Intra-Pelvic Organ Motion for Cervix Cancer Patient Using Imaging

NCT ID: NCT00957450

Last Updated: 2025-02-20

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

20 participants

Study Classification

OBSERVATIONAL

Study Start Date

2008-02-29

Study Completion Date

2029-02-28

Brief Summary

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Patients with cervix cancer having radiotherapy experience side-effects because the radiotherapy fields have to be quite large to account for tumour movement in the pelvis during treatment, this irradiates a lot of normal tissues. This study aims to characterize and model the tumour motion, as well as the motion of surrounding normal tissues, during treatment. By doing this, the investigators can look at ways to minimise tumour motion and spare more normal tissues. By tailoring the radiotherapy dose more accurately, the investigators will reduce the side-effects of treatment and improve local control of the tumour. By doing multiple magnetic resonance imaging (MRI) scans of the patients during treatment, the investigators can identify where the tumour and surrounding normal tissues are at that point in time. Collecting all the information from these scans, will allow the investigators to model the motion of the tumour and these pelvic organs, and investigate the best way to target the tumour while still sparing normal tissues.

Detailed Description

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At simulation: patients will have two MRI scans in addition to the standard planning CT scan. One MRI scan will be with bladder full, the other will be with bladder empty. During treatment: patients will have two or three MRI scans per week at their convenience. MRI scans will be scheduled close to radiotherapy treatment times to minimise inconvenience for the patient. On the same day they have an MRI scan, they will also have a CBCT at the time of treatment. None of the images will be used to alter or influence the treatment the patient is receiving. If the patient feels that the imaging schedule is too inconvenient, they will be given the option to reduce the frequency of the scanning or to withdraw from the study.All the images will be loaded onto a password secure server. The MRI scans will be fused to the planning CT scan using bone-to-bone matching. Tumour and intra-pelvic organs will be contoured on the MRI scans. The contours will be used to create surface meshes of each organ and with research software, we will be able to model the motion and deformation of these organs over the course of radiotherapy. Using this data, we will be able to simulate the dose impact of the organ motion on different intensity-modulated radiotherapy plans. We will also explore the impact of bladder \& rectal filling on tumour motion.

Conditions

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Cervix Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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1

Impact of organ motion

Characterize the impact of normal organ motion in the pelvic on tumour movement, during treatment. This will be assessed in patients with pelvic cancer.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Age ≥ 18years
* Biopsy confirmed cervix cancer
* Not suitable for surgery
* Suitable for radical radiotherapy
* ECOG 0-2
* Informed consent

Exclusion Criteria

* Patients unwilling or unable to give informed consent
* Prior pelvic radiotherapy
* Contraindications to MRI scan
Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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University Health Network, Toronto

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Michael Milosevic, MD

Role: PRINCIPAL_INVESTIGATOR

Univesity Health Network, Princess Margaret Hospital

Locations

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University Health Network

Toronto, Ontario, Canada

Site Status

Countries

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Canada

Other Identifiers

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UHN REB 08-0043-CE

Identifier Type: -

Identifier Source: org_study_id

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