The data analysis and modeling group provides mathematical analysis of the kinetics of biodistribution of radiopharmaceutical as both a research and a service component. In particular, we will extend residue analysis to each of the projects over the next five years and apply novel heterogeneity analysis to the characterization of tumors using PET imaging. The clinical utility of image-based information needs to be tested in terms of what additional information the PET-derived measurements contribute to the prediction of patient outcome at the treatment planning stage. Each of our hypotheses describes an observational study with imaging data, assays of relevant biomarkers, and measures of patient response/survival. Our goal is to identify imaging procedures where a clinically important improvement in predictive accuracy, beyond that attained with existing clinical and diagnostic methods, can be achieved. Because the improved prediction will have clear therapeutic implications and our results will pave the way for these hypotheses to be tested in future cooperative clinical trials, the consultants in biostatistics play a critical role in focusing protocols and directing data analysis in anticipation of cooperative prospective trials. In order to increase the level of biostatistical involvement in protocol design and hypothesis testing, this new data analysis core will include a sub-contract with F O'Sullivan and the local leadership of M Muzi and D Mankoff plus new effort by L Kessler that are essential to the quality and overall productivity of our research program. It will build on our research to generalize the role of the more well established imaging agents through several smaller patient trials in a range of tumor histologies. Our goal is to develop a strategy to convince the cancer community in general and FDA in particular that mechanistically validated imaging agents can be used in parallel with new treatment trials. That is, qualification of an imaging agent should not be tumor-specific;it should be validated for a specific characteristic of the tumor phenotype.. Our goal is to make a convincing case that new imaging methods should be engaged in treatment trials sooner rather than later. The recent addition of L Kessler, a health policy expert who recently worked for FDA, to our faculty is important for this objective.
Careful data analysis is essential to extracting the most complete information possible for every imaging study. The new objective of integrating experimental imaging in early clinical trials of therapy should lead to more efficient clinical trials with useful drugs getting to the clinic sooner.
|Fowler, Amy M; Clark, Amy S; Katzenellenbogen, John A et al. (2016) Imaging Diagnostic and Therapeutic Targets: Steroid Receptors in Breast Cancer. J Nucl Med 57 Suppl 1:75S-80S|
|Kurland, Brenda F; Muzi, Mark; Peterson, Lanell M et al. (2016) Multicenter Clinical Trials Using 18F-FDG PET to Measure Early Response to Oncologic Therapy: Effects of Injection-to-Acquisition Time Variability on Required Sample Size. J Nucl Med 57:226-30|
|Muzi, Mark; Krohn, Kenneth A (2016) Imaging Hypoxia with Â¹â¸F-Fluoromisonidazole: Challenges in Moving to a More Complicated Analysis. J Nucl Med 57:497-8|
|Currin, Erin; Peterson, Lanell M; Schubert, Erin K et al. (2016) Temporal Heterogeneity of Estrogen Receptor Expression in Bone-Dominant Breast Cancer: 18F-Fluoroestradiol PET Imaging Shows Return of ER Expression. J Natl Compr Canc Netw 14:144-7|
|Kurland, Brenda F; Peterson, Lanell M; Lee, Jean H et al. (2016) Estrogen Receptor Binding (18F-FES PET) and Glycolytic Activity (18F-FDG PET) Predict Progression-Free Survival on Endocrine Therapy in Patients with ER+ Breast Cancer. Clin Cancer Res :|
|Wolsztynski, E; O'Sullivan, F; O'Sullivan, J et al. (2016) Statistical assessment of treatment response in a cancer patient based on pre-therapy and post-therapy FDG-PET scans. Stat Med :|
|Link, Jeanne M (2015) Publish or perishâ€¦but where? What is the value of impact factors? Nucl Med Biol 42:426-7|
|Peck, M; Pollack, H A; Friesen, A et al. (2015) Applications of PET imaging with the proliferation marker [18F]-FLT. Q J Nucl Med Mol Imaging 59:95-104|
|Wangerin, Kristen A; Muzi, Mark; Peterson, Lanell M et al. (2015) Effect of (18)F-FDG uptake time on lesion detectability in PET imaging of early stage breast cancer. Tomography 1:53-60|
|Rockne, Russell C; Trister, Andrew D; Jacobs, Joshua et al. (2015) A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET. J R Soc Interface 12:|
Showing the most recent 10 out of 191 publications