Physics in Medicine and Biology · 2017 · 34 citations · 46 references
MedicineBioengineeringNeurologyBiomedical ImagingDiagnostic ImagingUltrasonographyCardiovascular ImagingCerebrovascular DiseaseCerebrovascular ImagingCognitive AssessmentCognitive ImpairmentStrokeCarotid Artery AtherosclerosisCarotid Artery UltrasonographyCarotid Artery UltrasoundNoninvasive Imaging DiagnosisNoninvasive Vascular ImagingPlaque Morphology AssessmentVulnerable Plaque Assessment
Vulnerability and instability in carotid artery plaque has been assessed based on strain variations using noninvasive ultrasound imaging. We previously demonstrated that carotid plaques with higher strain indices in a region of interest (ROI) correlated to patients with lower cognition, probably due to cerebrovascular emboli arising from these unstable plaques. This work attempts to characterize the strain distribution throughout the entire plaque region instead of being restricted to a single localized ROI. Multiple ROIs are selected within the entire plaque region, based on thresholds determined by the maximum and average strains in the entire plaque, enabling generation of additional relevant strain indices. Ultrasound strain imaging of carotid plaques, was performed on 60 human patients using an 18L6 transducer coupled to a Siemens Acuson S2000 system to acquire radiofrequency data over several cardiac cycles. Patients also underwent a battery of neuropsychological tests under a protocol based on National Institute of Neurological Disorders and Stroke and Canadian Stroke Network guidelines. Correlation of strain indices with composite cognitive index of executive function revealed a negative association relating high strain to poor cognition. Patients grouped into high and low cognition groups were then classified using these additional strain indices. One of our newer indices, namely the average L - 1 norm with plaque (AL1NWP) presented with significantly improved correlation with executive function when compared to our previously reported maximum accumulated strain indices. An optimal combination of three of the new indices generated classifiers of patient cognition with an area under the curve (AUC) of 0.880, 0.921 and 0.905 for all (n = 60), symptomatic (n = 33) and asymptomatic patients (n = 27) whereas classifiers using maximum accumulated strain indices alone provided AUC values of 0.817, 0.815 and 0.813 respectively.
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