Maxillary CystAIpreopNCT07505485
Artificial Intelligence-Based Assessment of Endosseous Lesions
A study testing AI assisted Evaluation in people with Maxillary Cyst and Mandibular Cyst, run by University of Bari Aldo Moro at 2 sites in Italy.
Trial summary
Despite these advances, CBCT interpretation remains largely qualitative and dependent on the clinician's experience. Conventional evaluation is based on two-dimensional slices and linear measurements, which may underestimate lesion complexity and spatial distribution. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Maxillary Cyst, Mandibular Cyst
- What is being tested?
- AI assisted Evaluation
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 10 participants
- Where
- 2 sitesItaly
- Study dates
- 1 Apr 2026to 1 May 2026
- Phase
- Interventional
- 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 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Good health according to the System of the American Society of Anesthesiology
- Aged older than 18 years
- No general medical contraindication for surgery
Who cannot join
- Smoking more than 15 cigarettes a day
- Pregnancy
- Acute infections
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Saverio Capodiferro, Prof. contact
Italy2 sites, 2 recruiting
- Recruiting
University of Bari Aldo Moro
Bari, 70021
Giuseppe D'Albis, +393495103642, dalbisgiuseppe@hotmail.com
- Recruiting
Dr. Giuseppe D'Albis
Bari, 70124
Giuseppe D'Albis, Dr., +393495103642, giuseppe.dalbis@uniba.it
About this study
Official title: Artificial Intelligence-Based Assessment of Endosseous Lesions: A Prospective Clinical Study
Despite these advances, CBCT interpretation remains largely qualitative and dependent on the clinician's experience. Conventional evaluation is based on two-dimensional slices and linear measurements, which may underestimate lesion complexity and spatial distribution.
Recent developments in Artificial Intelligence in Medicine have introduced automated image segmentation tools capable of identifying lesion boundaries and calculating volumetric data. These technologies allow a transition from subjective assessment to objective, reproducible quantification.
Read more
The potential clinical advantages include:
- Objective measurement of lesion size (volume in mm³)
- Improved surgical planning
- Enhanced prediction of anatomical involvement
- Reduction of diagnostic errors
- Standardization of follow-up and outcome assessment Therefore, the aim of the present study was to evaluate the clinical impact of AI-based segmentation and volumetric analysis of endosseous lesions compared to conventional CBCT interpretation.
- Conditions
- Maxillary Cyst, Mandibular Cyst
- Being tested
- AI assisted Evaluation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI assisted EvaluationDiagnostic test
CBCT scans were processed using AI-based software capable of:
- Automated segmentation of the lesion
- 3D reconstruction
- Volumetric calculation
| Study group | Role | What they receive |
|---|---|---|
| Patients with endosseous lesion-Analyzed using conventional CBCT | No intervention | Not described |
| Patients with endosseous lesion- AI-assisted evaluation | Experimental | * Automated segmentation of the lesion
* 3D reconstruction
* Volumetric calculation Receives: Diagnostic Test: AI assisted Evaluation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time required for CBCT interpretation (minutes)
assessment of the time required for CBCT interpretation by the surgeon. A digital stopwatch was used to record the operative time required for each procedural step, with measurements expressed in seconds, in order to obtain an objective and standardized assessment of execution time.
Measured: Day 1
Secondary outcomes (1)
Intraoperative and Postoperative Complications
- Unexpected endodontic treatment of adjacent teeth
- Intraoperative nerve exposure
- Paresthesia
- Excessive bone removal
- Incomplete lesion removal
- Postoperative infection
- Delayed healing
- Sinus involvement
- Root damage to adjacent teeth
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Apr 2026
- Study start1 Apr 2026 (estimated)
- Primary completion1 May 2026 (estimated)
- Study completion1 May 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Maxillary CystStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 10 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Bari Aldo Moro
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Giuseppe D'Albis, University of Bari Aldo Moro
- Investigators
- Giuseppe D'Albis, Dr, Principal investigator, University of Bari Aldo MoroSaverio Capodiferro, Prof, Study director, University of Bari Aldo Moro
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07505485
- Sponsor's protocol ID
- AIpreoperative
- Acronym
- AIpreop
- Status last verified
- Apr 2026
- First submitted
- 21 Mar 2026
- Last updated
- 15 Apr 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 15 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-Based Assessment of Endosseous Lesions: A Prospective Clinical Study
- ClinicalTrials.gov ID
- NCT07505485
- Acronym / sponsor ID
- AIpreop / AIpreoperative
- Conditions
- Maxillary Cyst, Mandibular Cyst
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 10 participants (estimated)
- Lead sponsor
- University of Bari Aldo MoroUniversity, hospital or other
- Study start
- 1 Apr 2026 (estimated)
- Primary completion
- 1 May 2026 (estimated)
- Study completion
- 1 May 2026 (estimated)
- First posted
- 1 Apr 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.
Despite these advances, CBCT interpretation remains largely qualitative and dependent on the clinician's experience. Conventional evaluation is based on two-dimensional slices and linear measurements, which may underestimate lesion complexity and spatial distribution.
Recent developments in Artificial Intelligence in Medicine have introduced automated image segmentation tools capable of identifying lesion boundaries and calculating volumetric data. These technologies allow a transition from subjective assessment to objective, reproducible quantification.
The potential clinical advantages include:
- Objective measurement of lesion size (volume in mm³)
- Improved surgical planning
- Enhanced prediction of anatomical involvement
- Reduction of diagnostic errors
- Standardization of follow-up and outcome assessment Therefore, the aim of the present study was to evaluate the clinical impact of AI-based segmentation and volumetric analysis of endosseous lesions compared to conventional CBCT interpretation.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients with endosseous lesion-Analyzed using conventional CBCT | No intervention | – |
| Patients with endosseous lesion- AI-assisted evaluation | Experimental | Diagnostic Test: AI assisted Evaluation* Automated segmentation of the lesion * 3D reconstruction * Volumetric calculation |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Good health according to the System of the American Society of Anesthesiology
- Aged older than 18 years
- No general medical contraindication for surgery
Key exclusion criteria (3 listed)
- Smoking more than 15 cigarettes a day
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI assisted EvaluationCBCT scans were processed using AI-based software capable of: * Automated segmentation of the lesion * 3D reconstruction * Volumetric calculation | Diagnostic test | Patients with endosseous lesion- AI-assisted evaluation |
Primary outcome
Time required for CBCT interpretation (minutes)
Time frame: Day 1
assessment of the time required for CBCT interpretation by the surgeon. A digital stopwatch was used to record the operative time required for each procedural step, with measurements expressed in seconds, in order to obtain an objective and standardized assessment of execution time.
1 secondary outcome
Intraoperative and Postoperative Complications
Time frame: Day 1
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 15 Apr 2026.
- Individual participant dataSharing planned: Undecided
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.
Saverio Capodiferro, Prof. contact
Giuseppe D'Albis, Dr principal investigator
University of Bari Aldo Moro
Saverio Capodiferro, Prof study director
University of Bari Aldo Moro
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI assisted Evaluation in people with Maxillary Cyst and Mandibular Cyst, run by University of Bari Aldo Moro at 2 sites in Italy.
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 3 inclusion and 3 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 15 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Italy. 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 Giuseppe D'Albis, Dr. (+393495103642, giuseppe.dalbis@uniba.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time required for CBCT interpretation (minutes) (time frame: Day 1). 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 15 Apr 2026.