Is Any Additional Information Gained Regarding Margins Using 3D Tomosynthesis Vs 2D Conventional Digital Imaging When Imaging Operative Breast Specimens?

NCT ID: NCT02096185

Last Updated: 2016-10-21

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

UNKNOWN

Clinical Phase

NA

Total Enrollment

50 participants

Study Classification

INTERVENTIONAL

Study Start Date

2014-05-31

Study Completion Date

2017-05-31

Brief Summary

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Patients who are diagnosed with breast cancer will have surgery to remove the tumour. Where this is a local excision not mastectomy, the tissue removed is sent for x-ray imaging to assess that the abnormality has been removed and give an estimation of the distance from lesion to specimen edge. This allows the surgeon to decide whether to remove more tissue or not at the time. This study is designed to compare whether more accurate information about lesion to margin measurement can be obtained using 3 dimensional tomosynthesis imaging compared to 2 dimensional conventional digital imaging which is the type of imaging currently used. This has the potential to prevent some patients requiring a second operation to remove more tissue if the margins of the specimen are still involved with tumour.

The study involves x-raying the specimen under both conditions when it arrives from theatre. Only the 2D image will be reviewed at the time as is current practice. The 3D image will be reviewed later and the measurements for lesion to specimen margin compared. The lesion to margin measurement as recorded by the pathologist will be taken as the 'gold standard' and the imaging measurements will also be compared to that.

In theory, the use of 3D tomosynthesis should allow more accurate lesion to margin measurement because 3D can provide better visualisation of the lesion edges by removing the effect of superimposed tissue.

The hypothesis states that the use of 3 dimensional tomosynthesis imaging should provide better lesion visualisation compared to 2 dimensional conventional digital imaging thus allowing more accurate lesion to margin measurement.

Detailed Description

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Conditions

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Breast Cancer

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Investigators

Study Groups

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3 dimensional tomosynthesis imaging

Breast specimen to be x-rayed using both conditions 3 dimensional tomosynthesis imaging 2 dimensional conventional digital imaging

Group Type EXPERIMENTAL

3 dimensional tomosynthesis imaging

Intervention Type RADIATION

Each operative specimen will be imaged twice using each condition

2 dimensional digital imaging

Breast specimens to be x-rayed under both conditions 3 dimensional tomosynthesis imaging 2 dimensional digital imaging

Group Type EXPERIMENTAL

2 dimensional digital imaging

Intervention Type RADIATION

Interventions

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3 dimensional tomosynthesis imaging

Each operative specimen will be imaged twice using each condition

Intervention Type RADIATION

2 dimensional digital imaging

Intervention Type RADIATION

Eligibility Criteria

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Inclusion Criteria

* Patient requires surgery to remove breast cancer and operative specimen needs to be x-rayed

Exclusion Criteria

* Patients with breast cancer who need mastectomy
Minimum Eligible Age

30 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Sandwell & West Birmingham Hospitals NHS Trust

OTHER

Sponsor Role lead

Responsible Party

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Jennifer Waldron

Consultant Radiographer

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Jennifer Waldron

Role: PRINCIPAL_INVESTIGATOR

Sandwell & West Birmingham Hospitals NHS Trust

Locations

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Sandwell and West Birmingham Hospitals NHS Trust

Birmingham, West Midlands, United Kingdom

Site Status

Countries

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United Kingdom

Other Identifiers

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Breast Specimen Imaging Ver3

Identifier Type: -

Identifier Source: org_study_id

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