MRI pyschophysics: An experimental framework relating image quality to diagnostic performance metrics

Daniel J. Durand, John A. Carrino, Laura M. Fayad, Thierry A.G.M. Huisman, Abdel Monem M. El-Sharkawy, William A. Edelstein

Research output: Contribution to journalArticle

Abstract

Purpose: To determine the minimal image quality needed to preserve diagnostic performance relative to arthroscopy in the knee. Materials and Methods: Synthetic noise was added to images from clinical MRI scans (three-dimensional SPACE pulse sequence; Siemens) from five patients who had undergone knee MRI with arthroscopic follow-up, resulting in 25 simulated sets of images with standardized signal-to-noise ratios (SNRs) of 1, 2, 5, 10, or 20. All cases were scored by four musculoskeletal radiologists progressing from low to high SNR and grading all cartilage surfaces, major ligaments and menisci on a 5-point scale. Receiver operator characteristic (ROC) curves were constructed for the detection of meniscal tears and cartilage abnormalities. The area under the ROC curve (AUC) was determined for each structure at each SNR level. In addition, reader confidence was measured and pairwise comparisons across SNR levels were performed. Results were compared with arthroscopy as the reference standard. Results: ROC AUC was maximized for meniscal tears at SNR = 5 (structure specific CNR = 3.2) and for cartilage abnormalities at SNR = 10 (CNR = 4.2). Observer confidence was maximized for menisci at SNR = 5 (CNR = 8.0), for ligaments at SNR = 10 (CNR = 13.6) and cartilage at SNR = 10 (CNR = 8.2). Conclusion: For 3D isotropic imaging in the knee, images with SNR < 10 or CNR < 10 should be rejected as nondiagnostic.

Original languageEnglish (US)
Pages (from-to)1402-1408
Number of pages7
JournalJournal of Magnetic Resonance Imaging
Volume37
Issue number6
DOIs
StatePublished - Jun 1 2013

Keywords

  • contrast-to-noise ratio
  • diagnostic performance
  • healthcare quality
  • healthcare quality medtrics
  • image quality
  • image quality metrics
  • imaging throughput
  • magnetic resonance imaging
  • observer performance
  • psychophysics
  • rapid imaging
  • signal-to-noise ratio
  • utilization management

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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    Durand, D. J., Carrino, J. A., Fayad, L. M., Huisman, T. A. G. M., El-Sharkawy, A. M. M., & Edelstein, W. A. (2013). MRI pyschophysics: An experimental framework relating image quality to diagnostic performance metrics. Journal of Magnetic Resonance Imaging, 37(6), 1402-1408. https://doi.org/10.1002/jmri.23922