Airway ManagementNCT07766382
Artificial Intelligence-Assisted Ultrasound Assessment of Laryngeal Mask Airway Placement
An observational study of Airway Management, run by Duzce University at 1 site in Turkey (Türkiye).
Trial summary
This prospective observational study aims to develop and evaluate artificial intelligence-based models for the assessment of laryngeal mask airway (LMA) placement in adult patients undergoing elective surgery under general anesthesia. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Airway Management
- How many people
- 200 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 10 Aug 2026to 15 May 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult patients (aged 18 years or older) with ASA physical status I-III who are scheduled for elective surgery under general anesthesia and in whom a laryngeal mask airway is planned for airway management will constitute the study population. Patients will be recruited prospectively from the operating rooms of Düzce University Research and Application Hospital.
Who may be able to join
- Adults undergoing elective surgery under general anesthesia in whom LMA use is clinically planned; ASA physical status I-III; ability to provide written informed consent.
Who cannot join
- Emergency surgery; pregnancy; anticipated difficult airway; major upper airway or neck anatomical abnormality or previous major neck surgery; clinically significant aspiration risk or contraindication to LMA use; inability to obtain adequate ultrasound images or fiberoptic assessment.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Turkey (Türkiye)1 site, 1 recruiting
- Recruiting
Duzce University
Düzce, Düzce
gizem demir şenoğlu, 05059313588, gizemsenoglu@duzce.edu.tr
About this study
Official title: Artificial Intelligence-Assisted Ultrasound Confirmation of Laryngeal Mask Airway Placement Using Fiberoptic Assessment as the Reference Standard: A Prospective Diagnostic Accuracy Study
This prospective observational study aims to develop and evaluate artificial intelligence-based models for the assessment of laryngeal mask airway (LMA) placement in adult patients undergoing elective surgery under general anesthesia. Following LMA insertion, standardized airway ultrasound images will be obtained and fiberoptic assessment will be performed as the anatomical reference standard. Fiberoptic findings will be classified as optimal (Brimacombe grades 3-4) or suboptimal (grades 1-2). Clinical and quantitative airway ultrasound variables will also be recorded. The predictive performance of tabular, image-only, and multimodal artificial intelligence models will be evaluated for identifying optimal versus suboptimal LMA placement.
Read the detailed description
Laryngeal mask airways are widely used for supraglottic airway management during general anesthesia. Although adequate ventilation can usually be achieved after insertion, satisfactory clinical ventilation does not necessarily indicate optimal anatomical placement. Fiberoptic assessment provides direct visualization of the relationship between the LMA and laryngeal structures but is invasive and not routinely available in all clinical settings.
Airway ultrasonography provides a non-invasive bedside method for evaluating LMA position. In this prospective observational study, standardized post-placement ultrasound images will be obtained in adult patients undergoing elective surgery with an LMA. Fiberoptic assessment will subsequently be performed and graded according to the Brimacombe fiberoptic scoring system. Grades 3-4 will constitute optimal placement and grades 1-2 suboptimal placement.
Three prediction approaches are planned. Model A will use prespecified clinical and quantitative ultrasound variables, including age, sex, body mass index, Mallampati class, mouth opening, thyromental distance, neck circumference, dentition status, tongue thickness, skin-to-epiglottis distance, and the hyomental distance ratio. Model B will use post-placement ultrasound images alone using a transfer-learning-based image model. Model C will integrate ultrasound image features with the prespecified tabular variables in a multimodal prediction model.
Model performance will be assessed using patient-level resampling procedures. The primary performance measure will be the area under the receiver operating characteristic curve (AUROC), with additional assessment of sensitivity, specificity, positive and negative predictive values, F1 score, precision-recall performance, and calibration. Images obtained from the same participant will remain within the same data partition to prevent information leakage
- Conditions
- Airway Management
- Keywords
- Laryngeal Mask Airway, Supraglottic Airway, Airway Ultrasonography, Artificial Intelligence, Machine Learning
What is being measured
The primary outcome is the main question the study is designed to answer.
Discrimination of Optimal Versus Suboptimal LMA Placement by the Multimodal Artificial Intelligence Model
The ability of the multimodal artificial intelligence model combining post-placement ultrasound images with prespecified clinical and quantitative ultrasound variables to discriminate optimal from suboptimal LMA placement, using fiberoptic assessment as the reference standard. Optimal placement will be defined as Brimacombe grades 3-4 and suboptimal placement as grades 1-2. Model discrimination will primarily be quantified using the area under the receiver operating characteristic curve (AUROC).
Measured: During the intraoperative assessment following LMA insertion, approximately within 15 minutes after placement
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Aug 2026
- Study start10 Aug 2026
- Primary completion1 May 2027 (estimated)
- Study completion15 May 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Airway ManagementStudies of the same condition, open and under way.
- 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
- Prospective
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Duzce University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Gizem Demir Şenoğlu, Duzce University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07766382
- Sponsor's protocol ID
- 2026/177
- Status last verified
- Aug 2026
- First submitted
- 11 Aug 2026
- Last updated
- 14 Aug 2026
- 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 14 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-Assisted Ultrasound Confirmation of Laryngeal Mask Airway Placement Using Fiberoptic Assessment as the Reference Standard: A Prospective Diagnostic Accuracy Study
- ClinicalTrials.gov ID
- NCT07766382
- Acronym / sponsor ID
- 2026/177
- Conditions
- Airway Management
- Keywords
- Laryngeal Mask Airway, Supraglottic Airway, Airway Ultrasonography, Artificial Intelligence, Machine Learning
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Duzce UniversityUniversity, hospital or other
- Study start
- 10 Aug 2026 (actual)
- Primary completion
- 1 May 2027 (estimated)
- Study completion
- 15 May 2027 (estimated)
- First posted
- 14 Aug 2026 (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.
This prospective observational study aims to develop and evaluate artificial intelligence-based models for the assessment of laryngeal mask airway (LMA) placement in adult patients undergoing elective surgery under general anesthesia. Following LMA insertion, standardized airway ultrasound images will be obtained and fiberoptic assessment will be performed as the anatomical reference standard. Fiberoptic findings will be classified as optimal (Brimacombe grades 3-4) or suboptimal (grades 1-2). Clinical and quantitative airway ultrasound variables will also be recorded. The predictive performance of tabular, image-only, and multimodal artificial intelligence models will be evaluated for identifying optimal versus suboptimal LMA placement.
Detailed description
Laryngeal mask airways are widely used for supraglottic airway management during general anesthesia. Although adequate ventilation can usually be achieved after insertion, satisfactory clinical ventilation does not necessarily indicate optimal anatomical placement. Fiberoptic assessment provides direct visualization of the relationship between the LMA and laryngeal structures but is invasive and not routinely available in all clinical settings.
Airway ultrasonography provides a non-invasive bedside method for evaluating LMA position. In this prospective observational study, standardized post-placement ultrasound images will be obtained in adult patients undergoing elective surgery with an LMA. Fiberoptic assessment will subsequently be performed and graded according to the Brimacombe fiberoptic scoring system. Grades 3-4 will constitute optimal placement and grades 1-2 suboptimal placement.
Three prediction approaches are planned. Model A will use prespecified clinical and quantitative ultrasound variables, including age, sex, body mass index, Mallampati class, mouth opening, thyromental distance, neck circumference, dentition status, tongue thickness, skin-to-epiglottis distance, and the hyomental distance ratio. Model B will use post-placement ultrasound images alone using a transfer-learning-based image model. Model C will integrate ultrasound image features with the prespecified tabular variables in a multimodal prediction model.
Model performance will be assessed using patient-level resampling procedures. The primary performance measure will be the area under the receiver operating characteristic curve (AUROC), with additional assessment of sensitivity, specificity, positive and negative predictive values, F1 score, precision-recall performance, and calibration. Images obtained from the same participant will remain within the same data partition to prevent information leakage
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients (aged 18 years or older) with ASA physical status I-III who are scheduled for elective surgery under general anesthesia and in whom a laryngeal mask airway is planned for airway management will constitute the study population. Patients will be recruited prospectively from the operating rooms of Düzce University Research and Application Hospital.
Key inclusion criteria (1 listed)
- Adults undergoing elective surgery under general anesthesia in whom LMA use is clinically planned; ASA physical status I-III; ability to provide written informed consent.
Key exclusion criteria (1 listed)
- Emergency surgery; pregnancy; anticipated difficult airway; major upper airway or neck anatomical abnormality or previous major neck surgery; clinically significant aspiration risk or contraindication to LMA use; inability to obtain adequate ultrasound images or fiberoptic assessment.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Discrimination of Optimal Versus Suboptimal LMA Placement by the Multimodal Artificial Intelligence Model
Time frame: During the intraoperative assessment following LMA insertion, approximately within 15 minutes after placement
The ability of the multimodal artificial intelligence model combining post-placement ultrasound images with prespecified clinical and quantitative ultrasound variables to discriminate optimal from suboptimal LMA placement, using fiberoptic assessment as the reference standard. Optimal placement will be defined as Brimacombe grades 3-4 and suboptimal placement as grades 1-2. Model discrimination will primarily be quantified using the area under the receiver operating characteristic curve (AUROC).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 Aug 2026.
- Individual participant dataSharing planned: No
Related trials for Airway Management
Not yet recruiting
Tizanidine Premedication Versus Placebo for Laryngeal Mask Airway Insertion and Recovery in Adults Undergoing Ambulatory Surgery
Airway Management
Not yet recruitingObservational study
AI-assisted Tracheal Intubation in Children
Intubation
Recruiting
Comparing Surfactant Administration Through Supraglottic Airway and Thin Catheter for Preterm Infants
Surfactant, Respiratory Distress Syndrome (Neonatal)
Not yet recruitingObservational study
Preoperative Frailty and Suboptimal Mask Ventilation in Cardiac Surgery Patients
Frailty, Suboptimal Mask Ventilation
Not yet recruitingPhase 2
A Study to Assess the Efficacy and Safety of Co-administration of GSK3862995B With GSK5784283 in Adult Participants With Moderate to Severe Chronic Obstructive Pulmonary Disease (COPD)
Pulmonary Disease, Chronic Obstructive
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.
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 Airway Management, run by Duzce University at 1 site in Turkey (Türkiye).
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: looking for participants now, as of the sponsor's last update on 14 Aug 2026. 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 Turkey (Türkiye). 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact gizem demir şenoğlu, ass. prof (05059313588, gizemsenoglu@duzce.edu.tr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Discrimination of Optimal Versus Suboptimal LMA Placement by the Multimodal Artificial Intelligence Model (time frame: During the intraoperative assessment following LMA insertion, approximately within 15 minutes after placement). 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 14 Aug 2026.