Predicting Cancer in Pancreatic Cystic Lesions Through Artificial Intelligence
Deep Learning for Malignant Degeneration Prediction of Pancreatic Cystic Lesions - Beyond High-risk Stigmata
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Andrea CHIERICI
- Phone Number: +33 0634799833
- Email: chierici.ap@chu-nice.fr
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
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.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
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.
|
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.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
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.
|
90 days from patients hospital discharge.
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy of performance evaluation
Time Frame: 90 days from patients hospital discharge.
|
the number of true positives and true negatives among all predictions.
It varies between 0 (no correct prediction) to 1 (full correct predictions).
|
90 days from patients hospital discharge.
|
|
Precision of performance evaluation
Time Frame: 90 days from patients hospital discharge.
|
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).
|
90 days from patients hospital discharge.
|
|
Recall of performance evaluation
Time Frame: 90 days from patients hospital discharge.
|
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).
|
90 days from patients hospital discharge.
|
|
Balanced accuracy
Time Frame: 90 days from patients hospital discharge.
|
the aritmethic mean of sensitivity and specificity.
It varies between 0 (no correct prediction) to 1 (full correct predictions).
|
90 days from patients hospital discharge.
|
|
F1-score
Time Frame: 90 days from patients hospital discharge.
|
It combines precision and recall.
It ranges from 0-100%, and a higher F1 score denotes a better quality classifier.
|
90 days from patients hospital discharge.
|
|
Confusion matrix
Time Frame: 90 days from patients hospital discharge.
|
A visual representation of true positives, false positives, true negatives, and false negatives.
It is depicted through a table.
|
90 days from patients hospital discharge.
|
|
Log-loss
Time Frame: 90 days from patients hospital discharge.
|
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.
|
90 days from patients hospital discharge.
|
|
Cohen's Kappa
Time Frame: 90 days from patients hospital discharge.
|
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).
|
90 days from patients hospital discharge.
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 25Chirdig01
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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