RecruitingObservational

Evaluation of a Novel Auto Segmentation Algorithm for Normal Structure Delineation in Radiation Treatment Planning

NCT ID: NCT06200116Sponsor: Mayo ClinicLast updated: 2025-07-24

Summary

This study measures the utility of a novel artificial intelligence (AI) algorithm for performing auto-segmentation of computed tomography (CT) scans for radiation therapy planning.

Detailed description

PRIMARY OBJECTIVE: I. To measure the observed utility of an AI algorithm for normal segmentation by recording study subjects' observations of its function. OUTLINE: This is an observational study. Participants complete surveys about the performance/functionality of the auto-segmentation algorithm on study.

Arms & interventions

OtherNon-Interventional Study
Non-interventional study

Outcome measures

Primary

Proportion of success
Will be evaluated by question 1 of the end user survey, which evaluates the level of modification to the artificial intelligence generated auto-segmentation structures that was required (no modification, minor modification, or major modification). Auto-segmentation algorithm data will be collected through an electronic data collection form.
Time frame: Baseline

Eligibility criteria

Sex: AllAge: All agesHealthy volunteers: Yes

Inclusion Criteria: * Employment at Mayo Clinic Arizona, Florida, or Rochester (which includes Regional Practice sites located at Mayo Clinic Health System locations) as train clinical staff that participate in normal tissue segmentation Exclusion Criteria: * Inability to complete study surveys