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Related Concept Videos

Computed Tomography01:10

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.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Next generation tomosynthesis image acquisition optimization for dedicated PET-DBT attenuation corrections.

Trevor L Vent1, Bruno Barufaldi1, Raymond J Acciavatti1

  • 1Department of Radiology, University of Pennsylvania, Philadelphia, United States.

Proceedings of Spie--The International Society for Optical Engineering
|November 26, 2024
PubMed
Summary

Next-generation tomosynthesis (NGT) with integrated positron emission tomography (PET-DBT) shows improved dense tissue classification and breast segmentation. Optimized acquisition geometries enhance image quality and reduce volume overestimation compared to conventional digital breast tomosynthesis.

Keywords:
attenuation correctionbinary classificationdigital breast tomosynthesismulti-modality imagingpositron emission tomographyray tracingsensitivity indexvirtual clinical trial

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Area of Science:

  • Medical Imaging
  • Radiology
  • Biomedical Engineering

Background:

  • Digital breast tomosynthesis (DBT) is a key imaging modality for breast cancer detection.
  • Integrating positron emission tomography (PET) with DBT (PET-DBT) offers potential for improved diagnostic accuracy.
  • Optimizing acquisition geometries is crucial for enhancing PET-DBT performance.

Purpose of the Study:

  • To investigate custom acquisition geometries for a next-generation tomosynthesis (NGT) prototype.
  • To improve dense/adipose tissue classification within the breast.
  • To enhance breast outline segmentation for better image analysis.

Main Methods:

  • Simulated various NGT acquisition geometries using the OpenVCT virtual clinical trial framework.
  • Employed anthropomorphic breast phantoms for realistic simulations.
  • Compared custom NGT geometries (40-200 mm PA motion) against conventional DBT.
  • Utilized receiver operating characteristic (ROC) curves and area under the curve (AUC) to quantify classification performance.
  • Calculated reconstructed breast volume and sensitivity index (d').

Main Results:

  • Increasing posteroanterior (PA) x-ray source motion in NGT reduced breast volume overestimation compared to conventional DBT.
  • Both AUC and sensitivity index (d') increased with greater PA source motion.
  • Custom NGT geometries demonstrated superior adipose-glandular classification and segmentation.

Conclusions:

  • Next-generation tomosynthesis (NGT) acquisition geometries can significantly improve breast tissue classification and segmentation.
  • Optimized NGT parameters enhance image quality for PET-DBT applications.
  • These findings suggest NGT offers improved attenuation corrections for PET-DBT over conventional DBT.