Diagnosis Of Intracranial Aneurysms Research Articles

Identification of Hub Genes Associated with the Pathogenesis of Intracranial Aneurysm via Integrated Bioinformatics Analysis.

BackgroundAt present, the pathogenesis of intracranial aneurysms (IA) remains unclear, which significantly hinders the development of novel strategies for the clinical treatment. In this study, bioinformatics methods were used to identify the potential hub genes and pathways associated with the pathogenesis of IA.MethodsThe gene expression datasets of patients with intracranial aneurysm were downloaded from the Gene Expression Database (GEO), and the different data sets were integrated by the robust rank aggregation (RRA) method to identify the differentially expressed genes between patients with intracranial aneurysm and the controls. The functional enrichment analyses of the significant differentially expressed genes (DEGs) were performed and the protein–protein interaction (PPI) network was constructed; thereafter, the hub genes were screened by cytoHubba plug-in of Cytoscape, and finally sequencing dataset GSE122897 was used to verify the hub genes.ResultsThe GSE15629, GSE75436, GSE26969, and GSE6551 expression profiles have been included in this study, including 34 intracranial aneurysm samples and 26 control samples. The four datasets obtained 136 significant DEGs (45 up-regulated, 91 down-regulated). Enrichment analysis showed that the extracellular matrix structural constituent and the ECM-receptor interaction were closely related to the occurrence of IA. It was finally determined that eight hub genes associated with the development of IA, including VCAN, COL1A1, COL11A1, COL5A1, COL5A2, POSTN, THBS2, and CDH2.ConclusionThe discovery of potential hub genes and pathways could enhance the understanding of the molecular mechanisms associated with the development of IA. These hub genes may be potential therapeutic targets for the management and new biomarker for the diagnosis of IA.

Non-Coding RNAs as Circulating Biomarkers for the Diagnosis of Intracranial Aneurysm: A Systematic Review and Meta-Analysis

BackgroundEarly diagnosis of intracranial aneurysm (IA) is arduous in the current situation, and no biomarker is available for the screening of IA. We here systematically evaluate the diagnostic value of circulating non-coding RNA (ncRNA) for the diagnosis of IA. MethodsWe searched PubMed, Web of Science, Embase, Scopus and Cochrane Library databases from inception to June 2020. We included studies that investigated the diagnostic performance of circulating ncRNAs for the diagnosis of IA. We performed Random-effect meta-analyses for the diagnostic test accuracy to calculate pooled estimates. Subgroup analyses and sensitivity analyses were conducted to explore the source of heterogeneity. ResultsThirteen studies, including 1,105 patients and 28 ncRNAs, were included. The pooled sensitivity and specificity were 0.80 (95% confidence interval [CI], 0.76–0.83) and 0.80 (95% CI, 0.76-0.84), respectively, and the area under the hierarchical summary receiver operating characteristic curve was 0.87 (95% CI, 0.84-0.89). The pooled positive and negative likelihood ratios were 3.97 (95% CI, 3.17-4.98) and 0.25 (95% CI, 0.21-0.31), corresponding with a diagnostic odds ratio of 15.63 (95% CI, 10.41-23.47). Subgroup analyses revealed that the diagnostic accuracy of miRNA, lncRNA and circRNA were not significantly different (p > 0.05). Circulating ncRNAs showed higher diagnostic accuracy for patients with unruptured IA than those with ruptured IA (p = 0.0122). ConclusionCurrent evidence suggests that the circulating ncRNA test could be an effective method for universal IA screening. Future clinical studies need to confirm the diagnostic role of specific ncRNAs.

Effect of combined acetylsalicylic acid and statins treatment on intracranial aneurysm rupture.

Acetylsalicylic acid (ASA) and statins have been identified as potentially reducing the risk of intracranial aneurysms (IA) rupture. We aim to determine the effect of this drugs on the risk of rupture of IA. We performed a retrospective cohort study from a prospective database of patients with IA treated in our institution between January 2013 and December 2018. Demographics, previous oral treatments, presence of multiple aneurysms, size of aneurysm, lobulation, location and morphology of the aneurysms were recorded. Patients were dichotomized as ruptured and unruptured IA. A total of 408 IA were treated, of which 283 (68.6%) were in women. The median age was 53, 194 (47.5%) were ruptured IA. 38 patients (9.3%) were receiving ASA and 84 (20.6%) were receiving statins at the moment of the IA diagnosis. In the multivariable regression analysis, ASA plus statin use and multiple aneurysms were independently associated with unruptured IA (OR 5.01, 95% CI, 1.37-18.33, P = 0.015 and OR 2.72, 95% CI 1.68-4.27, P<0.001, respectively). Whereas, lobulated wall aneurysm and PComA/AComA location were inversely and independently associated with unruptured IA condition (OR 0.34, 95% CI 0.21-0.55, P<0.001 and OR 0.37, 95% CI 0.23-0.60, P<0.001, respectively). However, ASA and statins in monotherapy were not independently associated with unruptured IA condition. In our study population ASA plus statins treatment is independently associated with unruptured IA. Larger and prospective studies are required to explore this potential protective effect against IA rupture.

Toward human intervention-free clinical diagnosis of intracranial aneurysm via deep neural network

SummaryIntracranial aneurysm (IA) is an enormous threat to human health, which often results in nontraumatic subarachnoid hemorrhage or dismal prognosis. Diagnosing IAs on commonly used computed tomographic angiography (CTA) examinations remains laborious and time consuming, leading to error-prone results in clinical practice, especially for small targets. In this study, we propose a fully automatic deep-learning model for IA segmentation that can be applied to CTA images. Our model, called Global Localization-based IA Network (GLIA-Net), can incorporate the global localization prior and generates the fine-grain three-dimensional segmentation. GLIA-Net is trained and evaluated on a big internal dataset (1,338 scans from six institutions) and two external datasets. Evaluations show that our model exhibits good tolerance to different settings and achieves superior performance to other models. A clinical experiment further demonstrates the clinical utility of our technique, which helps radiologists in the diagnosis of IAs.

Deep Learning for Detection of Intracranial Aneurysms From Computed Tomography Angiography Images

Background: The rates of the fatality and disability will be extremely high once the intracranial aneurysms rupture. Radiologic examination based on the computed tomography angiography (CTA) images is the preferred method for the diagnosis of intracranial aneurysms, where the interpretation of imaging data is usually performed by an experienced radiologist. However, the accuracy of the interpretation and the time spent highly rely on the professional competence of the radiologist, which may yield inconsistent diagnostic outcomes. In addition, with steadily increasing workloads of radiology departments for providing various imaging diagnostic services, the fatigue of radiologists due to overloading may cause them neglecting or mistaking interpretations. Therefore, the aim of this study was to develop a new method to automatically detect intracranial aneurysms from CTA images using deep learning based on convolutional neural network (CNN) implemented on the Deepmedic platform. This new method can serve as a clinical diagnostic tool or a preliminary reference for diagnosis of intracranial aneurysms. It will be of great clinical value in reducing the diagnosis time and the missed or mistaken diagnosis caused by radiologists' different professional levels or their fatigue. Methods: We implemented a deep learning architecture with a 3D CNN model on Deepmedic platform for automatic segmentation and detection of intracranial aneurysms from CTA images which were retrospectively collected. The retrospective dataset was preprocessed and then was divided into two parts: the training part (80 subjects) to train the CNN model, and the testing part (10 subjects) to evaluate the performance of the automatic detection system. Sensitivity, positive predictive value (PPV) and the false positives per case were evaluated with the reference standard of digital subtraction angiography (DSA) or intraoperative results. Findings: The overall sensitivity and PPV of this system for the detection of intracranial aneurysms from CTA images were 92.3% and 100%, and the segmentation sensitivity also was 92.3%. The performance of the system in the detection of intracranial aneurysms was related to their size: the detection sensitivity for tiny intracranial aneurysms with a diameter ≤ 3mm was 66.7%, whereas the sensitivities of detection for large and medium-sized intracranial aneurysms of > 3mm both were 100%. Interpretation: The deep learning architecture with a 3D CNN model on Deepmedic platform could reliably segment and detect intracranial aneurysms from CTA images with an extremely high sensitivity, especially for large and medium-sized intracranial aneurysms, and this required only very limited training samples. Moreover, the detection sensitivity of tiny intracranial aneurysms was higher than those reported recently in other studies. Funding Statement: This study was supported in part by National Natural Science Foundation of China (81601558), Breeding Foundation of Zhuhai People's Hospital of China (2019PY-16) and Medical Research Foundation of Zhuhai City of China (20191207A010017). Declaration of Interests: No authors report any financial relationships with commercial interests Ethics Approval Statement: This retrospective study was approved by the Ethics Committee of Zhuhai People’s Hospital and the First Affiliated Hospital of Harbin Medical University.

A Transparent Vessel-on-a-Chip Device for Hemodynamic Analysis and Early Diagnosis of Intracranial Aneurysms by CFD and PC-MRI.

Hemodynamics plays a critical role in early diagnosis and investigating the growth mechanism of intracranial aneurysms (IAs), which usually induce hemorrhagic stroke, serious neurological diseases, and even death. We developed a transparent blood vessel-on-a-chip (VOC) device for magnetic resonance imaging (MRI) to provide characteristic flow fields of early IAs as the reference for early diagnosis. This VOC device takes advantage of the transparent property to clearly exhibit the internal structure and identify the needless air bubbles in the biomimetic fluid experiment, which significantly affects the MRI image quality. Furthermore, the device was miniaturized and easily assembled with arbitrary direction using a 3D-printed scaffold in a radiofrequency coil. Computational fluid dynamics (CFD) simulations of the flow field were greatly consistent with those data from MRI. Both internal flow and wall shear stress (WSS) exhibited very low levels during the IA growth, thus leading to the growth and rupture of IAs. PC-MRI images can also provide a reasonable basis for the early diagnosis of IAs. Therefore, we believed that this proposed VOC-based MR imaging technique has great potential for early diagnostic of intracranial aneurysms.

Location of intracranial aneurysms is the main factor associated with rupture in the ICAN population

Background and purposeThe ever-growing availability of imaging led to increasing incidentally discovered unruptured intracranial aneurysms (UIAs). We leveraged machine-learning techniques and advanced statistical methods to provide new insights into rupture...

Prevalence of Intracranial Aneurysms in Patients with Infrarenal Abdominal Aortic Aneurysms: A Multicenter Experience.

Prior studies suggest high prevalence of intracranial aneurysms (IA) in patients with infrarenal abdominal aortic aneurysms (AAA). We reviewed our multicenter experience in clinical detection/treatment of IAs in AAA patients and estimated the risk of IA in patients with AAA relative to patients without AAA. We reviewed cases of vascular surgery infrarenal AAA repairs at three Mayo Clinic sites from January 1998 to December 2018. Concurrent controls were randomly matched in a 1:1 ratio by age, sex, smoking history, and head imaging characteristics. Conditional logistic regression was used to calculate odds ratios. We reviewed 2,300 infrarenal AAA repairs. Mean size of AAA at repair was 56.9 ± 11.4 mm; mean age at repair, 75.8 ± 8.0 years. 87.5% of the cases ( n = 2014) were men. Head imaging was available in 421 patients. Thirty-seven patients were found to have 45 IAs for a prevalence of 8.8%. Mean size of IA was 4.6 ± 3.5 mm; mean age at IA detection, 72.0 ± 10.8 years. Thirty (81%) out of 37 patients were men. Six patients underwent treatment for IA: four for ruptured IAs and two for unruptured IAs. All were diagnosed before AAA repair. Treatment included five clippings and one coil-assisted stenting. Time from IA diagnosis to AAA repair was 16.4 ± 11.0 years. Two of these patients presented with ruptured AAA, one with successful repair and a second one that resulted in death. Odds of IA were higher for patients with AAA versus those without AAA (8.8% [37/421] vs. 3.1% [13/421]; OR 3.18; 95% confidence interval, 1.62-6.27, p < 0.001). Co-prevalence of IA among patients with AAA was 8.8% and is more than three times the rate seen in patients without AAA. All IAs were diagnosed prior to AAA repair. Surveillance for AAA after IA treatment could have prevented two AAA ruptures and one death.

Experience, challenges and lessons learnt from microsurgical clipping of intracranial aneurysms at an emerging neurosurgical centre

Objectives: To share our experience, challenges faced, lessons learnt and analyze the results of surgical management by microsurgical clipping of intracranial aneurysms at an emerging neurosurgical centre at Guru Gobind Singh medical college and hospital (GGSMC&amp;H) Faridkot, Punjab. India.&#x0D; Material and Methods: This study includes all the patients who presented with the diagnosis of intracranial aneurysm on CT angiography and were treated with the microsurgical clipping, between March 2017 to April 2019.&#x0D; Results: There was a total of 23 patients 11female and 12 male. Age range 32 to 85years. On admission 22 patients had SAH on CT scan and one was admitted after incidental detection of the aneurysm without SAH. The time interval between ictus and admission was 0-3 days in 13 patients, 3-14 days in 8 patients and more than 14 days in 1 patient. WFNS grade (gd) I-15 patients, gd II-2, gd III-2, gd IV-3 patients. Fisher gd I-nil, gd II-9, gd III-4, gd IV-9 patients. In 23 patients 27 Aneurysms were clipped. Distribution of location was Anterior Communicating-12, Distal Anterior Cerebral Artery- 4, Middle cerebral artery (MCA) Bifurcation-3, MCA trifurcation-1, Anterior Choroidal-1, Posterior Communicating (P-com) -1, Ophthalmic Internal Carotid Artery (OICA)-4 and three patients had associated multiple aneurysms. Size of aneurysms varied from &lt; 02mm diameter in 2 patients, 2-25mm - 23 and, more than 25mm-2 aneurysms. There was intra op rupture in 2 cases. Post-operatively 2 patients developed hemiparesis, which recovered, nine patients developed vasospasm. Two patients developed chest related complications. One patient developed renal failure. There were 8 deaths. Patients are on follow up since March 2017 till date.&#x0D; Conclusions: Intracranial aneurysms are challenging to manage due to their proximity to vital intracranial structures, and difficulty in securing intracranial proximal control. Thorough knowledge of intracranial anatomy of adjacent relations, arachnoid planes and skilful dissection is a key element for a successful outcome. Data collected from GGSMC &amp; Hospital may not be representative of the entire state or country’s population. Therefore, a large-scale data collection is necessary to create our own database to ascertain the risk factors and preventive measures that are exclusive to our state and nation.

A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance.

To develop a deep learning algorithm for automated detection and localization of intracranial aneurysms on time-of-flight MR angiography and evaluate its diagnostic performance. In a retrospective and multicenter study, MR images with aneurysms based on radiological reports were extracted. The examinations were randomly divided into two data sets: training set of 468 examinations and internal test set of 120 examinations. Additionally, 50 examinations without aneurysms were randomly selected and added to the internal test set. External test data set consisted of 56 examinations with intracranial aneurysms and 50 examinations without aneurysms, which were extracted based on radiological reports from a different institution. After manual ground truth segmentation of aneurysms, a deep learning algorithm based on 3D ResNet architecture was established with the training set. Its sensitivity, positive predictive value, and specificity were evaluated in the internal and external test sets. MR images included 551 aneurysms (mean diameter, 4.17 ± 2.49 mm) in the training, 147 aneurysms (mean diameter, 3.98 ± 2.11 mm) in the internal test, 63 aneurysms (mean diameter, 3.23 ± 1.69 mm) in the external test sets. The sensitivity, the positive predictive value, and the specificity were 87.1%, 92.8%, and 92.0% for the internal test set and 85.7%, 91.5%, and 98.0% for the external test set, respectively. A deep learning algorithm detected intracranial aneurysms with a high diagnostic performance which was validated using external data set. • A deep learning-based algorithm for the automated diagnosis of intracranial aneurysms demonstrated a high sensitivity, positive predictive value, and specificity. • The high diagnostic performance of the algorithm was validated using external test data set from a different institution with a different scanner. • The algorithm might be robust and effective for general use in real clinical settings.

Study on Sensitivity and Accuracy of Diagnosis of Intracranial Aneurysms Based on 256-Slice Spiral CT Angiography

Objective: To investigate the value of 256-slice spiral CT angiography in the diagnosis and postoperative evaluation of patients with intracranial aneurysms. Methods: A total of 62 patients with intracranial aneurysms diagnosed by neurosurgery in our hospital were randomly collected from 2017.03–2018.11. The MSCTA was performed by labeling intravenous non-ionic contrast agent (iodosyls alcohol). The obtained image was imageprocessed at Sun's stand-alone workstation (Philip256iCT). Observe the position, shape, size of the aneurysm, the relationship between the neck and the artery and the structure of the skull base, and compare with the intraoperative findings to understand the anastomosis between the preoperative and intraoperative. Postoperatively, 28 cases were reviewed, and the surgical results, the patency of the arterial artery, and the presence or absence of aneurysm residual were confirmed. Results: Sixty-two patients with intracranial aneurysms were diagnosed with MSCTA and DSA. A total of 66 aneurysms and multiple aneurysms were found. Of these, 32 patients underwent direct operative MSCTA and 43 underwent craniotomy. Endovascular interventional therapy. The location, shape, size, relationship between the neck and the parental artery of the aneurysm and the DSA performance were basically consistent with MSCTA. No false positive results were found. Postoperative examination of MSCTA in 28 cases, all developed well, the arterial artery was well patency, no residual aneurysm was seen. Conclusion: MSCTA can accurately display the location, shape and size of the aneurysm, the relationship between the neck and the artery and the structure of the skull base. It can be used as an important tool for clinical diagnosis and treatment of aneurysm imaging. An important method for post-review and follow-up.

Artificial Blood Vessel Frameworks from 3D Printing-Based Super-Assembly as In Vitro Models for Early Diagnosis of Intracranial Aneurysms

Intracranial aneurysm (IA) is a bulge from the weak area in the wall of cerebral blood vessels and can cause serious diseases, such as hemorrhagic stroke and other neurologic diseases. Experimental...

A two-miRNA signature (miR-21 and miR-92) in peripheral whole blood as a potential biomarker for diagnosis of human cerebral aneurysms.

microRNAs (miRs) have been reported as blood-based noninvasive indicators for the diagnosis of various diseases. However, the utility of whole blood-based miRs in the diagnosis of intracranial aneurysm (IA) is still not clear. The present study aimed to examine miR expression profiling in the peripheral whole blood of IA patients and healthy controls. Seventy-three IA patients, including 34 unruptured and 39 ruptured, and 28 healthy subjects, were recruited for diagnostic analysis. microRNA (miR) expression profiling in whole blood from healthy controls and IA patients was evaluated using miRNA microarray assay. RT-qPCR was used to evaluate miR expression. Receiver operating characteristics (ROC) curves and the area under the ROC curves (AUC) were used to calculate the diagnostic power of miRs in whole blood of IA. We observed significantly higher miR-21 and miR-92 expression levels in aneurysmal tissues and whole blood of IA patients as compared to healthy subjects. miR-21 expression level was significantly positively correlated with miR-92 in IA tissues and whole blood of IA patients. ROC analysis revealed that miR-21 (AUC = 0.843, sensitivity = 0.849, specificity = 0.750) and miR-92 (AUC = 0.892, sensitivity = 0.945, specificity = 0.786) were promising in diagnosis of IA with high detectability. Intriguingly, miR-21 combined with miR-92 markedly improved the diagnostic power of IA (AUC = 0.920, sensitivity = 1.000, specificity = 0.786). miR-21 combined with miR-92 could be considered as a potential biomarker for IA screening.

Epidemiological analysis of 1404 patients with intracranial aneurysm followed in a single Brazilian institution.

Background:We sought to evaluate the epidemiology of intracranial aneurysms in relation to location, gender, age, presence of multiple aneurysms, and comorbidities in the Brazilian population.Methods:We performed a prospective analysis of a cohort of 1404 patients diagnosed with intracranial aneurysm admitted to the Hospital das Clinicas of the University of Sao Paulo, a referral hospital for the treatment of cerebrovascular diseases in Brazil. Patients admitted between September 2009 and September 2018 with radiological diagnosis of intracranial aneurysm were included in the study.Results:A total of 2251 aneurysms were diagnosed. Females accounted for 1090 aneurysms (77.6%) and the mean age at diagnosis was 54.9 years (ranging 15–88). The most common location was middle cerebral artery (MCA) with 593 aneurysms (26.3%) followed by anterior cerebral artery (ACA) with 417 aneurysms (18.5%) and internal carotid artery in the posterior communicating segment with 405 aneurysms (18.0%). Males had higher rates of ACA aneurysms (29.7%) while females had higher rates of MCA aneurysms (26.1%). Sorting by size, 492 aneurysms were <5 mm (21.8%), 1524 measured 5–10 mm (67.7%), 119 size 11–24 mm (5.3%), and 116 were >24 mm (5.2%). The occurrence of multiple aneurysms was associated with female gender (P < 0.001) and smoking (P < 0.001), but not with hypertension (P = 0.121).Conclusion:In this population, the occurrence of intracranial aneurysm is related to several factors, including gender, age, smoking, and hypertension. Our study brought to light important characteristics of a large number of Brazilian patients regarding epidemiology, location, size, and multiplicity of intracranial aneurysms.

Automatic Diagnosis Based on Spatial Information Fusion Feature for Intracranial Aneurysm.

Timely and accurate auxiliary diagnosis of intracranial aneurysm can help radiologist make treatment plans quickly, saving lives and cutting costs at the same time. At present, Digital Subtraction Angiography (DSA) is the gold standard for the diagnosis of intracranial aneurysm, but as radiologists interpret those imaging sequences frame by frame, misdiagnosis might occur. The utilization of computer-aided diagnosis (CAD) can ease the burdens of radiologists and improve the detection accuracy of aneurysms. In this article, a deep learning method is applied to detect the intracranial aneurysm in 3D Rotational Angiography (3D-RA) based on a spatial information fusion (SIF) method, and instead of a 3D vascular model, 2D image sequences are used. Given the intracranial aneurysm and vascular overlap having similar feature in the most time, rather than focusing on distinguishing them in one frame, the morphological differences between frames are considered as major feature. In the training data, consecutive frames of every imaging time series are extracted and concatenated in a specific way, so that the spatial contextual information could be embedded into a single two-dimensional image. This method enables the time series with obvious correlation between frames be directly trained on 2D convolutional neural network (CNN), instead of 3D-CNN with huge computational cost. Finally, we got an accuracy of 98.89%, with sensitivity and specificity of 99.38% and 98.19%, respectively, which proves the feasibility and availability of the SIF feature.

Association between surgical repair of aortic aneurysms and the diagnosis of intracranial aneurysms

ObjectiveAortic aneurysms (AAs) and intracranial aneurysms (IAs) share several clinical risk factors, a genetic predisposition, and molecular signaling pathways. Nonetheless, associations between IAs and AAs remain to be thoroughly validated in large-scale studies. In addition, no effective medical therapies exist for unruptured IAs or AAs. MethodsData for this nationwide, population-based, retrospective, cohort study described herein were obtained from the National Health Insurance Research Database in Taiwan. The study outcomes assessed were (1) the cumulative incidence of IAs, which was compared between AA and patients without an AA and (2) the cumulative incidence of IAs in patients with AAs during the 13-year follow-up period, which was further compared among those who underwent open surgical repair (OSR), endovascular aneurysm repair or nonsurgical treatment (NST). ResultsOur analyses included 20,280 patients with an AA and 20,280 propensity score-matched patients without an AA. Compared with the patients without an AA, patients with AA exhibited a significantly increased risk of an IA diagnosis (adjusted hazard ratio [HR], 3.395; P < .001). Furthermore, 6308 patients with AAs were treated with surgical intervention and another 6308 propensity score-matched patients with AAs were not. Patients with an AA who underwent OSR had a significantly lower risk of being diagnosed with an IA than patients with an AA who underwent endovascular aneurysm repair or NST (adjusted HR, 0.491 [P < .001] and adjusted HR, 0.473 [P < .001], respectively). ConclusionsWe demonstrated an association between IAs and AAs, even after adjusting for several comorbidities. We also found that OSR was associated with fewer recognized IAs than NST.

False Positive Diagnosis of Intracranial Aneurysm in the Context of Abusive Head Trauma

False Positive Diagnosis of Intracranial Aneurysm in the Context of Abusive Head Trauma

Application of the Pipeline Embolization Device for Giant Vertebrobasilar Dissecting Aneurysms in Pediatric Patients.

Objective: To evaluate the feasibility and effectiveness of the pipeline embolization device (PED) for the treatment of pediatric giant vertebrobasilar dissecting aneurysms (VBDAs).Methods: We retrospectively reviewed our institutional clinical database and identified 2,706 patients who presented with a diagnosis of intracranial aneurysms from January 2016 to June 2018. Among this group, 153 patients were diagnosed with VBDAs, and 54 of these patients underwent PED therapy. The PED technique was used in four patients who were 18 years old or younger at the time of presentation (two males, two females; mean age 9.25 years; age range 8–11 years).Results: All four included pediatric patients were managed with the PED. One patient (25%) was treated with the PED alone, while three (75%) were treated with the PED and coils. One patient died from brainstem infarction or compression of the brainstem, while follow-up of the other three patients revealed favorable outcomes. The mass effect was reduced in cases 1, 2, and 3 on follow-up MRI performed 6 months after the PED procedure.Conclusions: PEDs could be feasible in the treatment of pediatric giant VBDAs. However, the safety and efficacy of this method have not been clarified in this special pediatric population, and long-term follow-up is still necessary.

Pediatric Intracranial Aneurysms: Favorable Outcomes Despite Rareness and Complexity

Pediatric intracranial aneurysms (IAs) are rare and differ from their adult counterparts in terms of their aneurysmal characteristics, presentation, treatment, and outcomes. Their treatment is often more difficult and complex compared with that of adults. However, studies outlining the clinical effect of pediatric IAs remain sparse. We retrospectively reviewed the data from patients aged ≤18 years admitted to our hospital from 2000 to 2017 with a diagnosis of IAs. From the sample of 8207 patients with an IA diagnosis, 26 patients with 33 IAs were involved. Our cohort included 17 males and 9 females, with a mean age of 12.5 years. The mean follow-up duration was 4 years and 3 months. Seven patients (26.92%) were assumed to have a traumatic origin for their IAs. Ruptured aneurysms were more common than unruptured ones (61.53% vs. 38.46%). Complex features were observed in 14 aneurysms (42.42%). Initially, microsurgical and endovascular treatment were both performed in 10 patients (38.46%). A good recovery was obtained in 16 patients (61.54%) as determined by the Glasgow outcome scale scores at the 6-month follow-up visits. The complete obliteration of aneurysms was observed in 17 patients (65.38%). Endovascular treatment was the initial treatment in 3 patients with incomplete obliteration. The treatment of pediatric IAs is challenging and technically demanding owing to their discrete nature compared with adult IAs and the need for greater surgical skills. We found a male predominance, with internal carotid artery bifurcation as the most frequent location of the aneurysms. Despite the greater incidence of ruptured and complex aneurysm cases, many patients had experienced a good recovery at the 6-month follow-up examinations.

Comparison of Morphology of Intracranial Aneurysms on Computed Tomography Angiography with Digital Subtraction Angiography and Intraoperative Findings– A Single Centre Experience

Introduction: Multi-Detector Computed Tomography (MDCT) angiography is a non-invasive technique in emergency screening of Subarachnoid Haemorrhage (SAH) for accurately detecting aneurysms. Digital Subtraction Angiography (DSA) remains the gold standard for diagnosis of intracranial aneurysm. Computed Tomography Angiography (CTA) is being increasingly used for this purpose and can presently replace DSA as the most reliable means to detect intracranial aneurysms in SAH. Aim: To characterise the morphology of intracranial aneurysms with CTA and to compare it with DSA and intraoperative findings. Materials and Methods: This analytical study includes patients suspected to have intracranial aneurysm and underwent CTA on 16 slice MDCT scanner. Post-processing Multiplanar Reconstructions (MPR), 3D Volume Rendering (VR) and Maximum Intensity Projection (MIP) were performed. The findings of CTA findings were compared with DSA and intraoperative/indocyanine angiography images obtained by Leica neurosurgical operating microscope, wherever possible. Morphological parameters: size (dome, neck, height, dome to neck ratio, aspect ratio in saccular and length, diameter in fusiform), shape, lobulation, tit, location, thrombosis/ calcification, blood vessels arising, ruptured or not, grade of SAH (modified CT Fischer score) and vasospasm (grade, number/location of vasospastic segments) were assessed and compared with DSA and intraoperative findings. Results: In 71 patients, 97 intracranial aneurysms were studied. Saccular aneurysm was the most common and anterior communicating artery (ACOM) was the most common location. Significant correlation of dome: neck and aspect ratios between CTA and DSA (p=0.0089) was noted. The sensitivity, Positive Predictive Value (PPV) and accuracy of CTA for aneurysm >3 mm was 100%. Two aneurysms <3 mm were missed on CTA, but detected by DSA. Therefore, for aneurysms <3 mm in size, sensitivity was 92.86%, with a PPV and accuracy of 96.3% and 89.66%, respectively. Overall sensitivity of CTA irrespective of size was 97.9%, with 97.9% PPV and 95.9% accuracy was observed. Conclusion: MDCTA with 3D reconstructions and volume rendering is the ideal first line imaging modality in non-traumatic SAH for detection of aneurysm with a high degree of accuracy. DSA can be used to diagnose tiny aneurysms <3 mm if missed on CTA, if there is a high degree of suspicion.