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31 Aortic flow abnormalities can diagnose heart failure with preserved ejection fraction
  1. Zia Mehmood1,
  2. Hosamadin Assadi1,2,
  3. Rui Li1,2,
  4. Bahman Kasmai1,2,
  5. Gareth Matthews1,2,
  6. Ciaran Grafton-Clarke1,2,
  7. Aureo Sanz-Cepero1,
  8. Xiaodan Zhao3,
  9. Liang Zhong3,4,5,
  10. Nay Aung6,7,
  11. Kristian Skinner1,
  12. Charaka Hadinnapola1,
  13. Peter Swoboda8,
  14. Andrew J Swift9,
  15. Vassilios S Vassiliou1,2,
  16. Christopher Miller10,
  17. Rob J van der Geest11,
  18. Stephen Peterson6,7,
  19. Pankaj Garg1,2
  1. 1Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, UK
  2. 2Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, UK
  3. 3National Heart Research Institute Singapore, National Heart Centre Singapore, Singapore
  4. 4Cardiovascular Sciences Academic Clinical Program and Cardiovascular Metabolic Disorder Program, Duke National University of Singapore Medical School, Singapore
  5. 5Department of Biomedical Engineering, National University of Singapore
  6. 6William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
  7. 7Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, UK
  8. 8Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
  9. 9Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
  10. 10Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
  11. 11Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands


Introduction There is growing interest in identifying cardiovascular magnetic resonance (CMR) signatures in ageing due to their relevance to cardiovascular health.1 It also remains uncertain whether patients with heart failure with preserved ejection fraction (HFpEF) have disruptions in their aortic flow. This study aimed to explore sophisticated indicators of aortic flow disturbances in ageing and in HFpEF.

Materials and Methods This study used two-dimensional phase-contrast CMR data at an orthogonal plane just above the sino-tubular junction. We recruited 10 young healthy controls (HCs), 10 old HCs and 23 patients with HFpEF. We analysed average systolic aortic flow displacement (FDsavg), systolic flow reversal ratio (sFRR) and pulse wave velocity (PWV). In a sub-group analysis, we compared old HCs versus age-gender-matched HFpEF (N=10).

Results Differences were significant in mean age (P<0.001) among young HCs (22.9±3.5 years), old HCs (60.5±10.2 years) and HFpEF patients (73.7±9.7 years). FDsavg, sFRR and PWV varied significantly (P<0.001) in young HCs (8±4%, 2±2%, 4±2m/s), old HCs (16±5%, 7±6%, 11±8m/s), and HFpEF patients (23±10%, 11±10%, 8±3). No significant PWV differences existed between old HCs and HFpEF. (table 1, figure 1 and figure 2)

HFpEF had significantly higher FDsavgversus old HCs (23±10% vs 16±5%, P<0.001). A FDsavg > 17.7% achieved 74% sensitivity, 70% specificity for differentiating them. sFRR was notably higher in HFpEF (11±10% vs 7±6%, P<0.001). A sFRR > 7.3% yielded 78% sensitivity, 70% specificity in differentiating these groups. (figure 2)

In sub-group analysis, FDsavg remained distinctly elevated in HFpEF (22.4±9.7% vs 16±4.9%, P=0.029). FDsavg of >16% showed 100% sensitivity and 70% specificity (P=0.01). Similarly, sFRR remained significantly higher in HFpEF (11.3±9.5% vs 6.6±6.4%, P=0.007). A sFRR of >7.2% showed 100% sensitivity and 60% specificity (P<0.001). (figure 3)

Discussion This study is one of the first to show a rise in sFRR and FDsavg in both ageing and HFpEF with distinct differences between the two groups even when matched for age and gender. CMR-derived FDsavg and sFRR can assist in early detection and sub phenotyping of HFpEF. Our recent work2 demonstrated that these aortic flow abnormalities, particularly, FDsavg, can led to reduced exercise capacity and identify high risk individuals.

Abstract 31 Table 1

Aortic flow indices trend across the three groups

Abstract 31 Figure 1

Circular bar plot illustrating a linear correlation of age with left ventricular and aortic flow parameters via the multiple regression method using all other CMR variables as covariates - highlighting the correlation with FDsavg and AOmin

Abstract 31 Figure 2

A – Bar charts demonstrating flow displacement systolic average trends in young vs old healthy cohorts vs HFpEF patients. B – Bar charts demonstrating systolic flow reversal ratio trends in young and old healthy cohorts and HFpEF patients

Abstract 31 Figure 3

A – Bar charts demonstrating average systolic flow displacement trends in age-gender-matched old healthy cohorts and HFpEF patients. B – Bar charts demonstrating systolic flow reversal ratio trends in age-gender-matched old healthy cohorts vs HFpEF patients. C and D – Receiver operating characteristic (ROC) with area under the curve demonstrating acceptable correlation in age-gender-matched old HCs vs patients with HFpEF

Conclusion Aortic flow haemodynamics (FDsavg and sFRR) are significantly affected in ageing and HFpEF patients. Studies with larger and diverse cohort are required to draw definitive conclusions.


  1. Shah M, et al. Environmental and genetic predictors of human cardiovascular ageing. Nature Communications 2023;14(1).

  2. Zhao X, et al. Aortic flow is associated with aging and exercise capacity. European Heart Journal Open 2023;3(4).

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