title: Three-dimensional renal CT angiography for guiding segmental renal artery clamping during laparoscopic partial nephrectomy.
abstract: OBJECTIVE
  To evaluate the effectiveness of three-dimensional (3D) renal computed tomography angiography (CTA) in guiding segmental renal artery clamping during laparoscopic partial nephrectomy (LPN).
  
  
  METHODS
  Forty-three patients with renal tumours undergoing renal CTA before LPN were retrospectively enrolled in this study. 3D arteriogram reconstructed images were created to identify the renal tumour-supplying arteries. The number and location of these targeted vessels were annotated on 3D images preoperatively and compared with the clamped vessels during LPN. The consistency between target vessels annotated at CTA and clamped arteries at LPN was compared both using a patient-based analysis and vessel-based analysis. The χ(2) test was applied to analyse the influence of tumour size, location, and growth pattern on the number of clamped segmental renal branches.
  
  
  RESULTS
  On patient-based analysis, the number of targeted vessels was consistent with the clamped vessels during LPN in 33 of 43 patients. On vessel-based analysis, 56 of 65 target vessels annotated at CTA were clamped during LPN. More segmental renal branches (p = 0.04) were clamped in patients with tumours of larger size. Tumour location and growth pattern had no association with the number of clamped segmental branches during LPN.
  
  
  CONCLUSIONS
  High-quality CTA images and 3D reconstruction images can detect detailed information of tumour-supplying arteries to renal tumours. 3D renal CTA is an effective way to guide segmental renal artery clamping during LPN.
authors.affiliation: Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Xu
authors.forename: Pengfei
authors.initials: P
authors.lastname: Shao
authors.forename: Xiaomei
authors.initials: X
authors.lastname: Zhu
authors.forename: Qiang
authors.initials: Q
authors.lastname: Lv
authors.forename: Wangyan
authors.initials: W
authors.lastname: Liu
authors.forename: Hai
authors.initials: H
authors.lastname: Xu
authors.forename: Yinsu
authors.initials: Y
authors.lastname: Zhu
authors.forename: Guangyu
authors.initials: G
authors.lastname: Yang
authors.forename: Lijun
authors.initials: L
authors.lastname: Tang
authors.forename: Changjun
authors.initials: C
authors.lastname: Yin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003250:Constriction; D003287:Contrast Media; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007472:Iohexol / Q000031:analogs & derivatives; D010535:Laparoscopy / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009392:Nephrectomy / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D012077:Renal Artery / Q000000981:diagnostic imaging*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; D007472:Iohexol; C038192:iopromide