RATIONALE AND OBJECTIVES: To evaluate a newly developed algorithm for metal artifact reduction (MAR) in Computed Tomography (CT). METHODS: A projection interpolation algorithm for MAR with threshold-based metal segmentation was developed. First, the algorithm was tested with a simulated hip phantom. On demand, the presence of metallic inserts was simulated, representing total hip endoprostheses. Second, CT data of 20 patient with total hip endoprosthesis were reconstructed with and without application of the MAR algorithm. Image quality was independently assessed by 2 experienced radiologists using a qualitative score. The results of the in vitro study were evaluated with the Student's t test. Results of the in vivo study were analyzed using a repeated-measure analysis of variance. RESULTS: Applying the MAR algorithm the phantom study showed no significant difference between images with and without simulated metal contributions. The patient study revealed improved image quality using the MAR algorithm. Results were statistically significant for fat (P=0.0097), vessels (P=0.0091), and bone (P=0.0005). Improvement of the image quality for muscle was not statistically significant (P=0.0287). CONCLUSIONS: A new algorithm for metal artifact reduction was successfully introduced into clinical routine. The algorithm led to a robust reduction of metal artifacts. The MAR algorithm may serve for an improvement in image quality in patients with metallic implants.
RATIONALE AND OBJECTIVES: To evaluate a newly developed algorithm for metal artifact reduction (MAR) in Computed Tomography (CT). METHODS: A projection interpolation algorithm for MAR with threshold-based metal segmentation was developed. First, the algorithm was tested with a simulated hip phantom. On demand, the presence of metallic inserts was simulated, representing total hip endoprostheses. Second, CT data of 20 patient with total hip endoprosthesis were reconstructed with and without application of the MAR algorithm. Image quality was independently assessed by 2 experienced radiologists using a qualitative score. The results of the in vitro study were evaluated with the Student's t test. Results of the in vivo study were analyzed using a repeated-measure analysis of variance. RESULTS: Applying the MAR algorithm the phantom study showed no significant difference between images with and without simulated metal contributions. The patient study revealed improved image quality using the MAR algorithm. Results were statistically significant for fat (P=0.0097), vessels (P=0.0091), and bone (P=0.0005). Improvement of the image quality for muscle was not statistically significant (P=0.0287). CONCLUSIONS: A new algorithm for metal artifact reduction was successfully introduced into clinical routine. The algorithm led to a robust reduction of metal artifacts. The MAR algorithm may serve for an improvement in image quality in patients with metallic implants.
Authors: Hengyong Yu; Kai Zeng; Deepak K Bharkhada; Ge Wang; Mark T Madsen; Osama Saba; Bruno Policeni; Matthew A Howard; Wendy R K Smoker Journal: Acad Radiol Date: 2007-04 Impact factor: 3.173
Authors: Laura Filograna; Nicola Magarelli; Antonio Leone; Roman Guggenberger; Sebastian Winklhofer; Michael John Thali; Lorenzo Bonomo Journal: Skeletal Radiol Date: 2015-05-12 Impact factor: 2.199
Authors: Patrick T Liu; William P Pavlicek; Mary B Peter; Mark J Spangehl; Catherine C Roberts; Robert G Paden Journal: Skeletal Radiol Date: 2009-01-14 Impact factor: 2.199