Clinical Scales in Aneurysm Rupture Prediction

Sanchez, Sebastian; Miller, Jacob M.; Samaniego, Edgar A.

doi:10.1161/svin.123.000625

Cited by 3 publications

(1 citation statement)

References 75 publications

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“…Scales intended to forecast the risk of aneurysm hemorrhage or offer clinical guidance are not commonly integrated into clinical practice [24]. Additionally, these scales suffer from a notable deficit of prospective evaluation, a crucial element requisite for establishing a robust scientific basis to support their widespread implementation [19].…”

Section: Limitations Of Aneurysm Scale Usementioning

confidence: 99%

Retrospective Application of Risk Scores to Unruptured Anterior Communicating Artery Aneurysms

Wójtowicz,

Przepiorka,

Kujawski

et al. 2024

JCM

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Background: Treatment decisions for unruptured intracranial aneurysms (UIAs) pose a challenge for neurosurgeons, prompting the development of clinical scales assessing hemorrhage risk to provide management guidance. This study compares recommendations from the PHASES and UIA treatment scores (UIATS) applied to anterior communicating artery (AComA) UIAs against real-world management. Methods: While UIATS recommends management, for PHASES, an aneurysm with score of 10 or more was considered “high-risk”. Analysis involved assessing the concordance in each group alongside comparison to real-word management. Results: Among 129 patients, 46.5% were observed and 53.5% were treated. PHASES scores were significantly higher in the treatment group (p = 0.00002), and UIATS recommendations correlated with real-world decisions (p < 0.001). We observed no difference in the frequencies of UIATS recommendations between high- and low-risk groups. When comparing the UIATS and PHASES, 33% of high-risk aneurysms received a UIATS conservative management recommendation. In 39% of high-risk aneurysms, the UIATS recommendation was not definitive. Conversely, 27% of low-risk aneurysms obtained a UIATS UIA repair recommendation. Overall, concordance between PHASES and UIATS was 32%. Conclusions: Significant discordance in therapeutic suggestions underscores the predominant influence of center experience and individual assessments. Future studies should refine and validate decision-making strategies, potentially exploring alternative applications or developing tailored scales.

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Section: Limitations Of Aneurysm Scale Usementioning

confidence: 99%

Retrospective Application of Risk Scores to Unruptured Anterior Communicating Artery Aneurysms

Wójtowicz,

Przepiorka,

Kujawski

et al. 2024

JCM

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Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms

Veeturi,

Saleem,

Ojeda

et al. 2024

Transl. Stroke Res.

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Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms

Veeturi,

Saleem,

Ojeda

et al. 2024

Preprint

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Background: Aneurysm wall enhancement (AWE) has the potential to be used as an imaging biomarker for the risk stratification of intracranial aneurysms (IAs). Radiomics provides a refined approach to quantify and further characterize AWE's textural features. This study examines the performance of AWE quantification combined with clinical information in detecting symptomatic IAs. Methods: Ninety patients harboring 104 IAs (29 symptomatic and 75 asymptomatic) underwent high-resolution magnetic resonance imaging (HR-MRI). The assessment of AWE was performed using two different methods: 3D-AWE mapping and composite radiomics-based score (RadScore). The dataset was split into training and testing subsets. The testing set was used to build two different nomograms using each modality of AWE assessment combined with patients’ demographic information and aneurysm morphological data. Finally, each nomogram was evaluated on an independent testing set. Results: A total of 22 radiomic features were significantly different between symptomatic and asymptomatic IAs. The 3D-AWE Mapping nomogram achieved an area under the curve (AUC) of 0.77 (63% accuracy, 78% sensitivity and 58% specificity). The RadScore nomogram exhibited a better performance, achieving an AUC of 0.83 (77% accuracy, 89% sensitivity and 73% specificity). Conclusions: Combining AWE quantification through radiomic analysis with patient demographic data in a clinical nomogram achieved high accuracy in detecting symptomatic IAs.

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Clinical Scales in Aneurysm Rupture Prediction

Cited by 3 publications

References 75 publications

Retrospective Application of Risk Scores to Unruptured Anterior Communicating Artery Aneurysms

Retrospective Application of Risk Scores to Unruptured Anterior Communicating Artery Aneurysms

Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms

Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms

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