Combining MRI With PET for Partial Volume Correction Improves Image-Derived Input Functions in Mice

Accurate kinetic modelling using dynamic PET requires knowledge of the tracer concentration in plasma, known as the arterial input function (AIF). AIFs are usually determined by invasive blood sampling, but this is prohibitive in murine studies due to low total blood volumes. As a result of the low...

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Bibliographic Details
Published in:IEEE transactions on nuclear science 2015-06, Vol.62 (3), p.628-633
Main Authors: Evans, Eleanor, Buonincontri, Guido, Izquierdo, David, Methner, Carmen, Hawkes, Rob C., Ansorge, Richard E., Krieg, Thomas, Carpenter, T. Adrian, Sawiak, Stephen J.
Format: Article
Language:English
Subjects:
Arterial input function
Blood
Drugs
geometric transfer matrix
Magnetic resonance imaging
Mice
MRI
Myocardium
partial volume correction
Positron emission tomography
small animal PET
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Summary:Accurate kinetic modelling using dynamic PET requires knowledge of the tracer concentration in plasma, known as the arterial input function (AIF). AIFs are usually determined by invasive blood sampling, but this is prohibitive in murine studies due to low total blood volumes. As a result of the low spatial resolution of PET, image-derived input functions (IDIFs) must be extracted from left ventricular blood pool (LVBP) ROIs of the mouse heart. This is challenging because of partial volume and spillover effects between the LVBP and myocardium, contaminating IDIFs with tissue signal. We have applied the geometric transfer matrix (GTM) method of partial volume correction (PVC) to 12 mice injected with 18 F - FDG affected by a Myocardial Infarction (MI), of which 6 were treated with a drug which reduced infarction size [1]. We utilised high resolution MRI to assist in segmenting mouse hearts into 5 classes: LVBP, infarcted myocardium, healthy myocardium, lungs/body and background. The signal contribution from these 5 classes was convolved with the point spread function (PSF) of the Cambridge split magnet PET scanner and a non-linear fit was performed on the 5 measured signal components. The corrected IDIF was taken as the fitted LVBP component. It was found that the GTM PVC method could recover an IDIF with less contamination from spillover than an IDIF extracted from PET data alone. More realistic values of Ki were achieved using GTM IDIFs, which were shown to be significantly different (p
ISSN:0018-9499
1558-1578
DOI:10.1109/TNS.2015.2433897