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Link to original content: https://doi.org/10.1007/s11548-016-1487-z
Acquisition models in intraoperative positron surface imaging | International Journal of Computer Assisted Radiology and Surgery Skip to main content

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Acquisition models in intraoperative positron surface imaging

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

Abstract

Purpose

Intraoperative imaging aims at identifying residual tumor during surgery. Positron Surface Imaging (PSI) is one of the solutions to help surgeons in a better detection of resection margins of brain tumor, leading to an improved patient outcome. This system relies on a tracked freehand beta probe, using \(^{18}\)F-based radiotracer. Some acquisition models have been proposed in the literature in order to enhance image quality, but no comparative validation study has been performed for PSI.

Methods

In this study, we investigated the performance of different acquisition models by considering validation criteria and normalized metrics. We proposed a reference-based validation framework to perform the comparative study between acquisition models and a basic method. We estimated the performance of several acquisition models in light of four validation criteria: efficiency, computational speed, spatial accuracy and tumor contrast.

Results

Selected acquisition models outperformed the basic method, albeit with the real-time aspect compromised. One acquisition model yielded the best performance among all according to the validation criteria: efficiency (1-Spe: 0.1, Se: 0.94), spatial accuracy (max Dice: 0.77) and tumor contrast (max T/B: 5.2). We also found out that above a minimum threshold value of the sampling rate, the reconstruction quality does not vary significantly.

Conclusion

Our method allowed the comparison of different acquisition models and highlighted one of them according to our validation criteria. This novel approach can be extended to 3D datasets, for validation of future acquisition models dedicated to intraoperative guidance of brain surgery.

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Notes

  1. A suxel is defined as the smallest element of the SOI.

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Acknowledgments

The authors would like to thanks CAMPUS FRANCE (PROCOPE Program), Rennes Métropole and Le Ministère des Affaires étrangères et du Développement international for French-Bavaria student exchanges and also the French Cancer League for material support.

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Authors and Affiliations

  1. LTSI INSERM, UMR 1099, Campus de Villejean, Université de Rennes 1, 2, Avenue du Pr. Léon Bernard, 35043, Rennes Cedex, France

    Frédéric Monge, Xavier Morandi & Pierre Jannin

  2. Translational Imaging Group/CMIC, University College London, London, UK

    Dzhoshkun I. Shakir

  3. Centre Eugène Marquis, Rennes, 35000, France

    Florence Lejeune

  4. CHU Rennes, Service de Neurochirurgie, Rennes, 35000, France

    Xavier Morandi

  5. CAMP, Technische Universität München, Munich, Germany

    Nassir Navab

Authors
  1. Frédéric Monge
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  2. Dzhoshkun I. Shakir
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  3. Florence Lejeune
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  4. Xavier Morandi
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  5. Nassir Navab
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  6. Pierre Jannin
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Corresponding author

Correspondence to Frédéric Monge.

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Monge, F., Shakir, D.I., Lejeune, F. et al. Acquisition models in intraoperative positron surface imaging. Int J CARS 12, 691–703 (2017). https://doi.org/10.1007/s11548-016-1487-z

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