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Automating Breast Radiation Therapy (RT)

NCT00923871 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 160

Last updated 2022-10-18

No results posted yet for this study

Summary

Breast radiation treatment is planned from a Computed Tomography (CT) scan. This study is designed to investigate a method to reduce the time between the planning of radiation treatment and its actual start by automating the intensity-modulated radiation therapy (IMRT) planning process. The investigators plan to examine data from another scan called Cone Beam Computed Tomography (CBCT). A CBCT scan provides similar information to a conventional CT scan, however the images for CBCT are acquired at the treatment unit (linear accelerator used for treatment). Using these x-ray pictures of patients, the study team consisting of a radiation oncologist, a medical physicist and a radiation therapist will create a custom treatment plan unique to each patient. By doing this, the investigators hope to reduce the amount of time spent waiting for treatment and the number of hospital visits for patients in the future.

Conditions

Interventions

PROCEDURE

Cone Beam CT

Patients will also have a CBCT scan when they are having their first IMRT treatment.

Sponsors & Collaborators

  • Princess Margaret Hospital, Canada

    collaborator OTHER

  • University Health Network, Toronto

    lead OTHER

Principal Investigators

  • Anne Koch, MD · University Health Network, Princess Margaret Hospital

Study Design

Allocation
NA
Purpose
TREATMENT
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2009-06-30
Primary Completion
2015-01-05
Completion
2016-04-29

Countries

  • Canada

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT00923871 on ClinicalTrials.gov