title: CT-based automated planning of acetabular cup for total hip arthroplasty (THA) based on hybrid use of two statistical atlases.
abstract: OBJECTIVE
  This study describes the use of CT images in atlas-based automated planning methods for acetabular cup implants in total hip arthroplasty (THA). The objective of this study is to develop an automated cup planning method considering the statistical distribution of the residual thickness.
  
  
  METHODS
  From a number of past THA planning datasets, we construct two statistical atlases that represent the surgeon's expertise. The first atlas is a pelvis-cup merged statistical shape model (PC-SSM), which encodes global spatial relationships between the patient anatomy and implant. The other is a statistical residual thickness map (SRTM) of the implant surface, which encodes local spatial constraints of the anatomy and implant. In addition to PC-SSM and SRTM, we utilized the minimum thickness as a threshold constraint to prevent penetration.
  
  
  RESULTS
  The proposed method was applied to the pelvis shapes segmented from CT images of 37 datasets of osteoarthritis patients. Automated planning results with manual segmentation were compared to the plans prepared by an experienced surgeon. There was no significant difference in the average cup size error between the two methods (1.1 and 1.2 mm, respectively). The average positional error obtained by the proposed method, which integrates the two atlases, was significantly smaller (3.2 mm) than the previous method, which uses single atlas (3.9 mm). In the proposed method with automated segmentation, the size error of the proposed method for automated segmentation was comparable (1.1 mm) to that for manual segmentation (1.1 mm). The average positional error was significantly worse (4.2 mm) than that using manual segmentation (3.2 mm). If we only consider mildly diseased cases, however, there was no significance between them (3.2 mm in automated and 2.6 mm in manual segmentation).
  
  
  CONCLUSIONS
  We infer that integrating PC-SSM and SRTM is a useful approach for modeling experienced surgeon's preference during cup planning.
authors.affiliation: Graduate Faculty of Interdisciplinary Research, University of Yamanashi, 4-3-11, Takeda, Kofu, Yamanashi, Japan.
authors.forename: Yoshiyuki
authors.initials: Y
authors.lastname: Kagiyama
authors.affiliation: Graduate School of Engineering, Kobe University, 1-1, Rokkodai, Nada, Kobe, Japan.|Department of Radiology, Graduate School of Medicine, Osaka University, 2-2, Yamadaoka, Suita, Osaka, Japan.|Canon Inc., 3-30-2, Shimomaruko, Ota, Tokyo, Japan.
authors.forename: Itaru
authors.initials: I
authors.lastname: Otomaru
authors.affiliation: Department of Orthopaedic Surgery, Graduate School of Medicine, Osaka University, 2-2, Yamadaoka, Suita, Osaka, Japan.
authors.forename: Masaki
authors.initials: M
authors.lastname: Takao
authors.affiliation: Department of Orthopaedic Medical Engineering, Graduate School of Medicine, Osaka University, 2-2, Yamadaoka, Suita, Osaka, Japan.
authors.forename: Nobuhiko
authors.initials: N
authors.lastname: Sugano
authors.affiliation: Department of Radiology, Graduate School of Medicine, Osaka University, 2-2, Yamadaoka, Suita, Osaka, Japan.|EBM Inc., 4-6-15, Omoriminami, Ota, Tokyo, Japan.
authors.forename: Masahiko
authors.initials: M
authors.lastname: Nakamoto
authors.affiliation: Graduate School of Information Science, Nara Institute of Science and Technology (NAIST), 8916-5, Takayama, Ikoma, Nara, Japan.
authors.forename: Futoshi
authors.initials: F
authors.lastname: Yokota
authors.affiliation: Department of Radiology, Graduate School of Medicine, Osaka University, 2-2, Yamadaoka, Suita, Osaka, Japan.
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Tomiyama
authors.affiliation: Graduate School of System Informatics, Kobe University, 1-1, Rokkodai, Nada, Kobe, Japan.
authors.forename: Yukio
authors.initials: Y
authors.lastname: Tada
authors.affiliation: Graduate School of Information Science, Nara Institute of Science and Technology (NAIST), 8916-5, Takayama, Ikoma, Nara, Japan. yoshi@is.naist.jp.
authors.forename: Yoshinobu
authors.initials: Y
authors.lastname: Sato
mesh_terms: D000077:Acetabulum / Q000000981:diagnostic imaging* / Q000601:surgery; D019644:Arthroplasty, Replacement, Hip / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D015207:Osteoarthritis, Hip / Q000601:surgery*; D010388:Pelvis / Q000000981:diagnostic imaging / Q000601:surgery; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods
keywords: Computer-assisted surgery; Implant surgery; Multi-object statistical shape model; Residual bone thickness; Surgeon’s expertise; Surgical planning