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An open tool for input function estimation and quantification of dynamic PET FDG brain scans

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study.

Methods

Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation.

Results

The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with \({<}5\,\%\) relative error in the estimated influx versus ground truth on phantoms.

Conclusions

The main contribution of this article is the development of an open-source, free to use tool that encapsulates several well-known methods for the estimation of the input function and the quantification of dynamic PET FDG studies. Some alternative strategies are also proposed and implemented in the tool for the segmentation of blood pools and parameter estimation. The tool was tested on phantoms with encouraging results that suggest that even bloodless estimators could provide a viable alternative to blood sampling for quantification using graphical analysis. The open tool is a promising opportunity for collaboration among investigators and further validation on real studies.

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Notes

  1. http://slicer.kitware.com/midas3/slicerappstore/extension/view?extensionId=68825.

  2. www.slicer.org/.

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Acknowledgments

This work was supported by Comision Sectorial de Investigacion Cientıfica (CSIC, Universidad de la Republica, Uruguay) under program “Proyecto de Inclusión Social.” The authors are grateful for the valuable comments of Dr. Rodolfo Ferrando, Dr. Andrés Damián, Dr. Patrick Dupont, and personal from CUDIM and Centro de Medicina Nuclear of Hospital de Clínicas.

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Authors and Affiliations

  1. Instituto de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay

    Martín Bertrán, Natalia Martínez, Guillermo Carbajal, Alicia Fernández & Álvaro Gómez

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  1. Martín Bertrán
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  2. Natalia Martínez
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  3. Guillermo Carbajal
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  4. Alicia Fernández
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  5. Álvaro Gómez
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Corresponding author

Correspondence to Guillermo Carbajal.

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Conflict of interest

Martín Bertran, Natalia Martínez, Guillermo Carbajal, Alicia Fernández and Alvaro Gómez declare that they have no conflict of interest.

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Bertrán, M., Martínez, N., Carbajal, G. et al. An open tool for input function estimation and quantification of dynamic PET FDG brain scans. Int J CARS 11, 1419–1430 (2016). https://doi.org/10.1007/s11548-015-1307-x

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  • DOI: https://doi.org/10.1007/s11548-015-1307-x

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