title: A pre-operative CT and non-contrast-enhanced C-arm CT registration framework for trans-catheter aortic valve implantation.
abstract: Contrast-enhanced C-arm CT is routinely used for intra-operative guidance during the trans-catheter aortic valve implantation (TAVI); however, the requirement for contrast agent injection is not preferable, especially for patients with renal insufficiencies. To address this problem, we present a novel framework for fully automatic registration of pre-operative CT and non-contrast-enhanced C-arm CT. The proposed framework provides an improved workflow and minimizes the usage of contrast agent in the TAVI procedure. Our framework consists of three steps: coarse rigid-body alignment, anatomical knowledge-based prior deformation field generation, and fine deformable registration. We validated the proposed framework on 20 real patient data sets. Based on the 20 data sets, the mesh-to-mesh errors at the aortic root from different methods are measured. Our proposed method significantly outperforms the other state-of-the-art methods. Specifically, we achieve the registration accuracy at 1.76±0.43 mm which is clinically plausible. Quantitative evaluation on real non-contrast enhanced C-arm CT data sets confirms the applicability in the clinical usage. The proposed heart registration method is generic and hence can be easily applied to other cardiac applications.
authors.affiliation: NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 117456 Singapore, Singapore. Electronic address: migang.michong@gmail.com.
authors.forename: Yongning
authors.initials: Y
authors.lastname: Lu
authors.affiliation: Department of Electrical and Computer Engineering, National University of Singapore, 117583 Singapore, Singapore.
authors.forename: Ying
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Siemens Corporation, Corporate Research and Technology, Princeton, NJ 08540, USA.
authors.forename: Rui
authors.initials: R
authors.lastname: Liao
authors.affiliation: NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 117456 Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, 117583 Singapore, Singapore.
authors.forename: Sim Heng
authors.initials: SH
authors.lastname: Ong
mesh_terms: D059925:Anatomic Landmarks / Q000000981:diagnostic imaging; D001021:Aortic Valve / Q000000981:diagnostic imaging* / Q000601:surgery*; D003287:Contrast Media; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011300:Preoperative Care / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D065467:Transcatheter Aortic Valve Replacement / Q000379:methods*
chemical_list: D003287:Contrast Media
keywords: Image registration; Non-contrast-enhanced C-arm CT; Pre-operative CT; TAVI