Noninvasive imaging modalities to visualize atherosclerotic plaques

Uncovering the Cardiovascular Threat: A Comprehensive Examination of Liver Fibrosis and Subclinical Atherosclerosis in Non-alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) has emerged as a global epidemic intricately linked to the rising tide of obesity and metabolic syndrome. This comprehensive review delves into the complex web of relationships between NAFLD, liver fibrosis, and subclinical atherosclerosis, shedding light on their interplay, shared risk factors, and clinical implications. NAFLD encompasses a spectrum of liver conditions, from the benign non-alcoholic fatty liver (NAFL) to the more severe non-alcoholic steatohepatitis (NASH), characterized by inflammation and hepatocellular injury. Central to the discussion is the insidious development of liver fibrosis, the ominous harbinger of progressive liver damage, cirrhosis, and hepatocellular carcinoma. The increasing prevalence of NAFLD, now affecting a quarter of the global population, poses a significant public health challenge. Its association with obesity, insulin resistance, and metabolic syndrome highlights the multifactorial nature of this disease. However, NAFLD's repercussions extend beyond the liver. This review unveils a potent connection between NAFLD and subclinical atherosclerosis, the early precursor to cardiovascular disease. Individuals with NAFLD face an elevated risk of atherosclerosis, even without traditional cardiovascular risk factors. The intricate link between these two conditions is illuminated through shared pathophysiological pathways, including systemic inflammation, insulin resistance, and dyslipidemia. Understanding the interplay between liver fibrosis and subclinical atherosclerosis has profound clinical implications. Patients with advanced fibrosis or cirrhosis are not only at risk of liver-related complications but also of cardiovascular events. This necessitates a holistic approach to patient care, with lifestyle modifications and pharmacological interventions simultaneously managing both conditions. Physicians must prioritize early detection and collaborate across disciplines to provide comprehensive care. Looking ahead, the future holds promising avenues of research. Emerging areas include genetics and precision medicine, microbiome research, and epigenetics, which may unveil new therapeutic targets. Innovations in diagnostics and therapeutics, such as non-invasive biomarkers and combination therapies, offer hope for more effective management. Long-term outcomes and survivorship research will provide insights into the lasting impact of interventions. In conclusion, this review underscores the imperative of addressing liver fibrosis and atherosclerosis in the context of NAFLD. It is a call to action for healthcare professionals, researchers, and policymakers to work collaboratively, promote early detection, and advance our understanding of these interconnected conditions. By doing so, we can enhance patient outcomes and chart a course toward a healthier future for those grappling with NAFLD and its intricate web of consequences.

Comparing Focused-Tracked and Plane Wave-Tracked ARFI Log(VoA) In Silico and in Application to Human Carotid Atherosclerotic Plaque, Ex Vivo

A significant risk factor for ischemic stroke is carotid atherosclerotic plaque that is susceptible to rupture, with rupture potential conveyed by plaque morphology. Human carotid plaque composition and structure have been delineated noninvasively and in vivo by evaluating log(VoA), a parameter derived as the decadic log of the second time derivative of displacement induced by an acoustic radiation force impulse (ARFI). In prior work, ARFI-induced displacement was measured using conventional focused tracking; however, this requires a long data acquisition period, thereby reducing framerate. We herein evaluate if ARFI log(VoA) framerate can be increased without a reduction in plaque imaging performance using plane wave tracking instead. In silico, both focused- and plane wave-tracked log(VoA) decreased with increasing echobrightness, quantified as signal-to-noise ratio (SNR), but did not vary with material elasticity for SNRs below 40 dB. For SNRs of 40-60 dB, both focused- and plane wave-tracked log(VoA) varied with SNR and material elasticity. Above 60 dB SNR, both focused- and plane wave-tracked log(VoA) varied with material elasticity alone. This suggests that log(VoA) discriminates features according to a combination of their echobrightness and mechanical property. Further, while both focused- and plane-wave tracked log(VoA) values were artifactually inflated by mechanical reflections at inclusion boundaries, plane wave-tracked log(VoA) was more strongly impacted by off-axis scattering. Applied to three excised human cadaveric carotid plaques with spatially aligned histological validation, both log(VoA) methods detected regions of lipid, collagen, and calcium (CAL) deposits. These findings support that plane wave tracking performs comparably to focused tracking for log(VoA) imaging and that plane wave-tracked log(VoA) is a viable approach to discriminating clinically relevant atherosclerotic plaque features at a 30-fold higher framerate than by focused tracking.

Diagnostics of atherosclerosis: Overview of the existing methods

Atherosclerosis was and remains an extremely common and serious health problem. Since the elderly are most at risk of cardiovascular risk, and the average life expectancy is increasing, the spread of atherosclerosis and its consequences increases as well. One of the features of atherosclerosis is its asymptomaticity. This factor makes it difficult to make a timely diagnosis. This entails the lack of timely treatment and even prevention. To date, in the arsenal of physicians, there is only a limited set of methods to suspect and fully diagnose atherosclerosis. In this review, we have tried to briefly describe the most common and effective methods for diagnosing atherosclerosis.

Artificial intelligence in computed tomography plaque characterization: A review

Cardiovascular disease (CVD) is associated with high mortality around the world. Prevention and early diagnosis are key targets in reducing the socio-economic burden of CVD. Artificial intelligence (AI) has experienced a steady growth due to technological innovations that have to lead to constant development. Several AI algorithms have been applied to various aspects of CVD in order to improve the quality of image acquisition and reconstruction and, at the same time adding information derived from the images to create strong predictive models. In computed tomography angiography (CTA), AI can offer solutions for several parts of plaque analysis, including an automatic assessment of the degree of stenosis and characterization of plaque morphology. A growing body of evidence demonstrates a correlation between some type of plaques, so-called high-risk plaque or vulnerable plaque, and cardiovascular events, independent of the degree of stenosis. The radiologist must apprehend and participate actively in developing and implementing AI in current clinical practice. In this current overview on the existing AI literature, we describe the strengths, limitations, recent applications, and promising developments of employing AI to plaque characterization with CT.

Atherosclerosis: Making a U Turn

The development of potent cholesterol-reducing medications in the last decade of the twentieth century has altered the approach to prevention and treatment of cardiovascular disease (CVD). Initial experience with statins, and more recently with the addition of PCSK9 inhibitors, has proven that human CVD, like that in animal models, can be halted and regressed. Available clinical data show that the lower the achieved level of low-density lipoprotein cholesterol, the greater the regression of disease. Investigative studies are now aimed to understand those factors that both accelerate and impede this healing process. Some of these are likely to be modifiable, and the future of atherosclerotic CVD treatment is likely to be early screening, use of measures to repair atherosclerotic arteries, and prevention of most CVD events.

Coronary Atherosclerosis Imaging

Identifying patients at increased risk of coronary artery disease, before the atherosclerotic complications become clinically evident, is the aim of cardiovascular prevention. Imaging techniques provide direct assessment of coronary atherosclerotic burden and pathological characteristics of atherosclerotic lesions which may predict the progression of disease. Atherosclerosis imaging has been traditionally based on the evaluation of coronary luminal narrowing and stenosis. However, the degree of arterial obstruction is a poor predictor of subsequent acute events. More recent techniques focus on the high-resolution visualization of the arterial wall and the coronary plaques. Most acute coronary events are triggered by plaque rupture or erosion. Hence, atherosclerotic plaque imaging has generally focused on the detection of vulnerable plaque prone to rupture. However, atherosclerosis is a dynamic process and the plaque morphology and composition may change over time. Most vulnerable plaques undergo progressive transformation from high-risk to more stable and heavily calcified lesions, while others undergo subclinical rupture and healing. Although extensive plaque calcification is often associated with stable atherosclerosis, the extent of coronary artery calcification strongly correlates with the degree of atherosclerosis and with the rate of future cardiac events. Inflammation has a central role in atherogenesis, from plaque formation to rupture, hence in the development of acute coronary events. Morphologic plaque assessment, both invasive and non-invasive, gives limited information as to the current activity of the atherosclerotic disease. The addition of nuclear imaging, based on radioactive tracers targeted to the inflammatory components of the plaques, provides a highly sensitive assessment of coronary disease activity, thus distinguishing those patients who have stable disease from those with active plaque inflammation.

Prediction of cardiovascular outcomes by imaging coronary atherosclerosis

Over the last two decades, several invasive and non-invasive coronary atherosclerosis imaging modalities have emerged as predictors of cardiovascular outcomes in at-risk population. These modalities have demonstrated independent or incremental prognostic information over existing/standard risk stratification schemes, such as the Framingham risk score (FRS), by identifying characteristics of coronary artery diseases (CADs). In this review, we begin with discussing the importance of pre-test probability and quality of outcome measure, followed by specific findings of each modality in relation to prognosis. We focused on both short and long term prognostic aspects of coronary computed tomography (CT) (including coronary calcium score and coronary angiography) and magnetic resonance imaging as non-invasive tools, as well as invasive modalities including intravascular ultrasound (IVUS), optical coherence tomography (OCT), near infrared spectroscopy and Angioscopy.