journal article·2024-02-20Open access

Enhancing Soft Tissue Differentiation with Different Dual-Energy CT Systems: A Phantom Study

Pasqualina Gallo, Andrea D’Alessio, Riccardo Pascuzzo, Salvatore Gallo, Maria Luisa Fumagalli, Ornella Ortenzia, Chiara Tenconi, Claudia Cavatorta, Emanuele Pignoli, Caterina Ghetti, Maria Grazia Bruzzone, Elena De Martin

Applied Sciences· Volume 14· Issue 5

Abstract

To quantitatively evaluate the possible advantages of quantifying and differentiating various soft tissues using virtual monochromatic images (VMI) derived from different dual-energy computed tomography (DECT) technologies. This study involved four DECT scanners with different technologies. CIRS phantom images were acquired in single-energy (SECT) and DECT modes with each scanner. The analysis focused on five equivalent soft-tissue inserts: adipose, breast, liver, muscle, and bone (200 mg). The signal-to-noise ratio (SNR) was calculated for each equivalent soft-tissue insert. Finally, the contrasts of tissue pairs between DECT and SECT images were compared using Wilcoxon signed-rank tests adjusted for multiple comparisons. Average CT numbers and noise showed a significant difference pattern between DECT with respect to SECT for each CT scanner. Generally, energy levels of 70 keV or higher led to improved SNR in VMI for most of the equivalent soft-tissue inserts. However, energy levels of 40–50 keV showed significantly higher contrasts in most of the equivalent soft-tissue insert pairs. DECT images at low energies, especially at 40–50 keV, outperform SECT images in discriminating soft tissues across all four DECT technologies. The combined use of DECT images reconstructed at different energy levels provides a more comprehensive set of information for diagnostic and/or radiotherapy evaluation compared to SECT. Some differences between scanners are evident, depending on the DECT acquisition technique and reconstruction method.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced X-ray and CT Imaging · Radiation Dose and Imaging · Dental Radiography and Imaging

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Radiotherapy and Radiosurgery, Humanitas Research Center-IRCCS, Via G. Manzoni 56, Rozzano, 20089 Milan, Italy

Fondazione IRCCS Istituto Neurologico Carlo Besta, Via G. Celoria 11, 20133 Milan, Italy

Medical Physics Department, University Hospital “Maggiore della Carità”, Corso G. Mazzini 18, 28100 Novara, Italy

Physics Department “Aldo Pontremoli”, University of Milano, Via G. Celoria 16, 20133 Milan, Italy

Medical Physics Department, University Hospital of Parma, Via A. Gramsci 14, 43126 Parma, Italy

Medical Physics Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Via G. Venezian 1, 20133 Milan, Italy

Funding

talian Ministry of Health (RRC)

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