Rupture risk of intracranial aneurysms: Comparison between small ruptured intracranial aneurysms and large unruptured intracranial aneurysms.

To compare the differences in clinical and morphological features between small ruptured intracranial aneurysms and large unruptured intracranial aneurysms to evaluate the risk factors for the rupture of IAs. The clinical data of 189 consecutive patients with 193 IAs were reviewed. The patients and IAs were divided into ruptured (<5 mm) and unruptured groups (>10 mm). The characteristics of the patients and the intracranial aneurysms (IAs) were compared between the 2 groups, and the risk factors for rupture of IAs were assessed using multiple logistic regression. Patient age (odds ratio [OR], 0.955), IA located at the internal carotid artery (ICA, OR, 0.202), irregular shape (OR, 0.083) and parent vessel diameter (OR, 0.426) were negatively correlated with the risk of IA rupture. IAs located at bifurcations (OR, 6.766) were positively correlated with the risk of IA rupture. In addition to the size of the IAs, regardless of IAs shape, other factors, such as younger age (<63.5 years), location at a bifurcation, IAs located at the ICA and a small parent vessel diameter (<3.25 mm), can influence the risk of IA rupture.

Compare deep learning model and conventional logistic regression model for the identification of unstable saccular intracranial aneurysms in computed tomography angiography.

Background: It is crucial to distinguish unstable from stable intracranial aneurysms (IAs) as early as possible to derive optimal clinical decision-making for further treatment or follow-up. The aim of this study was to investigate the value of a deep learning model (DLM) in identifying unstable IAs from computed tomography angiography (CTA) images and to compare its discriminatory ability with that of a conventional logistic regression model (LRM). Methods: From August 2011 to May 2021, a total of 1,049 patients with 681 unstable IAs and 556 stable IAs were retrospectively analyzed. IAs were randomly divided into training (64%), internal validation (16%), and test sets (20%). Convolutional neural network (CNN) analysis and conventional logistic regression (LR) were used to predict which IAs were unstable. The area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the discriminating ability of the models. One hundred and ninety-seven patients with 229 IAs from Banan Hospital were used for external validation sets. Results: The conventional LRM showed 11 unstable risk factors, including clinical and IA characteristics. The LRM had an AUC of 0.963 [95% confidence interval (CI): 0.941-0.986], a sensitivity, specificity and accuracy on the external validation set of 0.922, 0.906, and 0.913, respectively, in predicting unstable IAs. In predicting unstable IAs, the DLM had an AUC of 0.771 (95% CI: 0.582-0.960), a sensitivity, specificity and accuracy on the external validation set of 0.694, 0.929, and 0.782, respectively. Conclusions: The CNN-based DLM applied to CTA images did not outperform the conventional LRM in predicting unstable IAs. The patient clinical and IA morphological parameters remain critical factors for ensuring IA stability. Further studies are needed to enhance the diagnostic accuracy.

A Prospective Follow-up Study on Risk Factors to Predict the Progression of Unruptured Intracranial Aneurysms on Enhanced HR-MRI.

RATIONALE AND OBJECTIVES: To prospectively investigate the potential correlation between qualitative and quantitative assessment of aneurysm wall enhancement (AWE) on initial enhanced high-resolution magnetic resonance imaging (HR-MRI) and aneurysm progression during follow-up. MATERIALS AND METHODS: From June 2016 to January 2021, we prospectively recruited patients with unruptured intracranial aneurysms (UIAs) for enhanced HR-MRI examination. The patients' demographic and clinical data and aneurysm characteristics, including AWE features, were collected and analyzed. Follow-up images were compared to evaluate IA progression. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the risk factors associated with aneurysm progression. RESULTS: Seventy-seven patients with 95 UIAs met our research criteria, and the median follow-up time was 15.7 months. Progression was observed in 18 aneurysms; the remaining 77 remained stable. Progressive UIAs were larger in size, more frequently displayed obvious AWE and showed a higher enhancement ratio (ER) than nonprogressive UIAs. Multivariate Cox regression analysis showed that both ER (hazard ratio, 6.304, p < 0.001) and aneurysm size (hazard ratio, 1.343, p = 0.014) were independent risk factors for aneurysm progression. The combination of ER and aneurysm size had an area under the curve of 0.920 for the prediction of aneurysm progression, with a sensitivity of 88.9% and specificity of 87.0%. CONCLUSION: A higher ER value of the aneurysm wall and a larger aneurysm size on initial HR-MRI may predict an increased risk of aneurysm progression, which suggests that closer monitoring by imaging or preventive intervention may be required for the clinical management of these aneurysms.

CT findings of Talaromyces marneffei infection among HIV patients with lymphadenopathy.

Background: Talaromyces marneffei (T. marneffei) is an opportunistic fungal pathogen commonly found in human immunodeficiency virus (HIV) patients that often infects lymph nodes. Knowledge about the computed tomography (CT) characteristics of T. marneffei lymphadenopathy in HIV patients is limited. The aim of this study was to investigate the clinical and CT characteristics of T. marneffei lymphadenopathy to improve its diagnosis and promote recognition of this type of infection in radiology. Methods: Between February 2019 and June 2021, we retrospectively reviewed the clinical features and CT characteristics of T. marneffei lymphadenopathy in 21 HIV patients. Results: The clinical symptoms of T. marneffei infection are non-specific. Anemia (100%), fever (85.7%) and cough and sputum production (76.2%) were the most frequent symptoms. Multiple lymphadenopathies, mainly in the mediastinum (76.2%) and mesentery (82.4%), can be fused (14.3%) and necrotic (52.4%), with slight (41.7%) and moderate enhancement (58.3%) that is heterogeneous. In addition to involving the lymph nodes, the lesions involved the lungs (81.0%), liver and spleen (42.9%), and small intestine (14.3%). Conclusions: T. marneffei is prone to affecting lymph nodes and extranodal organs in HIV patients. Although the clinical manifestations of T. marneffei infection are not specific, the possibility of T. marneffei infection should be considered if CT findings indicate multiple lesion sites.

Identification of ruptured intracranial aneurysms using the aneurysm-specific prediction score in patients with multiple aneurysms with subarachnoid hemorrhages- a Chinese population based external validation study.

BACKGROUND: For patients with aneurysmal subarachnoid hemorrhages (SAHs) and multiple intracranial aneurysms (MIAs), a simple and fast imaging method that can identify ruptured intracranial aneurysms (RIAs) may have great clinical value. We sought to use the aneurysm-specific prediction score to identify RIAs in patients with MIAs and evaluate the aneurysm-specific prediction score. METHODS: Between May 2018 and May 2021, 134 patients with 290 MIAs were retrospectively analyzed. All patients had an SAH due to IA rupture. CT angiography (CTA) was used to assess the maximum diameter, shape, and location of IAs to calculate the aneurysm-specific prediction score. Then, the aneurysm-specific prediction score was applied to RIAs in patients with MIAs. RESULTS: The IAs with the highest aneurysm-specific prediction scores had not ruptured in 17 (12.7%) of the 134 patients with 290 MIAs. The sensitivity, specificity, false omission rate, diagnostic error rate, and diagnostic accuracy of the aneurysm-specific prediction score were higher than those of the maximum diameter, shape, and location of IAs. CONCLUSIONS: The present study suggests that the aneurysm-specific prediction score has high diagnostic accuracy in identifying RIAs in patients with MIAs and SAH, but that it needs further evaluation.

Low attenuation plaque volume on coronary computed tomography angiography is associated with plaque progression.

BACKGROUND: Patient-related clinical factors, laboratory factors, and some imaging factors may lead to statistical bias when investigating coronary plaque progression. In this study, we avoided patient characteristics by comparing morphological characteristics of plaque progression and nonprogression within the same patient with multiple plaques. METHODS: From August 2011 to December 2018, 177 consecutive patients with 424 plaques who were followed with coronary computed tomography angiography (CTA) were reviewed retrospectively. Follow-up images of the plaques were used to determine whether the plaque volume or stenosis grade increased. The plaques were divided into progressive and nonprogressive groups. Logistic regression analysis was used to identify the factors associated with plaque progression. Through clinical follow-up, we analyzed whether the factors associated with plaque progression were related to major adverse cardiac events (MACEs). RESULTS: There were 223 plaques that progressed during a mean follow-up period of 27.6 ± 15.9 months. The univariate logistic regression model revealed that only low attenuation plaque (LAP) volume (P = 0.02) was associated with plaque progression. After a mean post-CTA follow-up period of 36.7 ± 18.4 months, 37 patients experienced MACEs, and LAP volume was significantly related to future MACEs. CONCLUSION: Only a high baseline LAP volume was associated with plaque progression, and patients with progressive plaques and a high LAP volume were more likely to have future MACEs. More attention should be given to plaques with LAP volumes larger than 2.4 mm3.

MRCP Combined With CT Promotes the Differentiation of Benign and Malignant Distal Bile Duct Strictures.

OBJECTIVE: To determine whether contrast-enhanced computed tomography (CT) can promote the identification of malignant and benign distal biliary strictures (DBSs) compared to the use of magnetic resonance cholangiopancreatography (MRCP) alone and to identify imaging findings of malignant DBSs. MATERIALS AND METHODS: A total of 168 consecutive patients with confirmed DBSs were reviewed. MRCP alone and MRCP combined with CT images were blindly analyzed by two radiologists (e.g., stricture pattern, margins), and malignant or benign DBSs were identified based on surgical findings, endoscopy findings, or follow-up. The diagnostic accuracy of the two reviewers using MRCP alone and MRCP combined with CT were evaluated. MRCP and CT features of malignant and benign DBSs were compared using multiple logistic regression analysis to identify independent malignant risk factors. RESULTS: MRCP combined with CT examination could improve the diagnostic accuracy, which increased from 70.2% to 81.5% in Doctor A and from 85.1% to 89.3% in Doctor B. The multiple logistic regression model revealed that stricture length [odds ratio (OR) 1.070, P=0.016], angle of the DBS (OR 1.061, P<0.001), double duct sign (OR 4.312, P=0.003) and low density in the arterial phase (OR 0.319, P=0.018) were associated with malignant DBS. A scoring model incorporating these four factors was established; at a threshold value of 1.75, and the sensitivity and specificity for the detection of malignant DBSs were 73.5 and 85.9%, respectively. CONCLUSIONS: Compared to the use of MRCP alone, MRCP combined with contrast-enhanced CT can improve the accuracy of DBS diagnosis. The scoring model accurately predicts malignant DBSs and helps make treatment decisions.

Risk factors for the progression of unruptured intracranial aneurysms in patients followed by CT/MR angiography.

BACKGROUND: The progression of an unruptured intracranial aneurysm (UIA) is associated with a higher rupture risk. The aim of this study was to identify the risk factors for the progression of UIAs among Chinese adults and compare them with the ELAPSS (Earlier subarachnoid hemorrhage, IA Location, Age, Population, IA Size and Shape) score. METHODS: Four hundred thirty-eight consecutive patients with 491 UIAs were followed and reviewed retrospectively from August 2011 to November 2019. Follow-up images of the UIAs were used to determine changes in IA size and shape. Patients and IAs were divided into non-progression and progression groups. In addition to the clinical characteristics of the patients, the features of the IAs (e.g., size and shape) were evaluated by computed tomography angiography (CTA) or magnetic resonance angiography (MRA). Independent risk factors for UIA progression were studied using multiple Cox proportional hazards regression analysis. In addition, the diagnostic value of the ELAPSS score for the prediction of UIA progression was calculated. RESULTS: Seventy-two IAs in 68 patients progressed during a mean follow-up time of 24.2±19.68 months. IAs located at the bifurcation [odds ratio (OR) 2.600], with an irregular shape (OR 2.981) or having a high aspect ratio (AR, OR 2.430) were correlated with progression. Based on these three factors, the threshold value of our predictive score was 0.5, and the area under the curve (AUC), sensitivity and specificity were 0.756, 93.1% and 40.6%, respectively, while the AUC, sensitivity and specificity of the ELAPSS score were 0.711, 55.6%, and 75.2%, respectively. CONCLUSIONS: IAs located at the bifurcation, with an irregular shape and with an elevated AR are risk factors for UIA progression in the Chinese population. Our predictive score is of great value in predicting the risk of UIA progression.

Normal pancreatic volume assessment using abdominal computed tomography volumetry.

ABSTRACT: To determine the normal range of pancreatic volume (PV) in Chinese adults using computed tomography (CT) volumetry. To assess the relationships of PV with patient demographics and clinical parameters. To analyze the degree of correlation between PV values determined by manual segmentation and those calculated by formulas.A total of 240 adults (120 women, 120 men) between the ages of 18 and 79 years were reviewed. There were 6 groups of patients, with 40 patients in each decade regarding age. PV was segmented manually on computed tomography images slice by slice for each patient, and 2 formulas were used to calculate PV∗ and PV#.The mean PV was 77.44 ±â€Š19.11 cm3 (range from 28.55-138.15 cm3). PV was significantly correlated with height (r = 0.427, P < .001), weight (r = 0.525, P < .001), body mass index (r = 0.377, P < .001), the width of the first lumbar vertebral body (r = 0.166, P = .01), the transverse abdominal diameter (r = 0.455, P < .001), and the sagittal abdominal diameter (r = 0.456, P < .001). There was a negative correlation between PV and age (r = -0.209, P = .001). The correlation coefficients between PV and PV∗ and PV# were 0.676 and 0.376, respectively, with both P < .001.PV associated with patient demographics and clinical parameters. A more accurate and simpler formula should be used in the future to calculate and monitor changes in PV.

Risk of Rupture of Small Intracranial Aneurysms (≤5 mm) Among the Chinese Population.

OBJECTIVE: We sought to develop a model to predict the risk of small intracranial aneurysm (SIA; ≤5 mm) rupture among Chinese adults and to compare the score predicted by our model with the PHASES (population, hypertension, age, size, earlier subarachnoid hemorrhage, aneurysm site) score. METHODS: From August 2011 to June 2015, 366 patients with 394 SIAs were retrospectively evaluated and followed up for ≥5 years. The clinical characteristics of the patients were reviewed from their medical records, and the SIA features were evaluated from the imaging studies. The independent risk factors for SIA rupture were studied using multiple Cox proportional hazards regression analysis. The diagnostic value of the PHASES score for the prediction of SIA rupture was also calculated. RESULTS: Six SIAs in 6 different patients had ruptured during a mean follow-up of 6.4 years. An irregular shape (odds ratio [OR], 31.464), a high aspect ratio (OR, 40.573), and a high size ratio (OR, 20.541) increased the risk of rupture. The predictive score incorporated these three factors. The threshold was 1.5, and the area under the curve, sensitivity, and specificity were 0.986, 100%, and 94.6%, respectively. For the PHASES score, the area under the curve, sensitivity, and specificity were 0.702, 83.3%, and 62.1%, respectively. CONCLUSIONS: An irregular shape, a high aspect ratio, and a high size ratio were associated with SIA rupture in the Chinese population. Our predictive score is of great value in predicting the risk of SIA rupture.

Discrimination of serous cystadenoma from mucinous cystic neoplasm and branch duct intraductal papillary mucinous neoplasm in the pancreas with CT.

PURPOSE: The imaging features of serous cystadenomas (SCAs) overlap with those of mucinous cystic neoplasms (MCNs) and branch duct intraductal papillary mucinous neoplasms (BD-IPMNs), and an accurate preoperative diagnosis is important for clinical treatment due to their different biological behaviors. The aim of this study was to provide a computed tomographic (CT) feature for the diagnosis of SCAs and estimate whether the "circumvascular sign" can contribute to the discrimination of SCAs from MCNs and BD-IPMNs. METHODS: From August 2011 through December 2019, a total of 71 patients (30 patients with 30 SCAs, 21 patients with 21 MCNs and 20 patients with 22 BP-IPMNs) were enrolled in this study. All patients underwent CT examination and were confirmed by surgical pathology. In addition to patient clinical information, CT features (e.g., location, shape) were evaluated via CT. RESULTS: Central scarring, central calcification and the circumvascular sign were found to be specific CT features for the diagnosis of SCAs and their differential diagnosis from MCNs and BD-IPMNs. All three CT features had high specificity, and both central scarring and central calcification had low sensitivity. When any one of these two features was combined with the circumvascular sign, the sensitivity increased to 83.3%. CONCLUSION: Pancreatic cystic neoplasms that show central scarring, central calcification or the circumvascular sign on CT could be diagnosed as SCAs. When either of the first two features is combined with the circumvascular sign, the diagnostic sensitivity could be increased.

A Simple Scoring Model for Prediction of Rupture Risk of Anterior Communicating Artery Aneurysms.

Background: The rupture risk of anterior communicating artery aneurysms (ACoAAs) has been known to be higher than that of aneurysms at other locations. Thus, the aim of this study is to investigate the clinical and morphological characteristics associated with risk factors for the rupture of ACoAAs. Methods: In total, 361 consecutive patients with 361 ACoAAs between August 2011 and December 2017 were retrospectively reviewed. Patients and ACoAAs were divided into ruptured and unruptured groups. In addition to clinical characteristics, ACoAA characteristics were evaluated by CT angiography (CTA). A multiple logistic regression analysis was used to identify the independent risk factors associated with ACoAA rupture. The assignment score of these variables depends on the ß coefficient. A receiver operating characteristic (ROC) curve analysis was used to calculate the optimal thresholds. Results: The multiple logistic regression model revealed that A1 dominance [odds ratio (OR) 3.034], an irregular shape (OR 3.358), and an aspect ratio ≥1.19 (AR; OR 3.163) increased the risk of rupture, while cerebral atherosclerosis (OR 0.080), and mean diameters ≥2.48 mm (OR 0.474) were negatively correlated with ACoAA rupture. Incorporating these five factors, the ROC analysis revealed that the threshold value of the multifactors was one, the sensitivity was 88.3%, and the specificity was 66.0%. Conclusions: The scoring model is a simple method that is based on A1 dominance, irregular shape, aspect ratio, cerebral atherosclerosis, and mean diameters from CTA and is of great value in the prediction of the rupture risk of ACoAAs.

Wall enhancement ratio determined by vessel wall MRI associated with symptomatic intracranial aneurysms.

PURPOSE: To study the association of the enhancement ratio (ER) of aneurysmal wall enhancement (AWE) with symptomatic intracranial aneurysms (IAs), we hypothesized that the ER of AWE would be stronger in symptomatic IAs than in asymptomatic IAs, as assessed by high-resolution magnetic resonance imaging (HRMRI). MATERIALS AND METHODS: Between February 2016 and February 2018, 80 consecutive patients with 89 unruptured IAs were reviewed. Patients and IAs were divided into symptomatic and asymptomatic groups. In addition to the clinical characteristics, the IA features (e.g., size, shape) were evaluated via computed tomography angiography, while the ER and enhanced patterns were evaluated by HRMRI. Multiple logistic regression analysis was performed to determine the independent risk factors for symptomatic IAs. Receiver operating characteristic curve analysis was used for the final model to obtain the optimal thresholds. RESULTS: Multiple logistic regression analysis indicated that only the ER was associated with symptomatic IAs. The threshold value of the ER was 60.5%. CONCLUSIONS: A higher ER was more frequently identified in symptomatic IAs. More attention should be paid to this factor in the management of IAs.

Relationships between aneurysmal wall enhancement and conventional risk factors in patients with intracranial aneurysm: A high-resolution MRI study.

BACKGROUND AND PURPOSE: Aneurysmal wall enhancement (AWE) is thought to reflect wall inflammation and is a novel imaging biomarker for intracranial aneurysm (IA) risk evaluation. However, the relationship between AWE and other conventional risk factors (e.g., size) remains unclear. The aim of this study was to investigate the relationship between AWE and other risk factors. MATERIAL AND METHODS: Seventy-six consecutive patients from February 2016 to April 2017 with 88 unruptured IAs were reviewed. Patients and IAs were divided into with AWE and without AWE groups according to high-resolution magnetic resonance imaging (HRMRI) images. In addition to the patients' clinical characteristics, the features of the IAs (e.g., size and aspect ratio (AR)) were evaluated via computed tomography angiography. Multiple logistic regression analysis was used to identify the association between AWE and other risk factors. A receiver operating characteristic curve analysis was performed for the final model to obtain optimal thresholds. RESULTS: IAs with an irregular shape (OR 12.544) and a high AR (OR 32.891) were associated with AWE. The threshold value of the AR was 1.05. CONCLUSIONS: AWE on contrast-enhanced HRMRI was correlated with IAs with an irregular shape and a high AR. AWE may be a marker of instability and even risk of rupture.

The Relationship of Arterial Wall Enhancement Ratio on MRI with the Degree of Inflammation in a Rabbit Aneurysm Model: A Pilot Study.

RATIONALE AND OBJECTIVES: To identify the relationship between enhancement ratio (ER) of aneurysm walls and degrees of inflammation. MATERIALS AND METHODS: Twenty-five white rabbits were used in this study; all underwent surgery to isolate the right common carotid artery (RCCA). Twenty rabbits underwent an aneurysm creation procedure, and 5 underwent a control procedure. In the aneurysm creation procedure, there was surgical exposure of the origin of RCCA and temporary occlusion with an aneurysm clip. The distal RCCA was ligated, and the trapped segment was infused with elastase for 20 minutes, after which the clip was removed. In the control procedure, the trapped segment was infused with saline. High-resolution magnetic resonance imaging was performed at weeks 2, 3, 4, and 5 after the procedure, and wall ER was calculated. After MRI, aneurysms were harvested and stained with hematoxylin-eosin. Pearson correlation analysis and scatter plots were used to evaluate the relationship between wall ER and the degree of inflammation. The relationships between the wall ER, the number of inflammatory cells and time were analyzed by linear graphs. RESULTS: Wall ER positively correlated with inflammatory cell count of the aneurysm wall (r = 0.877, p < 0.001). The relationships between wall ER, the number of inflammatory cells, and time increased and then decreased according linear graphs. CONCLUSION: In this study, the aneurysm wall ER was confirmed to be associated with the degree of inflammation on the rabbit aneurysm model.

Risk factors for ruptured intracranial aneurysms.

BACKGROUND & OBJECTIVES: The treatment of unruptured intracranial aneurysms (IAs) remains controversial; the ability to predict the risk of rupture for an aneurysm would be of clinical value. The aim of this study was to determine and evaluate the predictive value of the risk factors of IA rupture. METHODS: This retrospective study involved 379 consecutive patients with 441 aneurysms between August 2011 and July 2014. Based on clinical data and computed tomography angiography findings, the potential of risk factors to predict the aneurysmal rupture was assessed using statistical methods. RESULTS: Age, hypertension, heart disease, diabetes mellitus, cerebral atherosclerosis, aneurysms located at the internal carotid artery (ICA) and neck width (N) correlated negatively with rupture risk. Aneurysms located at the anterior communicating artery, bifurcation, irregularity, with a daughter sac, aneurysm height, maximum size, aspect ratio (AR), height-to-width ratio and bottleneck factor were significantly and positively correlated with rupture risk. The multivariate logistic regression model revealed that bifurcation aneurysm, irregular aneurysm and high AR increased the rupture risk, while cerebral atherosclerosis, aneurysm located on the ICA and greater N decreased the risk. Receiver operating characteristic analysis of AR curve values differed according to circumstances. INTERPRETATION & CONCLUSIONS: Cerebral atherosclerosis, location in the ICA and larger N were the protective factors against aneurysm rupture, and IAs located at bifurcations, irregular shape and increased AR indicated a greater rupture risk.

Computed Tomography Angiography Evaluation of Risk Factors for Unstable Intracranial Aneurysms.

OBJECTIVE: To evaluate risk factors for instability in intracranial aneurysms (IAs) using computed tomography angiography (CTA). METHODS: A total of 614 consecutive patients diagnosed with 661 IAs between August 2011 and February 2016 were reviewed. Patients and IAs were divided into stable and unstable groups. Along with clinical characteristics, IA characteristics were evaluated by CTA. Multiple logistic regression analysis was used to identify the independent risk factors associated with unstable IAs. Receiver operating characteristic (ROC) curve analysis was performed on the final model, and optimal thresholds were obtained. RESULTS: Patient age (odds ratio [OR], 0.946), cerebral atherosclerosis (CA; OR, 0.525), and IAs located at the middle cerebral artery (OR, 0.473) or internal carotid artery (OR, 0.512) were negatively correlated with instability, whereas IAs with irregular shape (OR, 2.157), deep depth (OR, 1.557), or large flow angle (FA; OR, 1.015) were more likely to be unstable. ROC analysis revealed threshold values of age, depth, and FA of 59.5 years, 4.25 mm, and 87.8°, respectively. CONCLUSIONS: The stability of IAs is significantly affected by several factors, including patient age and the presence of CA. IA shape and location also have an impact on the stability of IAs. Growth into an irregular shape, with a deep depth, and a large FA are risk factors for a change in IAs from stable to unstable.

Morphological characteristics associated with the rupture risk of mirror posterior communicating artery aneurysms.

OBJECTIVE: Patient related clinical factors and intracranial aneurysms (IAs) at different locations may lead to statistical bias when investigating the rupture risk of IAs. Thus the purpose of this study was to identify the morphological parameters that are related to the rupture of mirror posterior communicating artery aneurysms (PComAAs). METHODS: Between August 2011 and July 2017, 68 patients with mirror PComAAs and aneurysmal subarachnoid hemorrhage were diagnosed by CT angiography at three medical centers. Morphological characteristics for PComAAs included bifurcation, shape, neck width, width, depth, maximum size, flow angle, parent vessel diameter, aspect ratio (AR), depth/width ratio, bottleneck factor, and size ratio (SR). Multiple logistic regression analysis was performed to determine the independent risk factors for rupture. Receiver operating characteristic curve analysis was performed to obtain the optimal thresholds. RESULTS: AR (OR 5.623) and SR (OR 5.570) were more commonly observed in the ruptured cohort. The threshold values of AR and SR were 0.98 and 1.21, respectively. CONCLUSIONS: Mirror PComAAs are a useful model to investigate the rupture risk of PComAAs. AR (≥0.98) and SR (≥1.21) are better predictors of ruptured PComAAs.

Risk Factors for the Rupture of Intracranial Aneurysms Using Computed Tomography Angiography.

OBJECTIVE: To study the clinical and morphologic characteristics associated with risk factors for the rupture of intracranial aneurysms (IAs). METHODS: A total of 1115 consecutive patients with 1282 IAs were reviewed from August 2011 to February 2016. The patients and IAs were divided into ruptured and unruptured groups. Based on the clinical and morphologic findings, the risk factors for IA rupture were assessed using statistical methods. RESULTS: Age, hypertension, diabetes mellitus, and cerebral atherosclerosis were associated with ruptured IAs. IAs located in the anterior cerebral artery, the anterior communicating artery, the posterior communicating artery, and the internal carotid artery were associated with ruptured IAs. Ruptures were also associated with arterial bifurcations, irregular aneurysm shapes, and all continuous data, except neck width. Binary logistic regression showed that IAs located at bifurcations (odds ratio [OR], 1.804), with irregular shapes (OR, 4.677), with high aspect ratios (ARs) (OR, 5.037) or with small mean diameters (MDs) (OR, 0.495) are more prone to rupture. Receiver operating characteristic analysis showed that the threshold values of the AR and MD were 1 and 3.70 mm, respectively. CONCLUSIONS: Morphologic characteristics, such as being located at bifurcations, being irregularly shaped, having a high AR (>1), and having a small MD (<3.70 mm), were better predictors of rupture.