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Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Tomosynthesis-detected Architectural Distortion: Management Algorithm with Radiologic-Pathologic Correlation.

Melissa A Durand¹, Steven Wang¹, Regina J Hooley¹

¹From the Department of Radiology, Yale University School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520-8042 (M.A.D., R.J.H., M.R., L.E.P.); and Department of Radiology, Kaiser Permanente, Bakersfield, Calif (S.W.).

Radiographics : a Review Publication of the Radiological Society of North America, Inc

|March 11, 2016

Summary

This summary is machine-generated.

Digital breast tomosynthesis (DBT) detects architectural distortions missed by 2D mammography. This study proposes management strategies for these subtle findings, improving cancer detection.

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Area of Science:

Radiology
Breast Imaging
Oncology

Background:

Digital breast tomosynthesis (DBT) is increasingly used, revealing suspicious lesions not seen on 2D mammography.
Architectural distortion, a key indicator of malignancy, is detected more frequently with DBT.
Optimal management of DBT-detected architectural distortions remains undefined.

Purpose of the Study:

To outline practical methods for assessing architectural distortions identified by DBT.
To propose a management algorithm for tomosynthesis-detected architectural distortions.

Main Methods:

Utilizing DBT localization tools and enhanced visualization for identifying subtle distortions.
Employing focused ultrasonography (US) and magnetic resonance imaging (MRI) for diagnosis and biopsy guidance.
Considering tomosynthesis-guided biopsy, stereotactic biopsy, or needle localization for tissue diagnosis.

Main Results:

DBT significantly increases the detection of architectural distortions compared to 2D mammography.
Integrated imaging approaches (DBT, US, MRI) aid in the evaluation and biopsy of these lesions.
A proposed algorithm facilitates the management of tomosynthesis-detected architectural distortions.

Conclusions:

DBT enhances the detection of architectural distortions, necessitating refined management protocols.
A systematic approach involving advanced imaging and biopsy techniques improves diagnostic yield.
The proposed algorithm offers a framework for managing these challenging mammographic findings.