Noninvasive Measurement of Coronary Fractional Flow Reserve

Fan, Guoxin; Han, Ruoshuang; Luo, Jiachen; Huang, Bisheng; Jiang, Tao; Wang, Jikun

doi:10.4103/0366-6999.158383

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…[ 2 ] Therefore, it is pivotal to discriminate those lesions, which are causing ischemia, which will benefit the stenting or bypass surgery. [ 3 ] FFR is an accurate and lesion-specific index to indicate whether a particular stenosis should be responsible for ischemia. [ 4 ] FFR is defined as the ratio of maximum blood flow in a stenotic artery to maximum blood flow, if the same artery was normal.…”

Section: Oronary F Ractional mentioning

confidence: 99%

Fractional Flow Reserve

Fan¹,

Luo²,

Zhou³

et al. 2016

Chinese Medical Journal

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Section: Oronary F Ractional mentioning

confidence: 99%

Fractional Flow Reserve

Fan¹,

Luo²,

Zhou³

et al. 2016

Chinese Medical Journal

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Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images

Mohammadi

Ghasemi

Rahmani

et al. 2023

Texas Heart Institute Journal

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Background Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images. Methods A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR. Results A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P < .001; κ = 0.806; P < .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P < .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less. Conclusion A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.

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Noninvasive Measurement of Coronary Fractional Flow Reserve

Cited by 2 publications

References 32 publications

Fractional Flow Reserve

Fractional Flow Reserve

Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images

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