Validation of cardiac image derived input functions for functional PET quantification

Abstract

Functional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate measurement of the arterial input function (AIF) is crucial for quantification of fPET but traditionally requires invasive arterial blood sampling. While, image-derived input functions (IDIF) offer a non-invasive alternative, they are afflicted by drawbacks stemming from limited spatial resolution and field of view. Therefore, we conceptualized and validated a scan protocol for brain fPET quantified with cardiac IDIF.Twenty healthy individuals underwent fPET/MR scans using [18F]FDG or 6-[18F]FDOPA, with bed motion shuttling between the thorax and brain to capture cardiac IDIF and brain task- induced changes, respectively. Each session included arterial and venous blood sampling for IDIF validation, and participants performed a monetary incentive delay task. IDIFs from fixed- size regions of the left ventricle, ascending and descending aorta, and a composite of all 3 blood pools (3VOI) plus venous blood data (3VOIVB) were compared to the AIF. Quantitative task-specific images from both tracers were compared to assess the performance of each input function.For both radiotracer cohorts, moderate to high agreement was found between IDIFs and AIF in terms of area under the curve (r = 0.64 – 0.89) and quantified outcome parameters (CMRGlu and Ki(r)=0.84–0.99). The agreement further increased for composite IDIFs 3VOI and 3VOIVB for AUC(r)=0.87–0.93) and outcome parameters (r=0.96–0.99). Both methods showed equivalent quantitative values and high spatial overlap with AIF-derived measurements.Our proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax. These advancements increase applicability to virtually any PET scanner and to clinical research settings by reducing experimental complexity and increasing patient comfort.Graphical Abstract