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ORIGINAL ARTICLE
Year : 2019  |  Volume : 31  |  Issue : 1  |  Page : 78-85

Measurement of liver and spleen stiffness by acoustic radiation force impulse elastography for noninvasive detection of esophageal varices in Egyptian cirrhotic patients


1 Department of Internal Medicine, Ain Shams University, Cairo, Egypt
2 Department of Internal Medicine, National Research Centre, Cairo, Egypt
3 Department of Tropical Medicine, Ain Shams University, Cairo, Egypt

Correspondence Address:
Mohamed O Khalifa
Department of Tropical Medicine, Ain Shams University, Abbassia, Cairo
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejim.ejim_62_18

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Introduction and aim Screening for esophageal varices (EVs) is recommended in patients with cirrhosis. Recent studies have focused on noninvasive prediction of EVs. The aim of the study was to evaluate the accuracy of liver stiffness (LS) and spleen stiffness (SS) measured by acoustic radiation force impulse (ARFI) elastography for noninvasive detection of EVs in Egyptian cirrhotic patients. Patients and methods In this prospective study, we performed ARFI elastography to measure LS and SS on 30 patients with cirrhosis undergoing endoscopic screening for EVs and on 15 healthy volunteers (controls). The diagnostic utility of LS and SS for identifying the presence of EVs was compared. Results Patients with EVs showed higher LS and SS values than patients without varices. The diagnostic performance of LS for the detection of varices at a cutoff value of more than 2.47 showed a sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of 73.3, 66.7, 68.7, 71.4, and 71.3%, respectively. Regarding SS, at a cutoff value of more than 3.02, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 93.3, 73.3, 77.8, 91.7, and 87.6%, respectively. Conclusion SS measured using ARFI imaging is superior to LS with excellent diagnostic performance for predicting EVs and may be used as a noninvasive screening tool for the detection of EVs.


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