Clinical trial NCT06034093: Real-time Artificial Intelligent (AI)-Assisted Muscle Ultrasound for Monitoring Muscle Mass Reduction in ICU Patients
Official title: Real-time AI-assisted Muscle Ultrasound for Monitoring Muscle Mass Reduction in Intensive Care Unit Patients
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Tetanus
Keywords: Muscle Wasting
Intensive Care Unit
Muscle ultrasound
Artificial Intelligence
Deep Learning
Lead sponsor: Oxford University Clinical Research Unit, Vietnam
Sponsor class: OTHER
Collaborators: name: King's College London
First posted: 2023-09-13
Enrollment: 254
Sex: ALL
Minimum age (years): 16
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: 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 purpose: SUPPORTIVE_CARE

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

Detailed description: 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.

Eligibility criteria: 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

Exclusion Criteria:

* Informed consent not given
* Contraindication to ultrasound scan

Primary outcomes:
measure: Reproducibility of RFCSA measurements
timeFrame: during the study procedure
Secondary outcomes:
measure: Time spent on ultrasound examination
timeFrame: during the study procedure
Other outcomes:
Locations:
city: Ho Chi Minh City
country: Vietnam
facility: Hospital for Tropical Diseases at Ho Chi Minh city
Study officials:
affiliation: Oxford University Clinical Research Unit
name: Sophie Yacoub, PhD
role: PRINCIPAL_INVESTIGATOR
References: