Interobserver variability in quality assessment of magnetic resonance images

Rafal Obuchowicz1, Mariusz Oszust2, Adam Piorkowski3

  • 1Department of Diagnostic Imaging, Jagiellonian University Medical College, Kopernika Street 19, Cracow, 31-501, Poland.

BMC Medical Imaging
|September 23, 2020
PubMed
Abstract

Insights

Assessing magnetic resonance (MR) image quality reveals significant agreement among radiologists, though individual perception varies. This study confirms that MR image quality assessment skills can be effectively taught, improving diagnostic consistency.

Area of Science:

  • Medical Imaging Analysis
  • Radiology
  • Image Quality Assessment

Background:

  • Perceptual quality of magnetic resonance (MR) images is crucial for accurate diagnosis and effective treatment.
  • Image quality degradation can compromise diagnostic accuracy and treatment outcomes.
  • Understanding interobserver variability in MR image assessment is essential.

Purpose of the Study:

  • To evaluate how changes in MR image quality influence interobserver variability in assessment.
  • To quantify the agreement and consistency among radiologists evaluating MR image quality.

Main Methods:

  • A dataset of distorted MR images was assessed by 31 experienced radiologists.
  • Interobserver agreement was analyzed using Fleiss' kappa (κ).
  • Image Quality Assessment (IQA) performance was evaluated using Spearman correlation coefficients (ρ) against mean opinion scores (MOS).

Main Results:

  • Significant agreement was found among radiologists (κ=0.12, P<0.001), influenced by score subjectivity.
  • Spearman correlation (ρ) confirmed consistency, with a mean ρ of 0.5706 for all radiologists.
  • Interns showed higher consistency (mean ρ=0.6868), indicating successful training in MR image quality assessment.

Conclusions:

  • Agreement among radiologists from different centers highlights the subjective nature of MR image perception.
  • Image content and distortion severity significantly impact IQA.
  • Observer's psychosomatic condition and attitude are important factors in image quality perception.

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