Radiology Errors

Written by: James Demetrious, DC, DABCO

Board Certified Chiropractic Orthopedist

Radiology plays a pivotal role in diagnosing skeletal conditions, yet errors in interpreting musculoskeletal images remain a significant concern. Recent studies indicate that diagnostic inaccuracies in skeletal radiology persist, with error rates ranging from 3% to 30%, depending on the context and definition of error. [1]

Prevalence and Types of Errors

Diagnostic errors in radiology are broadly categorized into perceptual and cognitive errors. Perceptual errors, accounting for approximately 60% to 80% of diagnostic mistakes, occur when radiologists fail to detect abnormalities present in the images. Cognitive errors, comprising about 20% to 40%, involve misinterpretation of identified findings. [2]

In emergency department settings, the error rate for interpreting skeletal radiographs is approximately 3%, with higher rates observed in specific regions such as the upper limb, where misinterpretation occurs in about 8.5% of cases. These errors can lead to missed fractures or misdiagnosed conditions, impacting patient outcomes. [1]

Contributing Factors

Several factors contribute to diagnostic errors in skeletal radiology:

  • Complex Anatomy: The intricate structure of bones and joints can make interpretation challenging, especially in areas with overlapping structures.
  • Subtle Findings: Small or non-displaced fractures may be difficult to detect, particularly in the acute setting.
  • Technical Limitations: Poor image quality due to suboptimal positioning or exposure can obscure critical findings.
  • Human Factors: Fatigue, high workload, and cognitive biases can impair a radiologist’s ability to accurately interpret images. [3]

Advancements and Solutions

To mitigate these errors, several strategies have been proposed and implemented:

  • Double Reading: Having two radiologists independently interpret images can reduce error rates by providing a second opinion.
  • Structured Reporting: Using standardized templates ensures that all relevant anatomical areas are assessed systematically.
  • Artificial Intelligence (AI): AI algorithms have shown promise in detecting fractures and other skeletal abnormalities, serving as a supplementary tool to assist radiologists. [4]
  • Continuous Education: Ongoing training and awareness programs can help radiologists recognize and address common pitfalls in image interpretation.

Conclusion

While radiology is indispensable in evaluating skeletal structures, diagnostic errors remain a concern with significant implications for patient care. Understanding the prevalence and causes of these errors is crucial in developing effective strategies to enhance diagnostic accuracy. Through a combination of technological advancements, systematic approaches, and continuous education, the goal of reducing radiologic errors in skeletal assessments becomes increasingly attainable.

References

  1. York et al. Reporting errors in plain radiographs for lower limb trauma—a systematic review and meta-analysis. Skeletal Radiol 51, 171–182 (2022). https://doi.org/10.1007/s00256-021-03821-9.
  2. Zhang et al. Diagnostic error and bias in the department of radiology: a pictorial essay. Insights Imaging. 2023 Oct 2;14(1):163. doi: 10.1186/s13244-023-01521-7.
  3. Chen et al. Investigating the impact of cognitive biases in radiologists’ image interpretation: A scoping review. European Journal of Radiology,166,
    2023,111013. https://doi.org/10.1016/j.ejrad.2023.111013.
  4. Kraus et al. What’s new in pediatric musculoskeletal imaging. J Child Orthop. 2025 Mar 12;19(2):109-118. doi: 10.1177/18632521251325122.

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