Seyedamir Tavakoli Taba1, Patrycja Baran2, Sarah Lewis3, Robert Heard4, Serena Pacile5, Yakov I Nesterets6, Sherry C Mayo7, Christian Dullin8, Diego Dreossi9, Fulvia Arfelli10, Darren Thompson6, Mikkaela McCormack11, Maram Alakhras3, Francesco Brun5, Maurizio Pinamonti12, Carolyn Nickson13, Chris Hall14, Fabrizio Zanconati12, Darren Lockie15, Harry M Quiney2, Giuliana Tromba9, Timur E Gureyev16, Patrick C Brennan3. 1. 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. 2. ARC Centre of Excellence in Advanced Molecular Imaging, School of Physics, The University of Melbourne, Parkville, Australia. 3. Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Health Sciences, The University of Sydney, Sydney 2141, Australia. 4. Health Systems and Global Populations Research Group, Faculty of Health Sciences, The University of Sydney, Sydney, Australia. 5. Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy; Department of Engineering and Architecture, University of Trieste, Trieste, Italy. 6. Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia; School of Science and Technology, University of New England, Armidale, Australia. 7. Commonwealth Scientific and Industrial Research Organisation, Melbourne, Australia. 8. 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. 9. Elettra Sincrotrone Trieste, Basovizza, Trieste, Italy. 10. Department of Physics, University of Trieste, and INFN, Trieste, Italy. 11. TissuPath Specialist Pathology Services, Melbourne, Australia. 12. Department of Pathology, Academic Hospital of Trieste, Trieste, Italy. 13. Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia. 14. Australian Synchrotron, Clayton, Australia. 15. Maroondah BreastScreen, Melbourne, Australia. 16. 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.
Abstract
RATIONALE AND OBJECTIVES: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: The results of the present study will support future experimental and clinical attempts to further optimize this innovative approach to breast cancer imaging.
RATIONALE AND OBJECTIVES: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: The results of the present study will support future experimental and clinical attempts to further optimize this innovative approach to breast cancer imaging.
Authors: Seyedamir Tavakoli Taba; Patrycja Baran; Yakov I Nesterets; Serena Pacile; Susanne Wienbeck; Christian Dullin; Konstantin Pavlov; Anton Maksimenko; Darren Lockie; Sheridan C Mayo; Harry M Quiney; Diego Dreossi; Fulvia Arfelli; Giuliana Tromba; Sarah Lewis; Timur E Gureyev; Patrick C Brennan Journal: Eur Radiol Date: 2020-01-23 Impact factor: 5.315
Authors: S Pacilè; C Dullin; P Baran; M Tonutti; C Perske; U Fischer; J Albers; F Arfelli; D Dreossi; K Pavlov; A Maksimenko; S C Mayo; Y I Nesterets; S Tavakoli Taba; S Lewis; P C Brennan; T E Gureyev; G Tromba; S Wienbeck Journal: Sci Rep Date: 2019-09-24 Impact factor: 4.379
Authors: Sarina Wan; Benedicta D Arhatari; Yakov I Nesterets; Sheridan C Mayo; Darren Thompson; Jane Fox; Beena Kumar; Zdenka Prodanovic; Daniel Hausermann; Anton Maksimenko; Christopher Hall; Matthew Dimmock; Konstantin M Pavlov; Darren Lockie; Mary Rickard; Ziba Gadomkar; Alaleh Aminzadeh; Elham Vafa; Andrew Peele; Harry M Quiney; Sarah Lewis; Timur E Gureyev; Patrick C Brennan; Seyedamir Tavakoli Taba Journal: J Med Imaging (Bellingham) Date: 2021-07-12