New Quantitative Digital Image Analysis Method of Histological Features of Carotid Atherosclerotic Plaques.

OBJECTIVE

Atherosclerosis and its thrombotic complications are major causes of morbidity and mortality worldwide. Plaque stability assessment is considered to be important for both clinical and fundamental applications. The current gold standard method to investigate plaque stability is performed by histological assessment of plaque features using semi-quantitative classifications. However, these assessments can be limited by subjectivity and variability. Thus, the aim was to develop a new digital image analysis method to measure quantitatively individual plaque features that is more precise than existing semi-quantitative methods.

METHODS

A quantitative method was developed using Image Pro Primer software. Carotid plaque specimens were obtained from patients who underwent carotid endarterectomy and categorised according to stability (definitely stable, probably stable, probably unstable, definitely unstable) based on the gold standard semi-quantitative method that assesses 10 histological plaque features. Using the new quantitative method, plaque features (n = 15) from each stability grade were then analysed by two independent raters. For the semi-quantitative analysis, quadratic weighted Cohen's kappa was used to test intra- and inter-rater reliability, while for the quantitative analysis, intraclass correlation coefficients (ICCs) were assessed.

RESULTS

Intra-rater reliability demonstrated almost perfect agreement between both methods (Cohen's kappa range 0.831-0.969, ICC range 0.848-1.000). However, inter-rater reliability demonstrated mainly fair to moderate agreement (Cohen's kappa range 0.341-0.778) for the semi-quantitative analysis, while the digital image analysis method performed most optimally regarding reproducibility, yielding high ICCs close to 1 (ICC range 0.816-0.999). Using quantitative measurements, a statistically significant proportion of the individual plaque features (p < .05) were re-classified from one grade to another (shift by one) under the semi-quantitative classification.

CONCLUSION

A new quantitative digital image analysis was developed for the accurate assessment of histological plaque features, which demonstrated higher precision than the gold standard semi-quantitative methods, as measured by between and within rater analysis. Moreover, quantitative image analysis of histological plaque features provided more detailed insight into plaque morphology and composition.