Real-time Artificial Intelligent (AI)-Assisted Muscle Ultrasound for Monitoring Muscle Mass Reduction in ICU Patients

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

254 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-06-01

Study Completion Date

2023-10-31

Brief Summary

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This study aims to investigate the feasibility of using a real-time artificial intelligent (AI)-assisted tool for Rectus Femoris cross sectional area measurement from muscle ultrasound to improve reliability, reduce inter- and intra-observer variability and reduce operator time spent on ultrasound examination

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Detailed Description

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This project proposes to develop computational methods to automatically analyze conventional 2D muscle ultrasound images in real time to assist operators circumvent achieve high quality reproducible views and measurements specifically for Rectus Femoris muscle.

Study design: This is a prospective observational study to test the reliability of AI-assisted muscle ultrasound at the patient's bedside compared to standard RFCSA ultrasound. All measurements will be performed in adult patients with severe tetanus (Ablett Grade 3 or 4) admitted to the Adult ICU at HTD expected to stay at least 5 days. All patients are on mechanical ventilation, muscle relaxation and neuromuscular blockers following the Ministry of Health guidelines.

Study procedures: Three ultrasound examinations will be carried out according to a standard operating procedure where patients are in the supine position with the leg in neutral rotation. Measurements will be taken using 12L-RS linear probe, Venue Go ultrasound machine (General Electric Healthcare, London, UK).

Statistical analysis: Study will compare the intra- and interobserver variability of measurements and examination duration. All statistical analysis was performed with R version 4.0.4.

Conditions

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Tetanus

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

The developed AI assistant, named RAIMUS, was deployed in real-time using the PRETUS tool. The ultrasound machine HDMI output was connected to the laptop via a USB framegrabber. This allowed the user to use an external screen with an AI overlay instead of the screen of the ultrasound machine.

The interface to RAIMUS is as follows. On the right of the screen, there is a widget containing information from the automatic muscle segmentation, including the muscle delineation continuously overlaid onto the ultrasound image and the corresponding cross-sectional area in cm2. The segmentation overlay and related information can be enabled or disabled by the user.

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

NONE

Study Groups

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Real-time AI-assisted muscle ultrasound

RAIMUS software provides automatic segmentation and size measurement for the RFCSA

Group Type EXPERIMENTAL

Real-time AI-assisted muscle ultrasound

Intervention Type DEVICE

RAIMUS software provides automatic segmentation and size measurement for the RFCSA

Manual muscle ultrasound

Manual segmentation and size measurement for the RFCSA

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Real-time AI-assisted muscle ultrasound

RAIMUS software provides automatic segmentation and size measurement for the RFCSA

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Age ≥16 years
* Written informed consent
* Staff and equipment available for ultrasound
* Admitted to Viet Anh Ward ICU with a diagnosis of meningitis or encephalitis or Ablett Grade 3 or 4 tetanus
* Within 72 hours of ICU admission
* Duration of ICU stay expected at least 5 days