Image quality of mixed convolution kernel in thoracic computed tomography

Zusammenfassung: The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likertscale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P<0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilarlymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P<0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P<0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.Abbreviations: CT = computed tomography, HU = Hounsfield units

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch
• Anmerkungen: Medicine 95(44): p e5309. DOI 10.1097/MD.0000000000005309, issn: 1536-5964

Klassifikation und Themen

• Schlagwort: Computertomografie ; Bildqualität ; Diagnose ; Diagnostik ; Differentialdiagnose ; Pflegediagnose

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Freiburg
• (wer): Universität
• (wann): 2017
• Urheber: Neubauer, Jakob ; Spira, Eva Maria ; Strube, Juliane ; Langer, Mathias ; Voss, Christian ; Kotter, Elmar
• Beteiligte Personen und Organisationen: Medizinische Fakultät ; Klinik für Radiologie ; Albert-Ludwigs-Universität Freiburg

Weitere Informationen

• DOI: 10.1097/MD.0000000000005309
• URN: urn:nbn:de:bsz:25-freidok-114765
• Rechteinformation: Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 25.03.2025, 13:49 MEZ