Researchers at the University of California, Davis have developed methodologies that perform dynamic PET imaging and provide opportunities for tracing blood flow and other biological systems in real-time.
PET is the most sensitive molecular imaging modality available currently for tracing biomedical processes in vivo. However, compared to other imaging modalities, the images provided by PET scanners often have high noise. As a result, PET scans must take longer to capture enough signal, resulting in poor temporal resolution and motion blurring artifacts. To address this, some PET imaging applications require the use of external devices, such as ECG, a breathing belt, or optical markers and fast dynamic applications have not been feasible. This limitation has historically resulted in PET scanners being less effective for monitoring blood flow, as well as cardiac, respiratory or other human systems. Thus, a method providing high temporal resolution PET scanning would offer enhanced imaging applications.
Researchers at the University of California, Davis have developed a methodology for high temporal resolution, dynamic PET by applying the kernel-regularized reconstruction paradigm to PET scanner data. This technique provides high-quality images for tracking fast tracer dynamics, such as blood flow and dynamic responses to neural modulation. Furthermore, the improved PET methodology enables real-time blood flow/circulatory system tracking, as well as motion-freeze monitoring for cardiovascular, cerebrovascular, and respiratory system function. This imaging can now occur without the need for additional external devices – and can be applied to any clinical PET system for marker-free, motion-free, real-time, fast tracer tracking.
PET, temporal resolution, fast tracer imaging, real-time motion tracking, kernel-regularized reconstruction, penalized image reconstruction