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 - Scorecard - 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

Clinical Scorecard: Feature-based Analysis of Fibrotic Lesions in CT Imaging: A Conceptual Study on Predicting Gene Expression Distribution

At a Glance

CategoryDetail
ConditionIdiopathic interstitial pneumonia (IIP), including idiopathic pulmonary fibrosis (IPF)
Key MechanismsQuantification of fibrotic lesions in HRCT images using homology-based features (HFs) derived from Betti numbers (b0 and b1) via the homology-profile (HP) method
Target PopulationPatients with idiopathic interstitial pneumonia and COVID-19 cases exhibiting fibrotic lung lesions
Care SettingRadiology and diagnostic imaging settings utilizing high-resolution computed tomography (HRCT)

Key Highlights

  • IIP includes several categories with varying prognosis; IPF has the poorest prognosis and high mortality with acute exacerbations.
  • HRCT imaging is standard for diagnosing IIPs but has limitations due to inter-observer variability and difficulty in accurate classification.
  • The HP method quantifies fibrotic lesions by calculating Betti numbers representing connectivity and holes in CT image binary segments, potentially improving diagnostic accuracy.

Guideline-Based Recommendations

Diagnosis

  • Use HRCT imaging to identify typical fibrotic patterns such as traction bronchiectasis and honeycomb lung indicative of IPF.
  • Apply homology-profile (HP) method to HRCT images to quantify fibrotic lesions by analyzing connectivity features (Betti numbers).
  • Consider standardized thresholding between −700 to −400 HU for binarization in HP analysis.

Management

  • Recognize the poor prognosis of IPF and the importance of accurate diagnosis to guide treatment strategies.
  • Use quantitative imaging features to assist in differentiating fibrotic lesions from other lung abnormalities.

Monitoring & Follow-up

  • Monitor fibrotic lesion progression using serial HRCT imaging and homology-based feature mapping to assess changes in lesion connectivity and morphology.

Risks

  • Inter-observer variability in HRCT interpretation may lead to diagnostic inaccuracies.
  • Presence of interstitial lung abnormalities (ILAs) and lung cancer lesions can confound fibrotic lesion quantification.

Patient & Prescribing Data

Patients with idiopathic interstitial pneumonia and COVID-19 exhibiting fibrotic lung lesions

Quantitative imaging biomarkers derived from HP method may support clinical decision-making but no direct treatment data provided.

Clinical Best Practices

  • Employ HRCT imaging with standardized protocols for lung field extraction and image preprocessing.
  • Utilize homology-profile method with validated tile size (32×32 pixels) and shifting (8 pixels) for detailed fibrotic lesion mapping.
  • Exclude lung cancer lesions and obvious lung abnormalities when analyzing fibrotic lesions to reduce noise in quantification.

References

Original Source(s)

Related Content