Standardization of Preclinical PET/CT Imaging to Improve Quantitative Accuracy, Precision, and Reproducibility: A Multicenter Study

McDougald, Wendy; Vanhove, Christian; Lehnert, Adrienne L.; Lewellen, Barbara; Wright, John D.; Mingarelli, Marco; Corral, Carlos Alcaide; Schneider, Jürgen; Plein, Sven; Newby, David E.; Welch, Andrew; Miyaoka, Robert S.; Vandenberghe, Stefaan; Tavares, Adriana

doi:10.2967/jnumed.119.231308

Cited by 32 publications

(31 citation statements)

References 29 publications

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“…Most recently, Greenwood et al [12] characterized a commercial four-chamber bed on a Mediso preclinical PET scanner, using NEMA phantoms and mice. As in previous studies, they demonstrated a decrease in uniformity and recovery coefficients, and an increase in spillover ratios, in the multiple vs. single animal cases, though these increases were within the recently suggested limits for bias [13].…”

Section: Introductionsupporting

confidence: 80%

Influence of Multiple Animal Scanning on Image Quality for the Sedecal SuperArgus2R Preclinical PET Scanner

et al. 2021

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Background: Increased throughput in small animal preclinical studies using positron emission tomography leads to reduced costs and improved efficiency of experimental design, however the presence of multiple off-centre subjects, as opposed to a single centered one, may affect image quality in several ways.Methods: We evaluated the count rate performance using a NEMA scatter phantom. A Monte Carlo simulation of the system was validated against this dataset and used to simulate the count rate performance for dual scatter phantoms. NEMA NU4 image quality phantoms were then scanned in the central and offset positions, as well as in the offset position next to a uniform activity phantom. Uniformity, recovery coefficients and spillover ratios were then compared, as were two time frames for acquisition.Results: Count rate performance assessed with a single NEMA scatter phantom was in line with previous literature, with simulated data in good agreement. Simulation of dual scatter phantoms showed an increase in scatter fraction. For the NEMA Image Quality phantom, uniformity and Recovery coefficients were degraded in the offset, and dual phantom cases, while spillover ratios were increased, notably when the chamber was placed nearest the gantry. Image quality metrics were comparable between the 20- and 10 min timeframes.Conclusion: Dual animal scanning results in some loss of image quality on the Sedecal Argus PET scanner; however, this degradation is within acceptable limits.

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Section: Introductionsupporting

confidence: 80%

Influence of Multiple Animal Scanning on Image Quality for the Sedecal SuperArgus2R Preclinical PET Scanner

et al. 2021

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“…Arguably the expected high 18 F-FDG uptake by the myocardium and brain may have affected SUV quantification in bones in close proximity to these organs (namely sternum and skull) due to spill-over measurement errors. However, these are expected to contribute to a maximum of 10% quantitative bias, as per measurements in our scanner using phantoms and standard acquisition protocols developed by our group (17).…”

Section: Site-specific Metabolic Differences In Bones Identified By Wmentioning

confidence: 99%

A systems-level analysis of dynamic total-body PET data reveals complex skeletal energy metabolism networksin vivo

Suchacki

Alcaide-Corral

Nimale

et al. 2021

Preprint

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Bone is now regarded to be a key regulator of a number of metabolic processes, in addition to the regulation of mineral metabolism. However, our understanding of complex bone metabolic interactions at a systems level remains rudimentary, limiting our ability to assess systemic mechanisms underlying diseases and develop novel therapeutics. In vitro molecular biology and bioinformatics approaches have frequently been used to understand the mechanistic changes underlying disease at the cell level, however, these approaches lack the capability to interrogate dynamic multi-bone metabolic interactions in vivo. Here we present a novel and integrative approach to understand complex bone metabolic interactions in vivo using total-body positron emission tomography (PET) network analysis of murine 18F-FDG scans, as a biomarker of glucose metabolism signature in bones. In this report we show that different bones within the skeleton have a unique glucose metabolism and form a complex metabolic network. These data could have important therapeutic implications in the management of the metabolic syndrome and skeletal disease. The application of our approach to clinical and preclinical total-body PET studies promises to reveal further physiological and pathological tissue interactions, which simplistic PET standard uptake values analysis fail to interrogate, extending beyond skeletal metabolism, due to the diversity of PET radiotracers available and under development as well as the advent of clinical total-body PET systems.

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“…Over the years, numerous reports have highlighted considerations in small-animal PET imaging ( 54 – 56 ). Unfortunately, despite some progress, there are still gaps in standardization of small-animal imaging protocols and QI methods to produce consistent results as highlighted by recent works ( 119 , 120 ). Importantly, in line with the theme of this communication, there is a need to harmonize preclinical and clinical PET QI pipelines so as to enhance the translational impact of developments in PET imaging.…”

Section: Co-clinical Imaging Study Design Instruments and Standardimentioning

confidence: 99%

“…Lack of reproducibility in preclinical cancer research, including imaging, has been highlighted by numerous publications ( 119 , 166 ). Other than promoting open science, data sharing has been suggested as one solution to address reproducibility.…”

Section: Informatics Needs To Support Co-clinical Researchmentioning

confidence: 99%

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

et al. 2020

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The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

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Standardization of Preclinical PET/CT Imaging to Improve Quantitative Accuracy, Precision, and Reproducibility: A Multicenter Study

Cited by 32 publications

References 29 publications

Influence of Multiple Animal Scanning on Image Quality for the Sedecal SuperArgus2R Preclinical PET Scanner

Influence of Multiple Animal Scanning on Image Quality for the Sedecal SuperArgus2R Preclinical PET Scanner

A systems-level analysis of dynamic total-body PET data reveals complex skeletal energy metabolism networksin vivo

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

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