Online Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 186 - Biomarker and Diagnostic Test Evaluation
Type: Contributed
Date/Time: Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Medical Devices and Diagnostics
Abstract #312591
Title: A Statistical Evaluation of Alternative Techniques for Kinetic Analysis of Multiple Injection Dynamic PET Scans
Author(s): Fengyun Gu* and Finbarr O'Sullivan and Qi Wu and Mark Muzi and David Mankoff
Companies: University College Cork and University College Cork and University College Cork and University of Washington and University of Pennsylvania
Keywords: Multiple Injection PET Scans; Combined Kinetic Analysis; Mixture Modelling; Quantitative Advantages; Breast Cancer Study; Activation Study
Abstract:

The multiple injection dynamic positron emission tomography (PET) scanning is used in the clinical management of certain groups of cancer patients and in medical research. The analysis of these studies can be approached in combined or separate fashion. The simplicity of separate analysis has some practical appeal but may not be statistically efficient. Two examples of multiple injections studies with [O-15]-labeled water (H2O) and [F-18]-labeled fluorodeoxyglucose (FDG) are considered: (a) Flow-metabolism mismatch studies with H2O and FDG, (b) repeat H2O injection activation studies. Our work uses both asymptotic analysis and numerical simulation studies matched to the mathematical complexity of PET. We evaluate mean square error (MSE) characteristics of the underlying source distribution, for separate and combined analysis, both as a function of overall dose and relative dose/the number of injections involved. These factors are highlighted by the asymptotic analysis. Reported results give insight into differences between alternative analysis approaches and strongly support the benefits in the medical diagnostics if using a combined analysis methodology.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2020 program