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Exploring the Efficacy of Assistive Artificial Intelligence for Ultrasound Guided Regional Anesthesia in Residency Training

Exploring the Efficacy of Assistive Artificial Intelligence for Ultrasound Guided Regional Anesthesia in Residency Training

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06667401
Enrollment
20
Registered
2024-10-31
Start date
2025-03-10
Completion date
2026-01-01
Last updated
2026-03-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Regional Anesthesia

Keywords

Regional anesthesia, Artificial Intelligence, Resident training

Brief summary

The purpose of this study is to investigate the efficacy of a novel artificial intelligence (AI) device designed to assist in Ultrasound guided regional anesthesia (ScanNav Anatomy Peripheral Nerve Block; ScanNav), in the teaching and training of anesthesiology residents in the subspecialty of regional anesthesia.

Detailed description

Ultrasound-guided regional anesthesia (UGRA) relies on the precise acquisition and interpretation of ultrasound images. The necessary skills to attain this is dependent on the knowledge of the underlying anatomy. Notwithstanding, even experienced anesthesiologists can find this challenging, especially in the setting of anatomical variation, obesity and other potential confounders. This study aims to clarify if The ScanNav, a novel artificial intelligence device designed to assist in UGRA, when utilized with trainees, improves their uptake and training. We also aim to see the relationships of how it enhances teaching and training of residents by experienced regional anesthesia providers.

Interventions

DEVICEThe ScanNav, a novel artificial intelligence device designed to assist in Ultrasound guided regional anesthesia

The ScanNav, a novel artificial intelligence device designed to assist in Ultrasound guided regional anesthesia.We also aim to see of how it enhances teaching and training of residents by experienced regional anesthesia providers. We intend to use surveys/questionnaires of both resident and regional anesthesia provider as they utilize the device in real time.

Sponsors

Medical College of Wisconsin
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL

Inclusion criteria

* Inclusion criteria include any anesthesia resident with no prior experience with UGRA.

Exclusion criteria

*

Design outcomes

Primary

MeasureTime frameDescription
Qualtric questionaire of participantsFrom enrollment to the end of device use at 2 weeks.Improved teaching and training of anesthesiology residents in the subspecialty of regional anesthesia will be accessed via a questionnaire filled out by participants after use of the device. The questionnaire will access, the type of regional blocks, feasibility of block and ease of teaching with the artificial intelligence Ultrasound.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 4, 2026