Clinical trial NCT06954753: Predicting Cancer in Pancreatic Cystic Lesions Through Artificial Intelligence
Official title: Deep Learning for Malignant Degeneration Prediction of Pancreatic Cystic Lesions - Beyond High-risk Stigmata
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Pancreatic Cancer
Pancreatic Cystic Lesions
Lead sponsor: Centre Hospitalier Universitaire de Nice
Sponsor class: OTHER
First posted: 2025-05-02
Enrollment: 250
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
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.

Brief 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. 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.


Eligibility criteria: Inclusion Criteria:

* 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.

Exclusion Criteria:

* 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.

Primary outcomes:
measure: Prediction of malignant degeneration of pancreatic cystics lesions
timeFrame: 90 days from patients hospital discharge.
Secondary outcomes:
measure: Accuracy of performance evaluation
timeFrame: 90 days from patients hospital discharge.
measure: Precision of performance evaluation
timeFrame: 90 days from patients hospital discharge.
measure: Recall of performance evaluation
timeFrame: 90 days from patients hospital discharge.
measure: Balanced accuracy
timeFrame: 90 days from patients hospital discharge.
measure: F1-score
timeFrame: 90 days from patients hospital discharge.
measure: Confusion matrix
timeFrame: 90 days from patients hospital discharge.
measure: Log-loss
timeFrame: 90 days from patients hospital discharge.
measure: Cohen's Kappa
timeFrame: 90 days from patients hospital discharge.
Other outcomes:
Locations:
Study officials:
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