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Ultrasound Elastography: Prostate Cancer Detection Assessment Using A Phantom

Ultrasound Elastography: Prostate Cancer Detection Assessment Using A Phantom. Brett Coelho Medical Biophysics 3970Z March 26, 2013. Introduction. Prevalence and Early Detection Ultrasound Elastography Specificity and Sensitivity. B-mode Prostate Image. Introduction. Stiffness

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Ultrasound Elastography: Prostate Cancer Detection Assessment Using A Phantom

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  1. Ultrasound Elastography: Prostate Cancer Detection Assessment Using A Phantom • Brett Coelho • Medical Biophysics 3970Z • March 26, 2013

  2. Introduction • Prevalence and Early Detection • Ultrasound Elastography • Specificity and Sensitivity B-mode Prostate Image

  3. Introduction • Stiffness • Strain Images B- mode Image Strain Image

  4. Methods • Hooke’s Law • Young’s Modulus Reconstruction: Iterative

  5. Methods • Phantom Construction Phantom Ingredients

  6. Methods • Preparing Phantom Solutions • Gelatin – 70 • Agar – 80 • Formaldehyde – 90 • Glycerol – 90 • Sigma Cell • Cool Down

  7. Methods • Pouring The Moulds Prostate and Surrounding Tissue Moulds Tumor Moulds

  8. Methods • Pouring The Moulds Prostate and Sample Moulds

  9. Methods • Uniaxial Test Uniaxial Testing Machine and Cylindrical Sample

  10. Methods • Ultrasound Circular Ultrasound Array Linear Array

  11. Methods • Strain Images Strain Imaging

  12. Results • Uniaxial Results • Ratios Ep/Es=5.4 • Et1/Es=8.7 • Et2/Es = 9.3 Stress kPa Strain

  13. Results • Post Processing • Elastic Moduli Reconstruction Strain Image Frames

  14. Results • Post Processing • Ep/Es=2.2 • Et1/Es=6.0 • Et2/Es=8.9 Phantom Tissue Manual Selections

  15. Results • Tumour Mis Allocations • TM1=5.21 • TM2=5.68 B-mode Image Tumor Locating Reconstructed Image Tumor Locating

  16. Conclusions • Comparing the ratios • Tumor Misallocations

  17. Sources of Error • Strain Images • Uniaxial Test • Assumptions for Stress Calculation

  18. Future Research • Improve Detection and Modulus Calculations • Computational Time • Assumptions and Meshing

  19. Acknowledgements • Dr. Samani • Reza Mousavi • Thank you!

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