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NCT Number: NCT06817915

This Project At LMU Looks At How Using AI 2nd Opinion Report to Analyze Retinal Eye Scans Impact Doctors' Decisions About Treatment for Patients with a Specific Eye Disease (nAMD)

This is a research plan from the University of Munich (LMU) that aims to study how the use of AI reports can impact ophthalmologists' decisions regarding treatment for patients with neovascular age-related macular degeneration (nAMD). This disease is a leading cause of vision loss, and while anti-VEGF treatments are effective, they require careful monitoring and retreatment decisions to maximize benefits.

The study will involve up to 1000 ophthalmologists with varying levels of expertise. These ophthalmologists will review SD-OCT scans and make treatment decisions before and after reviewing AI-generated reports. The primary objective is to compare these decisions and see how the AI reports influence them. Secondary objectives include assessing the accuracy and safety of the AI reports.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

LMU Klinikum

Munich, Bavaria, 80336, Germany

Location contact

Ben Asani

CONTACT

Clinical Project Manager

CONTACT

[email protected]

+491749286564

Johannes Schiefelbein

CONTACT

Siegfried Priglinger, Prof Dr med

CONTACT

About this study

This research project at LMU delves into the intersection of artificial augmentation and ophthalmology, specifically focusing on how AI-generated 2nd opinion reports can aid in the treatment planning of neovascular age-related macular degeneration (nAMD). The project will involve a diverse group of up to 1000 ophthalmologists, categorized into six user groups based on their expertise, ranging from residents to seasoned retina specialists.

The core of the research involves assessing the impact of AI-generated 2nd opinion reports on ophthalmologists' treatment decisions for nAMD. Participants will review SD-OCT scans and make initial treatment decisions. Subsequently, they will review AI-generated reports for the same scans and have the opportunity to revise their decisions. This process aims to evaluate the influence of AI insights on clinical judgment.

The project will be conducted virtually, with participants enrolling online from various countries. Data collection will be facilitated through an electronic system, ensuring efficiency and security. Statistical analysis will primarily involve descriptive statistics to summarize the findings. The results of the study will be disseminated through publication in a peer-reviewed journal.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Electronically consented to the informed consent form (eICF)
  • Criteria to be included in one of the following six Ophthalmology user groups:

Group 1 Non-retina specialist Group: Ophthalmology, completed ophthalmology residence with no or another subspecialty other than retina (e.g., Glaucoma, refractive, etc) Group 2 Resident Group: <5 years in residency in ophthalmology Group 3 Fellow Group: Retina specialist in training Group: in fellowship in vitreoretinal medicine, medical retina Group 4 Retina specialist Group: completed retina training, regular requalification Group 5 Junior reader Group: have already gained experience in the reporting clinical routine with the diagnostics in question and completed the initial certification process at an Image and Reading Center (acc. to centre's SOP) Group 6 Senior reader Group: specialist with several years of experience in the relevant field or have completed at least 3 years of residency training. Completed the certification process at the Image and Reading Center (acc. to centre's SOP)

Exclusion criteria

  • Not an Ophthalmologist.
  • Does not have time to participate in the estimated project duration of 30 minutes.

Treatment and study plan

AI assisted assessment of SD-OCT scans

Behavioral

AI 2nd opinion report on nAMD treatment planning

Primary outcomes

  1. Ophthalmologist's Treatment Decision

    Time frame: There is only one survey filled out by the participant. In this survey, only one time point when participant views the SD-OCT and AI 2nd opinion report and fills out the survey questions.

    The number and percentage of initial treatment decisions that stayed the same after their review of the AI-CDS report The number and percentage of initial decisions that changed after their review of the AI-CDS report

Secondary outcomes

  1. Performance Accuracy

    Time frame: There is only one survey filled out by the participant. In this survey, only one time point when participant views the SD-OCT and AI 2nd opinion report and fills out the survey questions.

    The number and percentage of correct assessments (accuracy) made by AI-CDS report vs image grading/reading center (M³ Macula Monitor Münster) assessment (control / gold standard / ground truth) The percentage of correct assessments (accuracy) made by each of the 6 user group vs. image grading and reading center (M³ Macula Monitor Münster) assessment (control / gold standard / ground truth).

    How often is the AI-CDS report correct? How often is each of the 6 user groups correct after viewing just the SD-OCT image?

    Intra-rater reliability:

    How often are ophthalmologists (each user group) right/wrong after viewing AI-CDS report and made any decision changes?

  2. Safety prediciton assessment

    Time frame: There is only one survey filled out by the participant. In this survey, only one time point when participant views the SD-OCT and AI 2nd opinion report and fills out the survey questions.

    Yes/No prediction rates If an ophthalmologist is correct and AI-CDS report incorrect, how often does AI-CDS report mislead? Whether false-positive or false-negative? If an ophthalmologist is wrong and AI-CDS report correct, how often does AI-CDS report correct? Whether false-positive or false-negative?

  3. Exploratory AI-CDS report Impact on Decision Making

    Time frame: There is only one survey filled out by the participant. In this survey, only one time point when participant views the SD-OCT and AI 2nd opinion report and fills out the survey questions.

    impact of AI-CDS report on ophthalmologist's decision-making survey

Study contacts

Contact information is provided by the study sponsor or research team.

Clinical Project Manager

CONTACT

[email protected]

+491749286564

Sponsors and collaborators

Lead sponsor

Johannes Schiefelbein

Other

Collaborators

  • Deepeye Medical GmbH
  • M3 Macula Monitor Muenster
  • Technomics Research

Registry information

Official study title

LMU Project on the Impact of Reviewing AI Annotated SD-OCT Therapy Assistance Reports on Ophthalmologists' Treatment Decision-making for Anti-VEGF Therapy in NAMD Patients

Acronym: LMU ASSIST

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Feb 10, 2025
Registry last updated
Feb 10, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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