Assessment of cardiac implantable electric device lead perforation using a metal artifact reduction algorithm in cardiac computed tomography

•Accurate image-based diagnosis of lead perforation is critically important.•Metal artefacts caused by the lead tip affect the image quality.•Metal artefacts make a definitive diagnosis of perforation challenging.•The MAR algorithm effectively reduced metal artefacts.•The MAR algorithm allowed us to...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:European journal of radiology 2021-03, Vol.136, p.109530-109530, Article 109530
Hauptverfasser: Kidoh, Masafumi, Oda, Seitaro, Nakato, Kengo, Sakabe, Daisuke, Kanazawa, Hisanori, Takashio, Seiji, Nakaura, Takeshi, Nagayama, Yasunori, Sasao, Akira, Hatemura, Masahiro, Funama, Yoshinori, Kaikita, Koichi, Tsujita, Kenichi, Ikeda, Osamu, Azuma, Minako, Hirai, Toshinori
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•Accurate image-based diagnosis of lead perforation is critically important.•Metal artefacts caused by the lead tip affect the image quality.•Metal artefacts make a definitive diagnosis of perforation challenging.•The MAR algorithm effectively reduced metal artefacts.•The MAR algorithm allowed us to diagnose lead perforation in all cases. CT is considered the non-invasive gold standard for evaluating cardiac implantable electronic devices (CIEDs) lead perforation, but metal artifacts caused by the lead tip affect the image quality and make a definitive diagnosis challenging. We compared the performances of the metal artifact reduction (MAR) algorithm and the conventional algorithm for identification of the right ventricular (RV) lead tip position in cardiac CT studies of patients with CIEDs. Forty-seven consecutive patients (26 men; age 70.3 ± 15.4 years) with CIEDs underwent cardiac CT. Using the conventional and MAR algorithm, two image reconstructions were performed for each scan. We calculated the artifact index (AI) to assess the quantitative capability of the MAR algorithm for artifact reduction and visually assessed the RV lead tip position on both images as follows: non-perforation, perforation, and equivocal. The mean AIs were significantly lower with the MAR algorithm than with the conventional algorithm (96.7 ± 40.1 HU vs. 284.6 ± 134.1 HU, P 
ISSN:0720-048X
1872-7727
DOI:10.1016/j.ejrad.2021.109530