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NCT Number: NCT07648212

Artificial Intelligence (AI) for Proximal Caries Detection and Its Impact on Treatment Threshold

The purpose of this study is to assess the impact of artificial intelligence on proximal caries detection and subsequent treatment decisions of early learners and compare those with outcomes of experienced learners.

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Key information

Conditions

Caries,Dental Dental Caries Stomatognathic Diseases Tooth Demineralization Tooth Diseases

Age range

18 year–99 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University of Michigan

Ann Arbor, Michigan, 48109, United States

Location status: Recruiting

Location contact

Carmen Boren

CONTACT

[email protected]

Margherita Fontana, DDS, PhD

PRINCIPAL_INVESTIGATOR

Who can participate

Healthy volunteers accepted: No

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

Early learner Inclusion Criteria:

  • Provide informed consent
  • Willing to comply with all study procedures and be available for the duration of the study
  • Dental student in second, third, or fourth year of dental school at University of Michigan School of Dentistry

Late learner Inclusion Criteria:

  • Provide informed consent
  • Willing to comply with all study procedures and be available for the duration of the study
  • Dental resident or junior faculty having at least 2 years of clinical experience outside of a dental education setting

Exclusion criteria

for participants:

  • Dental students who do not have previous experience with caries detection (such as first year dental students)
  • Residents that do not have frequent exposure to caries detection, such as orthodontic, periodontic, oral surgery graduate residents.

Treatment and study plan

Review of Radiograph Images

Other

Participants will be asked to attend two visits and view a randomized series of dental radiographs (10 at each visit). Participants will answer a set of questions for each image reviewed. Some of the radiographs will have an Artificial Intelligence enhancement and some will not. Participants will be asked to return within about one week of the first visit to view the second set of x-rays and answer the survey questions.

Primary outcomes

  1. Lesion severity

    Time frame: approximately 1 week (2 sessions)

    Levels for this outcome will be sound, outer enamel, inner enamel/outer dentin, inner dentin.

  2. Diagnostic accuracy

    Time frame: Approximately 1 week (2 sessions)

  3. Specificity

    Time frame: Approximately 1 week (2 sessions)

  4. Overall sensitivity

    Time frame: Approximately 1 week (2 sessions)

  5. Sensitivity for outer enamel

    Time frame: Approximately 1 week (2 sessions)

  6. Sensitivity for inner enamel/outer dentin

    Time frame: Approximately 1 week (2 sessions)

  7. Sensitivity for inner dentin

    Time frame: Approximately 1 week (2 sessions)

Secondary outcomes

  1. Intervention

    Time frame: approximately 1 week (2 sessions)

    (levels for this outcome will be none, non-restorative, restorative)

Study contacts

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

Carmen Boren, DDS, FAGD

CONTACT

[email protected]

701-240-8191

Sponsors and collaborators

Lead sponsor

University of Michigan

Other

Collaborators

  • Delta Dental Plan of Michigan

Registry information

Official study title

Artificial Intelligence for Proximal Caries Detection and Its Impact on Treatment Threshold: Randomized Trial

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Jun 15, 2026
Registry last updated
Jul 9, 2026

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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