View clinical trials related to Cardiac Amyloidosis.
Filter by:Patients undergoing surgery for lumbar spinal stenosis will have biopsies of the ligamentum flavum sent to the department of pathology for histologic screening. If the ligament biopsy contains amyloid, patients will receive an echocardiogram, an ecg, biomarker testing, and a bone tracer scintigraphy diagnostic of cardiac amyloidosis.
The primary aim of our pilot study is to determine whether fibrosis in the heart can be measured with [68Ga]CBP8, a positron emission tomography (PET) probe, using PET/magnetic resonance imaging (MRI) imaging, in 30 individuals with documented cardiac amyloidosis. The investigators will also enroll 15 individuals with recent myocardial infarction and 15 individuals with hypertrophic cardiomyopathy as positive controls for fibrosis, and the investigators will enroll 5 individuals without cardiovascular disease to undergo [68Ga]CBP8 PET/MRI imaging as a healthy control group. The primary hypothesis of this study is that [68Ga]CBP8 will bind to interstitial collagen and quantify myocardial fibrosis in patients with cardiac amyloidosis. The investigators hypothesize that [68Ga]CBP8 uptake will be greater in patients with cardiac amyloidosis, myocardial fibrosis, and hypertrophic cardiomyopathy than in healthy controls. Secondly, the investigators also hypothesize that [68Ga]CBP8 activity more strongly correlates with standard MRI measures in patients with recent myocardial infarction and hypertrophic cardiomyopathy (where extracellular expansion is caused by myocardial fibrosis/collagen deposition) than in patients with cardiac amyloidosis (where myocardial fibrosis is combined with infiltration).
Amyloid deposition in the heart is called cardiac amyloidosis (CA); 95% is immunoglobulin light chain amyloidosis (AL) and transthyretin amyloidosis (ATTR). Hereditary (ATTRm) or wild-type (ATTRwt) depends on whether the ATTRm gene is mutated or not. The most common mutation in Taiwan is A97S, 80% have left ventricular hypertrophy. The good prognosis depends on early diagnosis and correct treatment strategy. Bone-avid tracers such as 99mTc-PYP/DPD/HMDP could detect CA. The mechanism is not clear yet, which may be related to the microcalcification. AL amyloidosis is mostly between visual score grade 0-2, and ATTR-CM is usually gradeā„2 on PYP scan, or heart to contralateral (H/CL) ratio, and it might replace invasive myocardial biopsy. However, there are no large-scale clinical studies, lack of standardization data, and limited information in comparison between clinical and imaging parameters. This project will enroll patients with suspected or diagnosed with CA according to CA diagnostic algorithm. Clinical data and image parameters are collected and compared. The project aims to set up prediction models based on the multi-parameters of PYP scan using artificial intelligence technology, including imaging registration and alignment technology, and standardization. We further use the key cardiovascular data elements and imaging-derived database using model training network to extract image features to develop the diagnostic and prognostic prediction models, which are expected to validate the clinical significance and improve patient-centric performance and efficient clinical decision making.
The purpose of this study is to assess a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis of cardiac amyloidosis (CA).
Use samples procured from patients to improve understanding of molecular, cellular, and tissue-level processes produced by cardiac amyloidosis and therapeutic interventions.
This is an open-label, multi-center pivotal Phase 3 study to visually and quantitatively assess PET images obtained after single application of 300 MBq [18F]florbetaben and PET scanning of patients with suspected cardiac amyloidosis.
Despite rapidly advancing developments in targeted therapeutics and genetic sequencing, persistent limits in the accuracy and throughput of clinical phenotyping has led to a widening gap between the potential and the actual benefits realized by precision medicine. Recent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and more precisely/accurately assess common measurements made in clinical practice. The investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis and will prospectively evaluate its accuracy in identifying patients whom would benefit from additional screening for cardiac amyloidosis.
This is a non-interventional, prospective, retrospective, non-comparative, multi-center study. In order not to interfere with patient management, the study is observational. Thus, no follow-up visit is imposed. The data collection will be limited to the data related to the management of the patients included throughout their follow-up. This study is intended for all patients with a confirmed or suspected diagnosis of cardiac amyloidosis. Three cohorts will be identified: the HEAR (Healthcare European Amyloidosis Registry)-Retrospective Cohort, the HEAR(Healthcare European Amyloidosis Registry)-Retrospective-Prospective Cohort and the HEAR (Healthcare European Amyloidosis Registry)-Prospective Cohort.
Cardiac amyloidosis is a condition where the heart muscle, amongst other tissues, is infiltrated by the abnormal build-up of proteins called amyloid. This stiffens and thickens the heart muscle over time which makes it less efficient and puts further stress and strain on the other chambers of the heart, leading to heart failure. The commonest form, that affects predominantly the elderly, is called 'wild-type' ATTR amyloid (TTR is the protein that accumulates). In this condition a patient has a 60% chance of admission to hospital each year after diagnosis. There is no current treatment for ATTR amyloid other than using water tablets to reduce excess fluid and prevent more serious fluid build up in lungs and other tissues. Increasing body weight is the most reliable clinical sign of this fluid build up. Tele-monitoring is the practice of monitoring patients from a distance and has been shown to reduce heart failure admissions and death in patients with heart failure from any cause. Due to reduced access to primary and secondary care during COVID-19 the investigators instigated tele-monitoring of heart failure in ATTR amyloid patients. This appeared to be an effective intervention in the pilot study. The investigators propose to monitor the weight of patients with cardiac amyloidosis at home and intervene where a build up of fluid is observed by telephone discussion with a doctor. The investigators propose to evidence this in a prospective clinical trial. The investigators will evaluate the effect fairly by comparing tele-monitoring with usual care.
The study team will generate preliminary data on whether patients with cardiac amyloidosis feel better when their beta-blocker is stopped. To achieve this objective, 20 N-of-1 trials (on vs. off) will be conducted, and the study team will subsequently interview participants to better understand their outcomes. Each subject will participate in 2 periods lasting between up to 6 weeks each based on each patient's health profile. We will also engage stakeholders to understand the acceptability and feasibility of deprescribing N-of-1 trials. The N-of-1 trials will be iteratively refined in real-time based on feedback.