Abstract
BackgroundAs is well known, limited spatial resolution leads to partial volume effects (PVE) and consequently to limited signal recovery. Determination of the mean activity concentration of a target structure is thus compromised even at target sizes much larger than the reconstructed spatial resolution. This leads to serious size-dependent underestimates of true signal intensity in hot spot imaging. For quantitative PET in general and in the context of therapy assessment in particular it is, therefore, mandatory to perform an adequate partial volume correction (PVC). The goal of our work was to develop and to validate a model-free PVC algorithm for hot spot imaging.MethodsThe algorithm proceeds in two automated steps. Step 1: estimation of the actual object boundary with a threshold based method and determination of the total activity A measured within the enclosed volume V. Step 2: determination of the activity fraction B, which is measured outside the object due to the partial volume effect (spill-out). The PVE corrected mean value is then given by Cmean = (A+B)/V. For validation simulated tumours were used which were derived from real patient data (liver metastases of a colorectal carcinoma and head and neck cancer, respectively). The simulated tumours have characteristics (regarding tumour shape, contrast, noise, etc.) which are very similar to those of the underlying patient data, but the boundaries and tracer accumulation are exactly known. The PVE corrected mean values of 37 simulated tumours were determined and compared with the true mean values.ResultsFor the investigated simulated data the proposed approach yields PVE corrected mean values which agree very well with the true values (mean deviation (± s.d.): (−0.8±2.5)%).ConclusionsThe described method enables accurate quantitative partial volume correction in oncological hot spot imaging.
Highlights
As is well known, limited spatial resolution leads to partial volume effects (PVE) and to limited signal recovery
The limited spatial resolution of PET leads to partial volume effects PVE and
Most often the PVE correction is computed on the basis of phantom measurements, where the signal recovery is determined for different object sizes and different background values
Summary
As is well known, limited spatial resolution leads to partial volume effects (PVE) and to limited signal recovery. Determination of the mean activity concentration of a target structure is compromised even at target sizes much larger than the reconstructed spatial resolution This leads to serious size-dependent underestimates of true signal intensity in hot spot imaging. The PVE correction is performed using the signal recovery of a phantom with approximately the same volume and background as the target structure. Another approach is to improve spatial resolution either via deconvolution of the reconstructed PET data [14,15,16,17,18,19] or via integrating partial volume correction into the image reconstruction [18,2025]. Most algorithms are not generally available, neither in the public domain nor in commercial tools
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