Multiresolution imaging of in-vivo ligand-receptor interactions

Philippe Thevenaz; Philippe Millet

doi:10.1117/12.428132

21 May 2001 Multiresolution imaging of in-vivo ligand-receptor interactions

Philippe Thevenaz, Philippe Millet

Proceedings Volume 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images; (2001) https://doi.org/10.1117/12.428132
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

The aim of this study is to obtain voxel-by-voxel images of binding parameters between [¹¹C]-flumazenil and benzodiazepine receptors using positron emission tomography (PET). We estimate five local parameters (k₁, k₂, B'_max, k_on/V_R, k_off) by fitting a three- compartment ligand-receptor model for each voxel of a PET time series. It proves difficult to fit the ligand-receptor model to the data. We trade noise and spatial resolution to get better results. Our strategy is based on the use of a multiresolution pyramid. It is much easier to solve the problem at coarse resolution because there are fewer data to process. To increase resolution, we expand the parameter maps to the next finer level and use them as initial solution to further optimization, which then proceeds at a fast pace and is more likely to escape false local minima. For this approach to work optimally, the residue between data at a given pyramid level and data at the next level must be as small as possible. We satisfy this constraint by working with spline-based least- squares pyramids. To achieve speed, the optimizer must be efficient, particularly when it is nearing the solution. To that effect, we have developed a Marquardt-Levenberg algorithm that exhibits superlinear convergence properties.

Citation Download Citation

Philippe Thevenaz and Philippe Millet "Multiresolution imaging of in-vivo ligand-receptor interactions", Proc. SPIE 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images, (21 May 2001); https://doi.org/10.1117/12.428132

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KEYWORDS

Data modeling

Positron emission tomography

Receptors

Data processing

Spatial resolution

Convolution

Blood

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