Management of incidental unruptured intracranial aneurysms

Follow-up care compliance among patients diagnosed with unruptured intracranial aneurysms

OBJECTIVES

Periodic imaging follow-up for patients with unruptured intracranial aneurysms (UIA) is crucial, as studies indicate higher rupture risk with aneurysm growth. However, few studies address patient adherence to follow-up recommendations. This study aims to identify compliance rates and factors influencing follow-up adherence.

METHODS

Patients with a UIA were identified from our institution's database from 2011-2021. Follow-up imaging (CT/MR Angiogram) was advised at specific intervals. Patients were categorized into compliant and non-compliant groups based on first-year compliance. Factors contributing to compliance were assessed through multivariate logistic regression. Phone interviews were conducted with non-compliant patients to understand reasons for non-adherence.

RESULTS

Among 923 UIA diagnosed patients, 337 were randomly selected for analysis. The median follow-up period was 1.4 years, with a 42% first-year compliance rate. The mean aneurysm size was 3.3 mm. Five patients had a rupture during follow-up, of which 4 died. Compared with patients consulting specialists at the initial diagnosis, those seen by non-specialists exhibited lower compliance (OR 0.25, p < 0.001). Loss to follow-up was greatest during transition from emergency service to specialist appointments. Patients who spoke languages other than English exhibited poorer compliance than those speaking English (OR 0.20, p = 0.01).

CONCLUSIONS

Significant amounts of UIA patients at low rupture risk were lost to follow-up before seeing UIA specialists. Main non-compliance factors include inadequate comprehension of follow-up instructions, poor care transfer from non-specialists to specialist, and insurance barriers.

Epidemiology and Risk Factors of Mycotic Aneurysm in Patients With Infective Endocarditis and the Impact of its Rupture in Outcomes. Analysis of a National Prospective Cohort

Background

Several aspects of the occurrence and management of mycotic aneurysm (MA) in patients with infective endocarditis (IE) have not been studied.

Objectives

To determine the incidence and factors associated with MA presence and rupture and to assess the evolution of those initially unruptured MA.

Methods

Prospective multicenter cohort including all patients with definite IE between January 2008 and December 2020.

Results

Of 4548 IE cases, 85 (1.9%) developed MA. Forty-six (54.1%) had intracranial MA and 39 (45.9%) extracranial MA. Rupture of MA occurred in 39 patients (45.9%). Patients with ruptured MA had higher 1-year mortality (hazard ratio, 2.33; 95% confidence interval, 1.49-3.67). Of the 55 patients with initially unruptured MA, 9 (16.4%) presented rupture after a median of 3 days (interquartile range, 1-7) after diagnosis, being more frequent in intracranial MA (32% vs 3.3%, P = .004). Of patients with initially unruptured MA, there was a trend toward better outcomes among those who received early specific intervention, including lower follow-up rupture (7.1% vs 25.0%, P = .170), higher rate of aneurysm resolution in control imaging (66.7% vs 31.3%, P = .087), lower MA-related mortality (7.1% vs 16.7%, P = .232), and lower MA-related sequalae (0% vs 27.8%, P = .045).

Conclusions

MA occurred in 2% of the patients with IE. Half of the Mas occurred in an intracranial location. Their rupture is frequent and associated with poor prognosis. A significant proportion of initially unruptured aneurysms result from rupture during the first several days, being more common in intracranial aneurysms. Early specific treatment could potentially lead to better outcomes.

Intracranial Aneurysms and Lipid Metabolism Disorders: From Molecular Mechanisms to Clinical Implications

Many vascular diseases are linked to lipid metabolism disorders, which cause lipid accumulation and peroxidation in the vascular wall. These processes lead to degenerative changes in the vessel, such as phenotypic transformation of smooth muscle cells and dysfunction and apoptosis of endothelial cells. In intracranial aneurysms, the coexistence of lipid plaques is often observed, indicating localized lipid metabolism disorders. These disorders may impair the function of the vascular wall or result from it. We summarize the literature on the relationship between lipid metabolism disorders and intracranial aneurysms below.

Magnetic resonance imaging findings in patients with idiopathic olfactory dysfunction and normal findings on nasoendoscopy

OBJECTIVE

In presentations of anosmia or dysosmia, magnetic resonance imaging may be required to screen for intracranial pathology such as olfactory neuroblastomas and other intracranial masses impacting on the olfactory pathway. This study aimed to establish positive magnetic resonance imaging findings of anosmia or dysosmia for scans performed before the coronavirus disease 2019 pandemic.

METHODS

The study examined the outcome of patients who presented with isolated olfactory dysfunction and who underwent magnetic resonance imaging between 2015 and 2019.

RESULTS

Of the 131 patients, 41 (31.3 per cent) had normal scan findings, 50 (38.2 per cent) had insignificant paranasal mucosal disease and 6 (4.6 per cent) had mucosal thickening significant enough to require additional intervention. These interventions included repeat nasoendoscopy or commencement of intranasal or oral steroids. No patients had olfactory neuroblastoma.

CONCLUSION

Only 4.6 per cent of the magnetic resonance imaging scans revealed abnormal findings related to anosmia or dysosmia, and none required ENT surgical intervention. None of the magnetic resonance imaging scans identified an olfactory neuroblastoma or intracranial masses impacting on the olfactory pathway.

SMART Registry: Safety and Performance of the Penumbra SMART COIL System for Patients With Intracranial Aneurysms 4 mm and Smaller

BACKGROUND

The Penumbra SMART COIL System includes a novel generation of embolic coils composed of complex and WAVE shape properties with varying levels of softness.

OBJECTIVE

To assess safety and efficacy of the SMART COIL System through a 1-year follow-up in patients with small intracranial aneurysms.

METHODS

This subset analysis of the SMART Registry, a prospective, multicenter study, includes patients with small intracranial aneurysms (≤4 mm) treated with the SMART COIL System. Registry end points include retreatment rates through 1 year, procedural device-related serious adverse events, and adequate occlusion postprocedure.

RESULTS

Of 905 enrolled patients with aneurysms, 172 (19.0%) had small (≤4 mm) aneurysms (75.6% female; mean age 57.2 ± 13.4 years). 30.8% (53/172) of small aneurysms were ruptured, of which 50.9% (27/53) had Hunt and Hess ≥3. 79.5% (132/166) were wide-necked. Stent-assisted coiling and balloon-assisted coiling were performed in 37.2% (64/172) and 22.1% (38/172) of patients, respectively. The mean packing density for very small aneurysms was 44.9 (SD 25.23). Raymond Class I and Class II were achieved in 89.5% (154/172) postprocedure and 97.2% (137/141) at 1 year. The retreatment rate through 1 year was 5.6% (8/142), and the recanalization rate was 7.1% (10/141). The periprocedural device-related serious adverse event rate was 2.9% (5/172). Intraprocedural aneurysm rupture occurred in 0.8% of patients.

CONCLUSION

This analysis suggests that the SMART COIL System is safe and efficacious in small aneurysms with satisfactory occlusion rates and low rates of rupture or rerupture. At 1 year, patients had low retreatment rates and good clinical outcomes.

Magnetic resonance imaging finding of coexistence of bilateral paraclinoid aneurysms in a patient with a nonfunctioning macroadenoma, simultaneous resection, and clipping: illustrative case

BACKGROUND

Unruptured incidental intracranial aneurysm can coexist with pituitary adenoma, however, the occurrence is extremely rare. Timely diagnosis of asymptomatic intracranial aneurysms with pituitary adenoma may lead to planning a tailored surgical strategy to deal with both pathologies simultaneously. A case of a patient who underwent transcranial resection of a pituitary adenoma with clipping of two mirror aneurysms is reported.

OBSERVATIONS

A 55-year-old female presented with deterioration of visual acuity that progressed over 1 year, as well as presence of right eyelid ptosis. Magnetic resonance imaging of the head showed the presence of an intrasellar pituitary macroadenoma. Bilateral paraclinoid aneurysms were documented to be in contact with the pituitary tumor. The patient underwent surgery with simultaneous aneurysm clipping and tumor resection through a standard pterional approach with intradural clinoidectomy. The aneurysms were successfully clipped after the tumoral debulking. After clipping, the pseudocapsule was fully resected.

LESSONS

Various treatment options are available. Although endovascular securing of the aneurysms prior to the tumor resection would be ideal, in cases in which this resource is not readily available at all times, the surgeon must be prepared to solve pathologies with an elevated level of complexity.

Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview

Intracranial aneurysms (IAs) are a significant public health concern. In populations without comorbidity and a mean age of 50 years, their prevalence is up to 3.2%. An efficient method for identifying subjects at high risk of an IA is warranted to provide adequate radiological screening guidelines and effectively allocate medical resources. Artificial intelligence (AI) has received worldwide attention for its impressive performance in image-based tasks. It can serve as an adjunct to physicians in clinical settings, improving diagnostic accuracy while reducing physicians' workload. AI can perform tasks such as pattern recognition, object identification, and problem resolution with human-like intelligence. Based on the data collected for training, AI can assist in decisions in a semi-autonomous manner. Similarly, AI can identify a likely diagnosis and also, select a suitable treatment based on health records or imaging data without any explicit programming (instruction set). Aneurysm rupture prediction is the holy grail of prediction modeling. AI can significantly improve rupture prediction, saving lives and limbs in the process. Nowadays, deep learning (DL) has shown significant potential in accurately detecting lesions on medical imaging and has reached, or perhaps surpassed, an expert-level of diagnosis. This is the first step to accurately diagnose UIAs with increased computational radiomicis. This will not only allow diagnosis but also suggest a treatment course. In the future, we will see an increasing role of AI in both the diagnosis and management of IAs.

Machine Learning and Intracranial Aneurysms: From Detection to Outcome Prediction

Machine learning (ML) is a rapidly rising research tool in biomedical sciences whose applications include segmentation, classification, disease detection, and outcome prediction. With respect to traditional statistical methods, ML algorithms have the potential to learn and improve their predictive performance when fed with large data sets without the need of being specifically programmed. In recent years, this technology has been increasingly applied for tackling clinical issues in intracranial aneurysm (IA) research. Several studies attempted to provide reliable models for enhanced aneurysm detection. Convolutional neural networks trained with variable degrees of human interaction on data from diverse imaging modalities showed high sensitivity in aneurysm detection tasks, also outperforming expert image analysis. Algorithms were also shown to differentiate ruptured from unruptured IAs, with however limited clinical relevance. For prediction of rupture and stability assessment, ML was preliminarily shown to achieve better performance compared to conventional statistical methods and existing risk scores. ML-based complication and functional outcome prediction in the event of SAH have been more extensively reported, in contrast with periprocedural outcome investigation in unruptured IA patients. ML has the potential to be a game changer in IA patient management. Currently clinical translation of experimental results is limited.