Stress echocardiography in valvular heart disease

Badiani, Sveeta; Lloyd, Guy

doi:10.1080/14779072.2018.1532791

Cited by 4 publications

(5 citation statements)

References 72 publications

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“…Once a C3VD patient develops symptoms, intervention becomes a class I recommendation 103 , 104 . However, at the time of diagnosis, symptoms are not reported by almost 40% of these patients 105 . Furthermore, there are often discrepancies found during clinical evaluation in one third of C3VD patients 105 , 106 .…”

Section: Discussionmentioning

confidence: 96%

“…However, at the time of diagnosis, symptoms are not reported by almost 40% of these patients 105 . Furthermore, there are often discrepancies found during clinical evaluation in one third of C3VD patients 105 , 106 . It is therefore essential to accurately diagnose individuals through careful hemodynamic evaluation to identify who may benefit from intervention (e.g., TAVR) and experience improved outcomes 106 – 108 .…”

Section: Discussionmentioning

confidence: 96%

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Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

Khodaei

Henstock

Sadeghi

et al. 2021

Sci Rep

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One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

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Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 96%

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

Khodaei

Henstock

Sadeghi

et al. 2021

Sci Rep

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“…Therefore, same day echocardiography should be available for all patients attending valve clinic. Additional data may be required to grade the severity of aortic stenosis in low flow states, objectively assess symptoms in patients who claim to be asymptomatic or identify dynamic changes in the severity of valve disease where there is a discrepancy between symptoms and the severity of valve disease at rest (12). Therefore, additional exercise testing and advanced imaging (stress echocardiography, transoesophageal echocardiography, computed tomography, magnetic resonance imaging) should be available within a short timeframe to allow timely risk stratification and decision making.…”

Section: Diagnostic Investigationsmentioning

confidence: 99%

What is a valve clinic?

Parkin

Pearce

2019

Echo Res Pract

Self Cite

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The prevalence of heart valve disease is increasing as the population ages. A series of studies have shown current clinical practice is sub-optimal. Some patients are referred for surgery at advanced stages of disease with impaired ventricular function or not even considered for surgery. Valve clinics seek to improve patient outcomes by providing an expert-led, patient-centred framework of care designed to provide an accurate diagnosis with active surveillance of valve pathology and timely referral for intervention at guideline directed trigger points. A range of different valve clinic models can be adopted depending on local expertise combining the skill set of cardiologist, physiologist/scientist and nurses. Essential components to all clinics include structured clinical review, echocardiography to identify disease aetiology and severity, patient education and access to both additional diagnostic testing and a multi-disciplinary meeting for complex case review. Recommendations for training in heart valve disease are being developed. There is a growing evidence base for heart valve clinics providing better care with increased adherence to guideline recommendations, more timely referral for surgery and better patient education than conventional care.

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“…However, at present, most of the current cardiac MRI images are mostly divided manually, which has problems such as subjectivity, poor repeatability, and time-consuming. In addition, quantitative diagnosis of cardiac diseases is carried out [ 8 ]. Some researchers applied deep learning algorithms to MRI image segmentation.…”

Section: Introductionmentioning

confidence: 99%

Effect of Different Nursing Interventions on Discharged Patients with Cardiac Valve Replacement Evaluated by Deep Learning Algorithm‐Based MRI Information

Zhang

Zhou

2022

Contrast Media & Molecular Imaging

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This study was aimed to explore the application of cardiac magnetic resonance imaging (MRI) image segmentation model based on U-Net in the diagnosis of a valvular heart disease. The effect of continuous nursing on the survival of discharged patients with cardiac valve replacement was analyzed in this study. In this study, the filling completion operation, cross entropy loss function, and guidance unit were introduced and optimized based on the U-Net network. The heart MRI image segmentation model ML-Net was established. We compared the Dice, Hausdorff distance (HD), and percentage of area difference (PAD) values between ML-Net and other algorithms. The MRI image features of 82 patients with valvular heart disease who underwent cardiac valve replacement were analyzed. According to different nursing methods, they were randomly divided into the control group (routine nursing) and the intervention group (continuous nursing), with 41 cases in each group. The Glasgow Outcome Scale (GOS) score and the Self-rating Anxiety Scale (SAS) were compared between the two groups to assess the degree of anxiety of patients and the survival status at 6 months, 1 year, 2 years, and 3 years after discharge. The results showed that the Dice coefficient, HD, and PAD of the ML-Net algorithm were (0.896 ± 0.071), (5.66 ± 0.45) mm, and (15.34 ± 1.22) %, respectively. The Dice, HD, and PAD values of the ML-Net algorithm were all statistically different from those of the convolutional neural networks (CNN), fully convolutional networks (FCN), SegNet, and U-Net algorithms P < 0.05 . Atrial, ventricular, and aortic abnormalities can be seen in MRI images of patients with valvular heart disease. The cardiac blood flow signal will also be abnormal. The GOS score of the intervention group was significantly higher than that of the control group P < 0.01 . The SAS score was lower than that of the control group P < 0.05 . The survival rates of patients with valvular heart disease at 6 months, 1 year, 2 years, and 3 years after discharge were significantly higher than those in the control group P < 0.05 . The abovementioned results showed that an effective segmentation model for cardiac MRI images was established in this study. Continuous nursing played an important role in the postoperative recovery of discharged patients after cardiac valve replacement. This study provided a reference value for the diagnosis and prognosis of valvular heart disease.

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Stress echocardiography in valvular heart disease

Cited by 4 publications

References 72 publications

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

What is a valve clinic?

Effect of Different Nursing Interventions on Discharged Patients with Cardiac Valve Replacement Evaluated by Deep Learning Algorithm‐Based MRI Information

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