The exact prevalence of unruptured intracranial aneurysms (UIAs) is unknown, but at least one in 20 to 30 adults is likely to carry an asymptomatic UIA. Approximately one quarter of these UIAs rupture in a lifetime. Complex methodological challenges in conducting studies of epidemiology and risk factors for UIAs and SAH might have led to conclusions being drawn on the basis of epidemiological data of variable quality. Korja et al. believe that, as a result, misconceptions about UIAs and SAH may have arisen. They discuss three possible misconceptions about the epidemiology of UIAs and SAH, and suggest how the quality of future research could be improved 1).
Aneurysm location and other morphologic variables could play a role in predicting overall risk of rupture. Morphological parameters can be divided into 3 main groups, those that are intrinsic to the aneurysm, those that are extrinsic to the aneurysm, and those that involve both the aneurysm and surrounding vasculature (transitional).
By studying the morphology of aneurysms and their surrounding vasculature, Ho et al. identified several parameters associated with ruptured aneurysms that include intrinsic, transitional, and extrinsic factors of cerebral aneurysms and their surrounding vasculature 2).
see PHASES score
Despite the fact that ruptured intracranial aneurysm (RIAs) can be prevented by microsurgical clipping or endovascular coiling, there are no reliable means of effectively predicting IA patients at risk for rupture.
In patients of working age alcohol consumption and cigarette smoking are modifiable risk factors for untimely death through several causes and should be taken into account when treatment is considered 3).
Unruptured saccular aneurysms less than 10 mm in diameter have a very low probability of subsequent rupture. The mean diameter of the aneurysms that subsequently ruptured was 21.3 mm, compared with a diameter of 7.5 mm for aneurysms defined after rupture at the same institution. Part of the explanation for this discrepancy may be that the size of the filling compartment of the aneurysm decreases after rupture. There is also evidence from a study that intracranial saccular aneurysms develop with increasing age of the patient and stabilize over a relatively short period, if they do not initially rupture, and that the likelihood of subsequent rupture decreases considerably if the initial stabilized size is less than 10 mm in diameter. Consequently, the critical size for aneurysm rupture is likely to be smaller if rupture occurs at the time of or soon after aneurysm formation. There seems to be a substantial difference in potential for growth and rupture between previously ruptured and unruptured aneurysms 4).
The annual rupture rate associated with small unruptured aneurysms is quite low. Careful attention should be paid to the treatment indications for single-type unruptured aneurysms <5 mm. If the patient is <50 years of age, has hypertension, and multiple aneurysms with diameters of >or=4 mm, treatment should be considered to prevent future aneurysmal rupture 5).
Cigarette smoking, patient age inversely, and the size and location of the unruptured intracranial aneurysm seem to be risk factors for aneurysm rupture. The risk of bleeding decreases with a very long-term follow-up 6).
The association of morphological characteristics with ruptured aneurysms has not been established in a systematic and location specific manner for the most common aneurysm locations.
Geometric or hemodynamic considerations favor identification of rupture status; however, retrospective identification of the rupture site remains a challenge for both engineers and clinicians. A more precise understanding of the hemodynamic factors involved in aneurysm wall pathology is likely required for computational fluid dynamics to add value to current clinical decision-making regarding rupture risk 7).
The fragility of the aneurysmal wall is an important predictive factor of rupture. Presently, however, it is difficult to determine when an operation for an unruptured tiny aneurysm is indicated; new neuroimaging techniques that detect the fragility of the aneurysmal wall are needed 8).
Fifty unruptured middle cerebral artery aneurysms were analyzed. Spatial and temporal maximum pressure (Pmax) areas were determined with a fluid-flow formula under pulsatile blood flow conditions. Intraoperatively, thin walled regions (TWRs) of aneurysm domes were identified as reddish areas relative to the healthy normal middle cerebral arteries; 5 neurosurgeons evaluated and divided these regions according to Pmax area and TWR correspondence. Pressure difference (PD) was defined as the degree of pressure elevation on the aneurysmal wall at Pmax and was calculated by subtracting the average pressure from the Pmax and dividing by the dynamic pressure at the aneurysm inlet side for normalization.
In 41 of the 50 cases (82.0%), the Pmax areas and TWRs corresponded. PD values were significantly higher in the correspondence group than in the noncorrespondence group (P = .008). A receiver-operating characteristic curve demonstrated that PD accurately predicted TWRs at Pmax areas (area under the curve, 0.764; 95% confidence interval, 0.574-0.955; cutoff value, 0.607; sensitivity, 66.7%; specificity, 82.9%).
A high PD may be a key parameter for predicting TWRs in unruptured cerebral aneurysms 9).
Suzuki et al., present in this issue the findings of their research on intracranial aneurysms and report the work on pressure elevations at the thin walled regions of an aneurysm dome using computational fluid dynamics (CFD) modeling in 51 unruptured middle cerebral artery aneurysms. The authors attempt to show that areas of maximum pressure may be important markers of thin-wall regions in unruptured cerebral aneurysms and theorize that by calculating the pressure difference value for each aneurysm type using computational fluid dynamics, it is possible to estimate the accuracies of predictions regarding thin-wall regions.It would seem that this is a good study and a worthwhile contribution to the literature. At the same time, it appears that not much has changed since Kallmes 10) wrote his poignant and perhaps provoking but timely editorial 4 years ago, and there continue to be publications that fail basic tests or internal consistency and validity.CFD modeling for intracranial aneurysms has emerged from an arcane interest of a few to a field producing a significant number of articles. A simple search in PubMed yields <2 results for the years 1990 to 1999 and >19 for the years 2015 to 2016 alone. This of course reflects the greater affordability and easier access to high-performance computing platforms, overall advances in computing power, and easier-to-use software packages complete with graphical user interfaces. A number of articles by very experienced researchers have questioned in the past the validity and value of CFD modeling 11) 12) 13) 14) 15) 16).
CFD analysis in particular is a field that is prone to data dredging and exploratory analysis. It should be considered paramount to raise the quality of the research done by requiring authors to clearly state the hypothesis tested in their work. It remains a basic, albeit often overlooked and perhaps at times consciously evaded, requirement for publication of research findings that the methods described allow a knowledgeable expert in the field to reproduce the findings. In line with the publishing of research in such a manner that it, in theory, could be reproducible and verifiable and with the almost limitless space offered by online supplementary data appendixes, we should call for, perhaps in an online appendix, a framework for defining physical quantities and boundary conditions and a demonstration that the modeling setup is able to reproduce parameters of basic known CFD experiments such as flow development in a curved tube or a stenotic tube. Demonstration of grid and mesh density independently of results should require authors to provide clearly stated definitions for these parameters and the details of their approximations in computational and experimental studies. This is especially important for research groups publishing their first results in this field, although perhaps less so for groups that can reference a body of previous works in which such testing of their setup was done in the past.CFD is exquisitely sensitive to assumptions made and boundary conditions entering the simulation, and results must be presented and analyzed with these assumptions in mind. Internal controls are difficult to come by, but it has been a best practice to explicitly describe the flow and wall parameter conditions in a assumed normal vessel segment. In other words, unless the simulation predicts a rather normal flow environment and wall shear conditions in the parent vessel of a side wall aneurysm proximal and distal to the aneurysmal segment, why abnormal values in the aneurysmal segment predicted by the simulation should be taken at face value deserves some explanation.
It is worth repeating the questions raised by Robertson and Watton 17) when conducting CFD research on intracranial aneurysms, asking to make judicious assumptions about boundary conditions, and an effort should be made to conduct an error or sensitivity analysis for assumptions that may influence the hemodynamics in the parent vessel tree and the aneurysm sac, especially when we have limited information about such assumptions. Idealizations are important and necessary tools for developing models and assumptions, but conclusions based on one specific anatomy may not hold up for other geometries. Using patient-based geometries but assuming the same inflow boundary condition for all cases would lead to unrealistic results, even when the model would be a simple straight vessel, disregarding the complication of an aneurysm attached to such a vessel. We know that shear conditions in a normal vessel are somewhat tightly regulated to ensure a healthy hemodynamic milieu for the endothelial cells.
The present publication not only adds another metric to the extensive table compiled by Xiang et al 18) but is more significant for the seemingly arbitrary construction of a dimensionless parameter called the pressure difference, which has the physical properties of a friction coefficient.
Perhaps on a more optimistic note, this continues to be a field with great potential, and more often than not, we see studies with innovative design and interesting approaches 19).
The value in simulation lies in linking physiological measurements to processes that cannot readily be measured but need to be quantified to explain the underlying mechanisms and processes and, in enhancing our understanding of these processes, to ultimately help our patients 20).
Morphological parameters associated with aneurysm rupture in that location were evaluated to generate 3-D models of the aneurysms and surrounding vasculature. Univariate and multivariate analyses were performed to evaluate morphological parameters including aneurysm volume, aspect ratio, size ratio, distance to ICA bifurcation, aneurysm angle, vessel angles, flow angles, and vessel-to-vessel angles. From 2005-2012, 148 PCoA aneurysms were treated in a single institution. Preoperative CTAs from 63 patients (40 ruptured, 23 unruptured) were available and analyzed. Multivariate logistic regression revealed that smaller volume (p = 0.011), larger aneurysm neck diameter (0.048), and shorter ICA bifurcation to aneurysm distance (p = 0.005) were the most strongly associated with aneurysm rupture after adjusting for all other clinical and morphological variables. Multivariate subgroup analysis for patients with visualized PCoA demonstrated that larger neck diameter (p = 0.018) and shorter ICA bifurcation to aneurysm distance (p = 0.011) were significantly associated with rupture. Intracerebral hemorrhage was associated with smaller volume, larger maximum height, and smaller aneurysm angle, in addition to lateral projection, male sex, and lack of hypertension. Ho et al., found that shorter ICA bifurcation to aneurysm distance is significantly associated with PCoA aneurysm rupture. This is a new physically intuitive parameter that can be measured easily and therefore be readily applied in clinical practice to aid in the evaluation of patients with PCoA aneurysms 21).
Murayama et al., 22) conservatively followed up a cohort of 1960 aneurysms for up to 10 years and performed a risk analysis of rupture. From January 2003 to December 2012, the authors enrolled 1556 patients with 1960 aneurysms of 2665 patients with 3434 aneurysms screened. Patients were eligible for the study if they had an aneurysm at least 2 mm in its largest dimension. Exclusion criteria included fusiform, traumatic, or mycotic aneurysms; treatment before enrollment in the study; carotid cavernous aneurysms; and infundibular dilations. The authors recommended observation for aneurysms <5 mm and treatment for aneurysms >10 mm. For aneurysms between 5 and 10 mm, risks of treatment vs observation were discussed with the patients. Patients were followed up until time of subarachnoid hemorrhage (SAH), death resulting from any cause, or last possible follow-up contact. Patients were divided into 2 groups. Group 1 was composed of patients with no history of SAH, and group 2 was composed of patients with a history of SAH. Patients who presented with signs and symptoms of mass effect were treated urgently. Mean follow-up was 7388 aneurysm-years. The most common was middle cerebral artery (MCA) aneurysms (535 aneurysms, 27.3%), followed by internal carotid artery (ICA) aneurysms not connected to the origin of the posterior communicating artery (PCom; 525 aneurysms, 26.8%). Aneurysms at the origin of the PCom were the third most common (401 aneurysms, 20.5%), followed by vertebral artery–basilar artery aneurysms (169 aneurysms, 8.6%). Fifty-six aneurysms ruptured during the follow-up period, with an overall annual incidence SAH of 0.76%. Mean duration to rupture from initial presentation was 547 days. Regarding the rupture risk factors, aneurysm size, specific location, history of SAH, and the presence of a daughter sac were found to be independent risk factors in both single and multivariate Cox proportional-hazard models. On the other hand, and surprisingly, smoking, family history of SAH, age, female sex, hypertension, and diabetes mellitus were not associated with risk of rupture. Average rupture size was 7.5 ± 5.74 mm. Of note, 39 ruptures (69.6%) occurred in aneurysms <7 mm in size. The probability of rupture increased with size. The authors then performed multiple analyses with the cutoff size set at 5, 6, 7, 8, 9, and 10 mm. They noted a statistical significance in all selected cutoff sizes with and without adjustment for other risk factors. In terms of locations, vertebrobasilar aneurysms were associated with the highest rupture risk, followed by PCom, MCA, anterior cerebral artery (ACA), and then finally ICA aneurysms. Vertebrobasilar and PCom aneurysms had a significantly higher hazard ratio of rupture, whereas MCA and ACA aneurysms had only a moderate increase in risk. Fifteen of the 56 aneurysm ruptures (26.8%) resulted in death, and 16 of the 56 (28.65) ended in moderate to severe disability (modified Rankin Scale score of 3-5). Fewer than half of the patients with ruptures returned to normal life. None of the patients who had large or giant aneurysms recovered without deficits. The mortality rate of these patients was 69% (9 of 13), whereas the mortality rate of aneurysms <5 mm was 18% (4 of 22).
This study confirms many concepts about intracranial aneurysms. More than half of the ruptured aneurysms ended in at least moderate disability, further revealing the devastating effect of aneurysmal SAH. Size and location have again been shown to be independent risk factors for rupture. Unlike ISUIA, however, this study showed what was suspected all along: that even small aneurysms rupture. Although the authors are to be commended for their efforts, this study has obvious limitations. First, there is a clear selection bias. Aneurysms suspected to be of high risk of rupture were treated outside of this cohort, which would explain the low incidence of SAH in their population. These include irregular aneurysms and aneurysms that presented with mass effect. In terms of risk factors, some findings replicated what has been previously published in the literature (eg, size, location, daughter sac, and history of SAH). Other conclusions failed to corroborate findings from other studies (eg, smoking, hypertension). Although this could be due to selection bias or small population size, it could also be explained by the variability in aneurysm natural history and further highlights our lack of understanding of the pathology.Although statistics generated by large-scale studies help us to better understand diseases, it should be noted that they apply for the general masses and give a global perspective and therefore have little implication for an individual in the clinic. This is particularly an issue when the number of variables increases such as in the case of aneurysms. As an example, a patient with a connective tissue disease with a 5-mm ACA aneurysm might be at a higher risk than an otherwise healthy patient with a 9-mm MCA aneurysm. When other variables such as age, aneurysm growth, shape, smoking, and SAH history are factored in, the complexity increases exponentially. In addition, aneurysm formation risk factors are not necessarily the same as rupture risk factors. In an ideal world, mathematically generated individualized risk assessment models would assist in decision-making and treatment algorithms. At this point in time, however, such a model remains out of immediate and practical reach. Further studies are required to improve our understanding of aneurysms on multiple levels, including clinical, biological, and mechanical 23).