Liver 4DMRI: A retrospective image-based sorting method

Authors

  • Paganelli Chiara,

    1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy
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  • Summers Paul,

    1. Division of Radiology, Istituto Europeo di Oncologia, Milano 20133, Italy
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  • Bellomi Massimo,

    1. Division of Radiology, Istituto Europeo di Oncologia, Milano 20133, Italy and Department of Health Sciences, Università di Milano, Milano 20133, Italy
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  • Baroni Guido,

    1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy and Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
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  • Riboldi Marco

    1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy and Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
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Abstract

Purpose:

Four-dimensional magnetic resonance imaging (4DMRI) is an emerging technique in radiotherapy treatment planning for organ motion quantification. In this paper, the authors present a novel 4DMRI retrospective image-based sorting method, providing reduced motion artifacts than using a standard monodimensional external respiratory surrogate.

Methods:

Serial interleaved 2D multislice MRI data were acquired from 24 liver cases (6 volunteers + 18 patients) to test the proposed 4DMRI sorting. Image similarity based on mutual information was applied to automatically identify a stable reference phase and sort the image sequence retrospectively, without the use of additional image or surrogate data to describe breathing motion.

Results:

The image-based 4DMRI provided a smoother liver profile than that obtained from standard resorting based on an external surrogate. Reduced motion artifacts were observed in image-based 4DMRI datasets with a fitting error of the liver profile measuring 1.2 ± 0.9 mm (median ± interquartile range) vs 2.1 ± 1.7 mm of the standard method.

Conclusions:

The authors present a novel methodology to derive a patient-specific 4DMRI model to describe organ motion due to breathing, with improved image quality in 4D reconstruction.

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