Development of Artificial Intelligence Models for Segmentation and Characterization of Prostate Cancer: a Single-center Retrospective Observational Study.

December 5, 2023 updated by: Chiti Arturo, IRCCS San Raffaele

Prostate cancer is the second most common cancer in the male population. This pathology represents an oncological and public health problem especially in developed countries, due to a greater presence of elderly men in the population.

Medical imaging plays a central role in the staging and restaging of prostate disease. Magnetic resonance imaging (MRI), computed tomography (CT) and positron emission tomography (PET) are among the methods commonly used in normal clinical practice for the characterization of prostate cancer. To date, the study of these images is limited to a qualitative visual analysis, however there is increasing evidence relating to the usefulness of introducing a quantitative (or semi-quantitative) analysis of biomedical images.

The current increase in available imaging data, and their quality, allows the application of artificial intelligence methods also in the medical field for the automation of tasks (e.g. automatic segmentation) and classification (e.g. tumor aggressiveness).

The extraction of quantitative data, and more generally the study of tumor lesions, requires manual segmentation by one or more doctors. This process requires very long times as each image must be processed individually; furthermore, the result also depends on the level of experience of the doctor carrying out the segmentation and this could create a source of heterogeneity, affecting the reproducibility of the segmentation.

AI-based automatic segmentation methods can be applied to medical images for the localization of tumor lesions, thus exceeding the limits of manual segmentation.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

350

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Italy
      • Milano, Italy, 20132
        • IRCCS San Raffaele

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

N/A

Sampling Method

Probability Sample

Study Population

Patients with prostate cancer undergoing PET examination with 68 Ga-PMSA (PET/CT or PET/MRI), since 01/06/2020, at the U.O. of Nuclear Medicine at the San Raffaele Hospital on the clinical indication of the specialist.

Description

Inclusion Criteria:

  • Patients with histological diagnosis of prostate cancer;
  • Patients who performed a PET exam with 68 Ga-PMSA.

Exclusion Criteria:

  • CT and MR images with artifacts that preclude interpretation of results.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Artificial intelligence algorithms for the classification of prostate cancer lesions on medical images.
Time Frame: 2 years
PET images from enrolled patients will be used to create models that investigate the ability of artificial intelligence to automate tumor segmentation tasks.
2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

IRCCS San Raffaele

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 6, 2020

Primary Completion (Actual)

June 1, 2022

Study Completion (Actual)

June 1, 2022

Study Registration Dates

First Submitted

December 5, 2023

First Submitted That Met QC Criteria

December 5, 2023

First Posted (Actual)

December 13, 2023

Study Record Updates

Last Update Posted (Actual)

December 13, 2023

Last Update Submitted That Met QC Criteria

December 5, 2023

Last Verified

December 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • AI_Pca

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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