Abstract
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Objectives: Dynamic 18F-FDG PET with tracer kinetic modeling has the potential to better detect lesions and assess cancer response to therapy. This potential, however, has not been fully studied in the clinic because conventional PET scanners have a limited axial field-of-view (15-30 cm) and are not capable of simultaneous dynamic imaging of widely separated lesions. The EXPLORER, a total-body (194 cm axial field-of-view) high-sensitivity PET/CT scanner, is being used for routine studies. To test its capability for kinetic modeling and parametric imaging of cancer, we designed a clinical study on total-body dynamic PET in patients with metastatic cancer. The objective of this paper is to report the results from the first patient scan and to demonstrate total-body dynamic PET for improved tumor detection and for enabling multiparametric characterization of metastases.
Methods: One patient with metastatic renal cell carcinoma was scanned on the uEXPLORER total-body PET/CT scanner. Prior Ethics Committee/IRB approval and informed consent were obtained. The subject was injected with 10 mCi of 18F-FDG. Total-body dynamic data were acquired in list-mode format for 60 minutes and binned into 29 time frames (6x10s, 2x30s, 6x60s, 5x120s, 4x180s, 6x300s). The static PET standardized uptake value (SUV) was calculated for the last time frame (55-60 minute). Kinetic modeling using the standard irreversible two-tissue compartmental model was performed for regional quantification in sixteen regions of interest (ROI) including major organs and multiple metastases. The time activity curve (TAC) from the left ventricle was used as the image-derived input function. The fractional blood volume (vb) and time delay were also included and jointly estimated in the kinetic model for joint estimation. The FDG net influx rate Ki was then calculated from the estimated micro kinetic parameters. Kinetic modeling was further implemented voxel-by-voxel to generate parametric images of the kinetic parameters. The kinetic data were then used to explore two aspects of total-body parametric PET of cancer: tumor detection and tumor characterization.
Results: The dynamic FDG-PET scan of the first patient was successful and provided dynamic imaging and visualization of the spatiotemporal pattern of multiple distant metastases. Six metastases were identified. The comparison between Ki and SUV for tumor-to-liver ratio indicated that Ki improved tumor contrast by a factor of about 3 as compared to SUV. For renal lesion detection, the Ki image effectively suppressed the background activity and significantly enhanced the lesion contrast, while the SUV image quality was compromised by the physiological excretion of FDG in renal pelvis. The parametric images of Ki and two FDG perfusion/transport parameters - fractional blood volume vb and blood-to-tissue delivery rate K1 - showed different spatial patterns across organs. The three parameters reflect different physiological aspects and can provide a multiparametric characterization of the metastases for improved subtyping. While the Ki values of different tumors were in a similar range, their K1 and vb values spread more widely, which may be related to the potential heterogeneity of local blood supply and tumor microenvironment.
Conclusions: We successfully conducted the first total-body dynamic FDG-PET scan of a patient with metastatic cancer on the uEXPLORER. It is feasible to perform total-body kinetic modeling and parametric imaging of metastatic cancer using this device. Parametric image of Ki improved tumor contrast over SUV in general and specifically led to improved lesion detection in renal cortex which has been historically challenging. Total-body kinetic quantification also provides multiparametric characterization of tumor metastases and organs of interest (e.g., spleen and bone marrow), which can be used for more quantitative assessment of tumor response and normal tissue effects following a range of anticancer therapies.
