| Summary: | <div class="WordSection1"><p><strong>Purpose: </strong>The accuracy of voxelized information in emission imaging is limited by spatial resolution (FWHM = 2.35σ) producing biases for objects smaller than 3 FWHM. If the signal distribution is non‐uniform within 3σ of the voxel of interest then equilibrium does not exist and partial volume effect (PVE) compromises voxel accuracy. We propose a mathematical model to improve the accuracy of quantitative images of arbitrary distribution by bounding true voxel signal and estimating PVE for each voxel.</p><p><strong>Methods</strong>: A monotonically increasing parametric dataset is created for each voxel of an emission image by radial integration from the voxel center to radius = 6σ. Each cumulative integration plot from r = 3σ to 6σ is fit to a function A*4π /3*r<sup>3</sup> + B*ΔV derived assuming a local uniform signal distribution (A) where ΔV is the voxel volume. The constant BΔV represents the converged within 3σ integral of PVE. B > 0 implies spill‐out, B < 0 spill‐in, and B = 0 no PVE. We tested the proposed model on simulations of 1D&2D datasets containing known signal distributions and 18F‐PET/CT images of a 6cc lung lesion and bladder.</p><p><strong>Results: </strong>Signal accuracy was > 99% in simulated 1D & 2D datasets. For the tumor, the original maximum value was 10kBq/ml. We obtained A = 3.5kBq/ml and B = 14kBq/ml for a total of 17.7kBq/ml. This yields (A+B)/original = 1.8 indicating substantial spill‐out of ~80% and a large error for the original voxel value. For a voxel in the center of the bladder, the original value was 46kBq/ml with A = 44kBq/ml, B = 7kBq/ml. (A+B)/original = 1.11 indicating near‐equilibrium at center of bladder and low spill-out of ~11% as expected. Local signal images (A) resemble low‐pass filtered original image and (B) shows the magnitude and direction of PVE.</p></div><p><strong><strong> Conclusion</strong>:</strong> A new mathematical model to estimate the accuracy of voxels in quantitative images of arbitrary distribution has been developed. Analysis of additional patients is underway.<strong><br /></strong></p><p><strong>-------------------------------------</strong></p><p><strong>Cite this article as:</strong> Mikell J, Kappadath SC. Voxel-based partial volume correction for accurate quantitative voxel values. Int J Cancer Ther Oncol 2014; 2(2):020229. <strong>DOI: 10.14319/ijcto.0202.29</strong><br /><br /><br /></p>
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