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Machine learning-based hemodynamics quantitative assessment of pulmonary circulation using computed tomographic

Hongyan Xie1, Xin Zhao2, Nan Zhang1

  • 1Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Rd, Chaoyang District, Beijing, China.

International Journal of Cardiology
|June 1, 2025
PubMed
Summary

A new radiomic feature model using computed tomographic pulmonary angiography (CTPA) offers a noninvasive method for evaluating pulmonary hemodynamics, potentially serving as an alternative to right heart catheterization (RHC). This model accurately predicts pulmonary hypertension (PH) and its associated hemodynamic parameters.

Keywords:
Artificial intelligenceComputed tomographyDiagnosisHemodynamicsPulmonary hypertensionRadiomic features

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Area of Science:

  • Cardiology
  • Radiology
  • Medical Imaging

Background:

  • Pulmonary hypertension (PH) is a severe condition affecting pulmonary circulation.
  • Right heart catheterization (RHC) is the standard for assessing pulmonary hemodynamics.
  • Noninvasive methods for quantitative hemodynamic evaluation are limited.

Purpose of the Study:

  • To develop and validate a noninvasive method for quantitative evaluation of pulmonary hemodynamics.
  • To assess the performance of a radiomic feature model derived from CTPA compared to RHC.
  • To determine the accuracy and reproducibility of the radiomic model in predicting PH and hemodynamic parameters.

Main Methods:

  • Patients with CTPA and RHC within two weeks were included.
  • A radiomic feature model and a 2D feature model were constructed.
  • Model performance was evaluated using mean squared error, ICC, AUC-PR, and Bland-Altman analysis.

Main Results:

  • The radiomic feature model, integrating 2D and 30 radiomic features, showed consistency with RHC results.
  • The radiomic model outperformed a 2D feature model.
  • The radiomic model demonstrated good reproducibility (ICC=0.87) and accurately identified PH (AUC-PR=0.99).

Conclusions:

  • CTPA-derived radiomic features offer a noninvasive approach for quantitative pulmonary hemodynamics assessment.
  • This method shows potential as an alternative to RHC for evaluating PH.
  • Further validation is needed before widespread clinical adoption.