Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients.

Journal: Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Published Date: Sep 1, 2023

Abstract

PURPOSE: Deep learning reconstruction (DLR) has been recommended as useful for improving image quality. Moreover, compressed sensing (CS) or DLR has been proposed as useful for improving temporal resolution and image quality on MR sequences in different body fields. However, there have been no reports regarding the utility of DLR for image quality and T-factor assessment improvements on T2-weighted imaging (T2WI), short inversion time (TI) inversion recovery (STIR) imaging, and unenhanced- and contrast-enhanced (CE) 3D fast spoiled gradient echo (GRE) imaging with and without CS in comparison with thin-section multidetector-row CT (MDCT) for non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine the utility of DLR for improving image quality and the appropriate sequence for T-category assessment for NSCLC patients.

Authors

  • Daisuke Takenaka
    From the Department of Radiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake 470-1192, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.O., S.S., T.Y.); Canon Medical Systems, Otawara, Japan (K.A.); Corporate Research and Development Center, Toshiba, Kawasaki, Japan (A.Y.); Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U., Y.K.); Department of Radiology, Kohnan Hospital, Kobe, Japan (Y.K.); and Department of Radiology, Hyogo Cancer Center, Akashi, Japan (D.T.).
  • Yoshiyuki Ozawa
    Department of Radiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
  • Kaori Yamamoto
    Canon Medical Systems Corporation, 1385, Shimoishigami, Otawara, Tochigi, 324-0036, Japan. Electronic address: kaori4.yamamoto@medical.canon.
  • Maiko Shinohara
    Canon Medical Systems Corporation.
  • Masato Ikedo
    Canon Medical Systems Corporation, 1385, Shimoishigami, Otawara, Tochigi, 324-0036, Japan. Electronic address: masato.ikedo@medical.canon.
  • Masao Yui
    Canon Medical Systems Corporation, 1385, Shimoishigami, Otawara, Tochigi, 324-0036, Japan. Electronic address: masao.yui@medical.canon.
  • Yuka Oshima
    Department of Radiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
  • Nayu Hamabuchi
    Department of Radiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
  • Hiroyuki Nagata
    Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
  • Takahiro Ueda
    Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan. Electronic address: t-ueda@fujita-hu.ac.jp.
  • Hirotaka Ikeda
    Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan. Electronic address: h-ikeda@fujita-hu.ac.jp.
  • Akiyoshi Iwase
    Department of Radiology, Fujita Health University Hospital, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan. Electronic address: mrrider@fujita-hu.ac.jp.
  • Takeshi Yoshikawa
    From the Department of Radiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake 470-1192, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.O., S.S., T.Y.); Canon Medical Systems, Otawara, Japan (K.A.); Corporate Research and Development Center, Toshiba, Kawasaki, Japan (A.Y.); Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U., Y.K.); Department of Radiology, Kohnan Hospital, Kobe, Japan (Y.K.); and Department of Radiology, Hyogo Cancer Center, Akashi, Japan (D.T.).
  • Hiroshi Toyama
    School of Medicine, Fujita Health University, 1-98 Dengakugakubo, Kutsukake cho, Toyoake City, Aichi, 470-1192, Japan.
  • Yoshiharu Ohno
    From the Department of Radiology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake 470-1192, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.O., S.S., T.Y.); Canon Medical Systems, Otawara, Japan (K.A.); Corporate Research and Development Center, Toshiba, Kawasaki, Japan (A.Y.); Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U., Y.K.); Department of Radiology, Kohnan Hospital, Kobe, Japan (Y.K.); and Department of Radiology, Hyogo Cancer Center, Akashi, Japan (D.T.).

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