title: [The application of 3D liver acquisition volume acceleration integrated with array spatial sensitivity encoding technique in liver dynamic-enhancement scanning].
abstract: OBJECTIVE
  To evaluate the application of 3D liver acquisition volume acceleration (3D-LAVA) integrated with array spatial sensitivity encoding technique (ASSET) in liver dynamic-enhancement scanning.
  
  
  METHODS
  One hundred forty-seven patients underwent conventional plain and contrast enhancement liver MR imaging. 3D-LAVA and 2D fast spoiled gradient recalled echo were used for contrast enhancement liver MR scanning in 90 and 57 patients respectively. In the 3D-LAVA group, integrated ASSET was used in 72 out of the 90 patients. Of the 57 patients who underwent examinations using 2D fast spoiled gradient recalled echo, portal vein CE-MRA was performed on 20. The ability of 3D-LAVA to detect the lesions and the advantage to shorten the acquisition time after integrating with ASSET were analyzed. Original images of 60 patients in the 3D-LAVA group were processed using MIP to illustrate the anatomy of the portal vein. They were compared with those shown by CE-MRA to evaluate the illustration abilities of the two approaches.
  
  
  RESULTS
  3D-LAVA is more sensitive than 2D-FSPGR in detecting metastatic hepatic carcinomas. In the 3D-LAVA group integrated with ASSET, earlier and peak arterial phase images were acquired in 34 cases; and earlier, peak and late arterial phase images were acquired in 23 cases. The illustrations of the portal vein anatomy by 3D-LAVA were similar to those shown by portal vein CE-MRA.
  
  
  CONCLUSIONS
  3D-LAVA integrated with ASSET can obtain higher quality multi-phase dynamic enhancement images of the liver in a shorter time, and in the meantime also shows the vascular anatomy.
authors.affiliation: Department of Radiology, Second Affiliated Hospital of Chongqing University of Medical Sciences, Chongqing 400010, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wu
authors.forename: Jian-nong
authors.initials: JN
authors.lastname: Zhao
authors.forename: Da-jing
authors.initials: DJ
authors.lastname: Guo
authors.forename: Wei-bo
authors.initials: WB
authors.lastname: Xie
authors.forename: Wei-jia
authors.initials: WJ
authors.lastname: Zhong
authors.forename: Yin-deng
authors.initials: YD
authors.lastname: Luo
authors.forename: Wei-juan
authors.initials: WJ
authors.lastname: Chen
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003287:Contrast Media; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008099:Liver / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity; D055815:Young Adult
chemical_list: D003287:Contrast Media