Diagnostic accuracy of quantitative flow ratio (QFR) and vessel fractional flow reserve (vFFR) estimated retrospectively by conventional radiation saving X-ray angiography Article Swipe
Chongying Jin
,
Anantharaman Ramasamy
,
Hannah Safi
,
Yakup Kilic
,
Vincenzo Tufaro
,
Retesh Bajaj
,
Guosheng Fu
,
Anthony Mathur
,
Christos V. Bourantas
,
Andreas Baumbach
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1007/s10554-020-02133-8
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1007/s10554-020-02133-8
Background Angiography derived FFR reveals good performance in assessing intermediate coronary stenosis. However, its performance under contemporary low X-ray frame and pulse rate settings is unknown. We aim to validate the feasibility and performance of quantitative flow ratio (QFR) and vessel fractional flow reserve (vFFR) under such angiograms. Methods This was an observational, retrospective, single center cohort study. 134 vessels in 102 patients, with angiograms acquired under 7.5fps and 7pps mode, were enrolled. QFR (fQFR and cQFR) and vFFR were validated with FFR as the gold standard. A conventional manual and a newly developed algorithmic exclusion method (M and A group) were both evaluated for identification of poor-quality angiograms. Results Good agreement between QFR/vFFR and FFR were observed in both M and A group, except for vFFR in the M group. The correlation coefficients between fQFR/cQFR/vFFR and FFR were 0.6242, 0.5888, 0.4089 in the M group, with r vFFR significantly lower than r fQFR (p = 0.0303), and 0.7055, 0.6793, 0.5664 in the A group, respectively. AUCs of detecting lesions with FFR ≤ 0.80 were 0.852 (95% CI 0.722–0.913), 0.858 (95% CI 0.778–0.917), 0.682 (95% CI 0.586–0.768), for fQFR/cQFR/vFFR in the M group, while vFFR performed poorer than fQFR (p = 0.0063) and cQFR (p = 0.0054). AUCs were 0.898 (95% CI 0.811–0.945), 0.892 (95% CI 0.803–0.949), 0.843 (95% CI 0.746–0.914) for fQFR/cQFR/vFFR in the A group. AUC vFFR was significantly higher in the A group than that in the M group (p = 0.0399). Conclusions QFR/vFFR assessment is feasible under 7.5fps and 7pps angiography, where cQFR showed no advantage compared to fQFR. Our newly developed algorithmic exclusion method could be a better method of selecting angiograms with adequate quality for angiography derived FFR assessment.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10554-020-02133-8
- https://link.springer.com/content/pdf/10.1007/s10554-020-02133-8.pdf
- OA Status
- hybrid
- Cited By
- 13
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3123004352
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- OpenAlex ID
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https://openalex.org/W3123004352Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s10554-020-02133-8Digital Object Identifier
- Title
-
Diagnostic accuracy of quantitative flow ratio (QFR) and vessel fractional flow reserve (vFFR) estimated retrospectively by conventional radiation saving X-ray angiographyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-16Full publication date if available
- Authors
-
Chongying Jin, Anantharaman Ramasamy, Hannah Safi, Yakup Kilic, Vincenzo Tufaro, Retesh Bajaj, Guosheng Fu, Anthony Mathur, Christos V. Bourantas, Andreas BaumbachList of authors in order
- Landing page
-
https://doi.org/10.1007/s10554-020-02133-8Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s10554-020-02133-8.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1007/s10554-020-02133-8.pdfDirect OA link when available
- Concepts
-
Fractional flow reserve, Medicine, Stenosis, Angiography, Cardiology, Nuclear medicine, Internal medicine, Single Center, Retrospective cohort study, Gold standard (test), Coronary angiography, Radiology, Myocardial infarctionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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13Total citation count in OpenAlex
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2025: 2, 2024: 3, 2023: 4, 2022: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.0.7055, | 159 |
| abstract_inverted_index.Methods | 49 |
| abstract_inverted_index.Results | 110 |
| abstract_inverted_index.between | 113, 135 |
| abstract_inverted_index.derived | 3, 283 |
| abstract_inverted_index.lesions | 170 |
| abstract_inverted_index.quality | 280 |
| abstract_inverted_index.reserve | 44 |
| abstract_inverted_index.reveals | 5 |
| abstract_inverted_index.vessels | 60 |
| abstract_inverted_index.0.0054). | 207 |
| abstract_inverted_index.0.0303), | 157 |
| abstract_inverted_index.0.0399). | 245 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 13 |
| abstract_inverted_index.QFR/vFFR | 114, 247 |
| abstract_inverted_index.acquired | 66 |
| abstract_inverted_index.adequate | 279 |
| abstract_inverted_index.compared | 261 |
| abstract_inverted_index.coronary | 11 |
| abstract_inverted_index.feasible | 250 |
| abstract_inverted_index.observed | 118 |
| abstract_inverted_index.settings | 24 |
| abstract_inverted_index.unknown. | 26 |
| abstract_inverted_index.validate | 30 |
| abstract_inverted_index.advantage | 260 |
| abstract_inverted_index.agreement | 112 |
| abstract_inverted_index.assessing | 9 |
| abstract_inverted_index.detecting | 169 |
| abstract_inverted_index.developed | 94, 266 |
| abstract_inverted_index.enrolled. | 73 |
| abstract_inverted_index.evaluated | 104 |
| abstract_inverted_index.exclusion | 96, 268 |
| abstract_inverted_index.patients, | 63 |
| abstract_inverted_index.performed | 196 |
| abstract_inverted_index.selecting | 276 |
| abstract_inverted_index.standard. | 87 |
| abstract_inverted_index.stenosis. | 12 |
| abstract_inverted_index.validated | 81 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.angiograms | 65, 277 |
| abstract_inverted_index.assessment | 248 |
| abstract_inverted_index.fractional | 42 |
| abstract_inverted_index.Angiography | 2 |
| abstract_inverted_index.Conclusions | 246 |
| abstract_inverted_index.algorithmic | 95, 267 |
| abstract_inverted_index.angiograms. | 48, 109 |
| abstract_inverted_index.angiography | 282 |
| abstract_inverted_index.assessment. | 285 |
| abstract_inverted_index.correlation | 133 |
| abstract_inverted_index.feasibility | 32 |
| abstract_inverted_index.performance | 7, 15, 34 |
| abstract_inverted_index.angiography, | 255 |
| abstract_inverted_index.coefficients | 134 |
| abstract_inverted_index.contemporary | 17 |
| abstract_inverted_index.conventional | 89 |
| abstract_inverted_index.intermediate | 10 |
| abstract_inverted_index.poor-quality | 108 |
| abstract_inverted_index.quantitative | 36 |
| abstract_inverted_index.respectively. | 166 |
| abstract_inverted_index.significantly | 150, 231 |
| abstract_inverted_index.0.746–0.914) | 221 |
| abstract_inverted_index.fQFR/cQFR/vFFR | 136, 189, 223 |
| abstract_inverted_index.identification | 106 |
| abstract_inverted_index.observational, | 53 |
| abstract_inverted_index.retrospective, | 54 |
| abstract_inverted_index.0.586–0.768), | 187 |
| abstract_inverted_index.0.722–0.913), | 179 |
| abstract_inverted_index.0.778–0.917), | 183 |
| abstract_inverted_index.0.803–0.949), | 217 |
| abstract_inverted_index.0.811–0.945), | 213 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/1 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | No poverty |
| citation_normalized_percentile.value | 0.87978846 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |