Abstract
Funding Acknowledgements
Type of funding sources: Other. Main funding source(s): Medical Research Scotland(MRS) Guerbet Group
Background
Cardiac MR texture analysis (TA) has the potential to distinguish subtle differences amongst myocardial diseases, but with limited evidence in a healthy population. The aim of this study was to assess the application of TA to cardiac CINE MR Images of the left ventricle to evaluate variability and consistency in a large-scale healthy population.
Method
A cohort of 600 healthy volunteers was recruited from the Tayside Screening for Prevention of Cardiac Events study. All subjects underwent short axis CINE CMR at 3T (including LVM), using a 2D ECG-gated breath-hold segmented steady-state gradient echo sequence with constant field-of-view and pixel size. For each subject, the mid short-axis slices of the left ventricle, at ED and ES, were extracted for image analysis. The TA parameters (n = 50) for all images were derived using Mazda v4.7 by a single observer. Three different regions-of-interest (ROI) were applied to the LV myocardium at ED and ES, as follows: 1) ‘whole wall’ (figure 1 a and d); 2) ‘septal wall’ (figure 1 b and e); and 3) ‘lateral wall’ (figure 1 c and f). Statistical comparisons were made for all texture features to establish how they varied between ED and ES, males versus females, different age ranges (40-45 years, 46-54 years, 55-63 years, and ≥ 64 years) and also between those with small (66.8 ± 5.88 g/m2), media (98.2 ± 15.28 g/m2) and large (146.2 ± 16.81 g/m2) LVM. Finally, the images of 30 volunteers were analysed by a second observer to derive test-retest inter-observer variation as an index of measurement repeatability for each TA feature.
Results
Of the original 50 TA features tested, the means of n = 45-49 features (number dependent on whether whole wall, septal wall or lateral wall) were significantly different when compared between ED and ES (p < 0.05). For comparisons with gender, the means of n = 36-43 of the original features were significantly different (p < 0.05). Additionally, the means of n = 15-29 features were significantly different when tested between sub-cohorts of different ages (p < 0.05). When these data were combined together, ‘lateral wall’ was less sensitive, but for ‘whole wall’ and ‘septal wall’, the means of n = 7 of the original TA features were able to identify statistically significant differences between (i) ED and ES, (ii) males and females, (iii) different sub-cohorts of age, and (iv) different sub-cohorts of LVM (figure 2). Further, the root mean square test-retest inter-observer coefficient of variation associated with the repeatability of these measures was <10%. The n = 7 most useful TA features were ‘GrMean’, ‘GrNonZeros’, ‘Average_RLNonUni’, ‘Average_LngREmph’, ‘Average_ShrtREmph’, ‘Average_Fraction’ and ‘S5_Average_Entropy’.
Conclusion
These findings showed the repeatability of CMR texture anaysis and capability to identify differences in a healthy population. Further work may identify whether these features are able to differentiate between different cardiovascular diseases.
Texture analysis of CINE CMR image in healthy volunteers-preliminary results