Vahid Mohammadi, Massoud Ghasemi, Reza Rahmani, Maryam Mehrpooya, Hamidreza Babakhani, Akbar Shafiee, Mohammad Sadeghian
{"title":"二维冠状动脉造影图像计算血流储备分数的有效性和诊断性能。","authors":"Vahid Mohammadi, Massoud Ghasemi, Reza Rahmani, Maryam Mehrpooya, Hamidreza Babakhani, Akbar Shafiee, Mohammad Sadeghian","doi":"10.14503/THIJ-20-7410","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.</p>","PeriodicalId":22352,"journal":{"name":"Texas Heart Institute journal","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969768/pdf/i1526-6702-50-1-e207410.pdf","citationCount":"0","resultStr":"{\"title\":\"Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images.\",\"authors\":\"Vahid Mohammadi, Massoud Ghasemi, Reza Rahmani, Maryam Mehrpooya, Hamidreza Babakhani, Akbar Shafiee, Mohammad Sadeghian\",\"doi\":\"10.14503/THIJ-20-7410\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.</p>\",\"PeriodicalId\":22352,\"journal\":{\"name\":\"Texas Heart Institute journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969768/pdf/i1526-6702-50-1-e207410.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Texas Heart Institute journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.14503/THIJ-20-7410\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Texas Heart Institute journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.14503/THIJ-20-7410","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images.
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.
期刊介绍:
For more than 45 years, the Texas Heart Institute Journal has been published by the Texas Heart Institute as part of its medical education program. Our bimonthly peer-reviewed journal enjoys a global audience of physicians, scientists, and healthcare professionals who are contributing to the prevention, diagnosis, and treatment of cardiovascular disease.
The Journal was printed under the name of Cardiovascular Diseases from 1974 through 1981 (ISSN 0093-3546). The name was changed to Texas Heart Institute Journal in 1982 and was printed through 2013 (ISSN 0730-2347). In 2014, the Journal moved to online-only publication. It is indexed by Index Medicus/MEDLINE and by other indexing and abstracting services worldwide. Our full archive is available at PubMed Central.
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