Image derived input functions for dynamic High Resolution Research Tomograph PET brain studies

Abstract The High Resolution Research Tomograph (HRRT) is a dedicated human brain positron emission tomography (PET) scanner. The aim of the present study was to validate the use of image derived input functions (IDIF) as an alternative for arterial sampling for HRRT human brain studies. To this end, IDIFs were extracted from 3D ordinary Poisson ordered subsets expectation maximization (OP-OSEM) and reconstruction based partial volume corrected (PVC) OP-OSEM images. IDIFs, either derived directly from regions of interest or further calibrated using manual samples taken during scans, were evaluated for dynamic [ 11 C]flumazenil data ( n  = 6). Results obtained with IDIFs were compared with those obtained using blood sampler input functions (BSIF). These comparisons included areas under the curve (AUC) for peak (0–3.3 min) and tail (3.3–55.0 min). In addition, slope, intercept and Pearson's correlation coefficient of tracer kinetic analysis results based on IDIF and BSIF were calculated for each subject. Good peak AUC ratios (0.83 ± 0.21) between IDIF and BSIF were found for calibrated IDIFs extracted from OP-OSEM images. This combination of IDIFs and images also provided good slope values (1.07 ± 0.11). Improved resolution, as obtained with PVC OP-OSEM, changed AUC ratios to 1.14 ± 0.35 and, for tracer kinetic analysis, slopes changed to 0.95 ± 0.13. For all reconstructions, non-calibrated IDIFs gave poorer results (> 61 ± 34% higher slopes) compared with calibrated IDIFs. The results of this study indicate that the use of IDIFs, extracted from OP-OSEM or PVC OP-OSEM images, is feasible for dynamic HRRT data, thereby obviating the need for online arterial sampling.