| Literature DB >> 30196677 |
Abstract
Cerebral aneurysm is a common cerebrovascular disease that is sometimes complicated by rupture or an enlarged mass. We are now aggressively evaluating and managing unruptured cerebral aneurysms based on a significant concern for the high morbidity and mortality related to its associated complications. However, the actual rupture rate is very low and the diagnostic and treatment modalities are expensive and invasive, which may lead to unnecessary costs and potential medical complications. This disproportionate situation is related to a poor understanding of the natural course and pathophysiology of cerebral aneurysms. In consideration of the concept that not all cerebral aneurysms must be removed, we need to examine their course and progression more accurately. Cerebral aneurysms may follow a variety of pathophysiological scenarios over their lifetime, from formation to growth and rupture. The disease course and the final outcome can differ depending on the timing and intensity of the pathological signals acting on the cerebral vessel wall. We should delineate a method of predicting the stability and risk of rupture of the lesion based on a comprehensive knowledge of the vessel wall integrity. This review deals with the basic knowledge and advanced concepts underlying the pathophysiology of cerebral aneurysms.Entities:
Keywords: Cerebral aneurysm; Outcome; Pathophysiology; Risk factors
Year: 2018 PMID: 30196677 PMCID: PMC6132027 DOI: 10.5469/neuroint.2018.01011
Source DB: PubMed Journal: Neurointervention ISSN: 2093-9043
Fig. 1.Structural alteration of a cerebral aneurysm. Intracranial arteries are normally composed of firm layers, including endothelial cell, internal elastic lamina, smooth muscle cells, extracellular matrices, and adventitia. Meanwhile, aneurysmal changes result from perturbations of one or more of these components.
Pathophysiological factors involved in aneurysm formation
| Molecular and histological changes | |
|---|---|
| Endothelial cells | Endothelial cell apoptosis |
| Pro-inflammatory endothelial cells | |
| Breakdown of endothelial barrier | |
| E-selectin, P-selectin, VCAM-1, ICAM-1 | |
| Smooth muscle cells | Phenotypic switching from contractile to inflammatory type |
| Pro-inflammatory vascular smooth muscle cells | |
| Smooth muscle cell apoptosis and degeneration | |
| Inflammation | Infiltration of macrophages, neutrophils, T cells and mast cells |
| NF-kB, TNFα, MCP-1, IL-1p, IL-8, IL-17 | |
| COX2, PGE2, angiotensin II, NO,TLR-4 | |
| MMP 1, 2, 9 and Cathepsins | |
| IgM, IgG | |
| Complement (C3a, C5a) | |
| Extracellular matrix | Alteration of collagen to elastic ratio |
| Breakdown of collage and elastin cross-link | |
| Matrix degradation | |
| Internal elastic lamina | Fragmentation, and wavy appearance |
| Break down and degradation |
VCAM-1, vascular cellular adhesion molecule-1; ICAM-1, intercellular adhesion molecule-1; TNFα, tumor necrosis factor-α; MCP-1, monocyte chemoattractant protein 1; IL, interleukin; COX, cyclooxygenase; PGE2, prostaglandin E2; NO, nitric oxide; TLR, toll-like receptor; MMP, matrix metalloproteinases.
Fig. 2.Cerebral aneurysms with eccentric features associated with intrinsic vessel wall deformities A 55-year old woman was admitted because of an aneurysmal subarachnoid hemorrhage (SAH) in the right sylvian fissure (A). A large aneurysm in the right middle cerebral artery (MCA) was considered as a culprit lesion of SAH (B). However, multiple, large aneurysms were also noted in the anterior communicating and anterior cerebral arteries (C), and basilar artery (D). The second patient was a 53-year old woman complaining of anterior chest discomfort. Computed tomography angiography showed a large aneurysm involving the descending thoracic aorta (E, F). An intracranial aneurysm was also detected in the right MCA bifurcation from the screening magnetic resonance angiography (G).
Hereditary disorders with susceptibility to an intracranial aneurysm
| Disorder | Gene | Function |
|---|---|---|
| Polycystic kidney disease | PKD-1, PKD-2, PKD-3 | mTOR signalling, endothelial barrier |
| Marfan syndrome | FBN1 | TGF-β signalling, ECM integrity |
| Osteogenesis imperfecta | COL1A1, COL1A2, IFITM5, SERPINF1, CRTAP, LEPRE1, P3H1, PPIB | Collagen metabolism, ECM integrity |
| Ehlers-Danlos syndromes | COL1A1, COL1A2, COL3A1, COL5A1, COL5A2, and TNXB, ADAMTS2, PLOD1, B4GALT7, DSE, D4ST1/CHST14 | Collagen metabolism, ECM integrity |
| Loeys-Dietz syndrome | TGFBR1, TGFBR2, SMAD3, TGFB2, TGFB3 | TGF-β signalling |
| Hereditary hemorrhagic telangiectasia | ENG, ACVRL1, MADH4 | TGF-β signalling |
| Neurofibromatosis | NF1 | Ras-MEK-ERK signalling |
| Tuberous sclerosis | TSC2 | mTOR signalling |
| Bicuspid valve | NOTCH1 | Neural crest development |
| Alagille syndrome | JAG1, NOTCH2 | Neural crest development |
| Familial thoracic aortic aneurysm | ACTA2, MYH11 | Smooth muscle development |
| Turner syndrome | Chromosomal anomaly, 45, X | Unknown |
PKD, polycystic kidney disease; mTOR, mammalian target of rapamycin; FBN1, fibrillin-1; TGF-β, transforming growth factor-β; ECM, extracellular matrix; IFITM5, interferon induced transmembrane protein 5; SERPINF1, serpin family f member 1; TSC2, tuberous sclerosis complex 2.
Fig. 3.Risk factor domains to predict outcomes of cerebral aneurysm. A multi-factorial model can be applied to predict outcomes of a cerebral aneurysm. This model is based on patient- and aneurysm-specific factors with potential systemic markers.