Current clinical guidelines for aortic diseases primarily establish intervention criteria based on morphological indicators[
1–
3]. For abdominal aortic aneurysms (AAA), the maximum aneurysm diameter and its growth rate serve as critical determinants for surgical indications. In the management of aortic dissection, the entry tear location revealed by CT angiography (CTA) dictates anatomical classification, while the degree of organ ischemia guides emergency surgical decisions. Similarly, the threshold for intervention in aortic stenosis entirely depends on the degree of luminal narrowing observed in imaging. These intuitive morphological criteria have greatly facilitated clinical decision-making for vascular surgeons and significantly improved patient outcomes. However, within the existing diagnostic and therapeutic framework, we must still ask ourselves: Is there room for further improvement? In other words, has the decision-making model based solely on anatomical characteristics reached its pinnacle? This reflection stems from numerous unresolved challenges in clinical practice. Taking AAA as an example, despite numerous clinical trials over the past two decades attempting to identify drugs that can inhibit aneurysm progression, no medication with definitive efficacy has been discovered to date. This phenomenon prompts us to delve deeper: Beyond statistical factors, could it be due to an overly narrow selection of endpoints in research? Existing studies almost exclusively use changes in aneurysm diameter as the primary endpoint, neglecting the assessment of aortic biological function[
4]. This limitation may obscure the potential protective effects of certain drugs on the biological properties of the aortic wall.
The 2024 EACTS/STS guidelines innovatively proposed that the aorta should be regarded as a complete "organ" rather than merely a vascular structure[
3]. As the largest elastic artery in the human body, the aorta not only serves a mechanical function in blood transport but also fulfills critical biological roles. From the perspective of organ preservation, the goal of treating aortic dilatation pathologies is to prevent rupture, which fundamentally relies on maintaining the biological homeostasis of the aortic wall against hemodynamic shear forces. This equilibrium is influenced by multiple factors: traditional cardiovascular risk factors, paracrine regulation from periaortic tissues (e.g., intramural thrombosis and perivascular adipose tissue), hemodynamic alterations, and potential environmental factors (e.g., high-altitude hypoxia). However, the weight of these factors in current clinical decision-making remains unclear. Coincidentally, Shalhub’s 2025 proposal of the "Aortic and Arterial Vulnerability Spectrum" (AAVS) for the first time incorporated biological risk into the assessment framework[
5]. This system comprises three dimensions: substrate vulnerability, clinical fragility, and mechanisms of failure. Notably, this approach innovatively employs skin biopsy as a surrogate for detecting aortic connective tissue abnormalities, though its quantitative model requires further refinement and validation.
Although certain biomarkers (e.g., MMP-9) can indicate aortic wall damage, no clinical consensus has been established. A comprehensive evaluation system for aortic biological function impairment is urgently needed. Modern multi-omics technologies (transcriptomics, proteomics, metabolomics, etc.), organ-on-a-chip systems, and artificial intelligence provide novel tools for this purpose. Particularly noteworthy is the integration of multimodal data from dedicated disease cohorts and machine learning, which may become a pivotal pathway to transcend the current diagnostic and therapeutic paradigm. The philosophy of aortic disease management must evolve from mere "morphological repair" to "functional reconstruction." In the era of AI and precision medicine, incorporating biological function assessment will offer new opportunities for truly individualized treatment. Although this transformation is fraught with challenges, it is an indispensable path to advancing the diagnosis and treatment of aortic diseases.
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