Automatic measurement of pharyngeal contraction ratio during deglutition using 2D cine MRI with deep learning: A pilot study.

Journal: Radiological physics and technology
Published Date: Nov 14, 2025

Abstract

This study aimed to develop a deep learning-based method for automatic segmentation of the pharyngeal area (PA) and measurement of the pharyngeal contraction ratio (PCR) during deglutition using cine magnetic resonance imaging (MRI). The proposed algorithm combines PA region extraction by a 2D U-Net with automatic calculation of PA and PCR. Segmentation performance was evaluated using the Dice coefficient (DC), and the PCR measured by the model ([Formula: see text]) was compared with that obtained manually ([Formula: see text]) using correlation and Bland-Altman analyses. Cine MRI data of 20 healthy adults (10 men, 10 women; age 22-29 years) were analyzed. The average DC in the test cases was 0.890 ± 0.025, and the PA of the model correlated well with the manual reference (r = 0.70-0.97). The mean [Formula: see text] was 0.105 ± 0.035, consistent with values reported in videofluoroscopic swallowing studies. These results demonstrate the technical feasibility of automatic PCR measurement from cine MRI using deep learning.

Authors

  • Masato Takahashi
    Graduate School of Health Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan.
  • Naoka Miyamoto
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Norikazu Koori
    Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Japan.
  • Masahiko Monma
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Yoshiyuki Ishimori
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Hiraku Fuse
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Shin Miyakawa
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Kenji Yasue
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Hiroki Nosaka
    Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2 Ami, Amimachi, Ibaraki, 300-0394, Japan.
  • Shinji Abe
    Graduate School of Health Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan.

Keywords

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