title: Utility of three-dimensional reconstruction of coronary angiography to guide percutaneous coronary intervention.
abstract: OBJECTIVE
  The goal of this study was to determine whether three-dimensional (3D) reconstruction of traditional coronary angiography could optimize the choice of drug-eluting stent (DES) length and number during percutaneous coronary intervention (PCI).
  
  
  BACKGROUND
  Coronary angiography is subject to significant foreshortening artifact that limits the ability of the operator to accurately determine lesion length.
  
  
  METHODS
  The angiographic images of the target vessels of consecutive PCI procedures were postprocessed using a 3D reconstruction algorithm. The appropriate length and optimal number of DES to span each target lesion were calculated and compared with the number and length of DES actually chosen by the operator.
  
  
  RESULTS
  A total of 42 target vessels were analyzed, and 3D reconstruction was successful in 38/42 (90.5%) of cases. The results of 3D analysis would have changed operator decision making in six cases (16%): in four cases, the stent chosen by the operator was too short requiring an additional DES; in two cases, the chosen DES was too long and exchanged for a shorter one. In each of these six cases, 3D analysis would have determined the correct stent length prior to stent selection. The optimal stent number derived by 3D reconstruction was significantly less than the actual number of stents per lesion used by the operator (1.31 +/- 0.47 versus 1.54 +/- 0.68, P = 0.01), and the optimal stent length trended less than the actual stented length (27.5 +/- 12.8 mm versus 28.7 +/- 14.7 mm, P = 0.23).
  
  
  CONCLUSIONS
  3D reconstruction algorithm of standard coronary angiography is a promising technique to improve DES utilization during PCI.
authors.affiliation: Division of Cardiovascular Diseases, Scripps Clinic, 10666 North Torrey Pines Road, La Jolla, CA 92037, USA.
authors.forename: Raghava R
authors.initials: RR
authors.lastname: Gollapudi
authors.forename: Rafael
authors.initials: R
authors.lastname: Valencia
authors.forename: Steve S
authors.initials: SS
authors.lastname: Lee
authors.forename: Garrett B
authors.initials: GB
authors.lastname: Wong
authors.forename: Paul S
authors.initials: PS
authors.lastname: Teirstein
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Price
mesh_terms: D000465:Algorithms; D015906:Angioplasty, Balloon, Coronary / Q000295:instrumentation; D019917:Blood Vessel Prosthesis Implantation / Q000295:instrumentation; D002317:Cardiovascular Agents / Q000627:therapeutic use; D017023:Coronary Angiography; D023903:Coronary Restenosis / Q000209:etiology / Q000517:prevention & control; D023921:Coronary Stenosis / Q000000981:diagnostic imaging* / Q000628:therapy*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007166:Immunosuppressive Agents / Q000627:therapeutic use; D017239:Paclitaxel / Q000627:therapeutic use; D011237:Predictive Value of Tests; D011474:Prosthesis Design / Q000295:instrumentation; D012107:Research Design; D020123:Sirolimus / Q000627:therapeutic use; D015607:Stents; D016896:Treatment Outcome
chemical_list: D002317:Cardiovascular Agents; D007166:Immunosuppressive Agents; D017239:Paclitaxel; D020123:Sirolimus