Accuracy of Root Canal Curvature AnalysisNCT07587060
Development and Diagnostic Accuracy of a Deep Learning Model for Root Canal Curvature Analysis in Mandibular Molars Using CBCT Scans: A Diagnostic Accuracy Study
An observational study of Accuracy of Root Canal Curvature Analysis, run by Cairo University at 1 site in Egypt.
Trial summary
Root canal preparation in endodontics poses significant challenges, particularly in curved canals of mandibular molars, where accurate preoperative assessment using CBCT imaging is crucial to avoid iatrogenic errors and improve treatment outcomes. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Accuracy of Root Canal Curvature Analysis
- How many people
- 207 participants
- Where
- 1 siteEgypt
- Study dates
- 1 Jun 2026to 1 Sep 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 to 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The accepted sample size (n) will be 207, when the accuracy is (90.48%) and marginal error (4 %) by adopting confidence interval (95%), using Staskingdom calculator.
Who may be able to join
- CBCT scans of mandibular molars of Egyptian patients aging from 18 to 65 years old
- Small Field of view (FOV) including maximum a quadrant
- Voxel size not larger than 2mm
- Mandibular molars showing complete root formation
- Carious or non-carious teeth
- Absence of artifacts, dental implants in the adjacent teeth
Who cannot join
- Mandibular first and second molars with developmental anomalies, external or internal root resorption, root canal calcification, previous root canal treatment, post restorations, and/or root caries
- CBCT images of sub-optimal quality or artifacts/high scatter interfering with proper assessment
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
Root canal preparation in endodontics poses significant challenges, particularly in curved canals of mandibular molars, where accurate preoperative assessment using CBCT imaging is crucial to avoid iatrogenic errors and improve treatment outcomes. This study aims to develop and evaluate the diagnostic accuracy of a deep learning model for analyzing root canal curvature angles in mandibular molars from CBCT scans, compared to human expert evaluations. The model will leverage advanced AI techniques to segment and measure curvatures objectively, addressing limitations in manual interpretation, potentially standardizing case difficulty assessments and aiding clinical decision-making.
- Keywords
- Artificial intelligence, Deep learning model, root canal curvature, Analysis of curvature
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Diagnostic test: Artificial intelligence | Diagnostic test: Artificial intelligence | |
| Reference group: Human Expert's opinion | Radiologist and Endodontist Human expert opinion compared to AI diagnostic test |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of analysis of root canal curvature angle
Curvature analysis classified according to its severity into 3 categories: "10 degrees or less"; as mild, "between 10 to 30 degrees"; as moderate and "30 degrees or more"; as severe curvature.
Measured: June 2026 to September 2027
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 May 2026
- Study start1 Jun 2026 (estimated)
- Primary completion1 Sep 2027 (estimated)
- Study completion1 Sep 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Accuracy of Root Canal Curvature AnalysisStudies of the same condition, open and under way.
- More trials run by Cairo UniversityThe 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 207 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Samaa Mohammed Osman Mohammed, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07587060
- Sponsor's protocol ID
- NEW Code 7-1-1
- Other IDs
- self funded
- Status last verified
- May 2026
- First submitted
- 4 May 2026
- Last updated
- 14 May 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The study is diagnostic accuracy study on CBCT data
Study at a glance
From the registry record, last updated by the sponsor on 14 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Diagnostic Accuracy of a Deep Learning Model for Root Canal Curvature Analysis in Mandibular Molars Using CBCT Scans: A Diagnostic Accuracy Study
- ClinicalTrials.gov ID
- NCT07587060
- Acronym / sponsor ID
- NEW Code 7-1-1
- Keywords
- Artificial intelligence, Deep learning model, root canal curvature, Analysis of curvature
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 207 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 1 Jun 2026 (estimated)
- Primary completion
- 1 Sep 2027 (estimated)
- Study completion
- 1 Sep 2027 (estimated)
- First posted
- 14 May 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.
Root canal preparation in endodontics poses significant challenges, particularly in curved canals of mandibular molars, where accurate preoperative assessment using CBCT imaging is crucial to avoid iatrogenic errors and improve treatment outcomes. This study aims to develop and evaluate the diagnostic accuracy of a deep learning model for analyzing root canal curvature angles in mandibular molars from CBCT scans, compared to human expert evaluations. The model will leverage advanced AI techniques to segment and measure curvatures objectively, addressing limitations in manual interpretation, potentially standardizing case difficulty assessments and aiding clinical decision-making.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Diagnostic test: Artificial intelligence | – | –Diagnostic test: Artificial intelligence |
| Reference group: Human Expert's opinion | – | –Radiologist and Endodontist Human expert opinion compared to AI diagnostic test |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The accepted sample size (n) will be 207, when the accuracy is (90.48%) and marginal error (4 %) by adopting confidence interval (95%), using Staskingdom calculator.
Key inclusion criteria (6 listed)
- CBCT scans of mandibular molars of Egyptian patients aging from 18 to 65 years old
- Small Field of view (FOV) including maximum a quadrant
- Voxel size not larger than 2mm
- Mandibular molars showing complete root formation
- Carious or non-carious teeth
Key exclusion criteria (2 listed)
- Mandibular first and second molars with developmental anomalies, external or internal root resorption, root canal calcification, previous root canal treatment, post restorations, and/or root caries
- CBCT images of sub-optimal quality or artifacts/high scatter interfering with proper 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
Accuracy of analysis of root canal curvature angle
Time frame: June 2026 to September 2027
Curvature analysis classified according to its severity into 3 categories: "10 degrees or less"; as mild, "between 10 to 30 degrees"; as moderate and "30 degrees or more"; as severe curvature.
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 May 2026.
- Individual participant dataSharing planned: No. The study is diagnostic accuracy study on CBCT data
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 Accuracy of Root Canal Curvature Analysis, run by Cairo University at 1 site in Egypt.
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 6 inclusion and 2 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: opening soon, as of the sponsor's last update on 14 May 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 Egypt. 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 Samaa M Mohammed, Assistant lecturer (00201060493152, samaa.mohammed@dentistry.cu.edu.eg), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of analysis of root canal curvature angle (time frame: June 2026 to September 2027). 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 May 2026.