Intraprocedure Model-Guided Electrophysiology

术中模型引导电生理学

• 批准号: 9789881
• 负责人: HENRY R HALPERIN
• 金额: $ 57.99万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789881
• 关键词: Ablation; Affect; Anatomy; Animals; Arrhythmia; Atrial Fibrillation; Cardiac ablation; Cauterize; Cessation of life; Cicatrix; Collaborations; Complex; Complication; Computer Simulation; Detection; Development; Dimensions; Electrophysiology (science); Future; Goals; Heart; Heart Abnormalities; Individual; Infarction; Intervention; Lesion; Location; Magnetic Resonance Imaging; Maps; Methodology; Methods; Modeling; Morphology; Myocardium; Nature; Necrosis; Normal tissue morphology; Pathway interactions; Patients; Procedures; Recurrence; Resolution; Risk; Running; Site; Symptoms; Techniques; Technology; Time; Tissues; United States; Universities; Update; Ventricular Tachycardia; body system; electrical property; hemodynamics; high resolution imaging; imaging modality; improved; improved outcome; novel strategies; pre-clinical; predictive modeling; success

Atrial fibrillation (AF) and ventricular tachycardia (VT) affect millions of patients in the United States. These arrhythmias can be cured with catheter ablation, but the arrhythmias often recur, and these recurrences are generally due to reversible conduction block from incomplete ablation. The inability to confirm the presence of completely ablated lesions in the desired locations is the major factor in the greater than 40% recurrence of VT after ablation, and the greater than 30 % recurrence of AF after ablation. In addition, it is not possible with current technology to adequately predict the pathways of VT through scar, which are the targets for ablation. The overall goal of this project is to combine high resolution Magnetic Resonance Imaging (MRI) and limited invasive mapping, with fast computational modeling, to predict arrhythmia circuits and targets for ablation. This goal includes using this technology to update ablation targets during a procedure to allow for identification and ablation of any remaining arrhythmogenic substrate as ablation is proceeding. We hypothesize that computational modeling, optimized with high-resolution MRI, and limited invasive mapping, can (1) aid in predicting the locations of arrhythmia circuits (2) aid in predicting the locations of critical ablation targets, and (3) aid in assessing the completeness of ablation. Once validated, these enhanced capabilities could help to dramatically improve the outcomes from complex ablations, become part of ablation methods of the future, and become a platform for improving outcomes from other interventions. We have already developed improved high resolution imaging methods that allow accurate differentiation of infarct scar and border zone from normal tissue. This high resolution imaging may also allow for detection of conducting channels that may be present in otherwise dense scar, and which may be a critical part of some VT circuits. We are also pursuing limited invasive mapping as a means to detect the presence of late potentials in scar to aid in the detection and/or verification of conducting channels, which may be difficult to identify with current MRI methods. We will further improve high resolution imaging for input for a computational model that along with the detection and/or confirmation of conduction channels from invasive mapping, will predict arrhythmia circuit locations, and allow the fast and accurate determination of optimal targets for ablation. In addition, since the model can be run in near real time, and since we can perform intra-procedure MRI, we will also study the use of the computational model for predicting when additional ablation is needed to complete the ablation of all arrhythmogenic substrate. Finally, we have developed imaging methods that differentiate incompletely ablated (reversibly damaged) tissue from completely ablated (necrotic) tissue. If ablation of some lesions is found to be incomplete during a procedure, additional ablation can be performed to complete the ablation, and likely substantially reduce arrhythmia recurrences. This project is a collaboration between the Johns Hopkins University (High Resolution MRI, invasive mapping), and Siemens (computational modeling).

心房颤动 (AF) 和室性心动过速 (VT) 影响着美国数百万患者。 这些心律失常可以通过导管消融治愈，但心律失常经常复发，并且这些复发 通常是由于不完全消融导致的可逆传导阻滞。无法确认存在 所需位置的病灶完全消融是导致 40% 以上复发的主要因素 消融后发生 VT，消融后 AF 复发率大于 30%。此外，这是不可能的 目前的技术可以充分预测 VT 通过疤痕的途径，疤痕是消融的目标。 该项目的总体目标是将高分辨率磁共振成像（MRI）和 有限的侵入性绘图，通过快速计算建模，预测心律失常回路和目标 消融。该目标包括使用该技术在手术过程中更新消融目标，以允许 当消融正在进行时，识别并消融任何剩余的致心律失常基质。 我们假设通过高分辨率 MRI 优化的计算模型和有限的侵入性 映射，可以 (1) 帮助预测心律失常回路的位置 (2) 帮助预测关键的位置 消融目标，(3) 帮助评估消融的完整性。一旦经过验证，这些增强的 能力可以帮助显着改善复杂消融的结果，成为消融的一部分 未来的方法，并成为改善其他干预措施结果的平台。 我们已经开发出改进的高分辨率成像方法，可以准确区分 正常组织的梗塞疤痕和边界区。这种高分辨率成像还可以检测 传导通道可能存在于其他致密的疤痕中，并且可能是某些疤痕的关键部分 VT 电路。我们还在追求有限的侵入性绘图，作为检测晚期电位是否存在的手段 在疤痕中帮助检测和/或验证导电通道，这可能很难识别 目前的 MRI 方法。我们将进一步改进计算模型输入的高分辨率成像， 随着侵入性测绘传导通道的检测和/或确认，将预测 心律失常回路位置，并允许快速准确地确定最佳消融目标。在 此外，由于模型可以近乎实时地运行，并且由于我们可以执行术中 MRI，因此我们将 还研究使用计算模型来预测何时需要额外的消融才能完成 所有致心律失常基质的消融。最后，我们开发了区分的成像方法 完全消融（坏死）组织的不完全消融（可逆性损伤）组织。如果消融一些 在手术过程中发现病灶不完整，可以进行额外的消融来完成 消融，并可能大大减少心律失常的复发。该项目是以下机构之间的合作 约翰·霍普金斯大学（高分辨率 MRI、侵入性测绘）和西门子（计算模型）。