Validation of cardiac image-derived input functions for functional PET quantification.
Murray Bruce ReedPatricia Anna HandschuhClemens SchmidtMatej MurgašDavid GomolaChristian MilzSebastian KlugBenjamin EggerstorferLisa AichingerGodber Mathis GodbersenLukas NicsTatjana Traub-WeidingerMarcus HackerRupert LanzenbergerAndreas HahnPublished in: European journal of nuclear medicine and molecular imaging (2024)
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 any PET scanner and clinical research setting by reducing experimental complexity and increasing patient comfort.
Keyphrases
- high resolution
- pet ct
- positron emission tomography
- computed tomography
- pet imaging
- randomized controlled trial
- case report
- deep learning
- resting state
- white matter
- left ventricular
- magnetic resonance imaging
- functional connectivity
- magnetic resonance
- heart failure
- mass spectrometry
- cerebral ischemia
- photodynamic therapy
- machine learning
- blood brain barrier