AI-Integrated 3D-Printed Videolaryngoscope for Orotracheal Intubation in Critically Ill Patients (VL-AI)

Clinical Performance and Usability of an AI Integrated 3D-Printed Videolaryngoscope for Orotracheal Intubation in Critically Ill Patients

Background: Orotracheal intubation is an essential procedure in critically ill patients requiring ventilatory support, and the use of videolaryngoscopy is recommended as the gold standard in clinical practice. In recent years, the development of videolaryngoscopes through additive manufacturing has demonstrated lower production costs, and their integration with artificial intelligence (AI) has shown promising results in improving procedural success and safety.

Aim: To evaluate the clinical performance and usability of a videolaryngoscope developed through additive manufacturing and integrated with artificial intelligence (AI) and computer vision, compared with a commercially available gold-standard videolaryngoscope.

Methods: This is a multicenter, randomized, controlled, superiority Phase I/II clinical trial with a single-blind design. A total of 120 critically ill patients admitted to intensive care units at four hospitals in southern Brazil will be enrolled. Participants will be individually randomized in a 1:1 allocation ratio to parallel groups. The interventions will be performed by at least 10 physicians. All physicians will receive standardized training on device use, and procedures will be monitored by trained research staff. Data will be recorded in electronic Excel spreadsheets, and statistical analyses will be conducted using IBM SPSS Statistics. All ethical principles will be strictly observed, including obtaining informed consent from participants or their legal representatives. A Data and Safety Monitoring Committee will be established to oversee the study.

Conclusions: If the expected results are confirmed, patients, healthcare professionals, and healthcare institutions may benefit from the improved performance, safety, and usability of the experimental device, particularly in critical care settings and public health emergencies.

Study Overview

• Status: Not yet recruiting
• Conditions: Orotracheal Intubation
• Intervention / Treatment: Device: Orotracheal intubation using a 3D videolaryngoscope integrated with artificial intelligence (VL-IA).; Device: Commercially available gold-standard videolaryngoscope (VL-C)

Detailed Description

Backgorund Orotracheal intubation (OTI) is an essential procedure in critically ill patients requiring mechanical ventilation to maintain gas exchange. It is estimated that OTI is the third most commonly performed procedure in hospitals worldwide, with more than 15 million people intubated annually in surgical centers and 650,000 in other clinical settings, generating over 2.1 billion dollars in global expenditures on intubation and airway protection devices.

Traditionally, a laryngoscope is used for direct visualization of the upper airways and insertion of the endotracheal tube. However, scientific evidence has demonstrated the superiority of videolaryngoscopy (VL), recommending its widespread use in all intubation scenarios as the primary technique in clinical practice.

During the COVID-19 pandemic, given the large number of patients with severe respiratory dysfunction, videolaryngoscopy became essential for managing difficult intubations. In this context, our research team developed a VL prototype using additive manufacturing with polylactic acid (PLA) and carbon fiber-reinforced PLA (PLA-Carbon), validated in realistic simulations for mechanical resistance and usability, with a patent registered at the Brazilian National Institute of Industrial Property (INPI) under number BR 10 2020 026194.

Currently, this VL is being enhanced through the integration of artificial intelligence (AI) using computer vision techniques based on machine learning and deep learning, such as convolutional neural networks, capable of automatically recognizing upper airway anatomical structures from pre-trained images. Given the high demand for orotracheal intubation and the inherent risk of severe complications, the limited availability of videolaryngoscopes due to high import costs in low- and middle-income countries represents a significant gap in care. To address this challenge, the development of a low-cost device using 3D printing combined with artificial intelligence is proposed. This technological integration is justified by its potential to expand access to clinical decision support and enhance procedural safety by providing real-time automated anatomical recognition to the operator.

Primary Objective To evaluate the effectiveness of an experimental videolaryngoscope integrated with artificial intelligence (AI-VL), developed using additive manufacturing, compared with a standard commercial videolaryngoscope (C-VL) during orotracheal intubation in adult patients admitted to the intensive care unit.

Study Design This is a multicenter, randomized, controlled, superiority, phase I/II, single-blinded clinical trial with individual randomization and 1:1 allocation into parallel groups (60 in the AI-VL group and 60 in the C-VL group). Interventions will be performed by at least 10 physicians.

Interventions and Comparator The study compares two devices for orotracheal intubation: a videolaryngoscope produced using additive manufacturing with embedded artificial intelligence and computer vision (AI-VL), and a standard commercial videolaryngoscope (C-VL), used as the comparator (gold standard). Participating physicians will receive prior training in the use of the AI-VL. In the intensive care unit, after confirmation of the indication for intubation and eligibility criteria, patients will be allocated to one of the study groups.

Administration of Interventions Each intensive care unit will include previously trained field researchers responsible for data collection and for the use of both AI-VL and C-VL devices. These researchers will oversee recruitment, physician training, intervention implementation, troubleshooting, and quality assurance. Following allocation, the assigned device will be used, and intubation will be performed as promptly as possible. The same physician may perform more than one intervention.

In both groups, patients will receive standard intubation care, including preoxygenation, monitoring, equipment preparation, selection of appropriate videolaryngoscope blade and endotracheal tube size, confirmation of tube placement, adequate ventilation (SpO₂ > 92%), tube fixation, and connection to mechanical ventilation.

Procedures for Individual Adaptation Both videolaryngoscopes will be available in different blade sizes to accommodate anatomical variability. For the AI-VL, the artificial intelligence software will be trained using an image database to enable automated glottic identification across different individuals.

Physical and Informational Materials Both devices will be accompanied by technical manuals and clinical use guidelines in physical and digital formats (QR code), as well as video tutorials covering assembly, operation, and cleaning. The AI-VL will additionally include instructions regarding the use of the embedded AI system.

Sample Size The study follows ISO 14155:2020, ISO 62366-2, IEC 62366, and ANVISA RDC No. 837/2023 guidelines for research involving medical devices. The sample size calculation, based on FDA CDRH (2016) and ISO 62366-2 recommendations, considered 80% power and a significance level of 5%. A total of 120 patients will be included, equally distributed across groups and institutions, along with at least 10 physicians, aiming at preliminary analyses of effectiveness and usability.

Recruitment Informational materials will be made available in advance within participating institutions and through digital media. Recruitment of patients and professionals will take place in the ICU, according to eligibility criteria. Professionals and patients capable of providing consent will be invited through direct contact. For patients unable to consent, consent may be obtained from family members or legal representatives, either prior to or following the procedure (deferred consent). Further details on consent are provided in the ethics section.

Sequence Generation The randomization sequence will be generated in Microsoft Excel by an external statistician using computer-generated random numbers, in equal-sized blocks and stratified by participating center.

Allocation Concealment Mechanism The allocation sequence will be placed in opaque, sealed envelopes by the principal investigator and distributed to field researchers at each of the four participating hospitals.

Implementation Field researchers, blinded to the allocation sequence, will enroll and assign participants individually in the ICU immediately before intubation to either the intervention group (AI-VL) or the comparator group (C-VL), in a 1:1 ratio.

Data Collection Methods

Data collection will be conducted by trained field researchers under the supervision of the research team. Data will be collected as follows:

• During the procedure: Field researchers will perform direct observation during intubation using a critical task checklist;
• Immediately after the procedure: Physicians will complete a sociodemographic characterization form, the System Usability Scale (SUS), the NASA Task Load Index (NASA-TLX), and a user perception questionnaire;
• After the procedure: Field researchers will collect patient sociodemographic and clinical data from medical records.

Data will be obtained through electronic questionnaires (tablets or QR codes) or paper forms, which will be compiled and stored in Microsoft Excel and SPSS.

A pilot study with the first 10 patients will be conducted to assess the reliability and validity of the instruments; these participants will be included in the final study sample. Reasons for non-adherence or loss to follow-up will be recorded.

Statistical Methods for Data Analysis Data will be analyzed using descriptive statistics according to variable type: continuous variables will be presented as mean ± standard deviation or median (interquartile range), after normality assessment using the Shapiro-Wilk test; categorical variables will be presented as absolute numbers and proportions (%).

Comparisons between non-parametric groups will be performed using the Kruskal-Wallis test. Predictors of intubation success will be analyzed using logistic regression, including subgroup analyses through regression models with interaction terms.

The internal consistency of the SUS scale will be assessed using Cronbach's alpha, and associations between usability (SUS), satisfaction, and overall perception will be examined using Spearman's correlation. For NASA-TLX score calculation, the unweighted version (Raw TLX) will be used; internal consistency will be assessed using Cronbach's alpha, and normality will be evaluated using the Shapiro-Wilk test. For inferential analysis, Wilcoxon and/or Mann-Whitney tests will be applied.

Missing data in Likert scales will be handled using multiple imputation (MICE), or alternative methods when appropriate. In cases where multiple imputation is not suitable, methods such as Last Observation Carried Forward (LOCF) will be used, if appropriate. Interim analyses will assess data consistency and outcome trends.

A significance level of 5% (p < 0.05) will be adopted for all tests, with 80% statistical power. Data will be analyzed using SPSS software. Responses from the user perception questionnaire will be subjected to qualitative analysis.

Data and Safety Monitoring Committee

The Data and Safety Monitoring Committee, established in accordance with recommendations from the Brazilian Ministry of Health (Brazil, 2008), will be responsible for overseeing study conduct, evaluating the effectiveness and safety of interventions, and protecting participants. The committee will be appointed by the project coordinator and composed of four members with the following qualifications:

• Physician: experience in conducting studies related to the study topic;
• Nurse: experience in conducting studies related to the study topic;
• Statistician: undergraduate or postgraduate degree in a relevant field and experience in health data analysis;
• Other healthcare professionals: experience in the design, conduct, or analysis of clinical trials.

Members will be independent of the funding source and will not receive financial compensation. The committee will meet monthly, remotely, to review study progress and issue recommendations regarding continuation, modification, suspension, or termination, which will be communicated to the Research Ethics Committees.

An interim analysis will be conducted by the statistician after inclusion of 50% of the sample (n = 60) to assess the need for early termination of the study if statistical (p < 0.05) and clinical superiority of the AI-VL is demonstrated, according to the criteria in Tables 1 and 2. The committee, not blinded, will evaluate safety issues and will be notified in cases of serious adverse events.

ANTICIPATED RESULTS It is expected that the results of this clinical trial will demonstrate superior effectiveness and usability of the AI-integrated videolaryngoscope (AI-VL) compared to the standard commercial videolaryngoscope (C-VL) for orotracheal intubation in critically ill patients. If this hypothesis is confirmed, healthcare systems may benefit from improved performance and safety, reduced complications, cost optimization, enhanced response in high-stress or crisis situations, reduced risk of pathogen exposure, and positive impacts on professional training.

• Study Type: Interventional
• Enrollment (Estimated): 120
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Rafael G Lund, PhD; Phone Number: +55 (53) 99125-7668; Email: rglund@ufpel.edu.br
• Study Contact Backup: Name: Ana CBK de Moraes, PhD; Phone Number: +55 53 9176-9898; Email: anacristinabkmoraes@gmail.com

Study Locations

• Brazil
  • Rio Grande do Sul
    • Pelotas, Rio Grande do Sul, Brazil, 96020-220
      • Husfp - Ucpel
      • Contact: Ana C Moraes, PhD; Phone Number: +55 53 9176-9898; Email: anacristinabkmoraes@gmail.com
    • Pelotas, Rio Grande do Sul, Brazil, 96020-360
      • Ebserh/Ufpel
      • Contact: Rafael G Lund, PhD; Phone Number: +55 53 9125-7668; Email: rafael.lund@gmail.com
      • Contact: Marcelo C Ribeiro, Master's degree; Phone Number: +55 11 97309-0603; Email: mcribeiro@inf.ufpel.edu.br
    • Rio Grande, Rio Grande do Sul, Brazil, 96200-190
      • Ebserh/Furg
  • South Carolina
    • Florianópolis, South Carolina, Brazil, 88040-370
      • Ebserh/Ufsc
      • Contact: Camila X Dalcól, PhD; Phone Number: +55 (43) 999856389; Email: camila.dalcol@ufsc.br
      • Contact: Andressa S Barboza, PhD; Phone Number: +55 53 8448-1042; Email: d.andressabarboza@gmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

Patient:

• Age ≥18 years.
• Both sexes.
• Clinical indication for orotracheal intubation.

Physician:

• Both sexes.
• Working in emergency or ICU settings.
• Minimum of one year of experience in laryngoscopy and/or orotracheal intubation.

Exclusion Criteria:

Patient:

• Clinically unstable or with contraindications to participation in experimental research.
• Significant airway malformations.
• Previously intubated or with a functioning tracheostomy.
• Pregnant.

Physicians:

• On vacation or leave during the study period.
• Orthopedic, visual, or cognitive limitations that impair participation.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Videolaryngoscope 3D with artificial intelligence (VL-AI); Patients in the intervention group will receive the usual care for orotracheal intubation, differing only in the use of VLP-IA for opening and visualizing the upper airways.	Device: Orotracheal intubation using a 3D videolaryngoscope integrated with artificial intelligence (VL-IA).; The videolaryngoscope (VL) incorporates a microcamera at the tip of the blade, enabling real-time visualization of anatomical structures via a monitor. The VL to be used in the intervention was manufactured through additive manufacturing using polylactic acid (PLA) and polyethylene terephthalate glycol (PETG). It was validated in high-fidelity simulations for mechanical strength and usability and is patented under number BR 10 2020 026194 with the Brazilian National Institute of Industrial Property (INPI). The VL is currently being enhanced through the integration of artificial intelligence (AI) using computer vision techniques based on Machine Learning and Deep Learning, including convolutional neural networks capable of automatically recognizing upper airway anatomical structures from previously trained image datasets. The embedded system will provide real-time visual and audio guidance during intubation with less than one-second latency.
Active Comparator: Commercially available gold-standard videolaryngoscope (VL-C); Patients in the comparator group will receive standard care for orotracheal intubation, using the gold-standard VLP-C for airway opening and visualization of the upper airways.	Device: Commercially available gold-standard videolaryngoscope (VL-C); Scientific evidence recommends the use of VL in all cases of intubation, across various clinical scenarios, as the primary intubation technique in clinical practice. The videolaryngoscope incorporates a microcamera at the tip of the blade, allowing visualization of anatomical structures in real time via a monitor.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Correct glottis visualization rate (%)	Refers to the accurate visualization of the glottis and vocal cords on the VL monitor, in agreement with direct visualization - Cormack-Lehane Classification	immediately after insertion of the videolaryngoscope
First-attempt intubation success rate (%)	Defined as the successful establishment of the artificial airway after a single insertion of the VL blade and orotracheal tube.	immediately after the first intubation
Number of attempts required for successful intubation (n)	An attempt is defined as the insertion of the VL blade into the oral cavity, with successful intubation being the correct placement of the tube in the trachea. In the intervention group, up to three attempts with the AI-enhanced VL will be allowed.	immediately after a successful intubation
Conversion rate to conventional laryngoscope (%)	Conversion is defined as the use of a conventional laryngoscope for intubation after discontinuing the use of the allocated VL (intervention or comparator).	immediately after a failure to use the video laryngoscope

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Connection time between VL and mobile software (seconds)	Measured from the moment the VL is handed to the bedside physician until the real-time image is displayed on the monitor, captured with the blade still outside the oral cavity.	Before intubation
Glottis visualization time (seconds)	Time from the insertion of the VL blade into the oral cavity until the glottis is visualized on the monitor, verbally confirmed by the physician.	within 60 seconds after insertion of the videolaryngoscope
Orotracheal tube insertion time (seconds)	Time from the adequate visualization of the glottis and vocal cords to the complete insertion of the tube into the trachea, with removal of the VL from the oral cavity.	within 60 seconds after intubation
Total intubation time (seconds)	Time from the first insertion of the VL into the oral cavity to the successful placement of the orotracheal tube in the trachea, regardless of the number of attempts or device changes.	within 60 seconds after intubation
Adverse events and/or complications rate (%)	An adverse event is an incident causing unintended harm related to healthcare, not associated with the underlying disease (e.g., oral mucosal injury, lacerations, bleeding, or perforations); complications are unfavorable outcomes resulting from these events (e.g., respiratory failure, infection, hypoxia, or bronchoaspiration).	during and immediately after intubation
Technical incident rate (%)	Refers to failures, instabilities, or difficulties related to the VL hardware or software (e.g., display malfunction, AI freezing, delayed feedback, or connectivity issues).	Before or during the use of the videolaryngoscope
Rate of factors associated with intubation failure (%)	Reasons linked to intubation failure, such as lack of glottis visualization, difficulty advancing the tube, anatomical variations, inadequate muscle relaxation, incorrect choice of VL or tube size, improper positioning, or selective intubation, among others.	During the use of the videolaryngoscope
System Usability Scale (SUS)	System Usability Scale (SUS) - This instrument consists of 11 questions that assess usability, effectiveness, and user satisfaction, with a total score ranging from 0 to 100; scores >68 indicate good usability and ≥85 indicate excellent usability.	within 30 minutes after intubation
NASA-TLX	NASA Task Load Index (TLX) is a widely used subjective tool for assessing perceived workload. An instrument evaluating six dimensions of workload (mental, physical, and temporal demand, effort, performance, and frustration), with 21 scoring levels per item. There are 15 possible pairwise comparisons across the six scales. Scores can range from 0 (irrelevant) to 5 (more important than any other factor).	within 30 minutes after intubation
Questionnaire on physicians' subjective perception	Questionnaire on physicians' subjective perception - A tool developed by the authors to assess image visualization, airway access difficulty, equipment setup, ease and difficulty of use, safety, risks, satisfaction (1-5 scale), and to collect comments or suggestions. In the satisfaction assessment, 1 is dissatisfied and 5 is completely satisfied.	within 30 minutes after intubation

Collaborators and Investigators

• Sponsor: Federal University of Pelotas
• Collaborators: Universidade Federal de Santa Catarina; Universidade Católica de Pelotas; Universidade Federal do Rio Grande (FURG)
• Investigators: Study Chair: Camila X Dalcól, PhD, University Federal of Santa Catarina; Study Chair: Ines M Hirdes, Specialist, University Catolic of Pelotas; Study Chair: Larissa O Daneluz, Master's degree, University Federal of Santa Catarina; Study Chair: Andressa S Barboza, PhD, University Federal of Santa Catarina; Study Chair: Marcelo C Ribeiro, Master's degree, University Federal of Pelotas; Study Chair: Tiago T Primo, PhD, University Federal of Pelotas

Publications and helpful links

Helpful Links

• Site

Study record dates

Study Major Dates

• Study Start (Estimated): March 20, 2027
• Primary Completion (Estimated): December 1, 2027
• Study Completion (Estimated): June 1, 2028

Study Registration Dates

• First Submitted: April 17, 2026
• First Submitted That Met QC Criteria: May 11, 2026
• First Posted (Actual): May 18, 2026

Study Record Updates

• Last Update Posted (Actual): May 18, 2026
• Last Update Submitted That Met QC Criteria: May 11, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: medical device; artificial intelligence; orotracheal intubation; clinical performance; videolaryngoscope; usability; computer vision; additive manufacturing
• Other Study ID Numbers: 406417/2024-5

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: All IPD that underlie results in a publication.
• IPD Sharing Time Frame: Individual patient data (IPD) will be available at the time of publication of the study results (expected in 2028), for an indefinite period.
• IPD Sharing Access Criteria: Individual patient data (IPD) will be accessible to researchers via a link that will be available along with the study results.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No