Differentiating malignant from benign splenic lesions: a meta-analysis and pictorial review of imaging features.

OBJECTIVES: Splenic lesions might exhibit overlapping imaging features, varying from benign entities like cysts and hemangiomas to malignancies such as lymphoma and angiosarcoma. This meta-analysis aims to delineate imaging characteristics that distinguish malignant from benign splenic lesions. METHODS: Adhering to PRISMA guidelines, we searched PubMed, Scopus, and Web of Science for studies on imaging features differentiating malignant from benign splenic lesions. We extracted data on splenic pathology and imaging characteristics and assessed the methodological quality via QUADAS-2. Odds ratio meta-analyses were performed using STATA (Version 17.0, Stata Corp, College Station, TX). RESULTS: Portal phase hypoenhancement, hypovascular enhancement pattern, diffusion restriction, and late phase hypoenhancement, with odds ratios above 10, highly indicate malignancy. Other features suggestive of malignancy include solid morphology, lymphadenopathy, presence of perisplenic fluid, arterial hypoenhancement, hypoechogenicity on ultrasound, splenomegaly, and presence of multiple lesions. In contrast, cystic morphology, hypervascular-washout and hypervascular-persistent pattern of enhancement, late phase hyperenhancement, anechogenicity on ultrasound, portal phase hyperenhancement, well-defined borders, and calcification are in favour of benign pathology. CONCLUSION: The study underscores the critical role of contrast-enhanced and diffusion-weighted imaging in distinguishing malignant from benign splenic lesions, emphasizing the role of features like portal phase hypoenhancement and restricted diffusion in diagnosing malignancies. Additionally, the study emphasizes the value of contrast-enhanced ultrasound, which allows for the visualization of key contrast-enhancement patterns without the risk of ionizing radiation exposure.

Diagnostic accuracy of CT-based radiomics and deep learning for predicting lymph node metastasis in esophageal cancer.

BACKGROUND: Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional diagnostics fall short. Integrating radiomics and deep learning (DL) with CT imaging for LNM diagnosis could revolutionize prognostic assessment and treatment planning. METHODS: A systematic review and meta-analysis were conducted by searching PubMed, Scopus, Web of Science, and Embase up to October 1, 2023. The focus was on studies developing CT-based radiomics and/or DL models for preoperative LNM detection in esophageal cancer. Methodological quality was assessed using the METhodological RadiomICs Score (METRICS). RESULTS: Twelve studies were reviewed, and seven were included in the meta-analysis, most showing excellent methodological quality. Training sets revealed a pooled AUC of 87 % (95 % CI: 78 %-90 %), and internal validation sets showed an AUC of 85 % (95 % CI: 76 %-89 %), with no significant difference (p = 0.39). Sensitivity and specificity for training sets were 78.7 % and 81.8 %, respectively, with validation sets at 81.2 % and 76.2 %. DL models in training sets showed better diagnostic accuracy than radiomics (p = 0.054), significant after removing outliers (p < 0.01). Incorporating clinical data improved sensitivity in validation sets (p = 0.029). No significant difference was found between models based on CE or non-CE imaging (p = 0.281) or arterial or venous phase imaging (p = 0.927). CONCLUSION: Integrating CT-based radiomics and DL improves LNM detection in esophageal cancer. Including clinical data could enhance model performance. Future research should focus on multicenter studies with independent validations to confirm these findings and promote broader clinical adoption.

Comparative meta-analysis of endovascular strategies for intracranial dissecting aneurysms: Flow diverters versus stents with or without coiling.

BACKGROUND: Intracranial dissecting aneurysms present a challenging subset linked to considerable morbidity and mortality, necessitating effective therapeutic strategies to prevent complications. Traditional treatments face technical limitations, while emerging endovascular modalities like stent-assisted coiling, multiple stenting, and flow-diverting devices (FDDs) offer promise in reducing periprocedural risks and enhancing patient outcomes. The aim of this study is to compare the safety and efficacy outcomes of endovascular treatment for intracranial dissecting aneurysms using FDDs versus stents (with or without coiling). METHODS: A systematic review and meta-analysis were conducted following established guidelines. The search included PubMed, Scopus, Web of Science, and Embase databases up to July 30, 2023. Eligible studies reporting outcomes of interest in both FDD and stent-treated groups were included, and the data was extracted and analyzed using STATA software. RESULTS: Six studies were analyzed, involving 131 patients in the FDD group and 199 patients in the stent group. The pooled rates for favorable functional outcomes (86.8% vs. 86%), mortality (3.9% vs. 6%), adequate occlusion (79.7% vs. 86.3%), aneurysm recurrence (1.3% vs. 13.3%), in-stent stenosis/thrombosis (7% vs. 6.9%), ischemic events/infarctions (6.7% vs. 7.8%), retreatment (7% vs. 8.6%), and technical success (100% vs. 98.7%) were comparable in individuals treated with FDDs and stents (p > 0.05 in all cases). Additionally, complete occlusion rates were not significantly different between FDD (62.7%) and stent-treated patients (75.2%) (p = 0.06). However, after excluding one study in a leave-one-out analysis of the random effects meta-analysis, a significant difference in the pooled rates of this outcome was observed between the FDD (59.2%) and stent (75.2%) groups (p = 0.034). CONCLUSION: FDDs present a promising approach for the treatment of intracranial dissecting aneurysms, yielding outcomes that are roughly comparable to stent-based methods. However, the absence of randomized trials and data limitations highlight the need for further research to enhance treatment strategies.

Current diversity in radiology: A comparative study.

PURPOSE: To compare the demographic characteristics of active physicians, trainees, medical school clinical sciences faculty, and department chairs in radiology with those in other medical specialties. METHODS: An analysis was conducted using publicly available deidentified aggregate data from the Association of American Medical Colleges (AAMC). Our data collection included information from the 2022 AAMC Physician Specialty Data Report, the 2022 AAMC Report on Residents, and the 2022 AAMC Faculty Roster. We examined factors such as graduation country, gender, and self-identified race/ethnicity. MedCalc software was used for the analyses. RESULTS: Compared to other specialties, active radiologists exhibited a significantly lower percentage of females, International Medical Graduates (IMGs), individuals of American Indian/Alaska Native (AIAN) descent, Black/African-American individuals, and individuals of Hispanic/Latino/Spanish origin. Conversely, the proportion of White active radiologists was higher. Among radiology trainees, there was a notably lower percentages of females, IMGs, individuals of Black/African-American descent, and individuals of Hispanic/Latino/Spanish origin, while the percentage of Asians was significantly higher. Furthermore, medical school radiology faculty showed a significant lower proportion of females, Black/African-American individuals, Hispanic/Latino/Spanish individuals, and individuals categorized under the white race/ethnicity, with Asians having a higher representation. As radiology department chairs, Asians were noted at significantly lower percentages compared to their proportions among medical school radiology faculty, while Black/African-American individuals were observed at significantly higher percentages in the same comparison. CONCLUSION: This study revealed a notable underrepresentation of females, individuals of Black/African-American descent, and those of Hispanic/Latino/Spanish origin among active radiologists, radiology trainees, and medical school radiology faculty when compared to their counterparts in other medical specialties. Given these findings, further investigation into the underlying causes of these disparities is warranted.

The Relation of Sleep Characteristics and Cognitive Impairment in Community-Dwelling Middle-Aged and Older Adults: Ardakan Cohort Study on Aging (ACSA).

Introduction: The rise in the elderly population has brought attention to mild cognitive impairment (MCI). Sleep disorders also affect many older adults, indicating an important area of research for disturbed sleep and faster brain aging. This population-based study aimed to investigate the association of several sleep indicators with cognitive performance. Methods: This cross-sectional study focused on adults over 50 in the Ardakan Cohort Study on Aging (ACSA). MCI was evaluated using the Mini-Mental State Examination (MMSE) and the Abbreviated Mental Test score (AMTS) in literate and illiterate individuals. Sleep characteristics were collected using the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, and Berlin questionnaire. The logistic regression models were used to analyze the data. Results: Overall, 3,380 literate and 1,558 illiterate individuals were included. In both groups, participants with MCI had a significantly higher PSQI global score (p < 0.05). Also, among the literate individuals, a significantly higher risk of having sleep-disordered breathing and poor sleep quality was observed in participants with MCI (p < 0.05). In illiterate individuals, higher sleep latency than 15 min increased odds of MCI (p < 0.05). However, after adjusting for all variables, only literate individuals with a sleep duration of more than 8 h had 66 percent increased odds of having MCI (p = 0.033). Conclusion: Sleep duration might be associated with cognitive function in the older Iranian population. Our findings underscore the importance of considering sleep patterns in relation to cognitive health.

Machine learning approaches in the prediction of positive axillary lymph nodes post neoadjuvant chemotherapy using MRI, CT, or ultrasound: A systematic review.

Background and objective: Neoadjuvant chemotherapy is a standard treatment approach for locally advanced breast cancer. Conventional imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound, have been used for axillary lymph node evaluation which is crucial for treatment planning and prognostication. This systematic review aims to comprehensively examine the current research on applying machine learning algorithms for predicting positive axillary lymph nodes following neoadjuvant chemotherapy utilizing imaging modalities, including MRI, CT, and ultrasound. Methods: A systematic search was conducted across databases, including PubMed, Scopus, and Web of Science, to identify relevant studies published up to December 2023. Articles employing machine learning algorithms to predict positive axillary lymph nodes using MRI, CT, or ultrasound data after neoadjuvant chemotherapy were included. The review follows the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, encompassing data extraction and quality assessment. Results: Seven studies were included, comprising 1502 patients. Four studies used MRI, two used CT, and one applied ultrasound. Two studies developed deep-learning models, while five used classic machine-learning models mainly based on multiple regression. Across the studies, the models showed high predictive accuracy, with the best-performing models combining radiomics and clinical data. Conclusion: This systematic review demonstrated the potential of utilizing advanced data analysis techniques, such as deep learning radiomics, in improving the prediction of positive axillary lymph nodes in breast cancer patients following neoadjuvant chemotherapy.

Quantitative analysis of lung lesions using unenhanced chest computed tomography images.

INTRODUCTION: Chest radiograph and computed tomography (CT) scans can accidentally reveal pulmonary nodules. Malignant and benign pulmonary nodules can be difficult to distinguish without specific imaging features, such as calcification, necrosis, and contrast enhancement. However, these lesions may exhibit different image texture characteristics which cannot be assessed visually. Thus, a computer-assisted quantitative method like histogram analysis (HA) of Hounsfield unit (HU) values can improve diagnostic accuracy, reducing the need for invasive biopsy. METHODS: In this exploratory control study, nonenhanced chest CT images of 20 patients with benign (10) and cancerous (10) lesion were selected retrospectively. The appearances of benign and malignant lesions were very similar in chest CT images, and only pathology report was used to discriminate them. Free hand region of interest (ROI) was inserted inside the lesion for all slices of each lesion. Mean, minimum, maximum, and standard deviations of HU values were recorded and used to make HA. RESULTS: HA showed that the most malignant lesions have a mean HU value between 30 and 50, a maximum HU less than 150, and a minimum HU between -30 and 20. Lesions outside these ranges were mostly benign. CONCLUSION: Quantitative CT analysis may differentiate malignant from benign lesions without specific malignancy patterns on unenhanced chest CT image.

Diagnostic performance of different imaging modalities for splenic malignancies: A comparative meta-analysis.

Background and objectives: The spleen hosts both benign and malignant lesions. Despite multiple imaging modalities, the distinction between these lesions poses a diagnostic challenge, marked by varying diagnostic accuracy levels across methods. In this study, we aimed to evaluate and compare the diagnostic performance of various imaging techniques for detecting malignant splenic lesions. Methods: Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Sciences databases for studies evaluating imaging techniques in detecting malignant splenic lesions. Data extraction included diagnostic accuracy metrics, and methodological quality was assessed using QUADAS-2. Diagnostic Test Accuracy meta-analyses were conducted using R (version: 4.2.1). Subgroup analyses and meta-regression were performed to compare different modalities and clinical settings. Results: Our study included 28 studies (pooled sample size: 2358), primarily using retrospective designs with histopathology as the reference standard. PET scan demonstrated the highest diagnostic accuracy (AUC: 92 %), demonstrating a sensitivity of 93 % (95 % CI: 80.4 % - 97.7 %) and a specificity of 82.8 % (95 % CI: 71.1 % - 90.4 %). Contrast-enhanced ultrasound (CEUS), Contrast-enhanced CT scan, and contrast-enhanced MRI also showed impressive performance with AUCs of 91.4 %, 90.9 %, and 85.3 %, respectively. Differences among these modalities were not statistically significant, but they outperformed non-contrast-enhanced methods. PET and CEUS exhibited higher specificity for lymphoma cases compared to studies including other malignancies. Conclusion and clinical implications: Overall, PET emerges as the best modality for splenic malignancies, and CEUS and CE-MRI show promise as potential alternatives, notably due to their reduced radiation exposure. Further research is essential for precise malignancy differentiation.

Ultrasound and magnetic resonance imaging features of fetal urogenital anomalies: A pictorial essay.

This pictorial essay focuses on ultrasound (US) and magnetic resonance imaging (MRI) features of fetal urogenital anomalies. Fetal urogenital malformations account for 30%-50% of all anomalies discovered during pregnancy or at birth. They are usually detected by fetal ultrasound exams. However, when ultrasound data on their characteristics is insufficient, MRI is the best option for detecting other associated anomalies. The prognosis highly depends on their type and whether they are associated with other fetal abnormalities.

Diagnostic utility of ultrasound in pediatric nasal bone fractures: a systematic review and meta-analysis.

Ultrasonography, a radiation-free and cost-effective modality, stands out as a promising tool for evaluating nasal bone fractures. Despite limited literature on its pediatric application, there is an increasing recognition of its potential to enhance diagnostic precision. To evaluate the diagnostic efficacy of ultrasound in detecting pediatric nasal bone fractures. Employing established guidelines, a systematic review and meta-analysis were conducted through a comprehensive literature search in PubMed, Scopus, Web of Science, and Embase databases until December 5, 2023. Inclusion criteria encompassed studies reporting diagnostic accuracy measures of ultrasound in pediatric patients with nasal bone fractures. Data extraction and analysis were undertaken for the selected studies. Involving four studies with 277 patients, ultrasound demonstrated a pooled sensitivity of 66.1% (95% CI: 35.1-87.5%) and specificity of 86.8% (95% CI: 80.1-91.4%) in diagnosing pediatric nasal fractures. The area under the receiver operating characteristic curve (AUC) was 0.88 (95% CI: 0.72-0.93). After excluding an outlier study, sensitivity and specificity increased to 78.0% (95% CI: 65.6-86.9%) and 87.8 (95% CI: 78.1-93.6%), respectively, with an AUC of 0.79 (95% CI: 0.75-0.94). Pooled positive and negative likelihood ratios were 5.11 (95% CI: 2.12-9.15) and 0.40 (95% CI: 0.14-0.77) before exclusion and 6.75 (95% CI: 3.47-12.30) and 0.26 (95% CI: 0.15-0.40) after exclusion of an outlier study, respectively. This study highlighted ultrasonography's utility in diagnosing pediatric nasal bone fractures with high accuracy and specificity. However, caution is advised in relying solely on ultrasound due to suboptimal overall diagnostic performance, evident in likelihood ratios.

A meta-analysis on the diagnostic utility of ultrasound in pediatric distal forearm fractures.

Pediatric distal forearm fractures, comprising 30% of musculoskeletal injuries in children, are conventionally diagnosed using radiography. Ultrasound has emerged as a safer diagnostic tool, eliminating ionizing radiation, enabling bedside examinations with real-time imaging, and proving effective in non-hospital settings. The objective of this study is to evaluate the diagnostic efficacy of ultrasound for detecting distal forearm fractures in the pediatric population. A systematic review and meta-analysis were conducted through a comprehensive literature search in PubMed, Scopus, Web of Science, and Embase databases until October 1, 2023, following established guidelines. Eligible studies, reporting diagnostic accuracy measures of ultrasound in pediatric patients with distal forearm fractures, were included. Relevant data elements were extracted, and data analysis was performed. The analysis included 14 studies with 1377 patients, revealing pooled sensitivity and specificity of 94.5 (95% CI 92.7-95.9) and 93.5 (95% CI 89.6-96.0), respectively. Considering pre-test probabilities of 25%, 50%, and 75% for pediatric distal forearm fractures, positive post-test probabilities were 83%, 44%, and 98%, while negative post-test probabilities were 2%, 6%, and 15%, respectively. The bivariate model indicated significantly higher diagnostic accuracy in the subgroup with trained ultrasound performers vs. untrained performers (p = 0.03). Furthermore, diagnostic accuracy was significantly higher in the subgroup examining radius fractures vs. ulna fractures (p < 0.001), while no significant differences were observed between 4-view and 6-view ultrasound subgroups or between radiologist ultrasound interpreters and non-radiologist interpreters. This study highlighted ultrasound's reliability in detecting pediatric distal forearm fractures, emphasizing the crucial role of expertise in precisely confirming fractures through ultrasound examinations.

Net water uptake as a predictive neuroimaging marker for acute ischemic stroke outcomes: a meta-analysis.

OBJECTIVE: To assess the role of net water uptake (NWU) in predicting outcomes in acute ischemic stroke (AIS) patients. METHODS: A systematic review and meta-analysis were performed, adhering to established guidelines. The search covered PubMed, Scopus, Web of Science, and Embase databases until July 1, 2023. Eligible studies reporting quantitative ischemic lesion NWU in admission CT scans of AIS patients, stratified based on outcomes, were included. Data analysis was performed using R software version 4.2.1. RESULTS: Incorporating 17 original studies with 2217 AIS patients, NWU was significantly higher in patients with poor outcomes compared to those with good outcomes (difference of medians: 5.06, 95% CI: 3.00-7.13, p < 0.001). Despite excluding one outlier study, considerable heterogeneity persisted among the included studies (I2 = 90.8%). The meta-regression and subgroup meta-analyses demonstrated significantly higher NWU in patients with poor functional outcome, as assessed by modified Rankin Scale (difference of medians: 3.83, 95% CI: 1.98-5.68, p < 0.001, I2 = 72.9%), malignant edema/infarct (difference of medians: 8.30, 95% CI: 4.01-12.58, p < 0.001, I2 = 95.6%), and intracranial hemorrhage (difference of medians: 5.43, 95% CI: 0.44-10.43, p = 0.03, I2 = 91.1%). CONCLUSION: NWU on admission CT scans shows promise as a predictive marker for outcomes in AIS patients. Prospective, multicenter trials with standardized, automated NWU measurement are crucial for robustly predicting diverse clinical outcomes. CLINICAL RELEVANCE STATEMENT: The potential of net water uptake as a biomarker for predicting outcomes in acute ischemic stroke patients holds significant promise. Further validation through additional research could lead to its integration into clinical practice, potentially improving the accuracy of clinical decision-making and allowing for the development of more precise patient care strategies. KEY POINTS: • Net water uptake, a CT-based biomarker, quantifies early brain edema after acute ischemic stroke. • Net water uptake is significantly higher in poor outcome acute ischemic stroke patients. • Net water uptake on CT scans holds promise in predicting diverse acute ischemic stroke outcomes.

Mechanical Thrombectomy for In-Hospital Onset Stroke: A Comparative Systematic Review and Meta-Analysis.

BACKGROUND AND PURPOSE: In-hospital onset stroke (IHOS) accounts for a significant proportion of large vessel occlusion acute ischemic strokes, leading to worse outcomes due to delays in evaluation and treatment. Limited data is available on the effectiveness of mechanical thrombectomy in IHOS patients. This study aims to assess the safety and efficacy of mechanical thrombectomy for patients with IHOS and compare the outcomes with those of community-onset strokes (COS). METHODS: We conducted a systematic review and meta-analysis following established guidelines, by searching PubMed, Scopus, Web of Science, and Embase databases up to April 11, 2023. Eligible studies reporting outcomes of interest were included, and relevant data was extracted and analyzed using Stata software version 17.0. RESULTS: In a meta-analysis of nine studies, comprising 540 cases of IHOS and 5,744 cases of COS, IHOS cases had a significantly lower rate of good functional outcomes on follow-up (35.46% vs. 40.74%, P<0.01) and a higher follow-up mortality rate (26.29% vs. 18.08%, P<0.01) compared to COS patients. Both groups had comparable successful recanalization rates (IHOS: 79.32% vs. COS: 81.44%, P=0.11), incidence rates of periprocedural complications (IHOS: 15.10%, COS: 12.96%, P=0.78), and symptomatic intracranial hemorrhage (IHOS: 6.24%, COS: 6.88%, P=0.67). It is worth noting that much of the observed effect size for mortality and good functional outcomes on follow-up was derived from only one and two studies, respectively. CONCLUSION: While the current literature suggests that mechanical thrombectomy is a safe and effective treatment for IHOS, further research is necessary to comprehensively evaluate its impact, particularly during follow-up.

Flow diverters in the treatment of intracranial dissecting aneurysms: a systematic review and meta-analysis of safety and efficacy.

BACKGROUND: Intracranial dissecting aneurysms present clinical challenges, demanding immediate intervention due to their high bleeding risk. While traditional treatments have limitations, the potential of flow diverters shows promise but remains a subject of ongoing debate for optimal management. The aim of this study was assess the safety and efficacy of flow diverters in the treatment of intracranial dissecting aneurysms. METHODS: A systematic review and meta-analysis was performed following established guidelines. The search encompassed PubMed, Scopus, Web of Science, and Embase databases up to July 20, 2023. Eligible studies reporting outcomes of interest were included, and relevant data were extracted and analyzed using R software. RESULTS: The analysis, based on data pooled from 20 included studies involving 329 patients, revealed a favorable functional outcome rate of 89.7% at the last follow-up. The mortality rate during the follow-up period was 2.4%, decreasing to 0.9% when excluding the outlier study. In the final angiographic follow-up, a complete occlusion rate of 71.7% and an adequate occlusion rate of 88.3% were observed. Notably, studies with longer angiographic follow-up times exhibited lower rates of complete (P=0.02) and adequate (P<0.01) occlusion. A minimal aneurysm recurrence/rebleeding rate of 0.1% was noted, while in-stent stenosis/thrombosis occurred at a rate of 1.14%. Additionally, ischemic events/infarctions were seen in 3.3% of cases. The need for retreatment was minimal, with a rate of 0.9%, and the technical success rate was impressively high at 99.1%. CONCLUSION: This study highlights the safety and efficacy of flow diverters in treating intracranial dissecting aneurysms. Further research, encompassing larger multicenter studies with extended follow-up periods, is crucial for comprehending occlusion dynamics, refining treatment strategies, improving long-term outcomes, and addressing methodological limitations.

A systematic review and meta-analysis on the diagnostic utility of ultrasound for clavicle fractures.

BACKGROUND: Ultrasound's real-time, high-resolution imaging, and accessibility at the point of care make it a valuable tool for diagnosing clavicle fractures, with growing evidence supporting its diagnostic accuracy compared to other imaging modalities. OBJECTIVE: To assess the diagnostic utility of ultrasound in detecting clavicle fractures. METHODS: A systematic review and meta-analysis were conducted by performing a comprehensive literature search in PubMed, Scopus, Web of Science, and Embase databases up to March 10, 2023, following established guidelines. Eligible studies that reported outcomes of interest were included, relevant data elements were extracted, and data analysis was performed using STATA software version 17.0. RESULTS: Meta-analysis of seven included studies showed high-pooled sensitivity (0.94) and specificity (0.98) values for ultrasonography in diagnosing clavicle fractures, with low to moderate heterogeneity for sensitivity and high heterogeneity for specificity. Meta-regression and subgroup analyses revealed that pediatric studies had higher sensitivity but significantly lower specificity (P=0.01) compared to mixed or adult studies. Additional subgroup analysis in the pediatric group indicated decreased heterogeneity for specificity. Fagan plot analysis demonstrated favorable post-test probabilities for both positive and negative results across varying pre-test probabilities. Additionally, the likelihood ratio scatter matrix showed moderate to high test performance for both exclusion and confirmation purposes. CONCLUSION: The current literature supports ultrasound as a reliable imaging modality for detecting clavicle fractures. It offers accurate diagnosis without exposing patients, especially children, to radiation.

Radiology as a Specialty in the Era of Artificial Intelligence: A Systematic Review and Meta-analysis on Medical Students, Radiology Trainees, and Radiologists.

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) is changing radiology by automating tasks and assisting in abnormality detection and understanding perceptions of medical students, radiology trainees, and radiologists is vital for preparing them for AI integration in radiology. MATERIALS AND METHODS: A systematic review and meta-analysis were conducted following established guidelines. PubMed, Scopus, and Web of Science were searched up to March 5, 2023. Eligible studies reporting outcomes of interest were included, and relevant data were extracted and analyzed using STATA software version 17.0. RESULTS: A meta-analysis of 21 studies revealed that 22.36% of individuals were less likely to choose radiology as a career due to concerns about advances in AI. Medical students showed higher rates of concern (31.94%) compared to radiology trainees and radiologists (9.16%) (P < .01). Radiology trainees and radiologists also demonstrated higher basic AI knowledge (71.84% vs 35.38%). Medical students had higher rates of belief that AI poses a threat to the radiology job market (42.66% vs 6.25%, P < .02). The pooled rate of respondents who believed that "AI will revolutionize radiology in the future" was 79.48%, with no significant differences based on participants' positions. The pooled rate of responders who believed in the integration of AI in medical curricula was 81.75% among radiology trainees and radiologists and 70.23% among medical students. CONCLUSION: The study revealed growing concerns regarding the impact of AI in radiology, particularly among medical students, which can be addressed by revamping education, providing direct AI experience, addressing limitations, and emphasizing medico-legal issues to prepare for AI integration in radiology.

A Meta-analysis of Burnout in Radiology Trainees and Radiologists: Insights From the Maslach Burnout Inventory.

RATIONALE AND OBJECTIVES: Burnout, stemming from chronic work stress, is a significant issue in the medical field, especially among radiologists. It leads to compromised patient care and reduced job satisfaction. Addressing burnout in radiology is essential for the well-being of radiologists and, in turn, for improving patient care. This study aimed to assess the prevalence and dimensions of burnout among radiology trainees (RTs) and practicing radiologists (PRs). MATERIALS AND METHODS: A systematic review and meta-analysis were conducted in accordance with established guidelines. The search encompassed PubMed, Scopus, Web of Science, and Embase databases up to June 20, 2023. Eligible studies that assessed the rate of burnout syndrome and/or its subscales, including depersonalization (DP), emotional exhaustion (EE), and personal accomplishment (PA), among RTs and/or PRs using the Maslach Burnout Inventory (MBI), were included. Relevant data were extracted and analyzed using R and STATA. RESULTS: Among the 22 included studies, the pooled rates of positive MBI subscales for RTs and PRs were as follows: 54.7% (95% confidence interval [CI]: 43.8%-65.1%, I2 = 95.2%) for DP, 57.2% (95% CI: 48.7%-65.4%, I2 = 92.9%) for EE, and 38.6% (95% CI: 27%-51.7%, I2 = 95.5%) for low PA. The pooled rate indicating the presence of at least one positive MBI subscale was 82.9% (95% CI: 79.2%-86.1%, I2 = 57.4%). For two or more positive MBI subscales, the pooled rate was 55.5% (95% CI: 49.7%-61.3%, I2 = 60.2%), and for three positive MBI subscales, it was 16.7% (95% CI: 11.7%-23.3%, I2 = 82.7%). CONCLUSION: This study emphasizes a notable prevalence of burnout in the radiology specialty, with 8 of 10 individuals exhibiting positive results in at least one MBI subscale. This highlights the urgent need for interventions and support systems to protect the well-being of both trainees and practitioners and uphold the quality of patient care.

Diagnostic utility of multidetector CT scan in penetrating diaphragmatic injuries: A systematic review and meta-analysis.

Penetrating diaphragmatic injuries pose diagnostic and management challenges. Computed tomography (CT) scans are valuable for stable patients, but concern exists for missed injuries and complications in nonoperatively managed cases. The objective of this study was to explore the diagnostic utility of multidetector CT scan (MDCT) in identifying diaphragmatic injuries resulting from penetrating trauma. A systematic review and meta-analysis were conducted, following established guidelines, by searching PubMed, Scopus, Web of Science, and Embase databases up to July 6, 2023. Eligible studies reporting MDCT's diagnostic accuracy in detecting penetrating diaphragmatic injuries were included. Relevant data elements were extracted and analyzed using STATA software. The study included 9 articles comprising 294 patients with confirmed penetrating diaphragmatic injuries through surgical procedures. MDCT's diagnostic performance revealed a pooled sensitivity of 74% (95% CI: 56%-87%) and a pooled specificity of 92% (95% CI: 79%-97%) (Fig. two), with significant heterogeneity in both sensitivity and specificity across the studies. The Fagan plot demonstrated that higher pre-test probabilities correlated with higher positive post-test probabilities for penetrating diaphragmatic injury diagnosis using MDCT, but even with negative results, there remained a small chance of having the injury, especially in cases with higher pre-test probabilities. This study highlights MDCT's effectiveness in detecting diaphragmatic injury from penetrating trauma, with moderate to high diagnostic accuracy. However, larger sample sizes, multicenter collaborations, and prospective designs are needed to address observed heterogeneity, enhancing understanding and consistency in MDCT's diagnostic capabilities in this context.