Abstract
Computed tomography angiography (CCTA)-based calculations of fractional flow reserve (FFR) can improve the diagnostic performance of CCTA for physiologically significant stenosis but the computational resource requirements are high. This study aimed at establishing a simple and efficient algorithm for computing simulated FFR (S-FFR). A total of 107 patients who underwent CCTA and invasive FFR measurements were enrolled in the study. S-FFR was calculated using 145 evaluable coronary arteries with off-the-shelf softwares. FFR ≤ 0.80 was a reference threshold for diagnostic performance of diameter stenosis (DS) ≥ 50%, DS ≥ 70%, or S-FFR ≤ 0.80. FFR ≤ 0.80 was identified in 78 vessels (54%). In per-vessel analysis, S-FFR showed good correlation (r = 0.83) and agreement (mean difference = 0.02 ± 0.08) with FFR. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of S-FFR ≤ 0.80 for FFR ≤ 0.80 were 84%, 92%, 92%, 83%, and 88%, respectively. S-FFR ≤ 0.80 showed much higher predictive performance for FFR ≤ 0.80 compared with DS ≥ 50% or DS ≥ 70% (c-statistics = 0.92 vs. 0.58 or 0.65, p < 0.001, all). The classification agreement between FFR and S-FFR was > 80% when the average of FFR and S-FFR was < 0.76 or > 0.86. Per-patient analysis showed consistent results. In this study, a simple and computationally efficient simulated FFR (S-FFR) algorithm is designed and tested using non-proprietary off-the-shelf software. This algorithm may expand the accessibility of clinical applications for non-invasive coronary physiology study.
| Original language | English |
|---|---|
| Journal | International Journal of Cardiovascular Imaging |
| DOIs | |
| Publication status | Accepted/In press - 2018 Jan 1 |
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Keywords
- Computational coronary physiology
- Computed tomography
- Coronary circulation
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Cardiology and Cardiovascular Medicine
Cite this
Computationally simulated fractional flow reserve from coronary computed tomography angiography based on fractional myocardial mass. / Han, Huan; Bae, Yong Gyun; Hwang, Seung Tae; Kim, Hyung Yoon; Park, Il; Kim, Sung Mok; Choe, Yeonhyeon; Moon, Young June; Choi, Jin Ho.
In: International Journal of Cardiovascular Imaging, 01.01.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Computationally simulated fractional flow reserve from coronary computed tomography angiography based on fractional myocardial mass
AU - Han, Huan
AU - Bae, Yong Gyun
AU - Hwang, Seung Tae
AU - Kim, Hyung Yoon
AU - Park, Il
AU - Kim, Sung Mok
AU - Choe, Yeonhyeon
AU - Moon, Young June
AU - Choi, Jin Ho
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Computed tomography angiography (CCTA)-based calculations of fractional flow reserve (FFR) can improve the diagnostic performance of CCTA for physiologically significant stenosis but the computational resource requirements are high. This study aimed at establishing a simple and efficient algorithm for computing simulated FFR (S-FFR). A total of 107 patients who underwent CCTA and invasive FFR measurements were enrolled in the study. S-FFR was calculated using 145 evaluable coronary arteries with off-the-shelf softwares. FFR ≤ 0.80 was a reference threshold for diagnostic performance of diameter stenosis (DS) ≥ 50%, DS ≥ 70%, or S-FFR ≤ 0.80. FFR ≤ 0.80 was identified in 78 vessels (54%). In per-vessel analysis, S-FFR showed good correlation (r = 0.83) and agreement (mean difference = 0.02 ± 0.08) with FFR. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of S-FFR ≤ 0.80 for FFR ≤ 0.80 were 84%, 92%, 92%, 83%, and 88%, respectively. S-FFR ≤ 0.80 showed much higher predictive performance for FFR ≤ 0.80 compared with DS ≥ 50% or DS ≥ 70% (c-statistics = 0.92 vs. 0.58 or 0.65, p < 0.001, all). The classification agreement between FFR and S-FFR was > 80% when the average of FFR and S-FFR was < 0.76 or > 0.86. Per-patient analysis showed consistent results. In this study, a simple and computationally efficient simulated FFR (S-FFR) algorithm is designed and tested using non-proprietary off-the-shelf software. This algorithm may expand the accessibility of clinical applications for non-invasive coronary physiology study.
AB - Computed tomography angiography (CCTA)-based calculations of fractional flow reserve (FFR) can improve the diagnostic performance of CCTA for physiologically significant stenosis but the computational resource requirements are high. This study aimed at establishing a simple and efficient algorithm for computing simulated FFR (S-FFR). A total of 107 patients who underwent CCTA and invasive FFR measurements were enrolled in the study. S-FFR was calculated using 145 evaluable coronary arteries with off-the-shelf softwares. FFR ≤ 0.80 was a reference threshold for diagnostic performance of diameter stenosis (DS) ≥ 50%, DS ≥ 70%, or S-FFR ≤ 0.80. FFR ≤ 0.80 was identified in 78 vessels (54%). In per-vessel analysis, S-FFR showed good correlation (r = 0.83) and agreement (mean difference = 0.02 ± 0.08) with FFR. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of S-FFR ≤ 0.80 for FFR ≤ 0.80 were 84%, 92%, 92%, 83%, and 88%, respectively. S-FFR ≤ 0.80 showed much higher predictive performance for FFR ≤ 0.80 compared with DS ≥ 50% or DS ≥ 70% (c-statistics = 0.92 vs. 0.58 or 0.65, p < 0.001, all). The classification agreement between FFR and S-FFR was > 80% when the average of FFR and S-FFR was < 0.76 or > 0.86. Per-patient analysis showed consistent results. In this study, a simple and computationally efficient simulated FFR (S-FFR) algorithm is designed and tested using non-proprietary off-the-shelf software. This algorithm may expand the accessibility of clinical applications for non-invasive coronary physiology study.
KW - Computational coronary physiology
KW - Computed tomography
KW - Coronary circulation
UR - http://www.scopus.com/inward/record.url?scp=85051788552&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051788552&partnerID=8YFLogxK
U2 - 10.1007/s10554-018-1432-z
DO - 10.1007/s10554-018-1432-z
M3 - Article
C2 - 30128848
AN - SCOPUS:85051788552
JO - International Journal of Cardiovascular Imaging
JF - International Journal of Cardiovascular Imaging
SN - 1569-5794
ER -