Literature DB >> 27262145

Automated Quantitative Plaque Analysis for Discrimination of Coronary Chronic Total Occlusion and Subtotal Occlusion in Computed Tomography Angiography.

Adam D Staruch1, Maksymilian P Opolski, Piotr J Slomka, Michal Staruch, Cezary Kepka, Adam Witkowski, Mariusz Kruk, Damini Dey.   

Abstract

PURPOSE: The aim of this study was to evaluate the utility of automated plaque analysis in differentiating chronic total occlusion (CTO) from subtotal occlusion (SO) in patients with ambiguous coronary lesions on coronary computed tomography angiography (CTA).
MATERIALS AND METHODS: A total of 63 patients with 63 ambiguous coronary lesions on CTA were included. The lesion length (LL), diameter stenosis, plaque volume and composition, remodeling index, and contrast density difference (CDD) (reflecting intraluminal contrast kinetics over the lesion) were assessed using an automatic software tool. All patients underwent invasive coronary angiography.
RESULTS: Coronary angiography confirmed 28 CTOs and 35 SOs. CTOs showed significantly longer LL (6.4±12.3 vs. 1.0±2.2 mm, P=0.03) and higher CDD (74%±31% vs. 55%±32%, P=0.02) compared with SO. The optimal thresholds for prediction of CTO for CDD and LL were ≥43% and ≥1 mm, respectively (max. sensitivity: 82% for CDD, max. specificity: 77% for LL). The guidewire manipulation time correlated with LL (r=0.529, P=0.004) and CDD (r=0.435, P=0.021) in lesions attempted by percutaneous coronary intervention.
CONCLUSIONS: Automated computed tomography plaque analysis may be applied as a noninvasive tool to differentiate CTO from SO.

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Year:  2016        PMID: 27262145     DOI: 10.1097/RTI.0000000000000223

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  1 in total

1.  Accuracy of the Euro CTO(CASTLE) score obtained on coronary computed tomography angiography for Predicting 30-minute wire crossing in chronic total occlusions.

Authors:  Yan-Tan Yu; Zhi-Yi Sha; Shu-Min Chang; Du-Tian Zhai; Xiao-Jiao Zhang; Ai-Jie Hou; Wen-Jie Feng; Dao-Wei Li; Yong Wang; Bo Luan
Journal:  BMC Cardiovasc Disord       Date:  2022-04-19       Impact factor: 2.174

  1 in total

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