NCT06200116

Brief 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.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
200

participants targeted

Target at P75+ for all trials

Timeline
6mo left

Started Dec 2024

Geographic Reach
1 country

7 active sites

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress74%
Dec 2024Nov 2026

First Submitted

Initial submission to the registry

December 28, 2023

Completed
13 days until next milestone

First Posted

Study publicly available on registry

January 10, 2024

Completed
11 months until next milestone

Study Start

First participant enrolled

December 2, 2024

Completed
2 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

November 30, 2026

Expected
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

November 30, 2026

Last Updated

July 24, 2025

Status Verified

July 1, 2025

Enrollment Period

2 years

First QC Date

December 28, 2023

Last Update Submit

July 22, 2025

Conditions

Outcome Measures

Primary Outcomes (1)

  • 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.

    Baseline

Study Arms (1)

Observational

Participants complete surveys about the performance/functionality of the auto-segmentation algorithm on study.

Other: Non-Interventional Study

Interventions

Non-interventional study

Observational

Eligibility Criteria

Sexall
Healthy VolunteersYes
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

All employed medical dosimetrists or medical dosimetry assistants who routinely perform review of AI generated auto-segmentation of normal tissues.

You may qualify if:

  • 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

You may not qualify if:

  • Inability to complete study surveys

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (7)

Mayo Clinic in Arizona

Scottsdale, Arizona, 85259, United States

RECRUITING

Mayo Clinic in Florida

Jacksonville, Florida, 32224-9980, United States

RECRUITING

Mayo Clinic Health System in Albert Lea

Albert Lea, Minnesota, 56007, United States

RECRUITING

Mayo Clinic Health Systems-Mankato

Mankato, Minnesota, 56001, United States

RECRUITING

Mayo Clinic in Rochester

Rochester, Minnesota, 55905, United States

RECRUITING

Mayo Clinic Health System-Eau Claire Clinic

Eau Claire, Wisconsin, 54701, United States

RECRUITING

Mayo Clinic Health System-Franciscan Healthcare

La Crosse, Wisconsin, 54601, United States

RECRUITING

Related Links

Study Officials

  • Doug J. Moseley, PhD

    Mayo Clinic in Rochester

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Clinical Trials Referral Office

CONTACT

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

December 28, 2023

First Posted

January 10, 2024

Study Start

December 2, 2024

Primary Completion (Estimated)

November 30, 2026

Study Completion (Estimated)

November 30, 2026

Last Updated

July 24, 2025

Record last verified: 2025-07

Locations