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KF, kinetic filtering.
KF, kinetic filtering; SUV, standard uptake value.
KC, kinetic class; KF, kinetic filtering; p.i., post injection.
Gray et al. [10] proposed a supervised classification method based on kinetic filtering (KF) [11].
For dynamic [18F]FLT PET studies in NSCLC patients, kinetic filtering and an adaptive contrast-oriented isocontour method (A50%) have similar repeatability performance to define metabolically active tumour volume but only after careful optimisation of the kinetic-filtering method settings.
Using a kinetic filtering method that highlights liver metastatic uptake and excludes normal liver background uptake, a significant reduction in FLT was found in responders 2 weeks after treatment.
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On average, the original implementation of KF (using the Hammersmith kinetic filters) provided 97% larger volumes and 16% lower SUV than measured with A50%.
The kinetic classes and/or the kinetic-filtering method therefore requires a protocol-specific optimisation.
A kinetic-filtering (KF) classification algorithm has been suggested for segmentation of tumours in dynamic [18F]FLT PET data.
Figure 2A is an example of the result of post-processing a FBP-reconstructed image with the kinetic-filtering method.
The standard deviations for all time frames were obtained and used as weighting factors during KF segmentation, as described previously in the 'Kinetic-filtering algorithm' section (Equation 1).
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