Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.

Journal: Respiratory research
PMID: 39719582

Abstract

BACKGROUND: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI (CALIPER-CPI) was also developed to estimate the volume fraction of ILD measured by CALIPER, an automated quantitative CT postprocessing software. Recently, artificial intelligence-based quantitative CT image analysis software (AIQCT), which can be used to quantify the bronchial volume separately from the ILD volume, was developed and validated in IPF. The aim of this study was to develop AIQCT-derived CPI formulas to quantify CT abnormalities in IPF and to investigate the associations of these CPI formulas with survival.

Authors

  • Michihiro Uyama
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Tomohiro Handa
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Ryuji Uozumi
    Department of Biomedical Statistics and Bioinformatics, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Seishu Hashimoto
    Department of Respiratory Medicine, Tenri Hospital, Tenri, Japan.
  • Yoshio Taguchi
    Department of Respiratory Medicine, Tenri Hospital, Tenri, Japan.
  • Kohei Ikezoe
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Kiminobu Tanizawa
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Naoya Tanabe
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan. Electronic address: ntana@kuhp.kyoto-u.ac.jp.
  • Tsuyoshi Oguma
    Department of Respiratory Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Atsushi Matsunashi
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Takafumi Niwamoto
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Hiroshi Shima
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
  • Ryobu Mori
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Tomoki Maetani
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Yusuke Shiraishi
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
  • Tomomi W Nobashi
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Ryo Sakamoto
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
  • Takeshi Kubo
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Akihiko Yoshizawa
    Japanese Society of Pathology, Tokyo, Japan.
  • Kazuhiro Terada
    Department of Diagnostic Pathology, Kyoto University Hospital, Kyoto, Japan.
  • Yuji Nakamoto
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University.
  • Toyohiro Hirai
    Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.

Keywords

External Resources

Popular Topics
Recent Journals