Existing respiratory motion-correction methods are applied only to static PET imaging. We have previously developed an eventby-event respiratory motion-correction method with correlations between internal organ motion and external respiratory signals (INTEX). This method is uniquely appropriate for dynamic imaging because it corrects motion for each time point. In this study, we applied INTEX to human dynamic PET studies with various tracers and investigated the impact on kinetic parameter estimation. Methods: The use of 3 tracers-a myocardial perfusion tracer, 82 Rb (n = 7); a pancreatic β-cell tracer, 18 F-FP(+)DTBZ (n = 4); and a tumor hypoxia tracer, 18 F-fluoromisonidazole ( 18 F-FMISO) (n = 1)-was investigated in a study of 12 human subjects. Both rest and stress studies were performed for 82 Rb. The Anzai belt system was used to record respiratory motion. Three-dimensional internal organ motion in high temporal resolution was calculated by INTEX to guide event-by-event respiratory motion correction of target organs in each dynamic frame. Time-activity curves of regions of interest drawn based on endexpiration PET images were obtained. For 82 Rb studies, K 1 was obtained with a 1-tissue model using a left-ventricle input function. Rest-stress myocardial blood flow (MBF) and coronary flow reserve (CFR) were determined. For 18 F-FP(1)DTBZ studies, the total volume of distribution was estimated with arterial input functions using the multilinear analysis 1 method. For the 18 F-FMISO study, the net uptake rate K i was obtained with a 2-tissue irreversible model using a left-ventricle input function. All parameters were compared with the values derived without motion correction. Results: With INTEX, K 1 and MBF increased by 10% ± 12% and 15% ± 19%, respectively, for 82 Rb stress studies. CFR increased by 19% ± 21%. For studies with motion amplitudes greater than 8 mm (n 5 3), K 1 , MBF, and CFR increased by 20% ± 12%, 30% ± 20%, and 34% ± 23%, respectively. For 82 Rb rest studies, INTEX had minimal effect on parameter estimation. The total volume of distribution of 18 F-FP(1)DTBZ and K i of 18 F-FMISO increased by 17% ± 6% and 20%, respectively. Conclusion: Respiratory motion can have a substantial impact on dynamic PET in the thorax and abdomen. The INTEX method using continuous external motion data substantially changed parameters in kinetic modeling. More accurate estimation is expected with INTEX.

The problem of tumor hypoxia has been recognized and studied by the oncology community for over 60 years. From radiation and chemotherapy resistance to the increased risk of metastasis, the low oxygen concentrations in tumors have caused patients with many types of tumors to respond poorly to conventional cancer therapies. It is clear that patients with high levels of tumor hypoxia have a poorer overall treatment response and that the magnitude of hypoxia is an important prognostic factor. As a result, the development of methods to measure tumor hypoxia using invasive and non-invasive techniques has become desirable to the clinical oncology community. A variety of imaging modalities have been established to visualize hypoxia in vivo. Positron Emission Tomography (PET) imaging, in particular, has played a key role for imaging tumor hypoxia because of the development of hypoxia-specific radiolabelled agents. Consequently, this technique is increasingly used in the clinic for a wide variety of cancer types. Following a broad overview of the complexity of tumor hypoxia and measurement techniques to date, this review will focus specifically on the accuracy and reproducibility of PET imaging to quantify tumor hypoxia. Despite numerous advances in the field of PET imaging for hypoxia, we continue to search for the ideal hypoxia tracer to both qualitatively and quantitatively define the tumor hypoxic volume in a clinical setting to optimize treatments and predict response in cancer patients.