Experimental optimization of the energy for breast-CT with synchrotron radiation

Breast Computed Tomography (bCT) is a three-dimensional imaging technique that is raising interest among radiologists as a viable alternative to mammographic planar imaging. In X-rays imaging it would be desirable to maximize the capability of discriminating different tissues, described by the Contr...

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Veröffentlicht in:Scientific reports 2020-10, Vol.10 (1), p.17430-17430, Article 17430
Hauptverfasser: Oliva, Piernicola, Di Trapani, Vittorio, Arfelli, Fulvia, Brombal, Luca, Donato, Sandro, Golosio, Bruno, Longo, Renata, Mettivier, Giovanni, Rigon, Luigi, Taibi, Angelo, Tromba, Giuliana, Zanconati, Fabrizio, Delogu, Pasquale
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Sprache:eng
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Zusammenfassung:Breast Computed Tomography (bCT) is a three-dimensional imaging technique that is raising interest among radiologists as a viable alternative to mammographic planar imaging. In X-rays imaging it would be desirable to maximize the capability of discriminating different tissues, described by the Contrast to Noise Ratio (CNR), while minimizing the dose (i.e. the radiological risk). Both dose and CNR are functions of the X-ray energy. This work aims at experimentally investigating the optimal energy that, at fixed dose, maximizes the CNR between glandular and adipose tissues. Acquisitions of both tissue-equivalent phantoms and actual breast specimens have been performed with the bCT system implemented within the Syrma-3D collaboration at the Syrmep beamline of the Elettra synchrotron (Trieste). The experimental data have been also compared with analytical simulations and the results are in agreement. The CNR is maximized at energies around 26–28 keV. These results are in line with the outcomes of a previously presented simulation study which determined an optimal energy of 28 keV for a large set of breast phantoms with different diameters and glandular fractions. Finally, a study on photon starvation has been carried out to investigate how far the dose can be reduced still having suitable images for diagnostics.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-74607-7