International Union of Angiology (IUA) consensus paper on imaging strategies in atherosclerotic carotid artery imaging: From basic strategies to advanced approaches

Cardiovascular disease (CVD) is the leading cause of mortality and disability in developed countries. According to WHO, an estimated 17.9 million people died from CVDs in 2019, representing 32% of all global deaths. Of these deaths, 85% were due to major adverse cardiac and cerebral events. Early detection and care for individuals at high risk could save lives, alleviate suffering, and diminish economic burden associated with these diseases. Carotid artery disease is not only a well-established risk factor for ischemic stroke, contributing to 10%–20% of strokes or transient ischemic attacks (TIAs), but it is also a surrogate marker of generalized atherosclerosis and a predictor of cardiovascular events. In addition to diligent history, physical examination, and laboratory detection of metabolic abnormalities leading to vascular changes, imaging of carotid arteries adds very important information in assessing stroke and overall cardiovascular risk. Spanning from carotid intima-media thickness (IMT) measurements in arteriopathy to plaque burden, morphology and biology in more advanced disease, imaging of carotid arteries could help not only in stroke prevention but also in ameliorating cardiovascular events in other territories (e.g. in the coronary arteries). While ultrasound is the most widely available and affordable imaging methods, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), their combination and other more sophisticated methods have introduced novel concepts in detection of carotid plaque characteristics and risk assessment of stroke and other cardiovascular events. However, in addition to robust progress in usage of these methods, all of them have limitations which should be taken into account. The main purpose of this consensus document is to discuss pros but also cons in clinical, epidemiological and research use of all these techniques

Tissue properties and respiratory kinematics of the tongue base and soft palate in the obese OSA minipig.

Obesity is a common finding and a major pathogenetic factor in obstructive sleep apnea (OSA) in adults. To understand the mechanisms behind this, the present study investigated the tissue properties and respiratory kinematics of the tongue base and soft palate in the obese OSA minipig model. In 4 verified obese/OSA and 3 non-obese/non-OSA control minipigs, MRI fat-weighted images, ultrasound elastography (USE), and sleep video-fluoroscopy (SVF) were performed to quantify the fat composition, tissue stiffness, and respiratory kinematics of the tongue base and soft palate during sedated sleep. The results indicated that the fat composition gradually increased from the rostral to caudal tongue base, particularly in the posterior 1/3 of the tongue base, regardless of the presence of obesity and OSA. However, this trend was not seen in the soft palate and pharyngeal wall. The pharyngeal wall presented the highest fat composition as compared with the tongue base and soft palate. Overall, obese OSA minipigs showed stiffer tongue tissue than the controls, particularly in the rostral region of the tongue in obese Yucatan minipigs. The respiratory moving ranges of the soft palate were greater in both dorsal-ventral and rostral-caudal directions and during both respiratory and expiratory phases in OSA obese than control minipigs, and the largest moving ranges were seen in OSA obese Panepinto minipigs. The moving range of the tongue base was significantly smaller. These results suggest more fat infiltration in the caudal region of the tongue base regardless of the presence of obesity and/or OSA. The greater tissue stiffness of the tongue in obese OSA minipigs may result from altered neuromuscular drive

A novel sequence for simultaneous measurement of whole-brain static and dynamic MRA, intracranial vessel wall image, and T₁-weighted structural brain MRI

PURPOSE: To propose a highly time-efficient imaging technique named iSNAP for simultaneous assessment of lumen, vessel wall and blood flow in intracranial arteries. METHODS: iSNAP consists of pulsed arterial spin labeling (ASL) preparations and 3D golden angle radial acquisition. Images were reconstructed by k-space weighted image contrast (KWIC) method with optimized data-sharing strategies. Dynamic MRA (dMRA) for blood flow assessment was obtained from iSNAP by reconstruction at multiple inversion times and image subtraction, static MRA (sMRA) by both image subtraction approach and phase-sensitive inversion recovery (PSIR) technique, and vessel wall images (VWIs) by both reconstruction at zero-crossing time-point of blood and PSIR. A T1-weighted (T1W) brain MRI was also reconstructed from iSNAP. Preliminary comparison of iSNAP against the dedicated dMRA sequence 4D-TRANCE, MRA/vessel wall imaging sequence SNAP and vessel wall imaging sequence T1W VISTA was performed in healthy volunteers and patients. RESULTS: iSNAP has whole-brain coverage and takes ~6.5 min. The dedicated reconstruction strategies are feasible for each iSNAP image contrast and beneficial for image SNR. iSNAP-dMRA yields similar dynamic flow information as 4D-TRANCE and allows more flexible temporal resolution. The two types of iSNAP sMRA images complement each other in characterizing both proximal large arteries and distal small arteries. Depiction of vessel wall lesions in iSNAP VWIs is better than SNAP and may be similar to T1W VISTA, although the images are slightly blurred. CONCLUSION: iSNAP provides a time-efficient evaluation of intracranial arteries, and may have great potential for comprehensive assessment of intracranial vascular conditions using a single sequence

A vascular image registration method based on network structure and circuit simulation

Abstract Background Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. Results Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. Conclusions The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods