.63, respectively). There was a statistically significant difference with the two-category scale analysis between the dense and non-dense for both readers and versions of BI-RADS (McNemar's test, P < 0.001).

Conclusion

Although there were high intra- and inter-reader agreement levels when using both versions, the percentage of women having dense breasts increased when using the 5th edition, and the difference was statistically significant. There were no differences found with regard to the readers' level of experience in all analyses.

Increased trend of unnecessary use of radiological diagnostic modalities in Pakistan: radiologists perspective

BACKGROUND

Over the past few years, a significant overuse of radiological investigations influenced the quality and cost of healthcare of the country as it may lead to non-compliance of the patient due to non-affordability and also may harm the patient in terms of radiation hazards. Pakistan, being a low-income, resource-constraint country, is facing financial impact on families as well as health system due to multiple reasons.

OBJECTIVES

The purpose of study is to identify reasons of unnecessary use of radiological diagnostic modalities in Pakistani hospitals as perceived by radiologists.

METHODS

A cross-sectional study was conducted on a total of all 105 radiologists, having at least 1 year experience of working in radiology, working in five tertiary care hospitals in Lahore. A self-constructed, self-administered, pretested 5-point Likert scale opinion-based questionnaire was administered after taking informed consent. It includes questions about excessive radiological use that may be attributed to the physicians, investigations, patients and other non-categorized causes. Results were analyzed using SPSS version 23.

RESULTS

Since the assessment forms were handed over and collected from the radiologists in person, the response rate was 100%. Of a total of 105 respondents, 78 (74.28%) respondentsagreed that there is an actual increase, 25 (23.80%) respondents disagreed and 2 (1.90%) respondents were unsure. Most important reasons for increased usage of radiological investigations are 'need of accuracy of diagnosis' (P = 0.009), 'trend of physicians to repeat tests in order to confirm preset diagnoses' (P-value = 0.03), 'lack of knowledge about proper usage of radiological advances' (P-value = 0.005) and 'lack of proper clinical examination' (P-value = 0.04).

CONCLUSION

Unnecessary use of radiological investigations is actually there as perceived by radiologists, which is attributed to inadequate knowledge, attitude and training of physicians to refer patients to radiological resources. This research can be a stepping stone for future researchers as it can be used for elaborating these causes individually and finding ways as to how each of these causes can be controlled and minimized to bring about a decline in excessive usage of these modalities for the betterment of the patients.

Determining whether surgeons perform thyroid fine-needle aspiration as well as radiologists: an analysis of the adequacy and efficiency of ultrasound-guided fine-needle aspiration performed by newly trained head and neck surgeons and radiologists

Background

Ultrasound-guided fine-needle aspiration (FNA) cytology is a crucial diagnostic technique used to assess thyroid nodules. In the past, ultrasound-guided FNA was performed mainly by radiologists. However, many surgeons are increasingly being trained for this procedure now. In this study, we aimed to compare the adequacy and efficiency of ultrasound-guided FNA performed by newly trained head and neck surgeons with experienced radiologists in a single institution. We also assessed the malignancy rates in nondiagnostic nodules and the differences between benign and malignant nodules.

Methods

This is a retrospective study. The data from patients who underwent ultrasound-guided FNA performed by surgeons or radiologists in two consecutive years were collected. Medical records, cytology results, and surgical pathology results were analyzed.

Results

During the study period, a total of 2,405 ultrasound-guided FNAs were performed on 2,163 patients. The head and neck surgeons and radiologists performed 1,132 and 1,273 ultrasound-guided FNA procedures, respectively. The nondiagnostic rate was 14.49% for surgeons and 15.40% for radiologists (P=0.533). There were no differences in patient age, gender, nodule size, and other sonographic characteristics between the groups of patients who were treated by radiologists versus surgeons. The median waiting time from biopsy appointment to performing ultrasound-guided FNA was 0 days for head and neck surgeons, and 6 days for radiologists (P<0.001). Of the 40 patients who had a repeat FNA or surgery, 19 (47.50%) had a malignancy. Preoperative information about age, gender, operator, and characteristics of nodules did not predict the outcome of nodules with Bethesda category I.

Conclusions

The adequacy of ultrasound-guided FNAs performed by head and neck surgeons is similar to that of skilled radiologists, while surgeons are more efficient than radiologists. Nondiagnostic FNA reports should not be considered benign, and repeat FNA or selective surgical treatment is recommended.

How Safety Can Undermine Creativity

OBJECTIVE. Safety and creativity are important but are not entirely convergent medical goals: Physicians are responsible to avoid harm, but progress in medicine requires creativity and risk taking. To strike the appropriate balance between the two, radiologists need to understand potential points of tension between them, ensuring that neither completely overrides the other. CONCLUSION. For medical discovery and innovation to thrive in the future, we need to foster a culture that prizes habits of thinking outside the box, posing novel questions, and taking risks. Caution and safety are important but so too are courage and imagination. If our understanding is ever to reach a higher level, we must be willing to let go of the rung to which we are clinging.

Evaluation of self-reported confidence amongst radiology staff in initiating basic life support across hospitals in the Cape Town Metropole West region

Background

The immediate response to cardiac arrest is regarded as the most time-critical intervention. First responders for cardiac arrests in imaging departments are often radiology staff. The study aim was to determine radiology staff members' confidence in initiating basic life support.

Objectives

The objectives of this study included determining the general confidence levels regarding identifying cardiac arrest and initiation of basic life support (BLS) amongst Radiology staff within the studied sites, as well as to identify potential areas of uncertainty. Another objective included identifying what would contribute to increasing levels of confidence and competence in identifying cardiac arrest and initiating BLS.

Method

A multi-centre cross-sectional survey was conducted using peer-validated, anonymous questionnaires. Questionnaires were distributed to radiology staff working in public sector hospitals within the Cape Town Metropole West. Due to the limited subject pool, a convenience sample was collected. Data were therefore statistically analysed using only summary statistics (mean, standard deviation, proportions, and so on), and detailed comparisons were not made.

Results

We disseminated 200 questionnaires, and 74 were completed (37%). There were no incomplete questionnaires or exclusions from the final sample. Using a 10-point Likert scale, the mean ability to recognise cardiac arrest was 6.45 (SD ± 2.7), securing an airway 4.86 (SD ± 2.9), and providing rescue breaths and initiating cardiac compressions 6.14 (SD ± 2.9). Only two (2.7%) of the participants had completed a basic life support course in the past year; 11 (14.8%) had never completed any basic life support course and 28 (37.8%) had never completed any life support or critical care course. Radiologists, radiology trainees and nurses had the greatest confidence in providing rescue breaths and initiating cardiac compressions from all the groups.

Conclusion

The study demonstrated a substantial lack of confidence in providing basic life support in the participating hospital imaging departments' staff. The participants indicated that regular training and improved support systems would increase confidence levels and improve skills.

Dementia Care in Radiology

OBJECTIVE. Much of the radiology literature on dementia naturally focuses on the use of imaging for diagnosis. However, dementia presents other important challenges for radiology. One of the most important stems from the projected large increase in the number of patients with dementia who will be presenting for care in radiology departments. CONCLUSION. It is important, and increasingly so, that patient-facing radiology personnel understand dementia and the special needs of patients with dementia and their caregivers.

Interdisciplinary Comparison of PADUA and R.E.N.A.L. Scoring Systems for Prediction of Conversion to Nephrectomy in Patients with Renal Mass Scheduled for Nephron Sparing Surgery

PURPOSE

We examined interdisciplinary variability using 2 established preoperative nephrometry scores to predict conversion to nephrectomy in patients with a renal mass who were scheduled for partial nephrectomy.

MATERIALS AND METHODS

A total of 229 consecutive candidates for partial nephrectomy were included in this study at a single institution between January 2013 and May 2017. Patient, tumor and treatment characteristics were assessed. The PADUA (preoperative aspects and dimensions used for an anatomical) score and the R.E.N.A.L. (radius, exophytic/endophytic, nearness of tumor to collecting system or sinus, anterior/posterior, location relative to polar lines) score were independently calculated by board certified radiologists and urological residents using computerized tomography or magnetic resonance imaging. Statistical analyses were done with the κ statistic, ROC curves, and univariable and multivariable binary logistic regression analyses.

RESULTS

Partial nephrectomy was performed in 198 of the 229 cases (86.5%) while 31 (13.5%) were converted to nephrectomy. The prevalent tumor stage was pT1a, noted in 94 of the 229 cases (41.1%), and the predominant histological entity was clear cell carcinoma, found in 128 (55.9%). Radiologist and urologist interdisciplinary comparison of the PADUA and R.E.N.A.L. scores revealed a κ of 0.40 and 0.56, respectively. ROC curve analyses demonstrated a higher AUC predicting conversion to nephrectomy using the PADUA score by the urologist and the radiologist (0.79 and 0.782) compared to that of the R.E.N.A.L. score (0.731 and 0.766, respectively). Using a cutoff of 10 or greater the PADUA score determined by the urologist had 81% sensitivity and 71% specificity, and it was independently associated with conversion to nephrectomy (OR 10.98, p<0.001).

CONCLUSIONS

Our results indicate higher prediction of conversion to nephrectomy when using the PADUA score compared to the R.E.N.A.L. score. Calculation of the PADUA and the R.E.N.A.L. score by physicians without specialized radiological training is feasible and might achieve comparable results to predict conversion to nephrectomy compared to the gold standard provided by board certified radiologists. This information is helpful if nephrometry scores are not regularly included in the radiology report.