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Expert feedback on trainees' preliminary reports is crucial for radiologic training, but real-time feedback can be challenging due to non-contemporaneous, remote reading and increasing imaging volumes. Trainee report revisions contain valuable educational feedback, but synthesizing data from raw revisions is challenging. Generative AI models can potentially analyze these revisions and provide structured, actionable feedback. This study used the OpenAI GPT-4 Turbo API to analyze paired synthesized and open-source analogs of preliminary and finalized reports, identify discrepancies, categorize their severity and type, and suggest review topics. Expert radiologists reviewed the output by grading discrepancies, evaluating the severity and category accuracy, and suggested review topic relevance. The reproducibility of discrepancy detection and maximal discrepancy severity was also examined. The model exhibited high sensitivity, detecting significantly more discrepancies than radiologists (W = 19.0, p < 0.001) with a strong positive correlation (r = 0.778, p < 0.001). Interrater reliability for severity and type were fair (Fleiss' kappa = 0.346 and 0.340, respectively; weighted kappa = 0.622 for severity). The LLM achieved a weighted F1 score of 0.66 for severity and 0.64 for type. Generated teaching points were considered relevant in ~ 85% of cases, and relevance correlated with the maximal discrepancy severity (Spearman ρ = 0.76, p < 0.001). The reproducibility was moderate to good (ICC (2,1) = 0.690) for the number of discrepancies and substantial for maximal discrepancy severity (Fleiss' kappa = 0.718; weighted kappa = 0.94). Generative AI models can effectively identify discrepancies in report revisions and generate relevant educational feedback, offering promise for enhancing radiology training.

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Anaplastic large cell lymphoma (ALCL) is a rare non-Hodgkin T-cell lymphoma characterized by a cluster of differentiation-30 positivity. Subtypes are characterized by positive or negative anaplastic lymphoma kinase (ALK) expression. ALCLs account for about 10% to 15% of all pediatric non-Hodgkin lymphomas and more than 90% of the cases are ALK-positive. We report a rare case of pediatric systemic ALK-negative ALCL with an atypical presentation as a painful breast mass. Despite the general benign features of most pediatric breast masses, it is important to consider malignant systemic diagnoses like the one reported here.

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OBJECTIVE: To assess the feasibility of visualizing lenticulostriate vessels (LV) using a linear high-resolution ultrasound probe and characterize LV morphology to determine whether morphological alterations in LV are present in neonatal hypoxic-ischemic encephalopathy (HIE) as compared to the unaffected infants. METHODS: We characterized LV by their echogenicity, width, length, tortuosity, and numbers of visualized stems/branches in neurosonographic examinations of 80 neonates. Our population included 45 unaffected (non-HIE) and 35 with clinical and/or imaging diagnosis of HIE. Of the neonates with clinical diagnosis of HIE, 16 had positive MRI findings for HIE (HIE+MRI) and 19 had negative MRI findings (HIE-MRI). Annotations were performed twice with shuffled data sets at a 1-month interval and intrarater reliability was assessed. Focused comparison was conducted between non-HIE, HIE+MRI and HIE-MRI neonates whose images were acquired with a high frequency linear transducer. RESULTS: Studies acquired with the two most frequently utilized transducers significantly differed in number of branches (p = 0.002), vessel thickness (p = 0.007) and echogenicity (p = 0.009). Studies acquired with the two transducers also significantly differed in acquisition frequency (p < 0.001), thermal indices (p < 0.001) and use of harmonic imaging (p < 0.001). Groupwise comparison of vessels imaged with the most frequently utilized transducer found significantly fewer branches in HIE + MRI compared to HIE-MRI negative and non-HIE patients (p = 0.005). CONCLUSION: LV can be visualized in the absence of pathology using modern high-resolution neurosonography. Visualization of LV branches varies between HIE + MRI, HIE-MRI neonates and controls. ADVANCES IN KNOWLEDGE: High-resolution neurosonography is a feasible technique to assess LV morphology in healthy neonates and neonates with HIE.

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Tasks which are scheduled at irregular intervals afford greater scheduling flexibility but are also more difficult to remember. Difficulty remembering clinical tasks not only create potential inefficiencies in patient care but were also identified as a source of anxiety among our residents. We implemented RadRemind! an automated system of pager notifications in order to improve patient care and reduce residents' anxiety. RadRemind! utilizes only an external shared APACHE, MySQL, PHP server. A set of CRON jobs activate a PHP script which pulls information from our resident schedule as JSON data. It then identifies the appropriate residents to notify and then sends a cURL request to a web-based paging service to trigger notifications to residents' pagers. Each activation of the script was logged in an SQL database. An anonymous survey assessing multiple aspects of efficacy was sent to residents after 3 months of implementation. Seventeen of 29 residents responded to the survey. Residents reported a mean of 2 successful reminders (defined as responsibilities which had been otherwise forgotten prior to the page notification) in the last month which was found to be statistically significant via one-sample t test (t = 3.3, p < 0.01). Paired t test showed a statistically significant (t = 2.9, p = 0.01) decrease of 2 points in reported anxiety. Repeated measures analysis of variance found a statistically significant variation in reported utility (F(3,16) = 15.9, p < 0.01)) by type of reminder such that reminders for interventional radiology call were found to be more useful than reminders for other tasks. Use of an automated paging system is an effective method of reminding residents of irregularly scheduled responsibilities and is associated with reduced scheduling related anxiety.

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BACKGROUND: Glycogen storage disease type IV (GSD IV; Andersen's disease) is a rare autosomal recessive disease caused by mutation in the GBE1 gene. Presentation of GSD IV varies on a continuum of severity and symptomatology ranging from neonatal death to mild adult-onset disease with variable involvement of hepatic, muscular, neurologic, dermatologic, and cardiac systems. Cardiomyopathy seen in GSD IV is also heterogeneous and its appearance on cardiac magnetic resonance imaging (CMR) is rarely described. CASE SUMMARY: A 29-year-old man without previous medical history was admitted to our facility multiple times over 2 years for focal sensorimotor deficits, gout arthropathy, chronic hyperlactataemia and hyperuricaemia, and severe decompensated non-ischaemic cardiomyopathy complicated by episodes of thromboembolic organ infarction. Echocardiography and CMR showed severe biventricular failure with the presence of intraventricular thrombi with increased right ventricular trabeculation and absent late gadolinium enhancement. He underwent muscle biopsy which showed prominent glycogen in skeletal muscle followed by genetic testing showing a single heterozygous splicing mutation c.993-1G>T found at the junction of intron 7 and exon 8 of the GBE1 gene which had not previously been reported and was predicted to be pathologic. He was referred to a tertiary care centre with glycogen storage disease specialists but expired prior to establishing care at that facility. DISCUSSION: Discovery of GSD IV in our patient was unexpected due to a highly variant clinical presentation. Our case stresses the clinical heterogeneity of GSD IV and the importance of genetic sequencing studies in the evaluation of potential glycogen storage disease.