Statistical assessment of treatment response in a cancer patient based on pre-therapy and post-therapy FDG-PET scans.

This work arises from consideration of sarcoma patients in which fluorodeoxyglucose positron emission tomography (FDG-PET) imaging pre-therapy and post-chemotherapy is used to assess treatment response. Our focus is on methods for evaluation of the statistical uncertainty in the measured response for an individual patient. The gamma distribution is often used to describe data with constant coefficient of variation, but it can be adapted to describe the pseudo-Poisson character of PET measurements. We propose co-registering the pre-therapy and post- therapy images and modeling the approximately paired voxel-level data using the gamma statistics. Expressions for the estimation of the treatment effect and its variability are provided. Simulation studies explore the performance in the context of testing for a treatment effect. The impact of misregistration errors and how test power is affected by estimation of variability using simplified sampling assumptions, as might be produced by direct bootstrapping, is also clarified. The results illustrate a marked benefit in using a properly constructed paired approach. Remarkably, the power of the paired analysis is maintained even if the pre-image and post- image data are poorly registered. A theoretical explanation for this is indicated. The methodology is further illustrated in the context of a series of fluorodeoxyglucose-PET sarcoma patient studies. These data demonstrate the additional prognostic value of the proposed treatment effect test statistic. Copyright © 2016 John Wiley & Sons, Ltd.

A statistical modeling approach to the analysis of spatial patterns of FDG-PET uptake in human sarcoma.

Clinical experience with positron emission tomography (PET) scanning of sarcoma, using fluorodeoxyglucose (FDG), has established spatial heterogeneity in the standardized uptake values within the tumor mass as a key prognostic indicator of patient survival. But it may be that a more detailed quantitation of the tumor FDG uptake pattern could provide additional insights into risk. The present work develops a statistical model for this purpose. The approach is based on a tubular representation of the tumor mass with a simplified radial analysis of uptake, transverse to the tubular axis. The technique provides novel ways of characterizing the overall profile of the tumor, including the introduction of an approach for the measurement of its phase of development. The phase measure can distinguish between early phase tumors, in which the uptake is highest at the core, and later stage masses, in which there can often be central voids in FDG uptake. Biologically, these voids arise from necrosis and fluid, fat or cartilage accumulations. The tumor profiling technique is implemented using open-source software tools and illustrations are provided with clinically representative scans. A series of FDG-PET studies from 185 patients is used to formally evaluate the prognostic benefit. Significant improvements in the prediction of patient survival and progression are obtained from the tumor profiling analysis. After adjustment for other factors including heterogeneity, a typical one standard deviation increase in phase (as determined by the analysis) is associated with close to 20% more risk of progression or death. The work confirms that more detailed quantitative assessments of the spatial pattern of PET imaging data of tumor masses, beyond the maximum FDG uptake (SUV(max)) and previously considered measures of heterogeneity, provide improved prognostic information for potential input to treatment decisions for future patients.