Development of Radiographic Contrast Agents for Diagnostic Imaging

Imaging contrast agents, administered intravenously, are diverse, can be used for diagnostic and therapeutic purposes, and have specific regulatory requirements and development considerations. Collaborative relationships between industry and academia may provide the best approach for the development of these agents. Additional opportunities for development and commercialization include software specific for the analysis of contrast-enhanced examinations. There are special considerations for each class of imaging contrast agents with regards to market growth and potential avenues for future development

An exploration of the prognostic utility of shortened dynamic imaging protocols for PET-FDG scans

Standard whole-body clinical fluoro-deoxyglucose (FDG)-PET scans typically involve imaging for around 15 minutes about 60 minutes after tracer injection. The scan duration is often the critical constraint limiting patient through-put. Scans taken long after tracer injection restrict the ability to assess vascular and perfusion information that might be revealed by the early pattern of tracer uptake. On the other hand, early scanning may compromise the recovery of the late time uptake (SUV) which in many contexts has well established prognostic value. In this study, we explore the potential for short-duration dynamic scans, acquired immediately after tracer injection, to recover information that can predict late-stage uptake of FDG. The work involves re-analysis of existing series of dynamic brain and breast tumour imaging data to simulate the type of information that would arise from early and late scanning. Using a collection of machine learning techniques (including random forests, neural networks, gradient boosting), we find that short-duration clinical protocols, soon after the tracer injection, show significant potential to recover the late stage FDG flux information

A simple evaluation of the benefit of combined kinetic analysis of multiple injection dynamic PET scans

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 such studies can be approached in one of two ways: analyze individual injections separately to recover tracer kinetic information, or concatenate data from separate injections and carry out a combined analysis. Separate analysis offers some simplicity but may not be as efficient statistically. The mixture technique is readily implemented in a separated or combined analysis mode. We evaluate these approaches in a 1-D simulation setting matched to the mathematical complexity of PET. These simulations are largely guided by experience with breast cancer flow-metabolism mismatch studies using 15O-Water (H2O) and 18F-Fluorodeoxyglucose (FDG). An efficient implementation in the R (an open-source environment) is used to implement simulations. The simulations evaluate mean square error (MSE) characteristics, for separate and combined analysis, both as a function of dose. The relationship between MSE characteristics of the underlying source distribution is described and the combined analysis is found to reduce MSE by between 18.1% and 33.85%. The quantitative advantages of combined approach have been demonstrated

Quantitation of multiple injection dynamic PET scans: an investigation of the benefits of pooling data from separate scans when mapping kinetics

Multiple injection dynamic positron emission tomography (PET) scanning is used in the clinical management of certain groups of patients and in medical research. The analysis of these studies can be approached in two ways: (i) separate analysis of data from individual tracer injections, or (ii), concatenate/pool data from separate injections and carry out a combined analysis. The simplicity of separate analysis has some practical appeal but may not be statistically efficient. We use a linear model framework associated with a kinetic mapping scheme to develop a simplified theoretical understanding of separate and combined analysis. The theoretical framework is explored numerically using both 1D and 2D simulation models. These studies are motivated by the breast cancer flow-metabolism mismatch studies involving 15O-water (H2O) and 18F-Fluorodeoxyglucose (FDG) and repeat 15O-H2O injections used in brain activation investigations. Numerical results are found to be substantially in line with the simple theoretical analysis: mean square error characteristics of alternative methods are well described by factors involving the local voxel-level resolution of the imaging data, the relative activities of the individual scans and the number of separate injections involved. While voxel-level resolution has dependence on scan dose, after adjustment for this effect, the impact of a combined analysis is understood in simple terms associated with the linear model used for kinetic mapping. This is true for both data reconstructed by direct filtered backprojection or iterative maximum likelihood. The proposed analysis has potential to be applied to the emerging long axial field-of-view PET scanners

Assessment of the prognostic value of radiomic features in 18F-FMISO PET imaging of hypoxia in postsurgery brain cancer patients: secondary analysis of imaging data from a single-center study and the multicenter ACRIN 6684 trial

Hypoxia is associated with resistance to radiotherapy and chemotherapy in malignant gliomas, and it can be imaged by positron emission tomography with 18F-fluoromisonidazole (18F-FMISO). Previous results for patients with brain cancer imaged with 18F-FMISO at a single center before conventional chemoradiotherapy showed that tumor uptake via T/Bmax (tissue SUVmax/blood SUV) and hypoxic volume (HV) was associated with poor survival. However, in a multicenter clinical trial (ACRIN 6684), traditional uptake parameters were not found to be prognostically significant, but tumor SUVpeak did predict survival at 1 year. The present analysis considered both study cohorts to reconcile key differences and examine the potential utility of adding radiomic features as prognostic variables for outcome prediction on the combined cohort of 72 patients with brain cancer (30 University of Washington and 42 ACRIN 6684). We used both 18F-FMISO intensity metrics (T/Bmax, HV, SUV, SUVmax, SUVpeak) and assessed radiomic measures that determined first-order (histogram), second-order, and higher-order radiomic features of 18F-FMISO uptake distributions. A multivariate model was developed that included age, HV, and the intensity of 18F-FMISO uptake. HV and SUVpeak were both independent predictors of outcome for the combined data set (P < .001) and were also found significant in multivariate prognostic models (P < .002 and P < .001, respectively). Further model selection that included radiomic features showed the additional prognostic value for overall survival of specific higher order texture features, leading to an increase in relative risk prediction performance by a further 5%, when added to the multivariate clinical model

Clinical Trial Design and Development Work Group within the Quantitative Imaging Network

The Clinical Trial Design and Development Working Group within the Quantitative Imaging Network focuses on providing support for the development, validation, and harmonization of quantitative imaging (QI) methods and tools for use in cancer clinical trials. In the past 10 years, the Group has been working in several areas to identify challenges and opportunities in clinical trials involving QI and radiation oncology. The Group has been working with Quantitative Imaging Network members and the Quantitative Imaging Biomarkers Alliance leadership to develop guidelines for standardizing the reporting of quantitative imaging. As a validation platform, the Group led a multireader study to test a semi-automated positron emission tomography quantification software. Clinical translation of QI tools cannot be possible without a continuing dialogue with clinical users. This article also highlights the outreach activities extended to cooperative groups and other organizations that promote the use of QI tools to support clinical decisions

Assessment of a statistical AIF extraction method for dynamic PET studies with 15O water and 18F fluorodeoxyglucose in locally advanced breast cancer patients

Blood flow-metabolism mismatch from dynamic positron emission tomography (PET) studies with O-15-labeled water (H2O) and F-18-labeled fluorodeoxyglucose (FDG) has been shown to be a promising diagnostic for locally advanced breast cancer (LABCa) patients. The mismatch measurement involves kinetic analysis with the arterial blood time course (AIF) as an input function. We evaluate the use of a statistical method for AIF extraction (SAIF) in these studies. Fifty three LABCa patients had dynamic PET studies with H2O and FDG. For each PET study, two AIFs were recovered, an SAIF extraction and also a manual extraction based on a region of interest placed over the left ventricle (LV-ROI). Blood flow-metabolism mismatch was obtained with each AIF, and kinetic and prognostic reliability comparisons were made. Strong correlations were found between kinetic assessments produced by both AIFs. SAIF AIFs retained the full prognostic value, for pathologic response and overall survival, of LV-ROI AIFs. (c) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI