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

NCT06034093 | Completed DMC

• 2 other identifiers: 01NVbOxTREC 516-20
• Study Type: interventional
• Target: 254
• Locations: 1 country
• Sites: 1

Brief Summary

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

Conditions

Tetanus

Keywords

Muscle Wasting; Intensive Care Unit; Muscle ultrasound; Artificial Intelligence; Deep Learning

Outcome Measures

Primary Outcomes (1)

• Reproducibility of RFCSA measurements

  In this trial, the users are randomly assigned to scan muscle ultrasound with and without AI-assisted software to measure the size of the Rectus Femoris muscle. The investigators will compare the reliability and agreement metrics of the RF measurement

  during the study procedure

Secondary Outcomes (1)

• Time spent on ultrasound examination

  during the study procedure

Study Arms (2)

Real-time AI-assisted muscle ultrasound

EXPERIMENTAL

RAIMUS software provides automatic segmentation and size measurement for the RFCSA

Device: Real-time AI-assisted muscle ultrasound

Manual muscle ultrasound

NO INTERVENTION

Manual segmentation and size measurement for the RFCSA

Interventions

Real-time AI-assisted muscle ultrasound DEVICE

RAIMUS software provides automatic segmentation and size measurement for the RFCSA

Real-time AI-assisted muscle ultrasound

Eligibility Criteria

• Age: 16 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• 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

You may not qualify if:

• Informed consent not given
• Contraindication to ultrasound scan

Sponsors & Collaborators

• Oxford University Clinical Research Unit, Vietnam: lead
• King's College London: collaborator

Study Sites (1)

Hospital for Tropical Diseases at Ho Chi Minh city

Ho Chi Minh City, 700000, Vietnam

Location

MeSH Terms

Conditions

Tetanus; Muscular Atrophy

Condition Hierarchy (Ancestors)

Clostridium Infections; Gram-Positive Bacterial Infections; Bacterial Infections; Bacterial Infections and Mycoses; Infections; Neuromuscular Manifestations; Neurologic Manifestations; Nervous System Diseases; Atrophy; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms; Signs and Symptoms

Study Officials

• Sophie Yacoub, PhD

  Oxford University Clinical Research Unit

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: 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.

Study Record Dates

• First Submitted: August 30, 2023
• First Posted: September 13, 2023
• Study Start: June 1, 2020
• Primary Completion: August 10, 2023
• Study Completion: October 31, 2023
• Last Updated: March 20, 2024

Record last verified: 2024-03

Data Sharing

• IPD Sharing: Will not share

Locations

VN (1)