Severe left main coronary stenosis in a young female patient, 6 years after mediastinal radiation therapy for non-Hodgkin lymphoma: assessment by coronary angiography and intravascular ultrasound

2012 ◽  
Vol 101 (4) ◽  
pp. 317-320 ◽  
Author(s):  
Grigorios Korosoglou ◽  
Arnt V. Kristen ◽  
Martin Andrassy ◽  
Hugo A. Katus ◽  
Stefan E. Hardt
2021 ◽  
Vol 8 ◽  
Author(s):  
Menghuan Li ◽  
Iokfai Cheang ◽  
Yuan He ◽  
Shengen Liao ◽  
Hui Wang ◽  
...  

Objective: Intravascular ultrasound (IVUS) parameters, for example, minimal lumen area (MLA) and area stenosis (AS), poorly identified functional intermediate coronary stenosis (ICS). For detecting functional ICS defined by coronary angiography-derived fractional flow reserve (caFFR), our study aims to determine whether IVUS parameters integrated with lesion length (LL) by three-dimensional quantitative coronary analysis (3D-QCA) could improve diagnostic value.Methods: A total of 111 patients with 122 ICS lesions in the non-left main artery were enrolled. MLA and AS were calculated in all lesions by IVUS. Diameter stenosis (DS%) and LL were measured by 3D-QCA. caFFR was computed by the proprietary fluid dynamic algorithm, a caFFR ≤ 0.8 was considered as functional stenosis. Receiver-operating curve analyses were used to compare the diagnostic accuracy among indices to predict functional stenoses.Results: Mean caFFR values in all lesions were 0.86 ± 0.09. Lesions with caFFR ≤ 0.8 showed lower MLA and higher AS (MLA: 3.3 ± 0.8 vs. 4.1 ± 1.2, P = 0.002; AS: 71.3 ± 9.6% vs. 63.5 ± 1.3%, P = 0.007). DS% and LL were more severe in lesions with caFFR ≤ 0.8 (DS%: 45.5 ± 9.6% vs. 35.5 ± 8.2%, P < 0.001; LL: 31.6 ± 12.9 vs. 21.0 ± 12.8, P < 0.001). caFFR were correlated with MLA, AS, and LL (MLA: r = 0.36, P < 0.001; AS: r = −0.36, P < 0.001; LL: r = −0.41, P < 0.001). Moreover, a multiple linear regression analysis demonstrated that MLA (β = 0.218, P = 0.013), AS (β = −0.197, P = 0.029), and LL (β = −0.306, P > 0.001) contributed significantly to the variation in caFFR. The best cutoff value of MLA, AS, and LL for predicting caFFR ≤ 0.8 were 3.6 mm2, 73%, and 26 mm, with area under the curve (AUC) of 0.714, 0.688, and 0.767, respectively. Combined with MLA, AS, and LL for identifying functional ICS, the accuracy was the highest among study methods (AUC: 0.845, P < 0.001), and was significantly higher than each single method (All P < 0.05).Conclusion: Lesion length can improve the diagnostic accuracy of IVUS-derived parameters for detecting functional ICS.


2016 ◽  
Vol 11 (1) ◽  
pp. 11
Author(s):  
Sudheer Koganti ◽  
◽  
◽  
◽  
Tushar Kotecha ◽  
...  

Intracoronary imaging has the capability of accurately measuring vessel and stenosis dimensions, assessing vessel integrity, characterising lesion morphology and guiding optimal percutaneous coronary intervention (PCI). Coronary angiography used to detect and assess coronary stenosis severity has limitations. The 2D nature of fluoroscopic imaging provides lumen profile only and the assessment of coronary stenosis by visual estimation is subjective and prone to error. Performing PCI based on coronary angiography alone is inadequate for determining key metrics of the vessel such as dimension, extent of disease, and plaque distribution and composition. The advent of intracoronary imaging has offset the limitations of angiography and has shifted the paradigm to allow a detailed, objective appreciation of disease extent and morphology, vessel diameter, stent size and deployment and healing after PCI. It has become an essential tool in complex PCI, including rotational atherectomy, in follow-up of novel drug-eluting stent platforms and understanding the pathophysiology of stent failure after PCI (e.g. following stent thrombosis or in-stent restenosis). In this review we look at the two currently available and commonly used intracoronary imaging tools – intravascular ultrasound and optical coherence tomography – and the merits of each.


2017 ◽  
Vol 58 (11) ◽  
pp. 2755-2757
Author(s):  
Zachary David Guss ◽  
Abdossalam Madkhali ◽  
Qinyu Chen ◽  
Yin Zhang ◽  
Samson Dah ◽  
...  

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