Toward Improving Breast Cancer Imaging: Radiological Assessment of Propagation-Based Phase-Contrast CT Technology.


Journal

Academic radiology
ISSN: 1878-4046
Titre abrégé: Acad Radiol
Pays: United States
ID NLM: 9440159

Informations de publication

Date de publication:
06 2019
Historique:
received: 29 05 2018
revised: 05 07 2018
accepted: 09 07 2018
pubmed: 29 8 2018
medline: 25 4 2020
entrez: 29 8 2018
Statut: ppublish

Résumé

This study employs clinical/radiological evaluation in establishing the optimum imaging conditions for breast cancer imaging using the X-ray propagation-based phase-contrast tomography. Two series of experiments were conducted and in total 161 synchrotron-based computed tomography (CT) reconstructions of one breast mastectomy specimen were produced at different imaging conditions. Imaging factors include sample-to-detector distance, X-ray energy, CT reconstruction method, phase retrieval algorithm applied to the CT projection images and maximum intensity projection. Observers including breast radiologists and medical imaging experts compared the quality of the reconstructed images with reference images approximating the conventional (absorption) CT. Various radiological image quality attributes in a visual grading analysis design were used for the radiological assessments. The results show that the application of the longest achievable sample-to-detector distance (9.31 m), the lowest employed X-ray energy (32 keV), the full phase retrieval, and the maximum intensity projection can significantly improve the radiological quality of the image. Several combinations of imaging variables resulted in images with very high-quality scores. The results of the present study will support future experimental and clinical attempts to further optimize this innovative approach to breast cancer imaging.

Identifiants

pubmed: 30149975
pii: S1076-6332(18)30376-3
doi: 10.1016/j.acra.2018.07.008
pii:
doi:

Types de publication

Letter

Langues

eng

Sous-ensembles de citation

IM

Pagination

e79-e89

Informations de copyright

Copyright © 2018 The Association of University Radiologists. All rights reserved.

Auteurs

Seyedamir Tavakoli Taba (S)

Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Health Sciences, The University of Sydney, Sydney 2141, Australia. Electronic address: amir.tavakoli@sydney.edu.au.

Patrycja Baran (P)

ARC Centre of Excellence in Advanced Molecular Imaging, School of Physics, The University of Melbourne, Parkville, Australia.

Sarah Lewis (S)

Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Health Sciences, The University of Sydney, Sydney 2141, Australia.

Robert Heard (R)

Health Systems and Global Populations Research Group, Faculty of Health Sciences, The University of Sydney, Sydney, Australia.

Serena Pacile (S)

Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy; Department of Engineering and Architecture, University of Trieste, Trieste, Italy.

Yakov I Nesterets (YI)

Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia; School of Science and Technology, University of New England, Armidale, Australia.

Sherry C Mayo (SC)

Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia.

Christian Dullin (C)

Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy; Institute for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany; Max-Plank-Institute for Experimental Medicine, Goettingen, Germany.

Diego Dreossi (D)

Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy.

Fulvia Arfelli (F)

Department of Physics, University of Trieste, and INFN, Trieste, Italy.

Darren Thompson (D)

Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia; School of Science and Technology, University of New England, Armidale, Australia.

Mikkaela McCormack (M)

TissuPath Specialist Pathology Services, Melbourne, Australia.

Maram Alakhras (M)

Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Health Sciences, The University of Sydney, Sydney 2141, Australia.

Francesco Brun (F)

Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy; Department of Engineering and Architecture, University of Trieste, Trieste, Italy.

Maurizio Pinamonti (M)

Department of Pathology, Academic Hospital of Trieste, Trieste, Italy.

Carolyn Nickson (C)

Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia.

Chris Hall (C)

Australian Synchrotron, Clayton, Australia.

Fabrizio Zanconati (F)

Department of Pathology, Academic Hospital of Trieste, Trieste, Italy.

Darren Lockie (D)

Maroondah BreastScreen, Melbourne, Australia.

Harry M Quiney (HM)

ARC Centre of Excellence in Advanced Molecular Imaging, School of Physics, The University of Melbourne, Parkville, Australia.

Giuliana Tromba (G)

Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy.

Timur E Gureyev (TE)

Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Health Sciences, The University of Sydney, Sydney 2141, Australia; ARC Centre of Excellence in Advanced Molecular Imaging, School of Physics, The University of Melbourne, Parkville, Australia; Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia; School of Science and Technology, University of New England, Armidale, Australia; School of Physics and Astronomy, Monash University, Melbourne, Australia.

Patrick C Brennan (PC)

Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Health Sciences, The University of Sydney, Sydney 2141, Australia.

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Classifications MeSH