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- Galit Aviram, Chen Sirota-Cohen, Arie Steinvil, Gad Keren, Shmuel Banai, Jacob Sosna, Shlomo Berliner, and Ori Rogowski.
- Department of Radiology, Tel Aviv Sourasky Medical Center, affiliated to the Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. aviramgalit@hotmail.com
- Thromb Haemostasis. 2012 Aug 1; 108 (2): 384-93.
AbstractIdentification of patients with acute pulmonary embolism (PE) who might be at risk of circulatory collapse by using a fast, automated system is highly desired. It was our objective to investigate whether automated cardiac volumetric analysis following computerised tomographic pulmonary angiography (CTPA) is useful to identify increased clot load and adverse prognosis in patients with acute PE. We retrospectively analysed a consecutive series of non-gated CTPA studies of 124 patients with acute PE and 43 controls. Right and left ventricular diameters (RV/LV) were measured on four-chamber view, while each cardiac chamber underwent automatic volumetric measurements. Findings were correlated to the pulmonary arterial obstruction index (PAOI). Outcome was expressed by admission to an intensive care unit (ICU) or mortality within 30 days. There was a significant positive correlation between the PAOI and the volumes of the right side cavities (r=0.25 for the atrium and r=0.49 for the ventricle), and between the right-to-left atrial and ventricular volume ratios (r=0.49 and r=0.57, respectively). Results for the combined outcome of mortality or ICU admission that fell in the upper tertile of the right atrial and right ventricular volumes yielded hazard ratios of 3.9 and 3.3, respectively, compared to those in the lower tertile. RV/LV diameter ratio did not correlate with outcome. In conclusion, adverse outcome and significant pulmonary clot load in patients with acute PE are associated with a volume shift towards right heart cavities, which correlates to prognosis better than the CT-measured RV/LV diameter ratio, suggesting the advantage of using fast fully automatic volumetric analysis to identify patients at risk.
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