scholarly journals Dual Energy CT (DECT) Monochromatic Imaging: Added Value of Adaptive Statistical Iterative Reconstructions (ASIR) in Portal Venography

PLoS ONE ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. e0156830 ◽  
Author(s):  
Liqin Zhao ◽  
Sebastian Winklhofer ◽  
Rong Jiang ◽  
Xinlian Wang ◽  
Wen He
2018 ◽  
Vol 211 (3) ◽  
pp. 571-579 ◽  
Author(s):  
Bhavik N. Patel ◽  
Michael Rosenberg ◽  
Federica Vernuccio ◽  
Juan Carlos Ramirez-Giraldo ◽  
Rendon Nelson ◽  
...  

2011 ◽  
Vol 38 (12) ◽  
pp. 6371-6379 ◽  
Author(s):  
Lifeng Yu ◽  
Jodie A. Christner ◽  
Shuai Leng ◽  
Jia Wang ◽  
Joel G. Fletcher ◽  
...  

2018 ◽  
Vol 28 (6) ◽  
pp. 2525-2534 ◽  
Author(s):  
Sang Min Lee ◽  
Se Hyung Kim ◽  
Su Joa Ahn ◽  
Hyo-Jin Kang ◽  
Ji Hee Kang ◽  
...  

2016 ◽  
Vol 58 (1) ◽  
pp. 62-69 ◽  
Author(s):  
Fengdan Wang ◽  
Yan Zhang ◽  
Huadan Xue ◽  
Wei Han ◽  
Xianda Yang ◽  
...  

Background Spinal fusion surgery is an important procedure for treating spinal diseases and computed tomography (CT) is a critical tool for postoperative evaluation. However, CT image quality is considerably impaired by metal artifacts and image noise. Purpose To explore whether metal artifacts and image noise can be reduced by combining two technologies, adaptive statistical iterative reconstruction (ASIR) and monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. Material and Methods A total of 51 patients with 318 spinal pedicle screws were prospectively scanned by dual-energy CT using fast kV-switching GSI between 80 and 140 kVp. Monochromatic GSI images at 110 keV were reconstructed either without or with various levels of ASIR (30%, 50%, 70%, and 100%). The quality of five sets of images was objectively and subjectively assessed. Results With objective image quality assessment, metal artifacts decreased when increasing levels of ASIR were applied ( P < 0.001). Moreover, adding ASIR to GSI also decreased image noise ( P < 0.001) and improved the signal-to-noise ratio ( P < 0.001). The subjective image quality analysis showed good inter-reader concordance, with intra-class correlation coefficients between 0.89 and 0.99. The visualization of peri-implant soft tissue was improved at higher ASIR levels ( P < 0.001). Conclusion Combined use of ASIR and GSI decreased image noise and improved image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels ≥70%.


2017 ◽  
Vol 6 (2) ◽  
pp. 205846011769346 ◽  
Author(s):  
Masafumi Kidoh ◽  
Daisuke Utsunomiya ◽  
Seitaro Oda ◽  
Takeshi Nakaura ◽  
Yoshinori Funama ◽  
...  

Background An optimal metal artifact reduction (MAR) technique is needed for a reliable and accurate image-based diagnosis. Purpose Using a 320-row scanner, we compared the dual-energy computed tomography (CT)-based monochromatic and the single-energy metal artifact reduction (SEMAR) techniques for CT venography (CTV) to identify the better imaging method for diagnosing deep vein thrombosis (DVT) in patients who had undergone knee replacement surgery. Material and Methods Twenty-three consecutive patients with suspected DVT after unilateral knee replacement surgery underwent dual-energy CT (135/80 kVp). Monochromatic images of 35–135 keV were generated; the monochromatic image with the best signal-to-noise ratio (SNR) of the popliteal vein near the metal prosthesis were selected. The projection data of 80 kVp were reconstructed using MAR algorithm. The mean SNR ON MAR and the best SNR ON monochromatic images were compared. Two radiologists evaluated visualization of the metal artifacts on a four-point scale where 1 = extensive artifacts, 2 = strong artifacts, 3 = mild artifacts, and 4 = minimal artifacts. Results The mean SNR was significantly higher on the MAR than the monochromatic images (12.8 ± 4.7 versus 7.7 ± 5.1, P < 0.01) and the visual scores were significantly higher for MAR than monochromatic images (2.6 ± 0.8 versus 1.3 ± 0.4, P < 0.01). Conclusion For CTV after knee replacement surgery, the MAR technique is superior to the monochromatic imaging technique.


2015 ◽  
Vol 205 (3) ◽  
pp. W352-W359 ◽  
Author(s):  
Heba S. Takrouri ◽  
Mutaz M. Alnassar ◽  
Afsaneh Amirabadi ◽  
Paul S. Babyn ◽  
Rahim Moineddin ◽  
...  

2013 ◽  
Vol 37 (4) ◽  
pp. 618-625 ◽  
Author(s):  
Jian Dong ◽  
Xiaoying Wang ◽  
Xuexiang Jiang ◽  
Li Gao ◽  
Feiyu Li ◽  
...  

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