Evaluation of an optimized metal artifact reduction algorithm for flat-detector angiography compared to DSA imaging in follow-up after neurovascular procedures

评估一种优化的金属伪影减少算法在平面探测器血管造影中的应用,并将其与DSA成像在神经血管手术后随访中的应用进行比较。

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Abstract

BACKGROUND: Flat detector CT - angiography (FDCTA) has become a valuable imaging tool in post- and peri-interventional imaging after neurovascular procedures. Metal artifacts produced by radiopaque implants like clips or coils still impair image quality. METHODS: FDCTA was performed in periprocedural or follow-up imaging of 21 patients, who had received neurovascular treatment. Raw data was sent to a dedicated workstation and subsequently a metal artifact reduction algorithm (MARA) was applied. Two neuroradiologists examined the images. RESULTS: Application of MARA improved image appearance and led to a significant reduction of metal artifacts. After application of MARA only 8 datasets (34% of the images) were rated as having many or extensive artifacts, before MARA 15 (65%) of the images had extensive or many artifacts. Twenty percent more cases of reperfusion were diagnosed after application of MARA, congruent to the results of digital subtraction angiography (DSA) imaging. Also 3 (13% of datasets) images, which could not be evaluated before application of MARA, could be analyzed after metal artifact reduction and reperfusion could be excluded. CONCLUSION: Application of MARA improved image evaluation, reduced the extent of metal artifacts, and more cases of reperfusion could be detected or excluded, congruent to DSA imaging.

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