Georg Bier1, Malte Niklas Bongers2, Johann-Martin Hempel3, Anja Örgel3, Till-Karsten Hauser3, Ulrike Ernemann3, Florian Hennersdorf3. 1. Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany. georg.bier@med.uni-tuebingen.de. 2. Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany. 3. Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany.
Abstract
PURPOSE: This paper aims to evaluate a new iterative metal artifact reduction algorithm for post-interventional evaluation of brain tissue and intracranial arteries. METHODS: The data of 20 patients that underwent follow-up cranial CT and cranial CT angiography after clipping or coiling of an intracranial aneurysm was retrospectively analyzed. After the images were processed using a novel iterative metal artifact reduction algorithm, images with and without metal artifact reduction were qualitatively evaluated by two readers, using a five-point Likert scale. Moreover, artifact strength was quantitatively assessed in terms of CT attenuation and standard deviation alterations. RESULTS: The qualitative analysis yielded a significant increase in image quality (p = 0.0057) in iteratively processed images with substantial inter-observer agreement (ĸ = 0.72), while the CTA image quality did not differ (p = 0.864) and even showed vessel contrast reduction in six cases (30%). The mean relative attenuation difference was 27% without metal artifact reduction vs. 11% for iterative metal artifact reduction images (p = 0.0003). CONCLUSIONS: The new iterative metal artifact reduction algorithm enhances non-enhanced CT image quality after clipping or coiling, but in CT-angiography images, the contrast of adjacent vessels can be compromised.
PURPOSE: This paper aims to evaluate a new iterative metal artifact reduction algorithm for post-interventional evaluation of brain tissue and intracranial arteries. METHODS: The data of 20 patients that underwent follow-up cranial CT and cranial CT angiography after clipping or coiling of an intracranial aneurysm was retrospectively analyzed. After the images were processed using a novel iterative metal artifact reduction algorithm, images with and without metal artifact reduction were qualitatively evaluated by two readers, using a five-point Likert scale. Moreover, artifact strength was quantitatively assessed in terms of CT attenuation and standard deviation alterations. RESULTS: The qualitative analysis yielded a significant increase in image quality (p = 0.0057) in iteratively processed images with substantial inter-observer agreement (ĸ = 0.72), while the CTA image quality did not differ (p = 0.864) and even showed vessel contrast reduction in six cases (30%). The mean relative attenuation difference was 27% without metal artifact reduction vs. 11% for iterative metal artifact reduction images (p = 0.0003). CONCLUSIONS: The new iterative metal artifact reduction algorithm enhances non-enhanced CT image quality after clipping or coiling, but in CT-angiography images, the contrast of adjacent vessels can be compromised.
Entities:
Keywords:
Aneurysm; Artifacts; Computed tomography; Computed tomography angiography; Head
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