title: Effect of18F-FDG uptake time on lesion detectability in PET imaging of early stage breast cancer.
abstract: Prior reports have suggested that delayed FDG-PET oncology imaging can improve the contrast-to-noise ratio (CNR) for known lesions. Our goal was to estimate realistic bounds for lesion detectability for static measurements with one to four hours between FDG injection and image acquisition. Tumor and normal tissue kinetic model parameters were estimated from dynamic PET studies of patients with early stage breast cancer. These were used to generate time-activity curves (TACs) out to four hours, for which we assumed both nonreversible and reversible models with different rates of FDG dephosphorylation (k4). For each pair of tumor and normal tissue TACs, 600 PET sinogram realizations were generated, and images were reconstructed using OSEM. Test statistics for each tumor and normal tissue region of interest were output from the computer model observers and evaluated using an ROC analysis with the calculated AUC providing a measure of lesion detectability. For the nonreversible model (k4= 0), the AUC increased in 11/23 (48%) of patients for one to two hours after the current standard post-radiotracer injection imaging window of one hour. This improvement was driven by increased tumor/normal tissue contrast before the impact of increased noise due to radiotracer decay began to dominate the imaging signal. As k4was increased from 0 to 0.01 min-1, the time of maximum detectability shifted earlier, as the decreasing FDG concentration in the tumor lowered the CNR. These results imply that delayed PET imaging may reveal low-conspicuity lesions that would have otherwise gone undetected.
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, Washington.
authors.forename: Kristen A
authors.initials: KA
authors.lastname: Wangerin
authors.affiliation: Department of Radiology, University of Washington, Seattle, Washington.
authors.forename: Mark
authors.initials: M
authors.lastname: Muzi
authors.affiliation: Department of Radiology, University of Washington, Seattle, Washington.
authors.forename: Lanell M
authors.initials: LM
authors.lastname: Peterson
authors.affiliation: Department of Medicine, University of Washington, Seattle, Washington.
authors.forename: Hannah M
authors.initials: HM
authors.lastname: Linden
authors.affiliation: Department of Medicine, University of Washington, Seattle, Washington.
authors.forename: Alena
authors.initials: A
authors.lastname: Novakova
authors.affiliation: Department of Statistics, University of Cork, Cork, Ireland.
authors.forename: Finbarr
authors.initials: F
authors.lastname: O'Sullivan
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania.
authors.forename: Brenda F
authors.initials: BF
authors.lastname: Kurland
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: David A
authors.initials: DA
authors.lastname: Mankoff
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, Washington; Department of Radiology, University of Washington, Seattle, Washington.
authors.forename: Paul E
authors.initials: PE
authors.lastname: Kinahan
keywords: Breast Imaging; Lesion Detectability; PET; Physics; Virtual Clinical Trial