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High Performance Automated System for Analysis of Fast Cardiac SPECT

High Performance Automated System for Analysis of Fast Cardiac SPECT
用于快速心脏 SPECT 分析的高性能自动化系统
批准号:
9282634
负责人:
Piotr J Slomka
金额:
$60.01万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-07-18 至 2020-05-31

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Coronary artery disease remains a major public health problem worldwide. It causes approximately 1 of every 6 deaths in the United States. Imaging of myocardial perfusion (delivery of blood to the heart muscle) by myocardial perfusion single photon emission tomography (MPS) allows physicians to detect disease before a heart attack, and predict risk in millions of patients annually. This is currently limited by the need fo visual interpretation, which is highly variable and depends on the physician's experience. The long-term objective of this program is to improve the interpretation of this widely used heart imaging technique-achieving higher accuracy for disease detection than it is possible by the best attainable visual analysis. This proposal builds on our prior work in conventional myocardial MPS, and focuses on fast, low-radiation MPS imaging (fast-MPS) obtained by new high-efficiency scanners. Specifically, we aim to: 1) develop new image processing algorithms for a fully automated analysis of fast-MPS. The algorithms will include better heart muscle detection by training with correlated anatomical data and a novel approach for mapping the probability of abnormal perfusion for each location of the heart muscle; 2) enhance the diagnosis of heart disease from fast-MPS by machine- learning algorithms that integrate clinical data, stress test parameters, and quantitative image features; 3) demonstrate the clinical utility of the new algorithms applied to automatic canceling of the rest portion of the MPS scan, when not needed. The new system will be more accurate than the clinical expert analysis in the detection of obstructive coronary disease. By immediately indicating whether a stress scan is normal, the system will allow for the automatic cancellation of the rest imaging portion when it is not needed (estimated in over 60% of all MPS studies). Our research will demonstrate that the computer decision regarding rest-scan cancellation is safe for the patient, both from a diagnostic and prognostic standpoint. This will lead to a wide adoption of low-dose stress-only imaging for MPS studies, which would reduce the amount of radiation that patients are exposed to, and allow for significant healthcare savings. It will additionally lead to a paradigm shift in the practice of nuclear cardiology, which will ultimately result in better selection of patients who need intervention, and reduce the number of deaths due coronary artery disease.
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Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial Intelligence
  • 批准号:
    10353281
  • 项目类别:
  • 资助金额:
    $102.7万
  • 财政年份:
    2022
  • 负责人:
    Piotr J Slomka
  • 依托单位:
Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial Intelligence
  • 批准号:
    10601119
  • 项目类别:
  • 资助金额:
    $100.92万
  • 财政年份:
    2022
  • 负责人:
    Piotr J Slomka
  • 依托单位:
Integrated analysis of coronary anatomy and biology with 18F-fluoride PET and CT angiography
  • 批准号:
    9755492
  • 项目类别:
  • 资助金额:
    $75.62万
  • 财政年份:
    2017
  • 负责人:
    Piotr J Slomka
  • 依托单位:
Integrated analysis of coronary anatomy and biology with 18F-fluoride PET and CT angiography
  • 批准号:
    9539728
  • 项目类别:
  • 资助金额:
    $75.68万
  • 财政年份:
    2017
  • 负责人:
    Piotr J Slomka
  • 依托单位:
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