Advanced imaging of shunt valves in cranial CT scans with photon-counting scanner
This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient’s cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt v...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
25 April 2024
|
| In: |
Tomography
Year: 2024, Jahrgang: 10, Heft: 5, Pages: 654-659 |
| ISSN: | 2379-139X |
| DOI: | 10.3390/tomography10050050 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.3390/tomography10050050 Verlag, kostenfrei, Volltext: https://www.mdpi.com/2379-139X/10/5/50 
|
| Verfasserangaben: | Anna Klempka, Eduardo Ackermann, Stefanie Brehmer, Sven Clausen, Christoph Groden |
| Zusammenfassung: | This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient’s cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt valves were encountered: proGAV 2.0®, M.blue®, Codman Certas®, and proSA®. These scans were compared with those obtained from non-photon-counting scanners at different time points for the same patients. The analysis of these findings demonstrated the usefulness of photon-counting technology for the clear and precise visualization of shunt valves without any additional radiation or special reconstruction patterns. The enhanced utility of photon-counting is highlighted by providing superior spatial resolution compared to other CT detectors. This technology facilitates a more accurate characterization of shunt valves and may support the detection of subtle abnormalities and a precise assessment of shunt valves. |
|---|---|
| Beschreibung: | Gesehen am 11.12.2024 |
| Beschreibung: | Online Resource |
| ISSN: | 2379-139X |
| DOI: | 10.3390/tomography10050050 |