Key result
Combined 3D MRVWI morphology and T2-weighted signal intensity identify carotid early atherosclerosis with ~0.86 AUC.
Why the study?
Does 3D multicontrast magnetic resonance vessel wall imaging (MRVWI) accurately identify carotid early atherosclerosis compared to ultrasound in asymptomatic older subjects?
Cross-Sectional (n=61)
Does 3D multicontrast magnetic resonance vessel wall imaging (MRVWI) accurately identify carotid early atherosclerosis compared to ultrasound in asymptomatic older subjects?
Effect estimate: AUC 0.856-0.867
p-value: p=<0.001
Combining morphological parameters and T2-weighted signal intensity from 3D MR vessel wall imaging improves the identification of early carotid atherosclerosis compared to using either characteristic alone.
May aid noninvasive detection of early carotid atherosclerosis; hypothesis-generating and should not yet change practice.
Purpose To evaluate the usefulness of quantitative characteristics of morphology and signal intensity of arterial wall measured by 3D multicontrast magnetic resonance vessel wall imaging (MRVWI) in identification of carotid early atherosclerosis (CEAS). Materials and Methods In all, 61 older subjects (mean age 71.8 ± 5.6 years old; 25 males) without cardiovascular symptoms in the last 6 months were recruited. The carotid arteries without advanced plaque features on 3.0T MRI were included for analysis. Ultrasound imaging was used as a reference to identify CEAS. The morphological parameters including lumen area (LA), wall area (WA), wall thickness (WT), and normalized wall index (NWI = WA/[WA+LA] × 100%) and the signal intensity on 3.0T MR T2‐weighted images (T2SI) of the carotid arterial wall were measured. Three regression models were built to identify CEAS with the following parameters: Model 1 with both morphological and T2SI parameters; Model 2 with T2SI parameters; and Model 3 with morphological parameters. All models were adjusted for age and sex. Area under the curve (AUC) was calculated to validate models. Results Of the 86 carotid arteries without advanced plaques, 47 (54.7%) were found to have early plaques determined by ultrasound. Among three regression models, Model 1 showed the highest AUC values in identifying CEAS (left: AUC = 0.856, P < 0.001; right: AUC = 0.867, P < 0.001), followed by Model 2 (left: AUC = 0.843, P < 0.001; right: AUC = 0.798, P = 0.001), and Model 3 (left: AUC = 0.790, P = 0.002; right: AUC = 0.806, P < 0.001). Conclusion The combination of morphology and normalized T2SI of arterial wall measured by MRVWI is more effective than each characteristic alone in identification of CEAS. J. Magn. Reson. Imaging 2016;44:1270–1276.
No takes yet. Share an insight, caveat, or question.
Qiao et al. (2016) conducted a cross-sectional in Carotid early atherosclerosis (n=61). 3D multicontrast magnetic resonance vessel wall imaging (MRVWI) combining morphology and T2-weighted signal intensity vs. Morphology alone or T2-weighted signal intensity alone was evaluated on Identification of carotid early atherosclerosis (CEAS) (AUC 0.856-0.867, p=<0.001). The combination of morphology and normalized T2-weighted signal intensity measured by 3D MRVWI identified carotid early atherosclerosis with high accuracy (AUC 0.856-0.867, P<0.001).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: