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CT-based Automated Preoperative Planning of Acetabular Cup Size and Position using Pelvis-cup Integrated Statistical Shape Model
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CT-based Automated Preoperative Planning of Acetabular Cup Size and Position using Pelvis-cup Integrated Statistical Shape Model

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  • 1. CT-based automated preoperative planning of acetabular cup size and position using pelvis cup integrated statistical shape model Itaru OTOMARU a , Kazuto Kobayashi a , Toshiyuki OKADA b , Masahiko NAKAMOTO b , Masaki TAKAO b , Nobuhiko SUGANO b , Yukio TADA a and Yoshinobu SATO b a Graduate School of Engineering, Kobe University b Graduate School of Medicine, Osaka University
  • 2. Outline
    • Introduction
    • Methods
      • Cup planning of mildly and severely diseased pelvises
      • Construction of pelvis-cup integrated statistical shape model
      • Automated planning procedure
    • Experimental results
    • Discussions and future direction
  • 3. Outline
    • Introduction
    • Methods
      • Cup planning of mildly and severely diseased pelvises
      • Construction of pelvis-cup integrated statistical shape model
      • Automated planning procedure
    • Experimental results
    • Discussions and future direction
  • 4.
    • Surgical CAD/CAM is one of common frameworks of CAOS.
    • The CAM system ensure accurate execution of preoperative plans prepared using the CAD system .
    Surgical CAD/CAM Image acquisition CAD CAM Therefore, the quality of preoperative planning is becoming more critical. Preoperative planning Intraoperative assistance
  • 5.
    • In this framework, a large number of surgical data and preoperative plans are accumulated in some of the hospitals .
    • The feedback of these past planning can potentially improve the future planning.
    Atlas-based closed-loop surgery Image acquisition Statistical Surgical Atlas Statistical Analysis Patient’s data Pre-op plans Surgical log Intra-op data Atlas based preoperative planning Preoperative planning Intraoperative assistance Database of 3D/4D Patient & Surgical Data
  • 6. Objective
    • Our objective is to automate the preoperative planning to reduce its time consuming nature by utilizing the accumulated past planning data.
    • To achieve this, we construct a statistical atlas which models the expertise of the experienced surgeons .
    • We target acetabular cup planning for total hip arthroplasty.
  • 7. Outline
    • Introduction
    • Methods
      • Cup planning of mildly and severely diseased pelvises
      • Construction of pelvis-cup integrated statistical shape model
      • Automated planning procedure
    • Experimental results
    • Discussions and future direction
  • 8. Cup planning of mildly and severely diseased pelvises: Our problem Mildly diseased case Severely diseased case
    • In cup planning, it is somewhat difficult to predict the original anatomy for severely diseased acetabulum due to its severe deformation and shift.
  • 9. Pelvis-cup statistical shape model (PC-SSM)
    • We embed spatial relations between pelvis and cup , which are regarded as expertise of the surgeon, into SSM.
    Pelvis-cup statistical shape model Training datasets Principal component analysis
  • 10. Pelvis-cup statistical shape model (PC-SSM)
    • Given training datasets of cup plans prepared by experienced surgeon, merger of pelvis and cup surfaces of each plan is considered as one shape to construct SSM.
    Pelvis-cup statistical shape model Training datasets Principal component analysis
  • 11. Automated planning procedure
    • The statistical shape model is roughly registered to the segmented patient’s pelvis.
    White: Patient’s pelvis Yellow: Pelvis part of statistical atlas Red: Cup part of statistical atlas
  • 12. Automated planning procedure
    • Shape parameter of the statistical atlas is optimized so as to the difference between the pelvis part of the statistical atlas and the patient’s pelvis shape is minimized.
    White: Patient’s pelvis Yellow: Pelvis part of statistical atlas Red: Cup part of statistical atlas
  • 13. Automated planning procedure
    • Cup size and position are estimated using determined cup surface.
    White: Patient’s pelvis Yellow: Pelvis part of statistical atlas Red: Cup part of statistical atlas
  • 14. Outline
    • Introduction
    • Methods
      • Cup planning of mildly and severely diseased pelvises
      • Construction of pelvis-cup integrated statistical shape model
      • Automated planning procedure
    • Experimental results
    • Discussions and future direction
  • 15. Conditions
    • 28 cases (used for actual THA surgery via a navigation system) were used for atlas construction and evaluation.
    • Leave-one-out cross validation was used for evaluation.
    • We compared with the previous method [CAOS 2004] which was based on user-specified constraints obtained from surgeon’s interview.
    • Error was defined as the difference between the automated plan and the surgeon’s plan.
  • 16. Results
    • Mean size error: 1.4 mm (proposed), 2.1 mm (previous)
    • Mean positional error : 4.2 mm (proposed), 4.3 mm (previous)
    • Number of cases of penetration : 4 (proposed), 0 (previous)
    Mean size error was smaller in the proposed method. However, cup penetration occurred in four cases.
  • 17. Results of illustrative case
    • Same size was selected in the proposed method as the surgeon’s plan while the size error of the previous method was 8 mm.
    Previous Proposed Surgeon’s Size 58 Size 50 Size 50
  • 18. Outline
    • Introduction
    • Methods
      • Cup planning of mildly and severely diseased pelvises
      • Construction of pelvis-cup integrated statistical shape model
      • Automated planning procedure
    • Experimental results
    • Discussions and future direction
  • 19. Discussions
    • The proposed method shows better performance for size selection than the previous method.
    Statistically derived constraints could be successfully incorporated and are shown to be useful.
      • On the other hand, statistical constraints are insufficient to avoid the cup penetration.
    To avoid the penetration, we will add the constraints based on residual bone thickness between pelvis and cup.
  • 20.
    • In principle, given a sufficient number of planning datasets that a surgeon planned, the method is applicable to various implants for different bones.
    • We are planning to apply the method to the femoral stem .
    Future direction Femur-stem combined statistical atlas
  • 21. Thank you for your attention This research was supported in part by Stryker Japan K. K. and Biovisiq Japan, Inc.