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Kinetic Modeling

Kinetic Modeling. Edward Di Bella Dmitri Riabkov Harshali Bal Sathya Vijayakumar. Outline. Introduction to kinetic modeling Challenges 1. Formulation/selection of physiological model 2. Obtaining accurate input functions 3. Noise issues - optimal data groupings

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Kinetic Modeling

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  1. Kinetic Modeling Edward Di Bella Dmitri Riabkov Harshali Bal Sathya Vijayakumar

  2. Outline Introduction to kinetic modeling Challenges 1. Formulation/selection of physiological model 2. Obtaining accurate input functions 3. Noise issues - optimal data groupings 4. Noise issues - optimal reconstruction, non-linear optimization, use of constraints Applications

  3. Introduction Examples of tracer kinetics: • Intravascular (99mTc-albumin, MS-325) • Extracellular (gadolinium-DTPA) • Intracellular (99mTc-Sestamibi, 99mTc-Teboroxime) • More complex uptake and washout characteristics, including changes of state, binding (18FDG)

  4. Semi-quantitative Models Area under curve Upslope Percent Enhancement

  5. Tissue - Intracellular Two Compartments Tissue - Interstitial (ve) k capillary Vascular - plasma Vascular - red blood cells E = extraction, F = flow, t =time =volume of extravascular space

  6. Axial concentration gradient Tissue capillary Vascular - plasma (Cp) Vascular - red blood cells (Hct)

  7. Model with capillary transit time

  8. Early contrast 28 beats later FIESTA image 8 regions Canine Study (LAD occlusion)

  9. (a) (b) (c) 7 2 Myocardial Perfusion with Contrast MRI Region number (e) (d)

  10. Tissue - Intracellular Infarct - volume of distribution changes Tissue - ve Vascular - plasma (Cp) Vascular - red blood cells Normal Infarct

  11. Myocardial viability

  12. MRI and PET Viability (Upper panels) Non-viable apical region shown with FDG-PET, left, and contrast enhanced MRI, right. (Lower panels) Non-viable inferoposterior region shown with FDG-PET, left, and contrast enhanced MRI, right. Arrows indicate regions of non-viability.

  13. Input Function - challenges • MRI • Saturation • Flow effects • Dynamic PET and SPECT • Blood binding • Temporal sampling rate • Solution: Blind estimation of kinetic parameters

  14. Static SPECT: Dynamic SPECT: 20-30s 90-100s 290-300s 490-500s

  15. University of Utah

  16. SUMMARY Kinetic modeling is a very useful approach with many applications Numerous important and interesting research areas: • Acquisition • Automated robust processing • Input function • Modeling • Visualization and use of parametric images

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