Literature DB >> 23601293

Influence of observer experience and training on proficiency in coronary CT angiography interpretation.

Christopher Herzog1, J Matthias Kerl, Salvatore De Rosa, Tuna Tekin, Eike Boehme, Sven Liem, Miriam Scheuchenzuber, He-Ri Kim, Ralf W Bauer, Justin R Silverman, Peter L Zwerner, Hanns Ackermann, Thomas J Vogl, U Joseph Schoepf.   

Abstract

PURPOSE: To assess the influence of experience and training on the proficiency in coronary CT angiography (CCTA) interpretation of practitioners with different levels of experience. METHODS AND MATERIALS: Nine radiologist and cardiologist observers with varying prior CCTA experience ranging from novice to expert independently analyzed two case series of 50 catheter-correlated CCTA studies for coronary artery stenosis (0%, ≤49%, 50-74%, 75-99%, or 100%). Results of the first case series were unblinded and presented along with catheter angiography results to each reader before proceeding to the second series. Diagnostic accuracy on a per-segment basis was compared for all readers and both case series, respectively.
RESULTS: Correlation coefficients between CCTA and catheter angiography initially ranged between good (r=0.87) and poor (r=0.26), depending on reader experience, and significantly (p<0.05) improved in the second case series (range: r=0.42 to r=0.91). Diagnostic accuracy was significantly (p<0.05) higher for more experienced readers (range: 96.5-97.8%) as compared to less experienced observers (range: 90.7-93.6%). After completion of the second case series for less experienced readers sensitivity and PPV significantly (p<0.05) improved (range: 62.7-67.8%/51.4-84.1%), but still remained significantly (p<0.05) lower as compared to more experienced observers (range: 89.8-93.3%/80.6-93.3%).
CONCLUSION: The level of experience appears to be a strong determinant of proficiency in CCTA interpretation. Limited one-time training improves proficiency in novice readers, but not to clinically satisfactory levels.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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Year:  2013        PMID: 23601293     DOI: 10.1016/j.ejrad.2013.02.037

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  7 in total

1.  Central Core Laboratory versus Site Interpretation of Coronary CT Angiography: Agreement and Association with Cardiovascular Events in the PROMISE Trial.

Authors:  Michael T Lu; Nandini M Meyersohn; Thomas Mayrhofer; Daniel O Bittner; Hamed Emami; Stefan B Puchner; Borek Foldyna; Martin E Mueller; Steven Hearne; Clifford Yang; Stephan Achenbach; Quynh A Truong; Brian B Ghoshhajra; Manesh R Patel; Maros Ferencik; Pamela S Douglas; Udo Hoffmann
Journal:  Radiology       Date:  2017-11-27       Impact factor: 11.105

2.  Computer-aided CT coronary artery stenosis detection: comparison with human reading and quantitative coronary angiography.

Authors:  Matthias Rief; Anisha Kranz; Lisa Hartmann; Robert Roehle; Michael Laule; Marc Dewey
Journal:  Int J Cardiovasc Imaging       Date:  2014-08-13       Impact factor: 2.357

3.  Quality and safety of coronary computed tomography angiography at academic and non-academic sites: insights from a large European registry (ESCR MR/CT Registry).

Authors:  Borek Foldyna; Johannes Uhlig; Robin Gohmann; Christian Lücke; Thomas Mayrhofer; Lukas Lehmkuhl; Luigi Natale; Rozemarijn Vliegenthart; Joachim Lotz; Rodrigo Salgado; Marco Francone; Christian Loewe; Konstantin Nikolaou; Fabian Bamberg; David Maintz; Pal Maurovich-Horvat; Holger Thiele; Udo Hoffmann; Matthias Gutberlet
Journal:  Eur Radiol       Date:  2022-03-10       Impact factor: 7.034

4.  Total coronary atherosclerotic plaque burden assessment by CT angiography for detecting obstructive coronary artery disease associated with myocardial perfusion abnormalities.

Authors:  Satoru Kishi; Tiago A Magalhães; Rodrigo J Cerci; Matthew B Matheson; Andrea Vavere; Yutaka Tanami; Pieter H Kitslaar; Richard T George; Jeffrey Brinker; Julie M Miller; Melvin E Clouse; Pedro A Lemos; Hiroyuki Niinuma; Johan H C Reiber; Carlos E Rochitte; Frank J Rybicki; Marcelo F Di Carli; Christopher Cox; Joao A C Lima; Armin Arbab-Zadeh
Journal:  J Cardiovasc Comput Tomogr       Date:  2016-01-14

5.  Computer-aided analysis of 64- and 320-slice coronary computed tomography angiography: a comparison with expert human interpretation.

Authors:  Moshrik Abd Alamir; Pamela Noack; Kristine H Jang; Jhanna A Moore; Roman Goldberg; Michael Poon
Journal:  Int J Cardiovasc Imaging       Date:  2018-04-25       Impact factor: 2.357

6.  Artificial intelligence stenosis diagnosis in coronary CTA: effect on the performance and consistency of readers with less cardiovascular experience.

Authors:  Xianjun Han; Nan Luo; Lixue Xu; Jiaxin Cao; Ning Guo; Yi He; Min Hong; Xibin Jia; Zhenchang Wang; Zhenghan Yang
Journal:  BMC Med Imaging       Date:  2022-02-17       Impact factor: 1.930

7.  Automated Identification of Coronary Arteries in Assisting Inexperienced Readers: Comparison between Two Commercial Vendors.

Authors:  Domenico De Santis; Giuseppe Tremamunno; Carlotta Rucci; Tiziano Polidori; Marta Zerunian; Giulia Piccinni; Luca Pugliese; Benedetta Masci; Nicolò Ubaldi; Andrea Laghi; Damiano Caruso
Journal:  Diagnostics (Basel)       Date:  2022-08-16
  7 in total

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