Ultrasound B-mode descriptors and their association to age and automated IMT and IMT variability

The aim of this paper is to evaluate the association between four simple B-mode image descriptors and age, to further assess the association between the descriptors and automated intima-media thickness (IMT) and intima-media thickness variability (IMTV) measurements, and finally analyze the predictive value of the B-mode image descriptors. A database of 1774 images of the carotid artery is used to manually calculate the contrast and the signal-to-noise ratio (SNR) between the (i) intima-media complex and lumen, and (ii) adventitial wall layer and intima-media complex. A subset of 200 images is then used to automatically measure the IMT and IMTV parameters with a previously developed algorithm. Correlation studies and logistic regression analysis are then performed. The contrast and SNR between the intima-media complex and lumen (contrastIM and SNRIM) are 112.691±±247.427 and 19.542±±6.236, respectively; whereas between the adventitial wall layer and intima-media complex the parameters (contrastADV and SNRADV) are found to be 1.684±±1.182 and 32.859±±10.766, respectively. Pearson’s rho is significantly different from zero considering the contrastIM and the SNRADV descriptors when tested for the association with age. The automated IMT and IMTV measurements are 0.796±±0.152mm and 0.096±±0.044mm, respectively. Testing the association with the IMT and IMTV measurements yielded Pearson’s rho values which are significantly different from zero except in the case of contrastIM for the IMTV measurement. The logistic regression results showed the IMTV measurement and the SNR descriptor between the intima-media complex and the lumen has a significant predictive value. Considering the association between the IMT and IMTV, the B-mode image descriptors showed a strong and statistically significant association. Moreover, the SNR between the intima-media complex and lumen is found to be a predictive variable in demonstrating its effectiveness as an image descriptor