A comprehensive analysis of patients with cerebral arteriovenous malformation with headache: assessment of risk factors and treatment effectiveness.

BACKGROUND: Due to the high mortality and disability rate of intracranial hemorrhage, headache is not the main focus of research on cerebral arteriovenous malformation (AVM), so research on headaches in AVM is still scarce, and the clinical understanding is shallow. This study aims to delineate the risk factors associated with headaches in AVM and to compare the effectiveness of various intervention treatments versus conservative treatment in alleviating headache symptoms. METHODS: This study conducted a retrospective analysis of AVMs who were treated in our institution from August 2011 to December 2021. Multivariable logistic regression analysis was employed to assess the risk factors for headaches in AVMs with unruptured, non-epileptic. Additionally, the effectiveness of different intervention treatments compared to conservative management in alleviating headaches was evaluated through propensity score matching (PSM). RESULTS: A total of 946 patients were included in the analysis of risk factors for headaches. Multivariate logistic regression analysis identified that female (OR 1.532, 95% CI 1.173-2.001, p = 0.002), supply artery dilatation (OR 1.423, 95% CI 1.082-1.872, p = 0.012), and occipital lobe (OR 1.785, 95% CI 1.307-2.439, p < 0.001) as independent risk factors for the occurrence of headaches. There were 443 AVMs with headache symptoms. After propensity score matching, the microsurgery group (OR 7.27, 95% CI 2.82-18.7 p < 0.001), stereotactic radiosurgery group(OR 9.46, 95% CI 2.26-39.6, p = 0.002), and multimodality treatment group (OR 8.34 95% CI 2.87-24.3, p < 0.001) demonstrate significant headache relief compared to the conservative group. However, there was no significant difference between the embolization group (OR 2.24 95% CI 0.88-5.69, p = 0.091) and the conservative group. CONCLUSIONS: This study identified potential risk factors for headaches in AVMs and found that microsurgery, stereotactic radiosurgery, and multimodal therapy had significant benefits in headache relief compared to conservative treatment. These findings provide important guidance for clinicians when developing treatment options that can help improve overall treatment outcomes and quality of life for patients.

Assessment of gamma knife radiosurgery for unruptured cerebral arterioveneus malformations based on multi-parameter radiomics of MRI.

OBJECTIVE: The treatment of Gamma knife radiosurgery (GKS) for unruptured Arteriovenous Malformations (AVM) remains controversial. A safe, effective and non-invasive method to predict outcome seems attractive for GKS. The purpose of this study was to develop and validate a MRI based multi-parameter radiomics model predicting the outcome of GKS for unruptured AVM. METHODS: Eighty-eight unruptured AVM patients who initial underwent GKS between January 2011 and December 2016 in our hospital were included in this retrospective study. Patients were divided into two groups named as favourable and unfavourable outcome, according to the clinical outcome. Favourable outcome was defined as obliteration without post-SRS hemorrhage or permanent radiation-induced changes (RIC). Multivariate logistic regression analysis was used to select appropriate clinical features and construct a clinical predicting model. In terms of radiomic model, manually segmentation and radiomics extracted were performed on each AVM lesions. Finally, 1684 radiomics features were extracted and Recursive Feature Elimination (RFE) method combined with Random forest classifier were used for feature selection and model construction. The performance of the radiomics model was evaluated by the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, the favourable group was further divided into early and late respond subgroup according to the time of obliteration evaluated by 2 years. The selected features were further compared according the respond time. RESULTS: The median duration of neuroimaging follow-up was 65 months, 56 patients showed favourable outcome and 17 patients were observed obliteration within 2 years. The radiomics model constructed by 12 selected features achieved significant higher AUC of 0.88 (95% confidence interval 0.87-0.90) than traditional scoring system for predicting AVM outcome. Two selected radiomics features named "Dependence Variance" and "firstorder-Skewness" were found significant difference between the patients with early or late-respond. CONCLUSIONS: The results suggest that the radiomics features could be successfully used for the pretreatment prediction of outcome for GKS in unruptured AVMs, which is helpful for decision-making process on unruptured AVM patients.