Clinical Performance Comparison of a Long Versus a Short Axial Field-of-View PET/CT Using EARL-Compliant Reconstructions.
Mol Imaging Biol
; 26(5): 780-789, 2024 Oct.
Article
em En
| MEDLINE
| ID: mdl-39093483
ABSTRACT
PURPOSE:
To ensure comparable PET/CT image quality between or within centres, clinical inter-system performance comparisons following European Association of Nuclear Medicine Research Ltd. (EARL) guidelines is required. In this work the performance of the long axial field-of-view Biograph Vision Quadra is compared to its predecessor, the short axial field-of-view Biograph Vision. PROCEDURES To this aim, patients with suspected tumour lesions received a single weight-based (3 MBq/kg) 2-deoxy-2-[18F]fluoro-D-glucose injection and underwent routine clinical ( â¼ 15 min) scans on the Vision and 3-min scans on the Quadra in listmode in balanced order. Image quality (IQ), image noise (IN), and tumour demarcation (TD) were assessed visually by four nuclear medicine physicians using a 5-point Likert scale and semiquantitative analysis was performed using standardised uptake values (SUVs). Inter-reader agreement was tested using Wilcoxon's signed rank test and the SUVs were statistically compared using a paired t-test.RESULTS:
Twenty patients (mean age, 60 years ± 8.8 [standard deviation], 16 male) were enrolled. Inter-reader agreement ranged from good to very good for IQ and IN (0.62 ≤ W ≤ 0.81), and fair for TD (0.29 ≤ W ≤ 0.39). Furthermore, a significant difference was found for TD (p = 0.015) between the systems, showing improved TD for the Quadra.CONCLUSION:
This study demonstrates that the Quadra can be used in routine clinical practice with multiple PET/CT systems or in multicentre studies. This system provides comparable diagnostic image quality and semiquantitative accuracy, improved TD, and has the advantage of shorter scan durations.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article