Artificial Intelligence for Ultrasound Training

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: Stanford University

Disqualifiers: Ultrasound elective, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial explores how artificial intelligence (AI) can help internal medicine interns use ultrasound devices more effectively. The main goal is to determine if AI improves their ability to interpret ultrasound images, which aid in diagnosing and treating patients. Participants will be divided into two groups: one using ultrasound devices with AI support (Ultrasound with Artificial Intelligence Enabled) and the other using devices without it (Ultrasound without Artificial Intelligence Enabled). Ideal participants are internal medicine residents who have not taken an ultrasound elective in their residency program. As an unphased trial, this study provides a unique opportunity for residents to enhance their diagnostic skills with cutting-edge technology.

Will I have to stop taking my current medications?

The trial protocol does not specify whether you need to stop taking your current medications.

What prior data suggests that this ultrasound training method is safe?

Research has shown that using artificial intelligence (AI) in ultrasound is generally safe and well-received. Many medical settings already use AI-enhanced ultrasound machines, which are considered helpful and safe. These machines clarify ultrasound images, aiding doctors and medical students in making better decisions.

While no specific safety issues have been reported, it's important to note that AI tools only assist in interpreting images and do not directly interact with patients. The FDA has approved some AI-enabled medical devices, indicating that similar technologies have met safety standards for other uses.

In short, based on current knowledge, AI in ultrasound appears safe. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about using artificial intelligence (AI) to enhance ultrasound training because it promises to revolutionize how medical professionals learn this critical skill. Unlike traditional methods that rely heavily on human instructors and can vary in consistency, AI-enabled ultrasound training offers a more standardized and potentially faster learning experience. The AI system can provide immediate feedback, helping trainees improve their skills more efficiently. This technology could lead to more accurate and confident ultrasound users, benefiting patient care across the board.

What evidence suggests that artificial intelligence systems improve ultrasound training?

Research has shown that artificial intelligence (AI) can enhance the learning process for using ultrasound machines. In this trial, participants in the Artificial Intelligence Group will use AI-assisted ultrasound tools, which studies have found can increase users' skill and confidence. For instance, an AI-powered ultrasound system effectively diagnosed conditions like a collapsed lung. AI also enables doctors to perform scans more quickly and accurately, saving time and effort. Furthermore, AI in ultrasound training offers efficient and personalized learning, making it a valuable tool in medical education. Participants in the Non-Artificial Intelligence Group will use standard ultrasound tools without AI assistance. ^{1 3 4 6 7}

Who Is on the Research Team?

Andre D Kumar, MD

Principal Investigator

Stanford University

Are You a Good Fit for This Trial?

This trial is for internal medicine residents who haven't taken an ultrasound elective. They'll be using handheld ultrasound devices on general inpatient wards to see if artificial intelligence (AI) helps them learn better.

Inclusion Criteria

Internal medicine residents rotating on the general inpatient wards service

Exclusion Criteria

Residents who had taken an ultrasound elective offered by our residency program

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Training

Participants are randomized to receive personal access to handheld ultrasound devices with or without artificial intelligence for learning purposes

4 weeks

Weekly training sessions

Assessment

Participants' interpretive ability with ultrasound images/videos is assessed

1 day

1 visit (in-person)

Follow-up

Participants are monitored for device usage rates and performance on quizzes

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Ultrasound with Artificial Intelligence Enabled
• Ultrasound without Artificial Intelligence Enabled

Trial Overview The study tests whether AI improves interns' ability to understand and interpret medical images from ultrasounds. Interns will use either AI-enabled or regular ultrasound devices, and their skills will be compared.

How Is the Trial Designed?

Group I: Artificial Intelligence Group Experimental Treatment 1 Intervention

Group II: Non Artificial Intelligence Group Active Control 1 Intervention

Who Is Running the Clinical Trial?

Stanford University

Lead Sponsor

Trials

2,527

Recruited

17,430,000+

Published Research Related to This Trial

Microfocused Ultrasound with Visualization (MFU-V) has a well-established safety profile, showing only mild and transient side effects like tenderness and redness, with rare adverse events typically linked to improper technique.

When used correctly, MFU-V treatments are safe, with most side effects resolving quickly and without lasting effects, indicating its efficacy in cosmetic dermatology.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Review of the safety profile for microfocused ultrasound with visualization. Hitchcock, TM., Dobke, MK.[2022]

Ultrasound contrast agents are generally safe for clinical use, with serious adverse reactions being rare and most adverse events being minor and self-resolving, such as headache and nausea.

The Contrast Media Safety Committee found that while intolerance to some components can occur, generalized allergy-like reactions are infrequent, emphasizing the overall well-tolerated nature of these agents.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Safety of ultrasound contrast agents. Jakobsen, JA., Oyen, R., Thomsen, HS., et al.[2020]

In a large retrospective analysis involving over 78,000 doses of ultrasound contrast agents (Definity and Optison), only 0.01% of patients experienced severe adverse reactions, indicating a strong safety profile for these agents.

The study found that severe reactions were primarily in outpatients, with no serious events reported in critically ill patients, suggesting that ultrasound contrast agents are safe for use in a variety of clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The safety of deFinity and Optison for ultrasound image enhancement: a retrospective analysis of 78,383 administered contrast doses. Wei, K., Mulvagh, SL., Carson, L., et al.[2022]

In a study involving 23,188 abdominal examinations using the ultrasound contrast agent SonoVue, only 29 adverse events (AEs) were reported, indicating a very low incidence of complications.

The overall rate of serious adverse events was extremely low at 0.0086%, and SonoVue demonstrated a good safety profile, comparable to or better than other contrast agents used in radiology.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The safety of Sonovue in abdominal applications: retrospective analysis of 23188 investigations. Piscaglia, F., Bolondi, L.[2022]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8217795/

Artificial intelligence in medical ultrasonography: driving on ... An AI-enabled ultrasound diagnostic algorithm for pneumothorax has been investigated and proven clinically effective in a small number of patients [17].

2. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov/39555149/

Artificial intelligence-assisted focused cardiac ultrasound ... Conclusions: AI-assisted interactive FoCUS training can be an effective and powerful tool to increase ultrasound skills and confidence levels of ...

3. gehealthcare.co.uk gehealthcare.co.uk/insights/article/ai-for-gps-how-ai-ultrasound-tools-are-changing-the-game-for-general-practitioners

AI ultrasound tools can help general practitioners and other ... AI can help GPs perform scans more quickly and reliably, saving clinical and operational time and effort, and it can even simplify and expedite billing and ...

4. nature.com nature.com/articles/s41746-025-01633-y

Overcoming barriers in the use of artificial intelligence ... Point-of-care ultrasound is a portable, low-cost imaging technology focused on answering specific clinical questions in real time.

5. theultrasoundjournal.springeropen.com theultrasoundjournal.springeropen.com/articles/10.1186/s13089-024-00382-5

Student ultrasound education, current view and controversies ... Integrating advanced technologies such as AI in ultrasound education is a notable strength, offering efficient learning, tailored educational ...

6. fda.gov fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices

Artificial Intelligence-Enabled Medical Devices The AI-Enabled Medical Device List is a resource intended to identify AI-enabled medical devices that are authorized for marketing in the United ...

7. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12053551/

Artificial intelligence guided imaging as a tool to fill gaps in ... This study highlights the potential for AI guided imaging to address important gaps in health care delivery.