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

Abstract:

PURPOSE: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. METHOD: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. RESULTS: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 < 0.001). Thirteen (27.7 %) patients were diagnosed as equivocal using the conventional algorithm but were diagnosed with perforation (2 patients) and non-perforation (11 patients) using the MAR algorithm (equivocal rate: 27.7 % vs. 0%, P < 0.001). Using the MAR algorithm, all cases were diagnosed with perforation (6 patients, 12.8 %) or non-perforation (41 patients, 87.2 %). CONCLUSIONS:The MAR algorithm effectively reduced metal artifacts and allowed us to diagnose the presence or absence of perforation in all cases, whereas definitive diagnosis was difficult with the use of conventional algorithm in 27.7 % of cases.

journal_name

Eur J Radiol

authors

Kidoh M,Oda S,Nakato K,Sakabe D,Kanazawa H,Takashio S,Nakaura T,Nagayama Y,Sasao A,Hatemura M,Funama Y,Kaikita K,Tsujita K,Ikeda O,Azuma M,Hirai T

doi

10.1016/j.ejrad.2021.109530

subject

Has Abstract

pub_date

2021-01-09 00:00:00

pages

109530

eissn

0720-048X

issn

1872-7727

pii

S0720-048X(21)00010-3

journal_volume

136

pub_type

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