Diagnostic value of artificial intelligence technique on intracranial aneurysms in multi-slices spiral CTA for head and neck
10.3969/j.issn.1672-8270.2024.11.007
- VernacularTitle:人工智能技术在头颈部多层螺旋CT血管造影诊断颅内动脉瘤中的价值
- Author:
Chen ZUO
1
;
Chang LIU
;
Liyuan FU
Author Information
1. 中国人民解放军联勤保障部队第九○○医院放射诊断科 福州 350025
- Keywords:
Artificial intelligence(AI);
Intracranial aneurysm(IA);
Computed tomography angiography(CTA)for head and neck
- From:
China Medical Equipment
2024;21(11):35-38,56
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore diagnostic value of artificial intelligence(AI)technique on intracranial aneurysm(IA)in multi-slices computed tomography angiography(CTA)for head and neck.Methods:A retrospective analysis was performed on the cases data of 137 patients with suspected IA who were firstly diagnosed in Fuzong Teaching Hospital of Fujian University of Traditional Chinese Medicine from January 2022 to December 2023,all of them underwent CTA and digital subtraction angiography(DSA)examinations.The results of DSA examination were taken as the"gold standard".The work efficiency and detection effectiveness of two groups for IA were analyzed through manual post-processing and diagnosis(manual group)and CTA with intelligent assistant diagnostic system on head and neck(AI group).Results:In 137 patients with suspected IA,the DSA examination showed that there were 139 aneurysms in 112 patients.The post-processing time was(190.25±30.71)s in AI group,which was significantly shorter than that[(954.37±95.68)s]in manual group,and the difference was statistically significant(t=92.020,P＜0.001),and the image quality of AI group was higher.In the manual group,102 cases with aneurysms were found,which showed good consistency with the"gold standard"(Kappa=0.713),while the AI group found 93 cases with aneurysms,which showed moderate consistency with the"gold standard"(Kappa=0.518).Both groups had higher diagnostic accuracy for the presence or absence of subarachnoid hemorrhage of intracranial aneurysm,but the difference of that between them was not statistically significant difference(P＞0.05).The detection rates of anterior cerebral artery,middle cerebral artery,posterior cerebral artery,anterior communicating artery,posterior communicating artery,vertebral-basilar artery,and artery aneurysms of internal carotid in manual group and AI group were respectively 80.00％vs.80.00％,92.59％vs.81.48％,100.00％vs.100.00％,84.00％vs.52.00％,83.33％vs.0％,80.00％vs.60.00％,69.23％vs.57.69％,and both of them did not found lesions of posterior inferior cerebellar artery.The overall detection rates of two groups were respectively 78.42％and 57.55％,and the overall detection rate of lesion locations of manual group was higher than that of AI group,and the difference in overall coincidence rate between two groups was statistically significant(x2=13.899,P＜0.05).DSA confirmed 7 lesions which aneurysm's diameter was＜3 mm,and the manual group and the AI group identified respectively 3 cases and 1 case for the 7 lesions.A total of 60 lesions with 3～5 mm diameter were found by DSA,and the manual group and the AI group identified respectively 50 cases and 43 cases for the 60 lesions.A total of 72 lesions with＞5 mm diameter were found by DSA,and the manual group and the AI group identified respectively 63 cases and 63 cases,without statistically significant difference between them(P＞0.05).Conclusion:AI technique can significantly improve work efficiency of diagnosis for intracranial aneurysm,and obtain better processing effects of image.Although AI technique has shown a certain value of reference and auxiliary in diagnosing intracranial aneurysms,its diagnostic accuracy and precise in identifying lesion location are still lower than those of manual diagnosis,and it need further deep learning to improve its diagnostic ability.
