Computer-aided diagnosis improves detection of small intracranial aneurysms on MRA in a clinical setting

I. L. Štepán-Buksakowska, J. M. Accurso, F. E. Diehn, J. Huston, T. J. Kaufmann, P. H. Luetmer, C. P. Wood, X. Yang, D. J. Blezek, R. Carter, C. Hagen, D. Hořínek, A. Hejčl, M. Rǒcek, B. J. Erickson

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

BACKGROUND AND PURPOSE: MRA is widely accepted as a noninvasive diagnostic tool for the detection of intracranial aneurysms, but detection is still a challenging task with rather low detection rates. Our aim was to examine the performance of a computer-aided diagnosis algorithm for detecting intracranial aneurysms on MRA in a clinical setting.

MATERIALS AND METHODS: Aneurysm detectability was evaluated retrospectively in 48 subjects with and without computer-aided diagnosis by 6 readers using a clinical 3D viewing system. Aneurysms ranged from 1.1 to 6.0 mm (mean=3.12 mm, median=2.50 mm). We conducted a multireader, multicase, double-crossover design, free-response, observer-performance study on sets of images from different MRA scanners by using DSA as the reference standard. Jackknife alternative free-response operating characteristic curve analysis with the figure of merit was used.

RESULTS: For all readers combined, the mean figure of merit improved from 0.655 to 0.759, indicating a change in the figure of merit attributable to computer-aided diagnosis of 0.10 (95% CI, 0.03-0.18), which was statistically significant (F1,47 = 7.00, P = .011). Five of the 6 radiologists had improved performance with computer-aided diagnosis, primarily due to increased sensitivity.

CONCLUSIONS: In conditions similar to clinical practice, using computer-aided diagnosis significantly improved radiologists' detection of intracranial DSA-confirmed aneurysms of ≤6 mm.

Original languageEnglish (US)
Pages (from-to)1897-1902
Number of pages6
JournalAmerican Journal of Neuroradiology
Volume35
Issue number10
DOIs
StatePublished - Oct 1 2014

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

Fingerprint Dive into the research topics of 'Computer-aided diagnosis improves detection of small intracranial aneurysms on MRA in a clinical setting'. Together they form a unique fingerprint.

  • Cite this

    Štepán-Buksakowska, I. L., Accurso, J. M., Diehn, F. E., Huston, J., Kaufmann, T. J., Luetmer, P. H., Wood, C. P., Yang, X., Blezek, D. J., Carter, R., Hagen, C., Hořínek, D., Hejčl, A., Rǒcek, M., & Erickson, B. J. (2014). Computer-aided diagnosis improves detection of small intracranial aneurysms on MRA in a clinical setting. American Journal of Neuroradiology, 35(10), 1897-1902. https://doi.org/10.3174/ajnr.A3996