The Effect of Registration on Voxel-Wise Tofts Model Parameters and Uncertainties from DCE-MRI of Early-Stage Breast Cancer Patients Using 3DSlicer
Autor: | Frank S. Prato, Muriel Brackstone, Ilanit Ben-Nachum, Stewart Gaede, Anat Kornecki, Heather Biernaski, Matthew Mouawad, Michael Lock, Neil Gelman, R. Terry Thompson, Olga Shmuilovich |
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Rok vydání: | 2020 |
Předmět: |
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Radiological and Ultrasound Technology Uncertainty Contrast Media Image registration Breast Neoplasms computer.software_genre medicine.disease Magnetic Resonance Imaging Article Computer Science Applications Kinetics Transformation (function) Breast cancer Standard error Goodness of fit Voxel Statistics Dynamic contrast-enhanced MRI medicine Humans Radiology Nuclear Medicine and imaging computer Mathematics |
Zdroj: | J Digit Imaging |
ISSN: | 1618-727X 0897-1889 |
Popis: | We quantitatively investigate the influence of image registration, using open-source software (3DSlicer), on kinetic analysis (Tofts model) of dynamic contrast enhanced MRI of early-stage breast cancer patients. We also show that registration computation time can be reduced by reducing the percent sampling (PS) of voxels used for estimation of the cost function. DCE-MRI breast images were acquired on a 3T-PET/MRI system in 13 patients with early-stage breast cancer who were scanned in a prone radiotherapy position. Images were registered using a BSpline transformation with a 2 cm isotropic grid at 100, 20, 5, 1, and 0.5PS (BRAINSFit in 3DSlicer). Signal enhancement curves were analyzed voxel-by-voxel using the Tofts kinetic model. Comparing unregistered with registered groups, we found a significant change in the 90th percentile of the voxel-wise distribution of K(trans). We also found a significant reduction in the following: (1) in the standard error (uncertainty) of the parameter value estimation, (2) the number of voxel fits providing unphysical values for the extracellular-extravascular volume fraction (v(e) > 1), and (3) goodness of fit. We found no significant differences in the median of parameter value distributions (K(trans), v(e)) between unregistered and registered images. Differences between parameters and uncertainties obtained using 100PS versus 20PS were small and statistically insignificant. As such, computation time can be reduced by a factor of 2, on average, by using 20PS while not affecting the kinetic fit. The methods outlined here are important for studies including a large number of post-contrast images or number of patient images. |
Databáze: | OpenAIRE |
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