{"title":"血流速度和压力梯度在区分不同类型心衰患者中的价值。","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":"14 10","pages":"7612-7624"},"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":"{\"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\":\"14 10\",\"pages\":\"7612-7624\"},\"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}","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
摘要
背景:不同类型的心力衰竭(HF)患者通过心腔的血流速度和主动脉瓣的压力梯度各不相同,这归因于不同程度的心肌收缩力。评估这些动态变化有助于早期诊断高血压。本研究旨在分析左心室流出道(LVOT)血流参数,特别是四维血流心血管磁共振(4D flow CMR)得出的血流峰值速度和压力梯度,并评估 4D flow CMR 在区分 HF 类型方面的实用性:这项前瞻性横断面研究于2019年1月至2022年5月在宁夏医科大学总医院招募了115名心力衰竭患者,根据纽约心脏协会心力衰竭心功能分级分为II-IV级,同时还招募了对照组(n=30)。参试者接受了包括四维血流在内的心血管磁共振(CMR)检查。根据射血分数,心衰患者被分为射血分数降低型心衰(HFrEF,55 人)、射血分数轻度降低型心衰(HFmrEF,30 人)和射血分数保留型心衰(HFpEF,30 人)。心脏功能参数和主动脉瓣血流指数由 Circle Cardiovascular Imaging 测量。在主动脉瓣叶交界处下方3毫米处获得左心室4D血流数据,评估瓣膜上方和下方的峰值速度。采用单因素方差分析(ANOVA)分析不同组间心功能和血流参数的差异。使用接收器操作特征曲线(ROC)评估了这些参数在识别亚组方面的准确性:结果:对常规心功能参数的分析表明,与 HFpEF 和对照组相比,HFrEF 和 HFmrEF 组的左心室射血分数(LVEF)明显较低(P0.05)。四个研究组的主动脉瓣峰值压力梯度(Supra-APGmax)存在明显差异(5.01±1.09 vs. 6.23±2.94 vs. 7.63±1.81 vs. 8.89±2.97 mmHg,Pvs.137.2±16 vs. 147.15±24.55 cm/s):心房颤动患者在收缩期主动脉瓣压力梯度降低,表明心内血流动力学发生了改变。结合主动脉瓣速度和压力梯度有助于区分不同类型的心房颤动,包括心房颤动低氧血症患者。
The value of blood flow velocity and pressure gradient in differentiating patients with different types of heart failure.
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.