Breast Density Measurements in Digital Mammography and Breast Tomosynthesis Systems of Different Pixel Size
NCT ID: NCT04127175
Last Updated: 2020-07-22
Study Results
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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UNKNOWN
300 participants
OBSERVATIONAL
2019-10-01
2020-08-31
Brief Summary
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This study (1) evaluates the consistency between Volpara's breast density measurements and spatial distribution for the two imaging techniques (FFDM and DBT) in a Hologic Selenia Dimensions, and (2) compares VDB measurements with other similar tool (Quantra) and radiologists breast density manual classification.
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Detailed Description
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Inclusion criteria:
* Subjects over 18 years old.
* Acceptance of participation through a signed consent form.
* Asymptomatic subjects
Exclusion criteria:
* Subjects refusing to participate or sign the consent form.
* Subjects with prior history of breast surgery or biopsy with markers.
* Subjects with breast prostheses.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Volpara
This tool represents a physics-based model which extract pixel-wise information from the FFDM or DBT images, and combine it with metadata information from the DICOM header and appropriate linear attenuation coefficients of both adipose and glandular tissue.
Eligibility Criteria
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Inclusion Criteria
* Asymptomatic subjects
Exclusion Criteria
* Subjects with prior history of breast surgery or biopsy with markers.
* Subjects with breast prostheses.
* Subjects with biopsy marker clips
40 Years
99 Years
FEMALE
Yes
Sponsors
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University of Barcelona
OTHER
Universitat de Girona
OTHER
Corporacion Parc Tauli
OTHER
Responsible Party
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Oliver Diaz-Montesdeoca
Visiting researcher
Locations
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Radiology Breast Unit, Hospital Parc Taulí
Sabadell, Barcelona, Spain
Countries
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Central Contacts
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Facility Contacts
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Related Links
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Breast density software which will be evaluated
Other Identifiers
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2019/629
Identifier Type: -
Identifier Source: org_study_id
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