Preoperative estimation of the pathological breast tumor size in architectural distortions: a comparison of DM, DBT, US, CEM, and MRI - Takeaways - MDSpire

Preoperative estimation of the pathological breast tumor size in architectural distortions: a comparison of DM, DBT, US, CEM, and MRI

  • By

  • Javier Azcona Sáenz

  • Javier Molero Calafell

  • Marta Román Expósito

  • Elisenda Vall Foraster

  • Laura Comerma Blesa

  • Rodrigo Alcántara Souza

  • María del Mar Vernet Tomás

  • March 20, 2025

  • 0 min

Share

  • 1

    Architectural distortions (AD) account for nearly 6% of abnormalities detected on screening mammography and can indicate both benign and malignant processes.

  • 2

    Different imaging techniques yield varying maximum size measurements for ADs, with significant discrepancies often arising from mammographic assessments.

  • 3

    The study aims to evaluate which imaging technique best correlates with surgical specimen size of invasive carcinoma in cases of AD.

  • 4

    A retrospective cohort study identified 63 cases of AD from 59 patients, focusing on those diagnosed with carcinoma between 2018 and 2022.

  • 5

    The imaging modalities compared include digital mammography, digital breast tomosynthesis, ultrasound, contrast-enhanced mammography, and MRI.

Original Source(s)

Preoperative estimation of the pathological breast tumor size in architectural distortions: a comparison of DM, DBT, US, CEM, and MRI

  • by Javier Azcona Sáenz, Javier Molero Calafell, Marta Román Expósito, Elisenda Vall Foraster, Laura Comerma Blesa, Rodrigo Alcántara Souza, María del Mar Vernet Tomás

  • March 20, 2025

Related Content

A Transparent Machine Learning Approach Using Ultrasound Radiomics for Preoperative Distinction Between Granulomatous Lobular Mastitis and Breast Cancer

Mammography AI Spots Vascular Signals

Routine breast imaging offers opportunity for cardiovascular risk assessment.

Decoding Idiopathic Intracranial Hypertension

Marc Bouffard discusses Mass General Brigham’s recently launched initiative aimed at better understanding idiopathic intracranial hypertension