Sublingual Microcirculation Pattern and Parameter AnalysisNCT04957303
Machine Learning-assisted Analysis of Microcirculation Patterns and Parameters
An observational study of Sublingual Microcirculation Pattern and Parameter Analysis, run by National Taiwan University Hospital at 1 site in Taiwan.
Trial summary
Machine learning has been widely used in clinical medicine in recent years. It can be used for disease classification, disease severity grading, genetic testing, image analysis, adjuvant treatment recommendations, and predicting patient prognosis. Read more about this study
- Who is it for?
- Ages 20 years and olderHealthy volunteers can take part
- Conditions the study is for
- Sublingual Microcirculation Pattern and Parameter Analysis
- What is being tested?
- sublingual microcirculation video recording
- Type of treatment
- Medical device
- How many people
- 800 participants
- Where
- 1 siteTaiwan
- Study dates
- 3 Aug 2020to Apr 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Healthy volunteers Critically ill patients Surgical patients Patients with dialysis
Who may be able to join
- Microcirculation videos and images from previous clinical trials in the National Taiwan University Hospital with signed informed consent and agreement of further analysis
Who cannot join
- Microcirculation videos and images from previous clinical trials in the National Taiwan University Hospital with signed informed consent but disagreement of further analysis.
Trial locations and contacts
1 site in 1 country.
Taiwan1 site, 1 recruiting
- Recruiting
National Taiwan University Hospital
Taipei, 10002
Yu-Chang Yeh, MD, PhD, tonyyeh@ntuh.gov.tw
About this study
Machine learning has been widely used in clinical medicine in recent years. It can be used for disease classification, disease severity grading, genetic testing, image analysis, adjuvant treatment recommendations, and predicting patient prognosis. Because sublingual microcirculation can be used for guiding shock resuscitation, a real time automated analysis is required for rapid changes of clinical condition. This study aims to use machine learning to analyze the parameters and patterns of sublingual microcirculation.
Read the detailed description
The sublingual microcirculation videos are extracted from the 11 clinical trials conducting in the National Taiwan University Hospital.
In the first stage, the microcirculation videos and the related information are included in a de-identified manner. Each microcirculation video in the database will have a unique code. The video-related data will include the patient's height, weight, blood pressure, heartbeats, health status, major diseases, laboratory examination values, video quality description, automated vascular analysis (AVA) 3 software analysis results including total vessel density (TVD), perfused vessel density (PVD), proportion of perfused vessels (PPV), microvascular flow index (MFI), and heterogeneity index (HI). The length of each micro-cycle video is 4-6 seconds, and there are 25 frames per second. Take a picture as a representative image, each video can correspond to 4 images, and each micro-circulation image will also be marked with its image quality. Machine learning model will be trained for distinguishing the quality of videos and images. Only good-quality videos and images will be used for further analysis.
In the second stage, 80% of the microcirculation videos and images will be used for training and validation to find the best model, and then the remaining 20% of microcirculation videos and images will be used to test the model performance. The first training purpose is to automatically distinguish the size of blood vessels, calculate TVD, and draw a histogram of the number of microvessels of different diameters. The second training purpose is to measure the blood flow velocity in each small vessel and calculate PVD, MFI, and HI values.
- Being tested
- sublingual microcirculation video recording
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
sublingual microcirculation video recordingDevice
The sublingual microcirculation videos were recorded by video microscope
What is being measured
The primary outcome is the main question the study is designed to answer.
Perfused vessel density
Training machine learning models to view the videos of patients' sublingual microcirculation images and calculate the perfused vessel density. The videos of patients' sublingual microcirculation images are obtained and recorded by the video microscopes.
Measured: 6 seconds
Secondary outcomes (1)
Patterns of microcirculation
Training machine learning models to view the videos of patients' microcirculation images and distinguish the patterns of microcirculation images and videos among healthy volunteers and patients with specific diseases or clinical conditions (eg. dialysis, postoperative, or septic shock.) The videos of patients' sublingual microcirculation images are obtained and recorded by the video microscopes.
Measured: 6 seconds
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Jul 2021
- Study start3 Aug 2020
- Primary completionDec 2023 (estimated)
- Study completionApr 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Sublingual Microcirculation Pattern and Parameter AnalysisStudies of the same condition, open and under way.
- More trials run by National Taiwan University HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Taiwan University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04957303
- Sponsor's protocol ID
- 202003094RINA
- Status last verified
- Jul 2022
- First submitted
- 23 Jun 2021
- Last updated
- 13 Jul 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Jul 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning-assisted Analysis of Microcirculation Patterns and Parameters
- ClinicalTrials.gov ID
- NCT04957303
- Acronym / sponsor ID
- 202003094RINA
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- National Taiwan University HospitalUniversity, hospital or other
- Study start
- 3 Aug 2020 (actual)
- Primary completion
- Dec 2023 (estimated)
- Study completion
- Apr 2024 (estimated)
- First posted
- 12 Jul 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Machine learning has been widely used in clinical medicine in recent years. It can be used for disease classification, disease severity grading, genetic testing, image analysis, adjuvant treatment recommendations, and predicting patient prognosis. Because sublingual microcirculation can be used for guiding shock resuscitation, a real time automated analysis is required for rapid changes of clinical condition. This study aims to use machine learning to analyze the parameters and patterns of sublingual microcirculation.
Detailed description
The sublingual microcirculation videos are extracted from the 11 clinical trials conducting in the National Taiwan University Hospital.
In the first stage, the microcirculation videos and the related information are included in a de-identified manner. Each microcirculation video in the database will have a unique code. The video-related data will include the patient's height, weight, blood pressure, heartbeats, health status, major diseases, laboratory examination values, video quality description, automated vascular analysis (AVA) 3 software analysis results including total vessel density (TVD), perfused vessel density (PVD), proportion of perfused vessels (PPV), microvascular flow index (MFI), and heterogeneity index (HI). The length of each micro-cycle video is 4-6 seconds, and there are 25 frames per second. Take a picture as a representative image, each video can correspond to 4 images, and each micro-circulation image will also be marked with its image quality. Machine learning model will be trained for distinguishing the quality of videos and images. Only good-quality videos and images will be used for further analysis.
In the second stage, 80% of the microcirculation videos and images will be used for training and validation to find the best model, and then the remaining 20% of microcirculation videos and images will be used to test the model performance. The first training purpose is to automatically distinguish the size of blood vessels, calculate TVD, and draw a histogram of the number of microvessels of different diameters. The second training purpose is to measure the blood flow velocity in each small vessel and calculate PVD, MFI, and HI values.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Healthy volunteers Critically ill patients Surgical patients Patients with dialysis
Key inclusion criteria (1 listed)
- Microcirculation videos and images from previous clinical trials in the National Taiwan University Hospital with signed informed consent and agreement of further analysis
Key exclusion criteria (1 listed)
- Microcirculation videos and images from previous clinical trials in the National Taiwan University Hospital with signed informed consent but disagreement of further analysis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| sublingual microcirculation video recordingThe sublingual microcirculation videos were recorded by video microscope | Device | – |
Primary outcome
Perfused vessel density
Time frame: 6 seconds
Training machine learning models to view the videos of patients' sublingual microcirculation images and calculate the perfused vessel density. The videos of patients' sublingual microcirculation images are obtained and recorded by the video microscopes.
1 secondary outcome
Patterns of microcirculation
Time frame: 6 seconds
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Jul 2022.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sublingual Microcirculation Pattern and Parameter Analysis, run by National Taiwan University Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 13 Jul 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Yu-Chang Yeh, MD, PhD (+886-9-68661829, tonyyeh@ntuh.gov.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Perfused vessel density (time frame: 6 seconds). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Jul 2022.