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Efficacy of Computed Tomography Pulmonary Angiography as Non-invasive Imaging Biomarker for Risk Stratification of Acute Pulmonary Embolism

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Objectives: Massive and sub-massive pulmonary embolisms (PEs) are associated with high mortality and morbidity. The mainstay of treatment for PE is anticoagulation. However, high- and intermediate-risk patients may benefit from… Click to show full abstract

Objectives: Massive and sub-massive pulmonary embolisms (PEs) are associated with high mortality and morbidity. The mainstay of treatment for PE is anticoagulation. However, high- and intermediate-risk patients may benefit from interventional thrombolytic therapy. Computed tomography pulmonary angiography (CTPA) is widely available, fast, and non-invasive technique, and it can identify pulmonary thrombus down to at least a segmental level. In this study, we attempt to evaluate the efficacy of CTPA as a non-invasive imaging biomarker for risk stratification of acute PE (APE) patients. Material and Methods: This is a prospective study conducted on 150 patients who proved to have APE by CTPA. The simplified PE severity index score was obtained. The pulmonary artery obstruction index (PAOI) using and right to left ventricular (RV/LV) diameter ratios were calculated. Results: The patients were divided into (1) high risk (shocked) and (2) non-high risk groups. There was a significant difference between the 1st and 2nd groups regarding PAOI. Hemodynamically stable patients were further subclassified according to the right ventricular dysfunction (RVD) into Group Ia (intermediate risk) and Group Ib (low risk). There was a significant difference between subgroups regarding PAOI (P < 0.0001, r = 0.385). Receiver operating characteristic curve analysis revealed PAOI >47% associated with RV/LV ratio >1. Conclusion: Our results support the use of CTPA as a surrogate imaging biomarker for both diagnosis and risk stratification of APE patients. CTPA allows assessment of clot burden through PAOI calculation and identification of intermediate-risk PE through the assessment of RVD.

Keywords: risk stratification; non invasive; imaging biomarker; risk

Journal Title: Journal of Clinical Imaging Science
Year Published: 2020

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