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Abstract Objective To evaluate the performance of a semi-automated artificial intelligence (AI) software program (CerebralDoc® system) in aneurysm detection and morphological measurement. Methods In this study, 354 cases of computed tomographic angiography (CTA) were retrospectively collected in our hospital. Among them, 280 cases were diagnosed with aneurysms by either digital subtraction angiography (DSA) and CTA (DSA group, n = 102), or CTA-only (non-DSA group, n = 178). The presence or absence of aneurysms, as well as their location and related morphological features determined by AI were evaluated using DSA and radiologist findings. Besides, post-processing image quality from AI and radiologists were also rated and compared. Results In the DSA group, AI achieved a sensitivity of 88.24% and an accuracy of 81.97%, whereas radiologists achieved a sensitivity of 95.10% and an accuracy of 84.43%, using DSA results as the gold standard. The AI in the non-DSA group achieved 81.46% sensitivity and 76.29% accuracy, as per the radiologists’ findings. The comparison of position consistency results showed better performance under loose criteria than strict criteria. In terms of morphological characteristics, both the DSA and the non-DSA groups agreed well with the diagnostic results for neck width and maximum diameter, demonstrating excellent ICC reliability exceeding 0.80. The AI-generated images exhibited superior quality compared to the standard software for post-processing, while also demonstrating a significantly reduced processing time. Conclusions The AI-based aneurysm detection rate demonstrates a commendable performance, while the extracted morphological parameters exhibit a remarkable consistency with those assessed by radiologists, thereby showcasing significant potential for clinical application.

Background: Photophobia and phonophobia are the most prominent symptoms in patients with migraine without aura. Hypersensitivity to visual stimuli can lead to greater hypersensitivity to auditory stimuli, which suggests that the interaction between visual and auditory stimuli may play an important role in the pathogenesis of migraine. However, audiovisual temporal interactions in migraine have not been well studied. Therefore, our aim was to examine auditory and visual interactions in migraine. Methods: In this study, visual, auditory, and audiovisual stimuli with different temporal intervals between the visual and auditory stimuli were randomly presented to the left or right hemispace. During this time, the participants were asked to respond promptly to target stimuli. We used cumulative distribution functions to analyze the response times as a measure of audiovisual integration. Results: Our results showed that audiovisual integration was significantly elevated in the migraineurs compared with the normal controls (p < 0.05); however, audiovisual suppression was weaker in the migraineurs compared with the normal controls (p < 0.05). Conclusions: Our findings further objectively support the notion that migraineurs without aura are hypersensitive to external visual and auditory stimuli. Our study offers a new quantitative and objective method to evaluate hypersensitivity to audio-visual stimuli in patients with migraine. [ABSTRACT FROM AUTHOR]