Your browser doesn't support javascript.
loading
Enhancing diagnostic performance and image quality in coronary CT angiography: Impact of SnapShot Freeze 2 algorithm across varied heart rates in stent patients.
Wu, Zhehao; Han, Qijia; Liang, Yuying; Zheng, Zhijuan; Wu, Minyi; Ai, Zhu; Ma, Kun; Xiang, Zhiming.
Afiliação
  • Wu Z; Postgraduate Cultivation Base of Guangzhou University of Chinese Medicine, Panyu Central Hospital, Guangzhou, China.
  • Han Q; Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
  • Liang Y; Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
  • Zheng Z; Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
  • Wu M; Postgraduate Cultivation Base of Guangzhou University of Chinese Medicine, Panyu Central Hospital, Guangzhou, China.
  • Ai Z; Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
  • Ma K; Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
  • Xiang Z; Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, China.
J Appl Clin Med Phys ; 25(8): e14412, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38807292
ABSTRACT

PURPOSE:

To investigate the enhancement of image quality achieved through the utilization of SnapShot Freeze 2 (SSF2), a comparison was made against the results obtained from the original SnapShot Freeze algorithm (SSF) and standard motion correction (STND) in stent patients undergoing coronary CT angiography (CCTA) across the entire range of heart rates. MATERIALS AND

METHODS:

A total of 118 patients who underwent CCTA, were retrospectively included in this study. Images of these patients were reconstructed using three different algorithms SSF2, SSF, and STND. Objective assessments include signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), diameters of stents and artifact index (AI). The image quality was subjectively evaluated by two readers.

RESULTS:

Compared with SSF and STND, SSF2 had similar or even higher quality in the parameters (AI, SNR, CNR, inner diameters) of coronary artery, stent, myocardium, MV (mitral valve), TV (tricuspid valve), AV (aorta valve), and PV (pulmonary valve), and aortic root (AO). Besides the above structures, SSF2 also demonstrated comparable or even higher subjective scores in atrial septum (AS), ventricular septum (VS), and pulmonary artery root (PA). Furthermore, the enhancement in image quality with SSF2 was significantly greater in the high heart rate group compared to the low heart rate group. Moreover, the improvement in both high and low heart rate groups was better in the SSF2 group compared to the SSF and STND group. Besides, when using the three algorithms, an effect of heart rate variability on stent image quality was not detected.

CONCLUSION:

Compared to SSF and STND, SSF2 can enhance the image quality of whole-heart structures and mitigate artifacts of coronary stents. Furthermore, SSF2 has demonstrated a significant improvement in the image quality for patients with a heart rate equal to or higher than 85 bpm.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Stents / Angiografia Coronária / Razão Sinal-Ruído / Angiografia por Tomografia Computadorizada / Frequência Cardíaca Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Stents / Angiografia Coronária / Razão Sinal-Ruído / Angiografia por Tomografia Computadorizada / Frequência Cardíaca Idioma: En Ano de publicação: 2024 Tipo de documento: Article