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Diagnoses of pulmonary embolism from non-contrast 4DCT using image processing-derived quantitative perfusion scores

  • Hsu-Ting Kuo
  • , Yi-Kuan Liu
  • , Debarghya Chaki
  • , Girish Nair
  • , Danielle Turner-Lawrence
  • , Craig Stevens
  • , Jorge Cisneros
  • , Edward Castillo

Research output: Contribution to journalArticlepeer-review

Abstract

Computed tomography pulmonary angiography (CTPA) is the gold standard for pulmonary embolism (PE) diagnosis, but patients with iodinated contrast allergies or renal insufficiency are often ineligible. CT-derived perfusion (CTP) is a novel, non-contrast method to quantify pulmonary perfusion from an inhale/exhale CT image pair (4DCT). The resulting CT-P information can be used to identify hypo-perfused regions associated with PE. This pilot study introduces a thresholding approach that estimates the number of lung lobes with perfusion deficits according to optimally selected CTP thresholds. The number of lobes indicated as low-functioning provides a score to categorize patients as PE-positive, negative, or inconclusive. We trained and validated the model on a retrospective dataset of 123 suspected PE patients, achieving 72% accuracy, 75% sensitivity, and 69% specificity, with 17% of cases inconclusive. To our knowledge, this is the first PE diagnostic model from non-contrast 4DCT, showing the feasibility of non-contrast PE diagnosis strategies.

Original languageEnglish
Journalnpj biomedical innovations
Volume3
Issue number1
DOIs
StatePublished - May 4 2026

Bibliographical note

© 2026. The Author(s).

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