ArticleQuantitative imaging in medicine and surgery2023
Multiphase computed tomography angiography derived from computed tomography perfusion data for the differential diagnosis of intracranial aneurysm and infundibular dilation.
Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: As infundibular dilation (ID) is less likely to cause hemorrhage or other clinical sequelae than an intracranial aneurysm (IA) and treating infundibulum itself may put the patient at unnecessary risk for stroke, it is important to distinguish between the ID and IA. Given the limitations of conventional single-phase computed tomography angiography (sCTA) to show small branches of intracranial arteries, the application of multiphase computed tomography angiography (mCTA) for identification seems promising. Our main objective was to evaluate whether using mCTA derived from computed tomography perfusion (CTP) data can improve distinction between IA and ID. Methods: A total of 35 patients diagnosed with IA or ID of the posterior communicating artery at its junction with the internal carotid artery junction (ICA-PComA) by sCTA at the 8th Medical Center of Chinese PLA General Hospital between January 2019 and May 2022 were retrospectively selected. All patients underwent CTP. The simulated mCTA was reconstructed from 0.75 mm CTP data for assessment of vascular branches. All data were processed separately by 2 CTA post-processors; 2 observers diagnosed IA and ID by source and volume rendering (VR) images of sCTA and VR images of mCTA, and compared the diagnostic efficacy of source and VR images of sCTA with VR images of mCTA. Results: The quality of the reconstructed images was more consistent between the 2 post-processors mCTA (K=0.856) than sCTA (K=0.648). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the source image for ID identification were 78.9%, 86.7%, 84.2%, 81.3%, and 80.0% for sCTA, 73.7%, 81.2%, 82.3%, 72.2%, and 77.2% for the VR image of sCTA, and 94.7%, 87.5%, 90.0%, 93.3%, and 91.4% for the VR image based on mCTA, respectively. The net reclassification index (NRI) of mCTA for VR and the source image of sCTA was 0.273 and 0.220, respectively. VR base on mCTA was on average better than VR and the source image of sCTA at differentiating ID from IA (P=0.005 and P=0.001, respectively). Conclusions: Compared to sCTA, mCTA is more helpful in improving the distinction of ID and IA.
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