PURPOSE: To examine the associations between intracranial artery calcifications (IACs) and coronary artery calcifications (CACs) in patients with ischemic stroke and to assess the predictive value of IAC for asymptomatic coronary artery disease (CAD). MATERIALS AND METHODS: This retrospective study, approved by an institutional review board that waived the need for informed consent, included 314 consecutive patients who had acute ischemic stroke and who underwent both brain and coronary computed tomography (CT) within 1 month of stroke. IAC was quantified semiautomatically by calculating both Agatston scores (area of calcification multiplied by a weighted value assigned to its highest Hounsfield unit) and volumes on thin-section unenhanced images and was correlated with coronary calcium scores and volumes. Quartiles were created for IAC scores and were used for logistic regression analysis. An optimal IAC score cutoff value was determined and used to predict the presence of asymptomatic CAD. Independent factors for asymptomatic CAD were assessed by using multiple logistic regression analysis. Receiver operating characteristic curve analysis was performed to evaluate the added value of IAC scores for prediction of asymptomatic CAD. RESULTS: IAC and CAC were significantly correlated for both Agatston scores and volumes (R = 0.665 and 0.663, respectively; P < .001). A graded association was found between IAC scores and presence of asymptomatic CAD. Both IAC scores of 120.11 or greater (odds ratio [OR], 2.57; 95% confidence interval [CI]: 1.45, 4.55) and diabetes mellitus (OR, 4.23; 95% CI: 2.42, 7.4) were independent predictors for asymptomatic CAD. Adding the IAC score to analytic models significantly improved the ability to predict asymptomatic CAD. CONCLUSION: The IAC scores quantified by using unenhanced CT correlate significantly with coronary calcium scores and may serve as an independent predictor of asymptomatic CAD in patients with ischemic stroke.
PURPOSE: To examine the associations between intracranial artery calcifications (IACs) and coronary artery calcifications (CACs) in patients with ischemic stroke and to assess the predictive value of IAC for asymptomatic coronary artery disease (CAD). MATERIALS AND METHODS: This retrospective study, approved by an institutional review board that waived the need for informed consent, included 314 consecutive patients who had acute ischemic stroke and who underwent both brain and coronary computed tomography (CT) within 1 month of stroke. IAC was quantified semiautomatically by calculating both Agatston scores (area of calcification multiplied by a weighted value assigned to its highest Hounsfield unit) and volumes on thin-section unenhanced images and was correlated with coronary calcium scores and volumes. Quartiles were created for IAC scores and were used for logistic regression analysis. An optimal IAC score cutoff value was determined and used to predict the presence of asymptomatic CAD. Independent factors for asymptomatic CAD were assessed by using multiple logistic regression analysis. Receiver operating characteristic curve analysis was performed to evaluate the added value of IAC scores for prediction of asymptomatic CAD. RESULTS: IAC and CAC were significantly correlated for both Agatston scores and volumes (R = 0.665 and 0.663, respectively; P < .001). A graded association was found between IAC scores and presence of asymptomatic CAD. Both IAC scores of 120.11 or greater (odds ratio [OR], 2.57; 95% confidence interval [CI]: 1.45, 4.55) and diabetes mellitus (OR, 4.23; 95% CI: 2.42, 7.4) were independent predictors for asymptomatic CAD. Adding the IAC score to analytic models significantly improved the ability to predict asymptomatic CAD. CONCLUSION: The IAC scores quantified by using unenhanced CT correlate significantly with coronary calcium scores and may serve as an independent predictor of asymptomatic CAD in patients with ischemic stroke.
Authors: Frederik F Strobl; Beatrice Kuhlin; Robert Stahl; Bastian O Sabel; Andreas D Helck; Andreas Schindler; Matthias Witt; Fabian Bamberg; Maximilian F Reiser; Tobias Saam Journal: Radiol Med Date: 2018-01-30 Impact factor: 3.469
Authors: Kyoo Ho Cho; Dong Hyun Lee; Kyung Min Kim; Yun Ho Choi; Hyo Suk Nam; Ji Hoe Heo; Kyoung Heo; Young Dae Kim Journal: Front Neurol Date: 2019-07-31 Impact factor: 4.003
Authors: Sung Hyun Yoon; Eunhee Kim; Yongho Jeon; Sang Yoon Yi; Hee Joon Bae; Ik Kyung Jang; Joo Myung Lee; Seung Min Yoo; Charles S White; Eun Ju Chun Journal: Korean J Radiol Date: 2020-09 Impact factor: 3.500