Purpose: Breast cancer is the most common cancer in women in developing and developed countries and is responsible for 15% of women's cancer deaths worldwide. Conventional absorption-based breast imaging techniques lack sufficient contrast for comprehensive diagnosis. Propagation-based phase-contrast computed tomography (PB-CT) is a developing technique that exploits a more contrast-sensitive property of x-rays: x-ray refraction. X-ray absorption, refraction, and contrast-to-noise in the corresponding images depend on the x-ray energy used, for the same/fixed radiation dose. The aim of this paper is to explore the relationship between x-ray energy and radiological image quality in PB-CT imaging. Approach: Thirty-nine mastectomy samples were scanned at the imaging and medical beamline at the Australian Synchrotron. Samples were scanned at various x-ray energies of 26, 28, 30, 32, 34, and 60 keV using a Hamamatsu Flat Panel detector at the same object-to-detector distance of 6 m and mean glandular dose of 4 mGy. A total of 132 image sets were produced for analysis. Seven observers rated PB-CT images against absorption-based CT (AB-CT) images of the same samples on a five-point scale. A visual grading characteristics (VGC) study was used to determine the difference in image quality. Results: PB-CT images produced at 28, 30, 32, and 34 keV x-ray energies demonstrated statistically significant higher image quality than reference AB-CT images. The optimum x-ray energy, 30 keV, displayed the largest area under the curve ( AUC VGC ) of 0.754 ( p = 0.009 ). This was followed by 32 keV ( AUC VGC = 0.731 , p ≤ 0.001 ), 34 keV ( AUC VGC = 0.723 , p ≤ 0.001 ), and 28 keV ( AUC VGC = 0.654 , p = 0.015 ). Conclusions: An optimum energy range (around 30 keV) in the PB-CT technique allows for higher image quality at a dose comparable to conventional mammographic techniques. This results in improved radiological image quality compared with conventional techniques, which may ultimately lead to higher diagnostic efficacy and a reduction in breast cancer mortalities.
Purpose: Breast cancer is the most common cancer in women in developing and developed countries and is responsible for 15% of women's cancer deaths worldwide. Conventional absorption-based breast imaging techniques lack sufficient contrast for comprehensive diagnosis. Propagation-based phase-contrast computed tomography (PB-CT) is a developing technique that exploits a more contrast-sensitive property of x-rays: x-ray refraction. X-ray absorption, refraction, and contrast-to-noise in the corresponding images depend on the x-ray energy used, for the same/fixed radiation dose. The aim of this paper is to explore the relationship between x-ray energy and radiological image quality in PB-CT imaging. Approach: Thirty-nine mastectomy samples were scanned at the imaging and medical beamline at the Australian Synchrotron. Samples were scanned at various x-ray energies of 26, 28, 30, 32, 34, and 60 keV using a Hamamatsu Flat Panel detector at the same object-to-detector distance of 6 m and mean glandular dose of 4 mGy. A total of 132 image sets were produced for analysis. Seven observers rated PB-CT images against absorption-based CT (AB-CT) images of the same samples on a five-point scale. A visual grading characteristics (VGC) study was used to determine the difference in image quality. Results: PB-CT images produced at 28, 30, 32, and 34 keV x-ray energies demonstrated statistically significant higher image quality than reference AB-CT images. The optimum x-ray energy, 30 keV, displayed the largest area under the curve ( AUC VGC ) of 0.754 ( p = 0.009 ). This was followed by 32 keV ( AUC VGC = 0.731 , p ≤ 0.001 ), 34 keV ( AUC VGC = 0.723 , p ≤ 0.001 ), and 28 keV ( AUC VGC = 0.654 , p = 0.015 ). Conclusions: An optimum energy range (around 30 keV) in the PB-CT technique allows for higher image quality at a dose comparable to conventional mammographic techniques. This results in improved radiological image quality compared with conventional techniques, which may ultimately lead to higher diagnostic efficacy and a reduction in breast cancer mortalities.
Authors: P Baran; S Pacile; Y I Nesterets; S C Mayo; C Dullin; D Dreossi; F Arfelli; D Thompson; D Lockie; M McCormack; S T Taba; F Brun; M Pinamonti; C Nickson; C Hall; M Dimmock; F Zanconati; M Cholewa; H Quiney; P C Brennan; G Tromba; T E Gureyev Journal: Phys Med Biol Date: 2017-01-31 Impact factor: 3.609
Authors: T E Gureyev; Ya I Nesterets; P M Baran; S T Taba; S C Mayo; D Thompson; B Arhatari; A Mihocic; B Abbey; D Lockie; J Fox; B Kumar; Z Prodanovic; D Hausermann; A Maksimenko; C Hall; A G Peele; M Dimmock; K M Pavlov; M Cholewa; S Lewis; G Tromba; H M Quiney; P C Brennan Journal: Med Phys Date: 2019-10-20 Impact factor: 4.071
Authors: Brian L Sprague; Robert F Arao; Diana L Miglioretti; Louise M Henderson; Diana S M Buist; Tracy Onega; Garth H Rauscher; Janie M Lee; Anna N A Tosteson; Karla Kerlikowske; Constance D Lehman Journal: Radiology Date: 2017-02-28 Impact factor: 11.105
Authors: A Sztrókay; P C Diemoz; T Schlossbauer; E Brun; F Bamberg; D Mayr; M F Reiser; A Bravin; P Coan Journal: Phys Med Biol Date: 2012-04-20 Impact factor: 3.609
Authors: Emily F Conant; Elisabeth F Beaber; Brian L Sprague; Sally D Herschorn; Donald L Weaver; Tracy Onega; Anna N A Tosteson; Anne Marie McCarthy; Steven P Poplack; Jennifer S Haas; Katrina Armstrong; Mitchell D Schnall; William E Barlow Journal: Breast Cancer Res Treat Date: 2016-03-01 Impact factor: 4.872
Authors: J Ferlay; M Colombet; I Soerjomataram; C Mathers; D M Parkin; M Piñeros; A Znaor; F Bray Journal: Int J Cancer Date: 2018-12-06 Impact factor: 7.396