Abstract
Multicenter clinical trials that use positron emission tomography (PET) imaging frequently rely on stable bias in imaging biomarkers to assess drug effectiveness. Many well-documented factors cause variability in PET intensity values. Two of the largest scanner-dependent errors are scanner calibration and reconstructed image resolution variations. For clinical trials, an increase in measurement error significantly increases the number of patient scans needed. We aim to provide a robust quality assurance system using portable PET/computed tomography “pocket” phantoms and automated image analysis algorithms with the goal of reducing PET measurement variability. A set of the “pocket” phantoms was scanned with patients, affixed to the underside of a patient bed. Our software analyzed the obtained images and estimated the image parameters. The analysis consisted of 2 steps, automated phantom detection and estimation of PET image resolution and global bias. Performance of the algorithm was tested under variations in image bias, resolution, noise, and errors in the expected sphere size. A web-based application was implemented to deploy the image analysis pipeline in a cloud-based infrastructure to support multicenter data acquisition, under Software-as-a-Service (SaaS) model. The automated detection algorithm localized the phantom reliably. Simulation results showed stable behavior when image properties and input parameters were varied. The PET “pocket” phantom has the potential to reduce and/or check for standardized uptake value measurement errors.
Highlights
1,688,780 new cancer cases and 600,920 deaths from cancer are estimated for the United States in 2017 [1]
Quantitative Positron emission tomography (PET)/computed tomography (CT) is a valuable tool for assessment of an individual’s response to therapy and for clinical trials of novel cancer therapies, because it can measure metabolic changes, which are a better indicator of response than anatomical size changes [6]
PET imaging provides a reliable predictor for treatment responses and patient outcome
Summary
1,688,780 new cancer cases and 600,920 deaths from cancer are estimated for the United States in 2017 [1]. Quantitative PET/CT is a valuable tool for assessment of an individual’s response to therapy and for clinical trials of novel cancer therapies, because it can measure metabolic changes, which are a better indicator of response than anatomical size changes [6] Success with this approach has been shown using the glucose analogue 18F-fluorodeoxyglucose (FDG) for evaluation of therapy-induced changes in metabolic activity in several studies, including lung cancer [7] and gastrointestinal tumors [8]. The thymidine analogue 18F-fluorothymidine (FLT) provides accurate measurements of tumor proliferative activity and can be used to monitor tumor responses to treatment [9] In these cases, PET imaging provides a reliable predictor for treatment responses and patient outcome. This suggests that quantitative PET imaging has an enormous potential to boost the efficiency of evaluating clinical trials of new therapies [10]
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