Curriculum for Fundamentals of Ultrasound in Clinical Practice

doi:10.1002/jum.15090

Cited by 6 publications

(2 citation statements)

References 70 publications

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“…Point of care ultrasound (POCUS) has become an integral part of Emergency Medicine clinical care 1 , 2 , 3 , 4 , 5 . In addition, national POCUS standards have been developed for Emergency Medicine residency curricula, clinical credentialing and imaging criteria 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . There has been significant discussion of the potential diagnostic and procedural benefits of incorporating POCUS in various areas of pediatrics including: General Pediatrics, Hospital Medicine, Intensive Care, Neonatology, Emergency Medicine 14 , 15 , 16 .…”

Section: Introductionmentioning

confidence: 99%

A Longitudinal Evaluation of a Multimodal POCUS Curriculum in Pediatric Residents

Sabnani¹,

Willard²,

Vega³

et al. 2023

pocus

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Introduction: Pediatric residency programs often do not include a point of care ultrasound (POCUS) curriculum. We analyzed a novel POCUS curriculum for pediatric residents that incorporated an online question bank (QB), in addition to a traditional teaching model of didactic instruction and hands-on learning experience. Methods: Four high-yield POCUS topics were chosen: Focused Assessment by Sonography for Trauma (FAST), soft tissue, lung, and cardiac. Residents completed online multiple-choice quizzes before and after each of four in-person learning sessions, taught by ultrasound faculty and fellows. At the end of the academic year participants completed a knowledge retention quiz. Confidence surveys were administered to participants throughout the course of the study. Differences in means were compared by Student’s t-test. Results: Learners demonstrated post-intervention score improvement for each of the four modules. Retention testing demonstrated retained improvement for the soft tissue and cardiac modules, but not for the FAST module. Self-reported confidence increased across all four topics. Conclusion: A multimodal POCUS curriculum utilizing a combination of an online QB and in-person teaching demonstrated lasting knowledge for pediatric trainees.

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Section: Introductionmentioning

confidence: 99%

A Longitudinal Evaluation of a Multimodal POCUS Curriculum in Pediatric Residents

Sabnani¹,

Willard²,

Vega³

et al. 2023

pocus

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“…Ultrasound (US) is the most important imaging method for the assessment of thyroid diseases, allowing for detailed morphological estimations as well as organ and lesion size measurements [3,4]. Its widespread availability, almost no side effects, high level of acceptance by both healthcare professionals and patients, excellent resolution and contrast in soft tissue, real-time applicability, portability, possibility of de facto unlimited follow-up scans, and very low procedural costs are well-known advantages of US examinations in general [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Thyroid Volume Determination by Stitched 3D-Ultrasound Data Sets in Patients with Structural Thyroid Disease

et al. 2023

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Ultrasound (US) is the most important imaging method for the assessment of structural disorders of the thyroid. A precise volume determination is relevant for therapy planning and outcome monitoring. However, the accuracy of 2D-US is limited, especially in cases of organ enlargements and deformations. Software-based “stitching” of separately acquired 3D-US data revealed precise volume determination in thyroid phantoms. The purpose of this study is to investigate the feasibility and accuracy of 3D-US stitching in patients with structural thyroid disease. A total of 31 patients from the clinical routine were involved, receiving conventional 2D-US (conUS), sensor-navigated 3D-US (3DsnUS), mechanically-swept 3D-US (3DmsUS), and I-124-PET/CT as reference standard. Regarding 3DsnUS and 3DmsUS, separately acquired 3D-US images (per thyroid lobe) were merged to one comprehensive data set. Subsequently, anatomical correctness of the stitching process was analysed via secondary image fusion with the I-124-PET images. Volumetric determinations were conducted by the ellipsoid model (EM) on conUS and CT, and manually drawn segmental contouring (MC) on 3DsnUS, 3DmsUS, CT, and I-124-PET/CT. Mean volume of the thyroid glands was 44.1 ± 25.8 mL (I-124-PET-MC = reference). Highly significant correlations (all p < 0.0001) were observed for conUS-EM (r = 0.892), 3DsnUS-MC (r = 0.988), 3DmsUS-MC (r = 0.978), CT-EM (0.956), and CT-MC (0.986), respectively. The mean volume differences (standard deviations, limits of agreement) in comparison with the reference were −10.50 mL (±11.56 mL, −33.62 to 12.24), −3.74 mL (±3.74 mL, −11.39 to 3.78), and 0.62 mL (±4.79 mL, −8.78 to 10.01) for conUS-EM, 3DsnUS-MC, and 3DmsUS-MC, respectively. Stitched 3D-US data sets of the thyroid enable accurate volumetric determination even in enlarged and deformed organs. The main limitation of high time expenditure may be overcome by artificial intelligence approaches.

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An investigation study on the interpretation of ultrasonic medical reports using OpenAI's GPT‐3.5‐turbo model

Wang,

Huang

et al. 2023

J of Clinical Ultrasound

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ObjectivesUltrasound medical reports are an important means of diagnosing diseases and assessing treatment effectiveness. However, their professional terms and complex sentences often make it difficult for ordinary people to understand. Therefore, this study explores the clinical value of using artificial intelligence systems based on ChatGPT to interpret ultrasound medical reports.MethodsIn this study, a combination of online and offline questionnaires were used to survey both physicians and non‐medical individuals. The questionnaires evaluated ChatGPT's interpretation of ultrasound reports from both professional and comprehensibility perspectives, and the results were analyzed using Excel spreadsheets. Additionally, a portion of the research content was evaluated using the Likert Scale 5‐point method in the questionnaire.ResultsAccording to survey results, 67.4% of surveyed doctors believe that using ChatGPT for interpreting ultrasound medical reports can help improve work efficiency. At the same time, 69.72% of non‐medical professionals believe it is necessary to enhance their understanding of medical ultrasound reports through ChatGPT interpretation, and 62.58% support the application of ChatGPT to ultrasound medical reports. The non‐medical group's understanding of ultrasound medical reports significantly improved (p < 0.01) after implementing ChatGPT, However, 67.49% of the general public are concerned about ChatGPT's imperfect functionality, which may cause misleading information. This reflects that the public's trust in new technology is not high enough, and they are also worried about possible privacy leaks and security issues with ChatGPT technology.ConclusionsThe higher acceptance and support of non‐medical individuals for the interpretation of medical reports by ChatGPT might be due to the system's natural language processing abilities that allow them to better understand and evaluate report contents. However, the expertise and experience of physicians are still irreplaceable. This suggests that the ChatGPT‐based ultrasound medical report interpretation system has certain clinical value and application prospects, but further optimization is necessary to address its shortcomings in data quality and professionalism. This study provides a reference and inspiration for promoting the application and development of ultrasound technology and artificial intelligence systems in the medical field.

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Curriculum for Fundamentals of Ultrasound in Clinical Practice

Cited by 6 publications

References 70 publications

A Longitudinal Evaluation of a Multimodal POCUS Curriculum in Pediatric Residents

A Longitudinal Evaluation of a Multimodal POCUS Curriculum in Pediatric Residents

Optimization of Thyroid Volume Determination by Stitched 3D-Ultrasound Data Sets in Patients with Structural Thyroid Disease

An investigation study on the interpretation of ultrasonic medical reports using OpenAI's GPT‐3.5‐turbo model

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