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Feasibility of Low-Dose and Low-Contrast Media Volume Approach in Computed Tomography Cardiovascular Imaging Reconstructed with Model-Based Algorithm.
Ippolito, Davide; Porta, Marco; Maino, Cesare; Riva, Luca; Ragusi, Maria; Giandola, Teresa; Franco, Paolo Niccolò; Cangiotti, Cecilia; Gandola, Davide; De Vito, Andrea; Talei Franzesi, Cammillo; Corso, Rocco.
Afiliação
  • Ippolito D; Departement of Medicine and Surgery, University of Milano-Bicocca, Piazza OMS 1, 20100 Milano, Italy.
  • Porta M; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Maino C; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Riva L; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Ragusi M; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Giandola T; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Franco PN; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Cangiotti C; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Gandola D; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • De Vito A; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Talei Franzesi C; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
  • Corso R; Department of Diagnostic Radiology, Fondazione IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy.
Tomography ; 10(2): 286-298, 2024 Feb 16.
Article em En | MEDLINE | ID: mdl-38393291
ABSTRACT

Aim:

To evaluate the dose reduction and image quality of low-dose, low-contrast media volume in computed tomography (CT) examinations reconstructed with the model-based iterative reconstruction (MBIR) algorithm in comparison with the hybrid iterative (HIR) one.

Methods:

We prospectively enrolled a total of 401 patients referred for cardiovascular CT, evaluated with a 256-MDCT scan with a low kVp (80 kVp) reconstructed with an MBIR (study group) or a standard HIR protocol (100 kVp-control group) after injection of a fixed dose of contrast medium volume. Vessel contrast enhancement and image noise were measured by placing the region of interest (ROI) in the left ventricle, ascending aorta; left, right and circumflex coronary arteries; main, right and left pulmonary arteries; aortic arch; and abdominal aorta. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Subjective image quality obtained by consensus was assessed by using a 4-point Likert scale. Radiation dose exposure was recorded.

Results:

HU values of the proximal tract of all coronary arteries; main, right and left pulmonary arteries; and of the aorta were significantly higher in the study group than in the control group (p < 0.05), while the noise was significantly lower (p < 0.05). SNR and CNR values in all anatomic districts were significantly higher in the study group (p < 0.05). MBIR subjective image quality was significantly higher than HIR in CCTA and CTPA protocols (p < 0.05). Radiation dose was significantly lower in the study group (p < 0.05).

Conclusions:

The MBIR algorithm combined with low-kVp can help reduce radiation dose exposure, reduce noise, and increase objective and subjective image quality.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article