Details

Autor(en) / Beteiligte

• Hashoul, Sharbell, MD
• Gaspar, Tamar, MD
• Halon, David A., MBChB
• Lewis, Basil S., MD
• Shenkar, Yuval, MD
• Jaffe, Ronen, MD
• Peled, Nathan, MD
• Rubinshtein, Ronen, MD

Titel

Automated Computer-Assisted Diagnosis of Obstructive Coronary Artery Disease in Emergency Department Patients Undergoing 256-Slice Coronary Computed Tomography Angiography for Acute Chest Pain

Ist Teil von

• The American journal of cardiology, 2015-10, Vol.116 (7), p.1017-1021

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2015

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• A 256-slice coronary computed tomography angiography (CCTA) is an accurate method for detection and exclusion of obstructive coronary artery disease (OBS-CAD). However, accurate image interpretation requires expertise and may not be available at all hours. The purpose of this study was to evaluate the usefulness of a fully automated computer-assisted diagnosis (COMP-DIAG) tool for exclusion of OBS-CAD in patients in the emergency department (ED) presenting with chest pain. Three hundred sixty-nine patients in ED without known coronary disease underwent 256-slice CCTA as part of the assessment of chest pain of uncertain origin. COMP-DIAG (CorAnalyzer II) automatically reported presence or exclusion of OBS-CAD (>50% stenosis, ≥1 vessel). Performance characteristics of COMP-DIAG for exclusion and detection of OBS-CAD were determined using expert reading as the reference standard. Seventeen (5%) studies were unassessable by COMP-DIAG software, and 352 patients (1,056 vessels) were therefore available for analysis. COMP-DIAG identified 33% of assessable studies as having OBS-CAD, but the prevalence of OBS-CAD on CCTA was only 18% (66 of 352 patients) by standard expert reading. However, COMP-DIAG correctly identified 61 of the 66 patients (93%) with OBS-CAD with 21 vessels (2%) with OBS-CAD misclassified as negative. In conclusion, compared to expert reading, automated computer-assisted diagnosis using the CorAnalyzer showed high sensitivity but only moderate specificity for detection of obstructive coronary disease in patients in ED who underwent 256-slice CCTA. The high negative predictive value of this computer-assisted algorithm may be useful in the ED setting.