Asynchronous movement of the carotid atheromatous plaque from B-mode ultrasound has been previously reported, and associated with higher risk of stroke, but not quantitatively estimated. Based on the hypothesis that asynchronous plaque motion is associated with vulnerable plaque, in this study, synchronisation patterns of different tissue areas were estimated using cross-correlations of displacement waveforms. In 135 plaques (77 subjects), plaque radial deformation was synchronised by approximately 50% with the arterial diameter, and the mean phase shift was 0.4 s. Within the plaque, the mean phase shifts between the displacements of the top and bottom surfaces were 0.2 s and 0.3 s, in the radial and longitudinal directions, respectively, and the synchronisation about 80% in both directions. Classification of phase-shift-based features using Random Forests yielded Area-Under-the-Curve scores of 0.81, 0.79, 0.89 and 0.90 for echogenicity, symptomaticity, stenosis degree and plaque risk, respectively. Statistical analysis showed that echolucent, high-stenosis and high-risk plaques exhibited higher phase shifts between the radial displacements of their top and bottom surfaces. These findings are useful in the study of plaque kinematics.

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine.

Motion extracted from the carotid artery wall provides unique information for vascular health evaluation. Carotid artery longitudinal wall motion corresponds to the multiphasic arterial wall excursion in the direction parallel to blood flow during the cardiac cycle. While this motion phenomenon has been well characterized, there is a general lack of awareness regarding its implications for vascular health assessment or even basic vascular physiology. In the last decade, novel estimation strategies and clinical investigations have greatly advanced our understanding of the bi-axial behavior of the carotid artery, necessitating an up-to-date review to summarize and classify the published literature in collaboration with technical and clinical experts in the field. Within this review, the state-of-the art methodologies for carotid wall motion estimation are described, and the observed relationships between longitudinal-motion-derived indices and vascular health are reported. The vast number of studies describing the longitudinal motion pattern in plaque-free arteries, with its putative application to cardiovascular disease prediction, point to the need for characterizing the added value and applicability of longitudinal motion beyond established biomarkers. To this aim, the main purpose of this review is to provide a strong base of theoretical knowledge, together with a curated set of practical guidelines and recommendations for longitudinal motion estimation in patients, to foster future discoveries in the field, toward the integration of longitudinal motion in basic science as well as clinical practice.