人工智能后处理技术在颅脑CTA诊断颅内动脉瘤中的应用价值

doi:10.3969/j.issn.1671-7171.2026.02.016

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Abstract 【Objective】 To investigate the application value of artificial intelligence (AI) post-processing technology in the diagnosis of intracranial aneurysms by cranial CT angiography (CTA). 【Methods】 A total of 128 patients with intracranial aneurysms who underwent cranial CTA examination in our hospital from January 2023 to May 2025 were selected. Image reconstruction and analysis were performed using traditional manual post-processing and AI-assisted post-processing, respectively. Digital subtraction angiography (DSA) results were used as the gold standard. The differences between the two groups in post-processing time, subjective image quality score, aneurysm neck width, maximum aneurysm diameter, and diagnostic efficacy were compared. Kappa test was used to evaluate the consistency between the AI group and the DSA gold standard. 【Results】 The AI processing time was significantly shorter than the manual processing time, and the difference was statistically significant (t=87.362, P<0.05). The AI image quality score was slightly higher than that of manual processing, but the difference was not statistically significant (P>0.05). Consistency analysis results showed that: the consistency of aneurysm neck width measurement in the small aneurysm group detected by AI was poor (ICC value = 0.216); the consistency in the medium aneurysm group was moderate (ICC value=0.479); the consistency in the large aneurysm group was high (ICC value = 0.855). The consistency of maximum diameter measurement in the small aneurysm group detected by AI was poor (ICC value = 0.277); the consistency in the medium aneurysm group was moderate (ICC value = 0.543); the consistency in the large aneurysm group was high (ICC value = 0.891). Kappa analysis showed that the diagnostic consistency between AI and DSA in the small aneurysm group was moderate (Kappa = 0.531); in the medium aneurysm group, it showed good consistency (Kappa = 0.873); in the large aneurysm group, it reached complete consistency (Kappa = 1.00). 【Conclusion】 Artificial intelligence post-processing technology can significantly shorten the post-processing time of cranial CTA images, improve the detection capability of intracranial aneurysms, and effectively optimize image quality. It is an efficient and reliable auxiliary diagnostic method.

Key words： Intracranial Aneurysm Artificial Intelligence Computed Tomography Angiography Image Enhancement

Received: 30 October 2025

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R651.122

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	ZHANG Ying
	SUN Shuang

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ZHANG Ying,SUN Shuang. Application Value of Artificial Intelligence Post-Processing Technology in the Diagnosis of Intracranial Aneurysms by Cranial CTA[J]. JOURNAL OF CLINICAL RESEARCH, 2026, 43(2): 235-238.

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http://journal07.magtech.org.cn/yxlcyj/EN/10.3969/j.issn.1671-7171.2026.02.016 OR http://journal07.magtech.org.cn/yxlcyj/EN/Y2026/V43/I2/235

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