How to publish diagnostic imaging studies: Common mistakes and recommendations.

The research article discusses the challenges and best practices in publishing diagnostic imaging studies pertaining to equine veterinary medicine. It highlights areas such as establishing standards for comparisons, understanding statistical terms, the importance of sample selection and size planning, and considerations on imaging accuracy and precision.

The Gold Standard and Comparative Modalities

• The article talks about the ‘gold standard’ that all imaging studies are compared against, usually a histopathology or surgery report. This provides a comparison for the effectiveness and validity of the imaging modality being studied.
• However, the access to, and invasiveness of, such gold standard practices can be a challenge, leading to comparisons between different imaging modalities like ultrasound, CT, or MRI. These comparisons are typically based on assumed accuracy, which the authors caution against.

Statistics in Diagnostic Testing

• The paper describes the four possible outcomes of a diagnostic test – true positive, true negative, false positive, and false negative. These are important terms used to determine the accuracy and effectiveness of various imaging methods.
• The authors caution against assuming one modality (for instance, CT imaging) to be always accurate or superior than another (like radiographs), without a gold standard for comparison. This can lead to bias and misinformation.

Predictive Values and Disease Prevalence

• The research discusses the concept of ‘predictive values’ in the context of clinical settings. The positive and negative predictive values can provide insights into the real-world accuracy of a diagnostic tool, taking into account the prevalence of a specific disease within a population.
• The authors underline the significance of considering disease prevalence when looking at diagnostic test sensitivity and specificity. They provide an example of a study that demonstrates how disease prevalence influences predictive values.

Accuracy, Precision and Operator Impact

• The paper explains the terms ‘accuracy’ and ‘precision’ as they apply to imaging studies. Accuracy refers to the closeness of an observation to the true value, while precision is the repeatability of measurements.
• Lastly, the authors emphasize the impact of the operator on the imaging outcomes. They discuss intraoperator (single operator, multiple attempts), intraobserver (same observer, different times), and interobserver (different observers) variability, highlighting these are key considerations when analyzing the quality of a diagnostic imaging study.