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Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?

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Abstract

Purpose

To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA).

Materials and Methods

We included CTPA examinations of 79 patients (50 female, 52 ± 18 years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE. After 3 months all studies were reevaluated by the same two readers, this time aided by CAD prototype. A consensus read by three expert radiologists served as the reference standard. Statistical analysis used χ2 and McNemar testing.

Results

Expert consensus revealed 119 PEs in 32 studies. For PE detection, the sensitivity of CAD alone was 78%. Inexperienced readers’ initial interpretations had an average per-PE sensitivity of 50%, which improved to 71% (p < 0.001) with CAD as a second reader. False positives increased from 0.18 to 0.25 per study (p = 0.03). Per-study, the readers initially detected 27/32 positive studies (84%); with CAD this number increased to 29.5 studies (92%; p = 0.125).

Conclusion

Our results suggest that CAD significantly improves the sensitivity of PE detection for inexperienced readers with a small but appreciable increase in the rate of false positives.

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Acknowledgement

CF, LB, and MS are employees of Siemens. GB is a consultant for General Electric, Medrad, and Siemens. UJS is a medical consultant for and receives research support from Bayer-Schering, Bracco, General Electric, Medrad, and Siemens. The other authors have no conflict of interest.

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Authors and Affiliations

  1. Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226 25 Courtenay Drive, Charleston, SC, 29401, USA

    Kevin N. Blackmon, Joshua W. McCain, James D. Koonce, Heon Lee, Gorka Bastarrika, Christian Thilo, Philip Costello & U. Joseph Schoepf

  2. H IM SYNGO CAD Research and Development, Siemens AG, Malvern, PA, USA

    Charles Florin, Luca Bogoni & Marcos Salganicoff

  3. Department of Radiology, Seoul Medical Center, Seoul, Republic of Korea

    Heon Lee

  4. Department of Radiology, University of Navarra, Pamplona, Spain

    Gorka Bastarrika

  5. Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA

    Christian Thilo & U. Joseph Schoepf

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  1. Kevin N. Blackmon
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  2. Charles Florin
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  3. Luca Bogoni
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  4. Joshua W. McCain
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  8. Christian Thilo
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  9. Philip Costello
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  10. Marcos Salganicoff
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  11. U. Joseph Schoepf
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Correspondence to U. Joseph Schoepf.

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Blackmon, K.N., Florin, C., Bogoni, L. et al. Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?. Eur Radiol 21, 1214–1223 (2011). https://doi.org/10.1007/s00330-010-2050-x

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  • DOI: https://doi.org/10.1007/s00330-010-2050-x

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