Machine learning to identify suitable boundaries for band-pass spectral analysis of dynamic [ C]Ro15-4513 PET scan and voxel-wise parametric map generation.

Journal: EJNMMI research
Published Date: Jul 11, 2025

Abstract

BACKGROUND: Spectral analysis is a model-free PET quantification technique that treats the time-space signal as an impulse response to a bolus injection. Band-pass spectral analysis, considering specific frequency ranges, enables calculation of separate parametric maps of receptor subtype tracer binding for suitable radiopharmaceuticals such as [ C]Ro15-4513 binding to GABA 1/5 subunits. Frequency ranges are based on inspection of spectra, prior knowledge of receptor distribution, and blocking studies. The process currently requires the manual selection of frequency ranges based on the data. To enhance the efficiency of band-pass spectral analysis and extend its application to a broader range of tracers, we propose employing machine learning to automate the selection of spectral boundaries. Based on these boundaries, voxel-wise parametric maps can be generated. The machine learning models utilized in this study include 1D Convolutional Neural Network, Neural Network, Support Vector Machine, Logistic Regression, K-nearest neighbors, and Fine Tree.

Authors

  • Zeyu Chang
    Alife Health, Inc., 3717 Buchanan Street, Suite 400, San Francisco, CA, 94123, USA.
  • Colm J McGinnity
    School of Biomedical Engineering and Imaging Sciences, King's College London and Guy's and St Thomas' PET Centre, King's College London, Westminster Bridge Rd, London, SE1 7EH, UK.
  • Rainer Hinz
    Wolfson Molecular Imaging Centre, University of Manchester, 27 Palatine Rd, Manchester, M20 3LJ, UK.
  • Manlin Wang
    Business and Tourism Institute, Hangzhou Vocational and Technical College, Xueyuan St, Hangzhou, 310018, China.
  • Joel Dunn
    School of Biomedical Engineering and Imaging Sciences, King's College London and Guy's and St Thomas' PET Centre, King's College London, Westminster Bridge Rd, London, SE1 7EH, UK.
  • Ruoyang Liu
    School of Biomedical Engineering and Imaging, King's College London, Lambeth Palace Rd, London, SE1 7EU, UK.
  • Mubaraq Yakubu
    School of Biomedical Engineering and Imaging Sciences, King's College London and Guy's and St Thomas' PET Centre, King's College London, Westminster Bridge Rd, London, SE1 7EH, UK.
  • Paul Marsden
    School of Biomedical Engineering and Imaging Sciences, King's College London and Guy's and St Thomas' PET Centre, King's College London, Westminster Bridge Rd, London, SE1 7EH, UK.
  • Alexander Hammers
    King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

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