A fully automated explainable predictive model for diagnosing pre-capillary and post-capillary pulmonary hypertension on routine unenhanced CT: results from the ASPIRE registry

A fully automated model for multi-structure cardiothoracic segmentation on unenhanced CT is achievable. The model can predict PH and identify patients with pre-capillary PH and PH-LHD with promising performance.

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Publication Details

Journal
European Heart Journal - Digital Health
Published
2025-10-25
DOI
https://doi.org/10.1093/ehjdh/ztaf124
Primary Topic
Pulmonary Hypertension Research and Treatments
Type
article
Field-Weighted Citation Impact
0.00

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article

A fully automated explainable predictive model for diagnosing pre-capillary and post-capillary pulmonary hypertension on routine unenhanced CT: results from the ASPIRE registry

Ze Ming Goh, Elliot W Checkley, Khalid Alghamdi, Krit Dwivedi et al.
European Heart Journal - Digital Health
Pulmonary Hypertension Research and Treatments
article

A fully automated explainable predictive model for diagnosing pre-capillary and post-capillary pulmonary hypertension on routine unenhanced CT: results from the ASPIRE registry

Ze Ming Goh, Elliot W Checkley, Khalid Alghamdi, Krit Dwivedi, David Gerard Kiely, Jonathan Taylor, Alireza Hokmabadi, Pankaj Garg, Georgia Hyde, Lojain Abdulaal, Peter Metherall, Ahmed Maiter, Mahan Salehi, Michael J. Sharkey, Samer Alabed, Turki Nasser Alnasser, Andrew J. Swift
article en

Abstract

A fully automated model for multi-structure cardiothoracic segmentation on unenhanced CT is achievable. The model can predict PH and identify patients with pre-capillary PH and PH-LHD with promising performance.

European Heart Journal - Digital HealthVol. 7(1)
University of East Anglia (GB), King Saud bin Abdulaziz University for Health Sciences (SA), King Abdullah International Medical Research Center (SA), Sheffield Teaching Hospitals NHS Foundation Trust (GB), Insigneo (GB), Sheffield Health and Social Care NHS Foundation Trust (GB), National Guard Health Affairs (SA), University of Sheffield (GB)
Wellcome Trust, National Institute for Health and Care Research, Department of Health and Social Care
Openalex Percentile: Top 55%
Pulmonary Hypertension Research and Treatments
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