Wintermark Max, Glastonbury Christine, Tong Elizabeth, Lau Benison C, Schaeffer Sarah, Chien Jeffrey D, Haar Peter J, Saloner David
University of California, San Francisco, Department of Radiology, San Francisco, CA, United States.
J Neurol Sci. 2008 Jun 15;269(1-2):74-9. doi: 10.1016/j.jns.2007.12.023. Epub 2008 Jan 29.
To validate a semi-automated computer approach for the assessment of the degree of carotid artery luminal narrowing by comparing it to the visual evaluation by a neuroradiologist.
In a retrospective cross-sectional study, consecutive emergency department patients who underwent computed tomography angiography (CTA) of the carotid arteries were identified. CTA studies were reviewed by a neuroradiologist, and also independently processed with a computer algorithm that automatically measures the degree of luminal narrowing at the level of the internal carotid artery bulb. The findings of the neuroradiologist and computer assessment were compared using Chi2 tests/kappa calculations and linear regression for categorical and continuous measurements of carotid stenosis, respectively.
The study population consisted of 125 patients (74 no stroke/TIA, 18TIA, and 33 stroke). 201 carotid arteries showed no significant stenosis; 33 showed > or =70% stenosis, 5 showed 95-99% stenosis, and 11 showed complete occlusion. There was excellent agreement between the neuroradiologist's visual assessment and the automated computer evaluation of the category of carotid stenosis (kappa=0.918, p<0.001).
The automated computer algorithm for quantifying the degree of carotid stenosis is reliable and shows high concordance with the interpretation of an experienced neuroradiologist.
通过将一种半自动计算机方法与神经放射科医生的视觉评估进行比较,验证该方法用于评估颈动脉管腔狭窄程度的有效性。
在一项回顾性横断面研究中,确定了连续接受颈动脉计算机断层血管造影(CTA)的急诊科患者。CTA研究由神经放射科医生进行审查,并使用一种计算机算法独立处理,该算法可自动测量颈内动脉球部水平的管腔狭窄程度。分别使用卡方检验/卡帕计算和线性回归对神经放射科医生的评估结果与计算机评估结果进行比较,以对颈动脉狭窄进行分类和连续测量。
研究人群包括125例患者(74例无中风/短暂性脑缺血发作,18例短暂性脑缺血发作,33例中风)。201条颈动脉无明显狭窄;33条显示≥70%狭窄,5条显示95 - 99%狭窄,11条显示完全闭塞。神经放射科医生的视觉评估与颈动脉狭窄分类的自动计算机评估之间存在极好的一致性(卡帕=0.918,p<0.001)。
用于量化颈动脉狭窄程度的自动计算机算法可靠,且与经验丰富的神经放射科医生的解读高度一致。