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Pre-synopsis Seminar

Pre-synopsis Seminar. Geometric reasoning for Tumour joint reconstructive surgery planning. K. Subburaj (05410004). Guide Prof. B. Ravi. IIT Bombay 2009-04-27. Overview. Introduction Literature Review Problem Definition Research Methodology Experimental Plan

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Pre-synopsis Seminar

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  1. Pre-synopsis Seminar Geometric reasoning for Tumour joint reconstructive surgery planning K. Subburaj (05410004) Guide Prof. B. Ravi IIT Bombay 2009-04-27

  2. Overview • Introduction • Literature Review • Problem Definition • Research Methodology • Experimental Plan • Results and Discussion • Conclusions

  3. Introduction • Bone tumours (Osteosarcoma) • 6th leading cancer (35%) • 3rd leading cancer in adults • 80 % in joints (70 % in knee) • Limb Salvage Surgery: • allografts/ autografts/ prosthetic reconstruction • Endoprosthetic Replacement • recurrence, infection, aseptic loosening, fracture • more than 70% survival rate reported (5 years) • need to focus on functional outcome Courtesy: Dr. Manish Agarwal, Mumbai

  4. Literature Review – Conclusions • Major causes of failures and functional deficiency are • unconsidered bony deformities, • over or under-sized prosthesis components, • poor alignment of prostheses • Surgical outcome depends on surgeon’s skills and lack in robustness • Limited work on CAOS for tumour joint reconstructive surgery • Increasing need for patient-specific surgery planning • anatomical variations, unique challenge • Modularity increases difficulties in selecting prosthesis • No work reported on selection and positioning of tumour prosthesis • No systematic methodology to evaluate suitability for a patient • Highly interactive, subjective, and time-consuming pre-op planning

  5. Problem Definition • Research Goal • ‘a set of geometric reasoning methods for pre-operative recognition and analysis of anatomical features of a patient's limb to enable accurate tumour resection, better fixation, selection and position of prosthesis and thereby maximising the effectiveness of joint reconstructive surgery’ • Research Objectives • Development and validation of computer-aided methods for: • recognizing anatomical landmarks and labelling them for referencing • evaluating major anatomical deformities • optimally aligning prosthetic components in patient’s anatomical model • evaluating anatomical suitability of the prosthetic replacement

  6. Research Methodology Diagnostic imaging 3D Reconstruction and visualisation Landmarks Tumour resection Anat. dimensions Prosthesis selection Bone stock thickness Prosthesis positioning Deformities Pre-operative plan

  7. Mathematical Model Gauss- Bonnet theorem for polygonal cases (DoCarmo, 1976) Gaussian Curvature Peak Pit Mean Curvature Ridge Ravine

  8. Algorithm Results Medial tibial spine Lateral tibial spine Medial peak Lateral peak Lateral Peak Medial Peak Adductor magnus tubercle Lateral Epicondyle Medial epicondyle Tibial Tuberosity Medial distal point Lateral distal point Max Min

  9. Conclusions • New approach to recognize anatomical landmarks • Supported by geometry-driven fuzzy-logic decision tree • Successfully implemented in a 3D software and tested • Accuracy (< 2 mm error) comparable to expert surgeons • Useful for orthopedic implant surgery planning • Leading to more accurate outcomes. Thank You!

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