CT-based automated preoperative planning of acetabular cup size and position using pelvis cup integrated statistical shape...
Outline <ul><li>Introduction </li></ul><ul><li>Methods </li></ul><ul><ul><li>Cup planning of mildly and severely diseased ...
Outline <ul><li>Introduction </li></ul><ul><li>Methods </li></ul><ul><ul><li>Cup planning of mildly and severely diseased ...
<ul><li>Surgical CAD/CAM  is one of common frameworks of CAOS.  </li></ul><ul><li>The CAM system  ensure accurate executio...
<ul><li>In this framework,  a large number of surgical data and preoperative plans are accumulated  in some of the hospita...
Objective <ul><li>Our objective is  to automate the preoperative planning  to reduce its time consuming nature by utilizin...
Outline <ul><li>Introduction </li></ul><ul><li>Methods </li></ul><ul><ul><li>Cup planning of mildly and severely diseased ...
Cup planning of mildly and severely diseased pelvises: Our problem Mildly diseased case Severely diseased case <ul><li>In ...
Pelvis-cup statistical shape model (PC-SSM) <ul><li>We embed  spatial relations between pelvis and cup , which are regarde...
Pelvis-cup statistical shape model (PC-SSM) <ul><li>Given training datasets of cup plans prepared by experienced surgeon, ...
Automated planning procedure <ul><li>The statistical shape model is roughly registered to the segmented patient’s pelvis. ...
Automated planning procedure <ul><li>Shape parameter of the statistical atlas is optimized  so as to the difference betwee...
Automated planning procedure <ul><li>Cup size and position are estimated using determined cup surface. </li></ul>White: Pa...
Outline <ul><li>Introduction </li></ul><ul><li>Methods </li></ul><ul><ul><li>Cup planning of mildly and severely diseased ...
Conditions <ul><li>28 cases (used for actual THA surgery via a navigation system)  were used for atlas construction and ev...
Results <ul><li>Mean size error:  1.4 mm (proposed), 2.1 mm (previous) </li></ul><ul><li>Mean positional error : 4.2 mm (p...
Results of illustrative case  <ul><li>Same size was selected in the proposed method as the surgeon’s plan while the size e...
Outline <ul><li>Introduction </li></ul><ul><li>Methods </li></ul><ul><ul><li>Cup planning of mildly and severely diseased ...
Discussions <ul><li>The proposed method shows better performance  for size selection than the previous method.  </li></ul>...
<ul><li>In principle, given a sufficient number of planning datasets that a surgeon planned, the method is applicable to v...
Thank you for your attention This research was supported in part by  Stryker Japan K. K. and Biovisiq Japan, Inc.
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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

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