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Open Access Original research

A method for model-free partial volume correction in oncological PET

Frank Hofheinz1*, Jens Langner1, Jan Petr1, Bettina Beuthien-Baumann12, Liane Oehme2, Jörg Steinbach1, Jörg Kotzerke12 and Jörg van den Hoff12

Author Affiliations

1 PET Centre, Institute of Radiopharmacy, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany

2 Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany

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EJNMMI Research 2012, 2:16  doi:10.1186/2191-219X-2-16

Published: 24 April 2012

Abstract

Background

As 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.

Methods

The 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.

Results

For 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)%).

Conclusions

The described method enables accurate quantitative partial volume correction in oncological hot spot imaging.

Keywords:
Partial volume effect; Partial volume correction; Recovery correction; PET; Quantification