Abstract
Background Iterative computed tomography (CT) image reconstruction shows high potential for the preservation of image quality in diagnostic CT while reducing patients' exposure;it has become available for low-dose CT (LD-CT) in high-end hybrid imaging systems (e.g. single-photon emission computed tomography [SPECT]-CT). Purpose To examine the effect of an iterative CT reconstruction algorithm on image quality, image noise, detectability, and the reader's confidence for LD-CT data by a subjective assessment. Material and Methods The LD-CT data were validated for 40 patients examined by an abdominal hybrid SPECT-CT (U = 120 kV, I = 40 mA, pitch = 1.375). LD-CT was reconstructed using either filtered back projection (FBP) or an iterative image reconstruction algorithm (Adaptive Statistical Iterative Reconstruction [ASIR](R)) with different parameters (ASIR levels 50% and 100%). The data were validated by two independent blinded readers using a scoring system for image quality, image noise, detectability, and reader confidence, for a predefined set of 16 anatomic substructures. Results The image quality was significantly improved by iterative reconstruction of the LD-CT data compared with FBP (P <= 0.0001). While detectability increased in only 2/16 structures (P <= 0.03), the reader's confidence increased significantly due to iterative reconstruction (P <= 0.002). Meanwhile, at the ASIR level of 100%, the detectability in bone structure was highly reduced (P = 0.003). Conclusion An ASIR level of 50% represents a good compromise in abdominal LD-CT image reconstruction. The specific ASIR level improved image quality (reduced image noise) and reader confidence, while preserving detectability of bone structure.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-79815-5 |
ISSN: | 2058-4601 |
Sprache: | Englisch |
Dokumenten ID: | 79815 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Dez. 2021, 14:50 |
Letzte Änderungen: | 10. Mrz. 2023, 09:42 |