Jung Hyun Park1, Yeo Koon Kim2, Bohyoung Kim3, Joonghee Kim4, Hyuksool Kwon4, Kyuseok Kim4, Sang Il Choi1, Eun Ju Chun1. 1. Department of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Korea. 2. Department of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Korea. Electronic address: yeokoon@snubh.org. 3. Division of Biomedical Engineering, Hankuk University of Foreign Studies. 4. Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Korea.
Abstract
PURPOSE: The aims of this study were to simulate mobile consultation for the coronary computed tomography angiography (CCTA) at the emergency department (ED) and to measure the diagnostic performance of the mobile reading. MATERIALS AND METHODS: A total of 107 patients with acute chest pain who underwent CCTA and coronary angiography (CAG) were included. The CCTA images were reviewed by a cardiac radiologist using a smartphone. The degree of stenosis at each coronary segment was scored with 4-point scale (score 1, <50%; score 2, 51%-70%; score 3, 71%-90%; score 4, >90%). The degree of stenosis at each coronary segments were also scored with preliminary CCTA report by on-call residents, final CCTA reports by in-house attending cardiac radiologists, and CAG. Interobserver agreement was measured using κ statistics. The areas under the receiver operating characteristic curves (AUCs) for diagnosing segments with obstructive stenosis were compared between each reader and CAG. RESULTS: The smartphone reader's reading was more similar to the CAG results and in-house radiologists' reports than reading of on-call residents. The diagnostic performance of smartphone reading for detection of obstructive stenosis was significantly greater than that of on-call residents (AUC, 0.89 vs 0.75; P<.001) and did not significantly differ from that of the in-house radiologists (AUC, 0.89 vs 0.90; P=.05). CONCLUSION: Smartphone reading by the cardiac radiologist was superior to the on-call residents' reading. Further study with real-time mobile consultation needs to be investigated to evaluate whether improvement in diagnostic competency can make a difference in the outcome of patients.
PURPOSE: The aims of this study were to simulate mobile consultation for the coronary computed tomography angiography (CCTA) at the emergency department (ED) and to measure the diagnostic performance of the mobile reading. MATERIALS AND METHODS: A total of 107 patients with acute chest pain who underwent CCTA and coronary angiography (CAG) were included. The CCTA images were reviewed by a cardiac radiologist using a smartphone. The degree of stenosis at each coronary segment was scored with 4-point scale (score 1, <50%; score 2, 51%-70%; score 3, 71%-90%; score 4, >90%). The degree of stenosis at each coronary segments were also scored with preliminary CCTA report by on-call residents, final CCTA reports by in-house attending cardiac radiologists, and CAG. Interobserver agreement was measured using κ statistics. The areas under the receiver operating characteristic curves (AUCs) for diagnosing segments with obstructive stenosis were compared between each reader and CAG. RESULTS: The smartphone reader's reading was more similar to the CAG results and in-house radiologists' reports than reading of on-call residents. The diagnostic performance of smartphone reading for detection of obstructive stenosis was significantly greater than that of on-call residents (AUC, 0.89 vs 0.75; P<.001) and did not significantly differ from that of the in-house radiologists (AUC, 0.89 vs 0.90; P=.05). CONCLUSION: Smartphone reading by the cardiac radiologist was superior to the on-call residents' reading. Further study with real-time mobile consultation needs to be investigated to evaluate whether improvement in diagnostic competency can make a difference in the outcome of patients.
Authors: Sven Y Vetter; Svenja Schüler; Matthes Hackbusch; Michael Müller; Benedict Swartman; Marc Schnetzke; Paul Alfred Grützner; Jochen Franke Journal: J Digit Imaging Date: 2018-02 Impact factor: 4.056