{"title":"The value of blood flow velocity and pressure gradient in differentiating patients with different types of heart failure.","authors":"Jiaxuan Guo, Xiuzheng Yue, Wenying Liang, Lirong Ma, Xiao Sun, Huairong Zhang, Li Zhu","doi":"10.21037/qims-24-311","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Patients with different types of heart failure (HF) exhibit varying rates of blood flow through cardiac chambers and pressure gradients across the aortic valve, attributed to differing degrees of myocardial contractility. Assessment of these dynamics offers insights into early HF diagnosis. This study aimed to analyze left ventricular outflow tract (LVOT) blood flow parameters, specifically peak blood flow velocity and pressure gradient derived from four-dimensional flow cardiovascular magnetic resonance (4D flow CMR), and to evaluate 4D flow CMR's utility in distinguishing HF types.</p><p><strong>Methods: </strong>This prospective cross-sectional study recruited 115 HF patients from January 2019 to May 2022 at the General Hospital of Ningxia Medical University, classified by the New York Heart Association Cardiac Function Classification of Heart Failure as class II-IV, alongside a control group (n=30). Participants underwent cardiovascular magnetic resonance (CMR), including 4D flow. HF patients were categorized into heart failure with reduced ejection fraction (HFrEF, n=55), heart failure with mildly reduced ejection fraction (HFmrEF, n=30), and heart failure with preserved ejection fraction (HFpEF, n=30), based on ejection fraction. The cardiac functional parameters and aortic valve flow indices were measured using Circle Cardiovascular Imaging. LVOT 4D flow data were obtained 3 mm below the junction of the aortic valve leaflets, assessing peak velocities above and below the valve. Differences in cardiac function and blood flow parameters between groups were analyzed using one-way analysis of variance (ANOVA). The accuracy of these parameters in identifying subgroups was assessed using the receiver operating characteristic (ROC) curve.</p><p><strong>Results: </strong>Analysis of conventional cardiac function parameters revealed that left ventricular ejection fraction (LVEF) was significantly lower in the HFrEF and HFmrEF groups compared to the HFpEF and control groups (P<0.01). Additionally, end-diastolic volume and end-systolic volume were significantly higher in the HFrEF and HFmrEF groups than in the HFpEF and control groups (P<0.01). However, there were no significant differences in cardiac function parameters between the HFpEF and control groups (P>0.05). Significant differences were observed in aortic valve peak pressure gradients (Supra-APGmax) among the four study groups (5.01±1.09 <i>vs</i>. 6.23±2.94 <i>vs</i>. 7.63±1.81 <i>vs</i>. 8.89±2.97 mmHg, P<0.05). Aortic valve peak velocities in the HFrEF group differed significantly from the HFpEF and control groups (111.31±12.05 cm/s <i>vs</i>. 137.2±16 <i>vs</i>. 147.15±24.55 cm/s, P<0.001). The ROC curve for the pressure gradient below the aortic valve had an area under the curve (AUC) of 0.728 [95% confidence interval (CI): 0.591-0.864, P=0.002], with an optimal threshold of 4.72 mmHg (sensitivity: 0.8, specificity: 0.7, Youden index: 0.5).</p><p><strong>Conclusions: </strong>HF patients exhibit reduced pressure gradients across the aortic valve during systole, indicative of altered intracardiac blood flow dynamics. Combining aortic valve velocities and pressure gradients can aid in distinguishing different types of HF, including HFpEF patients.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485376/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Imaging in Medicine and Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/qims-24-311","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/26 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Patients with different types of heart failure (HF) exhibit varying rates of blood flow through cardiac chambers and pressure gradients across the aortic valve, attributed to differing degrees of myocardial contractility. Assessment of these dynamics offers insights into early HF diagnosis. This study aimed to analyze left ventricular outflow tract (LVOT) blood flow parameters, specifically peak blood flow velocity and pressure gradient derived from four-dimensional flow cardiovascular magnetic resonance (4D flow CMR), and to evaluate 4D flow CMR's utility in distinguishing HF types.
Methods: This prospective cross-sectional study recruited 115 HF patients from January 2019 to May 2022 at the General Hospital of Ningxia Medical University, classified by the New York Heart Association Cardiac Function Classification of Heart Failure as class II-IV, alongside a control group (n=30). Participants underwent cardiovascular magnetic resonance (CMR), including 4D flow. HF patients were categorized into heart failure with reduced ejection fraction (HFrEF, n=55), heart failure with mildly reduced ejection fraction (HFmrEF, n=30), and heart failure with preserved ejection fraction (HFpEF, n=30), based on ejection fraction. The cardiac functional parameters and aortic valve flow indices were measured using Circle Cardiovascular Imaging. LVOT 4D flow data were obtained 3 mm below the junction of the aortic valve leaflets, assessing peak velocities above and below the valve. Differences in cardiac function and blood flow parameters between groups were analyzed using one-way analysis of variance (ANOVA). The accuracy of these parameters in identifying subgroups was assessed using the receiver operating characteristic (ROC) curve.
Results: Analysis of conventional cardiac function parameters revealed that left ventricular ejection fraction (LVEF) was significantly lower in the HFrEF and HFmrEF groups compared to the HFpEF and control groups (P<0.01). Additionally, end-diastolic volume and end-systolic volume were significantly higher in the HFrEF and HFmrEF groups than in the HFpEF and control groups (P<0.01). However, there were no significant differences in cardiac function parameters between the HFpEF and control groups (P>0.05). Significant differences were observed in aortic valve peak pressure gradients (Supra-APGmax) among the four study groups (5.01±1.09 vs. 6.23±2.94 vs. 7.63±1.81 vs. 8.89±2.97 mmHg, P<0.05). Aortic valve peak velocities in the HFrEF group differed significantly from the HFpEF and control groups (111.31±12.05 cm/s vs. 137.2±16 vs. 147.15±24.55 cm/s, P<0.001). The ROC curve for the pressure gradient below the aortic valve had an area under the curve (AUC) of 0.728 [95% confidence interval (CI): 0.591-0.864, P=0.002], with an optimal threshold of 4.72 mmHg (sensitivity: 0.8, specificity: 0.7, Youden index: 0.5).
Conclusions: HF patients exhibit reduced pressure gradients across the aortic valve during systole, indicative of altered intracardiac blood flow dynamics. Combining aortic valve velocities and pressure gradients can aid in distinguishing different types of HF, including HFpEF patients.