Noninvasive measurement of oxygenation using quantitative susceptibility mapping (supplement)

使用定量磁化率图无创测量氧合（补充）

• 批准号: 10864405
• 负责人: Pascal Spincemaille
• 金额: $ 70.03万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10864405
• 关键词: Acceleration; Automation; Blood; Calcium; Cardiac; Catheterization; Cessation of life; Clinical; Clip; Congestive Heart Failure; Data; Decision Making; Development; Diagnosis; Disease; Failure; Fibrosis; Geometry; Goals; Heart; Heart failure; Individual; Ionizing radiation; Link; Magnetic Resonance Imaging; Magnetism; Manuals; Maps; Measurement; Measures; Methods; Mitral Valve; Mitral Valve Insufficiency; Mitral Valve Prolapse; Modality; Morbidity - disease rate; Myocardium; Operative Surgical Procedures; Outcome; Outcomes Research; Patient-Focused Outcomes; Patients; Phase; Physiological; Prediction of Response to Therapy; Predisposition; Prognosis; Pulmonary Hypertension; Radiation exposure; Recurrence; Reference Standards; Research; Resolution; Risk; Scanning; Severities; Shapes; Signal Transduction; Structure; Techniques; Testing; Therapeutic; Treatment outcome; United States; Validation; calcification; cardiac magnetic resonance imaging; cohort; implantable device; improved; improved outcome; insight; machine learning algorithm; magnetic field; mitral valve replacement; mortality; non-compliance; parent project; predicting response; prognostic; repair strategy; repaired; response; risk stratification; success; tool; treatment optimization; treatment response; ultrasound

PROJECT SUMMARY/ABSTRACT The goal of this research is to develop and validate cardiac quantitative susceptibility mapping (QSM) for the assessment of mitral annular calcification severity, towards the long-term objective of improving prediction of therapeutic response, therapeutic decision-making and clinical outcomes for patients with mitral valve prolapse (MVP). MVP occurs in over 7 million individuals in the United States and over 170 million worldwide. It is a leading cause of degenerative mitral regurgitation (DMR) which represents the most frequent form of mitral regurgitation (MR) requiring surgery. Percutaneous (mitral valve clip placement) or surgical (mitral valve repair) treatment can reduce MR, thus avoiding harmful untreated regurgitation or mitral valve replacement (MVR). However, MR recurs in 10-30% of patients, which impacts prognosis and increases risk for congestive heart failure and death. It is therefore critical to have early predictors of therapeutic success to optimize treatments and improve outcomes for patients with MVP. Mitral annular calcium (MAC) is one such key predictor of response to surgical and percutaneous repair in patients with MVP. MAC is known to decrease surgical treatment success and to increase morbidity and mortality. MAC is currently diagnosed using ultrasound (echo), which lacks quantitation, or CT, which exposes the patient to ionizing radiation and is not capable of measuring other predictors such as fibrosis or directly assessing MR itself. Cardiac MRI (CMRI) can measures these predictors but is currently incapable of quantifying MAC – thus limiting the utility of this powerful modality for assessment of physiologic determinants of MR and its response to therapy. Nevertheless, calcification has a strong effect on the MR signal due to its strong diamagnetic susceptibility, which significantly modifies the magnetic at and round the MAC. While severe MAC can be qualitatively detected using the resulting low magnitude signal, it is less sensitive at mild or moderate MAC levels and is not quantitative. QSM – an MRI technique pioneered by our group – is able to directly measure susceptibility and thus calcium content. We have obtained encouraging preliminary data showing the feasibility of using cardiac QSM to detect MAC and have shown preliminary validation of this method against cardiac CT reference. In this proposal, we propose to develop cardiac QSM acquisition and processing methods and perform its validation among a cohort of MVP patients through the following Specific Aims. (1) We will compare conventional to accelerated QSM for quantification of MAC among patients with MVP undergoing percutaneous or surgical repair. (2) We will develop and validate a fully automated machine learning algorithm to quantify MAC. (3) We will test whether QSM independently predicts therapeutic response to mitral valve repair. The expected outcome of this research is a non-invasive MRI based method to measure mitral annulus calcification severity, which is a key predictor of success of percutaneous or surgical treatment for mitral valve prolapse. Cardiac QSM holds broad significance towards the goal of therapeutic optimization for valvular disease.

项目总结/文摘