Homology-feature-assisted quantification of fibrotic lesions in computed tomography images: a proof of concept for CT image feature-based prediction for gene-expression-distribution - Takeaways - MDSpire

Homology-feature-assisted quantification of fibrotic lesions in computed tomography images: a proof of concept for CT image feature-based prediction for gene-expression-distribution

  • By

  • Kentaro Doi

  • Hodaka Numasaki

  • Yusuke Anetai

  • Yayoi Natsume-Kitatani

  • May 28, 2025

  • 0 min

Share

  • 1

    Idiopathic interstitial pneumonia (IIP) includes various categories, with idiopathic pulmonary fibrosis (IPF) having a significantly poorer prognosis.

  • 2

    High-resolution computed tomography (HRCT) images are essential for diagnosing IIPs, but accurate classification remains challenging due to inter-observer variability.

  • 3

    Homology-based image analysis can effectively capture features in medical images, improving the performance of radiomic analyses for conditions like lung cancer.

  • 4

    The study hypothesizes that homology-based features (HFs) can quantify fibrotic lesions in HRCT images, demonstrating potential for IIP diagnosis.

  • 5

    CT images from COVID-19 cases show fibrotic lesions similar to those in IIPs, supporting the application of the homology-profile method for quantification.

Original Source(s)

Homology-feature-assisted quantification of fibrotic lesions in computed tomography images: a proof of concept for CT image feature-based prediction for gene-expression-distribution

  • by Kentaro Doi, Hodaka Numasaki, Yusuke Anetai, Yayoi Natsume-Kitatani

  • May 28, 2025

Related Content

Postoperative Chylothorax Leading to Chylous Pericardial Tamponade After Right Upper Lobectomy: A Case Study of an Uncommon Condition

Research advances of tubeless thoracic surgery for pulmonary nodules: current status and future challenges

Perioperative Outcomes of Robot-Assisted versus Video-Assisted Thoracoscopic Surgery for Non-Small Cell Lung Cancer: A Meta-Analysis Focusing on Real-World Clinical Studies in the Past 10 Years