Pancreatic CancerNCT06954753
Predicting Cancer in Pancreatic Cystic Lesions Through Artificial Intelligence
An observational study of Pancreatic Cancer and Pancreatic Cystic Lesions, run by Centre Hospitalier Universitaire de Nice.
Trial summary
This international, multicenter retrospective study aims to develop a deep learning (DL)-based predictive model to identify malignant transformation in pancreatic cystic lesions, improving upon current clinical guidelines. The model will integrate clinical, biochemical, and multimodal imaging data. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pancreatic Cancer, Pancreatic Cystic Lesions
- What is being tested?
- Pancreatic surgery
- Type of treatment
- Surgery or procedure
- How many people
- 250 participants
- Where
- No sites listed yet
- Study dates
- 1 Jun 2025to 31 Dec 2026
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients who underwent pancreatic surgery for pancreatic cystic lesions, in the absence of preoperative evidence of cancer. Indication of surgery must be based on one or more current guidelines concerning pancreatic cystic lesions management.
Who may be able to join
- Patients diagnosed with PCL(s ) who underwent pancreatic surgery in one of the participant centers. Surgical indication must adhere to at least one of current guidelines on PCLs management (6), based on clinical, biochemical, and radiological (MR and/or EUS) features.
- Pancreatic surgery B83performed for supposed increased risk of cyst(s) malignant degeneration following current guidelines on PCLs management (6).
- Absence of clinical, biochemical, radiological, and anatomopathological evidence of pancreatic cancer at pancreatic surgery.
- Non-opposition to the anonymous data processing by the included patients.
Who cannot join
- Patients presenting with evidence of pancreatic cancer at surgery.
- PCL(s) diagnosis and treatment performed without one between EUS and pancreatic MR. surgery performed in the absence of the criteria proposed by current guidelines.
- Unavailability of both preoperative EUS and pancreatic MR data.
- Unavailability of postoperative PCL(s) anatomopathological analysis results.
- SBO diagnosis performed without CT-scan.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Deep Learning for Malignant Degeneration Prediction of Pancreatic Cystic Lesions - Beyond High-risk Stigmata
This international, multicenter retrospective study aims to develop a deep learning (DL)-based predictive model to identify malignant transformation in pancreatic cystic lesions, improving upon current clinical guidelines. The model will integrate clinical, biochemical, and multimodal imaging data. Several 3D convolutional neural networks will be trained using advanced preprocessing, data augmentation, and hybrid fusion techniques. Model performance will be compared to that of existing international guidelines. The study involves no additional procedures for patients and adheres to strict data anonymization and privacy regulations.
- Conditions
- Pancreatic Cancer, Pancreatic Cystic Lesions
- Being tested
- Pancreatic surgery
- Medical subject headings
- Pancreatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Pancreatic surgeryProcedure or surgery
Pancreatic resective surgery performed for pancreatic cystic lesions with high risk of malignant degeneration based on clinical, biochemical, and/or radiological features following current guidelines on pancreatic cystic lesions management.
| Study group | Role | What they receive |
|---|---|---|
| PCLs patients | Pancreatic resective surgery performed for pancreatic cystic lesions with high risk of malignant degeneration based on clinical, biochemical, and/or radiological features following current guidelines on pancreatic cystic lesions management. Receives: Procedure: Pancreatic surgery |
What is being measured
The primary outcome is the main question the study is designed to answer.
Prediction of malignant degeneration of pancreatic cystics lesions
Predict the presence of malignant degeneration (defined as: high grade dysplasia, in situ PADC, or T1 PADC) in pancreatic cystic lesion(s) using artificial intelligence model based on clinical, biochemical, and radiological features. This will be measured through Area Under the Receiver Operator Characteristic curve (AUROC) assesment. AUROC varies between 0.5 and 1, corresponding to no class separation capacity and full class separation capacity, respectively.
Measured: 90 days from patients hospital discharge.
Secondary outcomes (8)
Accuracy of performance evaluation
the number of true positives and true negatives among all predictions. It varies between 0 (no correct prediction) to 1 (full correct predictions).
Measured: 90 days from patients hospital discharge.
Precision of performance evaluation
The number of true positives divided by all the positive predictions (true positives and false positives). It varies between 0 (no correct prediction) to 1 (full correct predictions).
Measured: 90 days from patients hospital discharge.
Recall of performance evaluation
The number of true positives divided by the actual positive instances in the dataset (true positives and false negatives). It varies between 0 (no correct prediction) to 1 (full correct predictions).
Measured: 90 days from patients hospital discharge.
Balanced accuracy
the aritmethic mean of sensitivity and specificity. It varies between 0 (no correct prediction) to 1 (full correct predictions).
Measured: 90 days from patients hospital discharge.
F1-score
It combines precision and recall. It ranges from 0-100%, and a higher F1 score denotes a better quality classifier.
Measured: 90 days from patients hospital discharge.
Confusion matrix
A visual representation of true positives, false positives, true negatives, and false negatives. It is depicted through a table.
Measured: 90 days from patients hospital discharge.
Log-loss
It indicates how close the prediction probability is to the corresponding actual/true value (0 or 1 in case of binary classification). The more the predicted probability diverges from the actual value, the higher is the log-loss value.
Measured: 90 days from patients hospital discharge.
Cohen's Kappa
A metric used to measure the level of agreement between two raters which can be a useful tool to gauge the performance of a classification model. It accounts for the fact that the raters may happen to agree on some items purely by chance. It varies between 0 (no correct prediction) to 1 (full correct predictions).
Measured: 90 days from patients hospital discharge.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 May 2025
- Study start1 Jun 2025 (estimated)
- Primary completion1 Jun 2026 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pancreatic CancerStudies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 250 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Universitaire de Nice
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06954753
- Sponsor's protocol ID
- 25Chirdig01
- Status last verified
- Apr 2025
- First submitted
- 24 Apr 2025
- Last updated
- 2 May 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning for Malignant Degeneration Prediction of Pancreatic Cystic Lesions - Beyond High-risk Stigmata
- ClinicalTrials.gov ID
- NCT06954753
- Acronym / sponsor ID
- 25Chirdig01
- Conditions
- Pancreatic Cancer, Pancreatic Cystic Lesions
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 250 participants (estimated)
- Lead sponsor
- Centre Hospitalier Universitaire de NiceUniversity, hospital or other
- Study start
- 1 Jun 2025 (estimated)
- Primary completion
- 1 Jun 2026 (estimated)
- Study completion
- 31 Dec 2026 (estimated)
- First posted
- 2 May 2025 (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.
This international, multicenter retrospective study aims to develop a deep learning (DL)-based predictive model to identify malignant transformation in pancreatic cystic lesions, improving upon current clinical guidelines. The model will integrate clinical, biochemical, and multimodal imaging data. Several 3D convolutional neural networks will be trained using advanced preprocessing, data augmentation, and hybrid fusion techniques. Model performance will be compared to that of existing international guidelines. The study involves no additional procedures for patients and adheres to strict data anonymization and privacy regulations.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| PCLs patients | – | Procedure: Pancreatic surgeryPancreatic resective surgery performed for pancreatic cystic lesions with high risk of malignant degeneration based on clinical, biochemical, and/or radiological features following current guidelines on pancreatic cystic lesions management. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who underwent pancreatic surgery for pancreatic cystic lesions, in the absence of preoperative evidence of cancer. Indication of surgery must be based on one or more current guidelines concerning pancreatic cystic lesions management.
Key inclusion criteria (4 listed)
- Patients diagnosed with PCL(s ) who underwent pancreatic surgery in one of the participant centers. Surgical indication must adhere to at least one of current guidelines on PCLs management (6), based on clinical, biochemical, and radiological (MR and/or EUS) features.
- Pancreatic surgery B83performed for supposed increased risk of cyst(s) malignant degeneration following current guidelines on PCLs management (6).
- Absence of clinical, biochemical, radiological, and anatomopathological evidence of pancreatic cancer at pancreatic surgery.
- Non-opposition to the anonymous data processing by the included patients.
Key exclusion criteria (5 listed)
- Patients presenting with evidence of pancreatic cancer at surgery.
- PCL(s) diagnosis and treatment performed without one between EUS and pancreatic MR. surgery performed in the absence of the criteria proposed by current guidelines.
- Unavailability of both preoperative EUS and pancreatic MR data.
- Unavailability of postoperative PCL(s) anatomopathological analysis results.
- SBO diagnosis performed without CT-scan.
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 |
|---|---|---|
| Pancreatic surgeryPancreatic resective surgery performed for pancreatic cystic lesions with high risk of malignant degeneration based on clinical, biochemical, and/or radiological features following current guidelines on pancreatic cystic lesions management. | Procedure or surgery | PCLs patients |
Primary outcome
Prediction of malignant degeneration of pancreatic cystics lesions
Time frame: 90 days from patients hospital discharge.
Predict the presence of malignant degeneration (defined as: high grade dysplasia, in situ PADC, or T1 PADC) in pancreatic cystic lesion(s) using artificial intelligence model based on clinical, biochemical, and radiological features. This will be measured through Area Under the Receiver Operator Characteristic curve (AUROC) assesment. AUROC varies between 0.5 and 1, corresponding to no class separation capacity and full class separation capacity, respectively.
8 secondary outcomes
Accuracy of performance evaluation
Time frame: 90 days from patients hospital discharge.
Precision of performance evaluation
Time frame: 90 days from patients hospital discharge.
Recall of performance evaluation
Time frame: 90 days from patients hospital discharge.
Balanced accuracy
Time frame: 90 days from patients hospital discharge.
F1-score
Time frame: 90 days from patients hospital discharge.
Confusion matrix
Time frame: 90 days from patients hospital discharge.
Log-loss
Time frame: 90 days from patients hospital discharge.
Cohen's Kappa
Time frame: 90 days from patients hospital discharge.
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 2 May 2025.
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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.
Questions about this trial
What is this clinical trial studying?
An observational study of Pancreatic Cancer and Pancreatic Cystic Lesions, run by Centre Hospitalier Universitaire de Nice.
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 4 inclusion and 5 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 2 May 2025. Status can change between updates, so confirm with the study contact before making plans.
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 Andrea CHIERICI (+33 0634799833, chierici.ap@chu-nice.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Prediction of malignant degeneration of pancreatic cystics lesions (time frame: 90 days from patients hospital discharge.). 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 2 May 2025.